mirror of
https://github.com/langchain-ai/langgraph.git
synced 2026-08-17 21:25:46 +02:00
docs: standardize package README.md structure (#8064)
Aligns the repository's package READMEs around a shared documentation shape so users see consistent install, positioning, docs, release, and contribution guidance across LangGraph packages.
This commit is contained in:
Mason Daugherty
+9
-1
@@ -1,3 +1,11 @@
|
||||
# LangGraph examples
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||||
|
||||
This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview). Please refer to the LangChain docs for the most up-to-date examples and usage guidelines for LangGraph.
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This directory is retained purely for archival purposes and is no longer updated.
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||||
|
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## 🤔 What is this?
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||||
|
||||
The examples previously found here have been moved to the consolidated LangChain documentation. This directory remains available for historical reference, but new examples and usage guidance are published in the docs.
|
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|
||||
## 📖 Documentation
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||||
|
||||
For up-to-date LangGraph examples, tutorials, and guides, see the [LangGraph Docs](https://docs.langchain.com/oss/python/langgraph/overview). Get started with the [LangGraph Quickstart](https://docs.langchain.com/oss/python/langgraph/quickstart).
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|
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@@ -1,15 +1,27 @@
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# langgraph-checkpoint-conformance
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# LangGraph Checkpoint Conformance
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Conformance test suite for [LangGraph](https://github.com/langchain-ai/langgraph) checkpointer implementations.
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[](https://pypi.org/project/langgraph-checkpoint-conformance/#history)
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||||
[](https://opensource.org/licenses/MIT)
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||||
[](https://pypistats.org/packages/langgraph-checkpoint-conformance)
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||||
[](https://x.com/langchain_oss)
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||||
|
||||
Validates that a `BaseCheckpointSaver` subclass correctly implements the checkpoint storage contract — blob round-trips, metadata preservation, namespace isolation, incremental channel updates, and more.
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To help you ship LangGraph apps to production faster, check out [LangSmith](https://www.langchain.com/langsmith).
|
||||
[LangSmith](https://www.langchain.com/langsmith) is a unified developer platform for building, testing, and monitoring LLM applications.
|
||||
|
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## Installation
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## Quick Install
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|
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```bash
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pip install langgraph-checkpoint-conformance
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uv add langgraph-checkpoint-conformance
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```
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|
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## 🤔 What is this?
|
||||
|
||||
This library provides a conformance test suite for [LangGraph](https://github.com/langchain-ai/langgraph) checkpointer implementations. It validates that a `BaseCheckpointSaver` subclass correctly implements the checkpoint storage contract — blob round-trips, metadata preservation, namespace isolation, incremental channel updates, and more.
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|
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## 📖 Documentation
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|
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For full documentation, see the [API reference](https://reference.langchain.com/python/langgraph/). For conceptual guides on persistence and memory, see the [LangGraph Docs](https://docs.langchain.com/oss/python/langgraph/overview).
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|
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## Quick start
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|
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Register your checkpointer with `@checkpointer_test` and run `validate()`:
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@@ -110,3 +122,13 @@ async def pg_checkpointer():
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async with PostgresSaver.from_conn_string(CONN_STRING) as saver:
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yield saver
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```
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|
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## 📕 Releases & Versioning
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||||
|
||||
See our [Releases](https://docs.langchain.com/oss/python/release-policy) and [Versioning](https://docs.langchain.com/oss/python/versioning) policies.
|
||||
|
||||
## 💁 Contributing
|
||||
|
||||
As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.
|
||||
|
||||
For detailed information on how to contribute, see the [Contributing Guide](https://docs.langchain.com/oss/python/contributing/overview).
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|
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@@ -1,10 +1,28 @@
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# LangGraph Checkpoint Postgres
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Implementation of LangGraph CheckpointSaver that uses Postgres.
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[](https://pypi.org/project/langgraph-checkpoint-postgres/#history)
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||||
[](https://opensource.org/licenses/MIT)
|
||||
[](https://pypistats.org/packages/langgraph-checkpoint-postgres)
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||||
[](https://x.com/langchain_oss)
|
||||
|
||||
## Dependencies
|
||||
To help you ship LangGraph apps to production faster, check out [LangSmith](https://www.langchain.com/langsmith).
|
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[LangSmith](https://www.langchain.com/langsmith) is a unified developer platform for building, testing, and monitoring LLM applications.
|
||||
|
||||
By default `langgraph-checkpoint-postgres` installs `psycopg` (Psycopg 3) without any extras. However, you can choose a specific installation that best suits your needs [here](https://www.psycopg.org/psycopg3/docs/basic/install.html) (for example, `psycopg[binary]`).
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## Quick Install
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```bash
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uv add langgraph-checkpoint-postgres
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```
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||||
|
||||
## 🤔 What is this?
|
||||
|
||||
This library provides a Postgres implementation of LangGraph's checkpoint saver. Use it when you want LangGraph state persistence backed by Postgres for durable, long-running workflows and agents.
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|
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By default, `langgraph-checkpoint-postgres` installs `psycopg` (Psycopg 3) without any extras. You can choose a specific installation that best suits your needs in the [Psycopg installation docs](https://www.psycopg.org/psycopg3/docs/basic/install.html), for example `psycopg[binary]`.
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|
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## 📖 Documentation
|
||||
|
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For full documentation, see the [API reference](https://reference.langchain.com/python/langgraph.checkpoint.postgres). For conceptual guides on persistence and memory, see the [LangGraph Docs](https://docs.langchain.com/oss/python/langgraph/overview).
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||||
|
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## Security
|
||||
|
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@@ -20,10 +38,12 @@ By default `langgraph-checkpoint-postgres` installs `psycopg` (Psycopg 3) withou
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> When manually creating Postgres connections and passing them to `PostgresSaver` or `AsyncPostgresSaver`, make sure to include `autocommit=True` and `row_factory=dict_row` (`from psycopg.rows import dict_row`). See a full example in this [how-to guide](https://langchain-ai.github.io/langgraph/how-tos/persistence_postgres/).
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>
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> **Why these parameters are required:**
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>
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> - `autocommit=True`: Required for the `.setup()` method to properly commit the checkpoint tables to the database. Without this, table creation may not be persisted.
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> - `row_factory=dict_row`: Required because the PostgresSaver implementation accesses database rows using dictionary-style syntax (e.g., `row["column_name"]`). The default `tuple_row` factory returns tuples that only support index-based access (e.g., `row[0]`), which will cause `TypeError` exceptions when the checkpointer tries to access columns by name.
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>
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> **Example of incorrect usage:**
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>
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> ```python
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> # ❌ This will fail with TypeError during checkpointer operations
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> with psycopg.connect(DB_URI) as conn: # Missing autocommit=True and row_factory=dict_row
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@@ -118,3 +138,13 @@ async with AsyncPostgresSaver.from_conn_string(DB_URI) as checkpointer:
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# list checkpoints
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[c async for c in checkpointer.alist(read_config)]
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```
|
||||
|
||||
## 📕 Releases & Versioning
|
||||
|
||||
See our [Releases](https://docs.langchain.com/oss/python/release-policy) and [Versioning](https://docs.langchain.com/oss/python/versioning) policies.
|
||||
|
||||
## 💁 Contributing
|
||||
|
||||
As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.
|
||||
|
||||
For detailed information on how to contribute, see the [Contributing Guide](https://docs.langchain.com/oss/python/contributing/overview).
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||||
|
||||
@@ -1,6 +1,26 @@
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||||
# LangGraph SQLite Checkpoint
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||||
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||||
Implementation of LangGraph CheckpointSaver that uses SQLite DB (both sync and async, via `aiosqlite`)
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||||
[](https://pypi.org/project/langgraph-checkpoint-sqlite/#history)
|
||||
[](https://opensource.org/licenses/MIT)
|
||||
[](https://pypistats.org/packages/langgraph-checkpoint-sqlite)
|
||||
[](https://x.com/langchain_oss)
|
||||
|
||||
To help you ship LangGraph apps to production faster, check out [LangSmith](https://www.langchain.com/langsmith).
|
||||
[LangSmith](https://www.langchain.com/langsmith) is a unified developer platform for building, testing, and monitoring LLM applications.
|
||||
|
||||
## Quick Install
|
||||
|
||||
```bash
|
||||
uv add langgraph-checkpoint-sqlite
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||||
```
|
||||
|
||||
## 🤔 What is this?
|
||||
|
||||
This library provides a SQLite implementation of LangGraph's checkpoint saver, with both sync and async support via `aiosqlite`. Use it when you want LangGraph state persistence backed by SQLite for local development, testing, or lightweight deployments.
|
||||
|
||||
## 📖 Documentation
|
||||
|
||||
For full documentation, see the [API reference](https://reference.langchain.com/python/langgraph.checkpoint.sqlite). For conceptual guides on persistence and memory, see the [LangGraph Docs](https://docs.langchain.com/oss/python/langgraph/overview).
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||||
|
||||
## Security
|
||||
|
||||
@@ -91,3 +111,13 @@ async with AsyncSqliteSaver.from_conn_string(":memory:") as checkpointer:
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# list checkpoints
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||||
[c async for c in checkpointer.alist(read_config)]
|
||||
```
|
||||
|
||||
## 📕 Releases & Versioning
|
||||
|
||||
See our [Releases](https://docs.langchain.com/oss/python/release-policy) and [Versioning](https://docs.langchain.com/oss/python/versioning) policies.
|
||||
|
||||
## 💁 Contributing
|
||||
|
||||
As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.
|
||||
|
||||
For detailed information on how to contribute, see the [Contributing Guide](https://docs.langchain.com/oss/python/contributing/overview).
|
||||
|
||||
@@ -1,6 +1,26 @@
|
||||
# LangGraph Checkpoint
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||||
|
||||
This library defines the base interface for LangGraph checkpointers. Checkpointers provide a persistence layer for LangGraph. They allow you to interact with and manage the graph's state. When you use a graph with a checkpointer, the checkpointer saves a _checkpoint_ of the graph state at every superstep, enabling several powerful capabilities like human-in-the-loop, "memory" between interactions and more.
|
||||
[](https://pypi.org/project/langgraph-checkpoint/#history)
|
||||
[](https://opensource.org/licenses/MIT)
|
||||
[](https://pypistats.org/packages/langgraph-checkpoint)
|
||||
[](https://x.com/langchain_oss)
|
||||
|
||||
To help you ship LangGraph apps to production faster, check out [LangSmith](https://www.langchain.com/langsmith).
|
||||
[LangSmith](https://www.langchain.com/langsmith) is a unified developer platform for building, testing, and monitoring LLM applications.
|
||||
|
||||
## Quick Install
|
||||
|
||||
```bash
|
||||
uv add langgraph-checkpoint
|
||||
```
|
||||
|
||||
## 🤔 What is this?
|
||||
|
||||
This library defines the base interface for LangGraph checkpointers. Checkpointers provide a persistence layer for LangGraph: they save graph state at every superstep, enabling human-in-the-loop, memory between interactions, durable execution, and more.
|
||||
|
||||
## 📖 Documentation
|
||||
|
||||
For full documentation, see the [API reference](https://reference.langchain.com/python/langgraph.checkpoint). For conceptual guides on persistence and memory, see the [LangGraph Docs](https://docs.langchain.com/oss/python/langgraph/overview).
|
||||
|
||||
## Key concepts
|
||||
|
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@@ -24,7 +44,7 @@ You must pass these when invoking the graph as part of the configurable part of
|
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|
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### Serde
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||||
|
||||
`langgraph_checkpoint` also defines protocol for serialization/deserialization (serde) and provides an default implementation (`langgraph.checkpoint.serde.jsonplus.JsonPlusSerializer`) that handles a wide variety of types, including LangChain and LangGraph primitives, datetimes, enums and more.
|
||||
`langgraph-checkpoint` also defines protocol for serialization/deserialization (serde) and provides a default implementation (`langgraph.checkpoint.serde.jsonplus.JsonPlusSerializer`) that handles a wide variety of types, including LangChain and LangGraph primitives, datetimes, enums and more.
|
||||
|
||||
> [!IMPORTANT]
|
||||
> **Checkpoint deserialization security:** By default the serializer allows any Python type found in checkpoint data. New applications should set the environment variable `LANGGRAPH_STRICT_MSGPACK=true` or pass an explicit `allowed_msgpack_modules` list to `JsonPlusSerializer` to restrict deserialization to known-safe types.
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@@ -89,3 +109,13 @@ checkpointer.get(read_config)
|
||||
# list checkpoints
|
||||
list(checkpointer.list(read_config))
|
||||
```
|
||||
|
||||
## 📕 Releases & Versioning
|
||||
|
||||
See our [Releases](https://docs.langchain.com/oss/python/release-policy) and [Versioning](https://docs.langchain.com/oss/python/versioning) policies.
|
||||
|
||||
## 💁 Contributing
|
||||
|
||||
As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.
|
||||
|
||||
For detailed information on how to contribute, see the [Contributing Guide](https://docs.langchain.com/oss/python/contributing/overview).
|
||||
|
||||
+60
-29
@@ -1,29 +1,47 @@
|
||||
# LangGraph CLI
|
||||
|
||||
The official command-line interface for LangGraph, providing tools to create, develop, and deploy LangGraph applications.
|
||||
[](https://pypi.org/project/langgraph-cli/#history)
|
||||
[](https://opensource.org/licenses/MIT)
|
||||
[](https://pypistats.org/packages/langgraph-cli)
|
||||
[](https://x.com/langchain_oss)
|
||||
|
||||
## Installation
|
||||
To help you ship LangGraph apps to production faster, check out [LangSmith](https://www.langchain.com/langsmith).
|
||||
[LangSmith](https://www.langchain.com/langsmith) is a unified developer platform for building, testing, and monitoring LLM applications.
|
||||
|
||||
## Quick Install
|
||||
|
||||
Install via pip:
|
||||
```bash
|
||||
pip install langgraph-cli
|
||||
uv add langgraph-cli
|
||||
```
|
||||
|
||||
## 🤔 What is this?
|
||||
|
||||
The LangGraph CLI is the official command-line interface for LangGraph. It provides tools to create, develop, build, and run LangGraph applications locally or in Docker.
|
||||
|
||||
## 📖 Documentation
|
||||
|
||||
For full documentation, see the [LangGraph CLI reference](https://reference.langchain.com/python/langgraph-cli). For conceptual guides and tutorials, see the [LangGraph Docs](https://docs.langchain.com/oss/python/langgraph/overview).
|
||||
|
||||
For development mode with hot reloading:
|
||||
|
||||
```bash
|
||||
pip install "langgraph-cli[inmem]"
|
||||
uv add "langgraph-cli[inmem]"
|
||||
```
|
||||
|
||||
## Commands
|
||||
|
||||
### `langgraph new` 🌱
|
||||
Create a new LangGraph project from a template
|
||||
|
||||
Create a new LangGraph project from a template.
|
||||
|
||||
```bash
|
||||
langgraph new [PATH] --template TEMPLATE_NAME
|
||||
```
|
||||
|
||||
### `langgraph dev` 🏃♀️
|
||||
Run LangGraph API server in development mode with hot reloading
|
||||
|
||||
Run LangGraph API server in development mode with hot reloading.
|
||||
|
||||
```bash
|
||||
langgraph dev [OPTIONS]
|
||||
--host TEXT Host to bind to (default: 127.0.0.1)
|
||||
@@ -35,7 +53,9 @@ langgraph dev [OPTIONS]
|
||||
```
|
||||
|
||||
### `langgraph up` 🚀
|
||||
Launch LangGraph API server in Docker
|
||||
|
||||
Launch LangGraph API server in Docker.
|
||||
|
||||
```bash
|
||||
langgraph up [OPTIONS]
|
||||
-p, --port INTEGER Port to expose (default: 8123)
|
||||
@@ -47,7 +67,9 @@ langgraph up [OPTIONS]
|
||||
```
|
||||
|
||||
### `langgraph build`
|
||||
Build a Docker image for your LangGraph application
|
||||
|
||||
Build a Docker image for your LangGraph application.
|
||||
|
||||
```bash
|
||||
langgraph build -t IMAGE_TAG [OPTIONS]
|
||||
--platform TEXT Target platforms (e.g., linux/amd64,linux/arm64)
|
||||
@@ -56,7 +78,9 @@ langgraph build -t IMAGE_TAG [OPTIONS]
|
||||
```
|
||||
|
||||
### `langgraph dockerfile`
|
||||
Generate a Dockerfile for custom deployments
|
||||
|
||||
Generate a Dockerfile for custom deployments.
|
||||
|
||||
```bash
|
||||
langgraph dockerfile SAVE_PATH [OPTIONS]
|
||||
-c, --config FILE Config file path
|
||||
@@ -68,18 +92,18 @@ The CLI uses a `langgraph.json` configuration file with these key settings:
|
||||
|
||||
```json
|
||||
{
|
||||
"dependencies": ["langchain_openai", "./your_package"], // Required: Package dependencies
|
||||
"dependencies": ["langchain_openai", "./your_package"],
|
||||
"graphs": {
|
||||
"my_graph": "./your_package/file.py:graph" // Required: Graph definitions
|
||||
"my_graph": "./your_package/file.py:graph"
|
||||
},
|
||||
"env": "./.env", // Optional: Environment variables
|
||||
"python_version": "3.11", // Optional: Python version (3.11/3.12)
|
||||
"pip_config_file": "./pip.conf", // Optional: pip configuration
|
||||
"dockerfile_lines": [] // Optional: Additional Dockerfile commands
|
||||
"env": "./.env",
|
||||
"python_version": "3.11",
|
||||
"pip_config_file": "./pip.conf",
|
||||
"dockerfile_lines": []
|
||||
}
|
||||
```
|
||||
|
||||
See the [full documentation](https://langchain-ai.github.io/langgraph/cloud/reference/cli/) for detailed configuration options.
|
||||
See the [full documentation](https://reference.langchain.com/python/langgraph-cli) for detailed configuration options.
|
||||
|
||||
## Development
|
||||
|
||||
@@ -87,19 +111,26 @@ To develop the CLI itself:
|
||||
|
||||
1. Clone the repository
|
||||
2. Navigate to the CLI directory: `cd libs/cli`
|
||||
3. Install development dependencies: `uv pip install`
|
||||
3. Install development dependencies: `uv sync`
|
||||
4. Make your changes to the CLI code
|
||||
5. Test your changes:
|
||||
```bash
|
||||
# Run CLI commands directly
|
||||
uv run langgraph --help
|
||||
|
||||
# Or use the examples
|
||||
cd examples
|
||||
uv pip install
|
||||
uv run langgraph dev # or other commands
|
||||
```
|
||||
|
||||
## License
|
||||
```bash
|
||||
# Run CLI commands directly
|
||||
uv run langgraph --help
|
||||
|
||||
This project is licensed under the terms specified in the repository's LICENSE file.
|
||||
# Or use the examples
|
||||
cd examples
|
||||
uv sync
|
||||
uv run langgraph dev # or other commands
|
||||
```
|
||||
|
||||
## 📕 Releases & Versioning
|
||||
|
||||
See our [Releases](https://docs.langchain.com/oss/python/release-policy) and [Versioning](https://docs.langchain.com/oss/python/versioning) policies.
|
||||
|
||||
## 💁 Contributing
|
||||
|
||||
As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.
|
||||
|
||||
For detailed information on how to contribute, see the [Contributing Guide](https://docs.langchain.com/oss/python/contributing/overview).
|
||||
|
||||
@@ -10,7 +10,7 @@ This template demonstrates a simple chatbot implemented using [LangGraph.js](htt
|
||||
|
||||
The core logic, defined in `src/agent/graph.ts`, showcases a straightforward chatbot that responds to user queries while maintaining context from previous messages.
|
||||
|
||||
## What it does
|
||||
## 🤔 What is this?
|
||||
|
||||
The simple chatbot:
|
||||
|
||||
@@ -20,6 +20,10 @@ The simple chatbot:
|
||||
|
||||
This template provides a foundation that can be easily customized and extended to create more complex conversational agents.
|
||||
|
||||
## 📖 Documentation
|
||||
|
||||
For JavaScript and TypeScript documentation, see the [LangGraph.js docs](https://docs.langchain.com/oss/javascript/langgraph/overview). LangGraph Studio also integrates with [LangSmith](https://smith.langchain.com/) for tracing and collaboration with teammates.
|
||||
|
||||
## Getting Started
|
||||
|
||||
Assuming you have already [installed LangGraph Studio](https://github.com/langchain-ai/langgraph-studio?tab=readme-ov-file#download), to set up:
|
||||
|
||||
+24
-79
@@ -1,100 +1,45 @@
|
||||
<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>
|
||||
# 🦜🕸️ LangGraph
|
||||
|
||||
<div align="center">
|
||||
<h3>Low-level orchestration framework for building stateful agents.</h3>
|
||||
</div>
|
||||
[](https://pypi.org/project/langgraph/#history)
|
||||
[](https://opensource.org/licenses/MIT)
|
||||
[](https://pypistats.org/packages/langgraph)
|
||||
[](https://github.com/langchain-ai/langgraph/issues)
|
||||
[](https://x.com/langchain_oss)
|
||||
|
||||
<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_oss" target="_blank"><img src="https://img.shields.io/twitter/url/https/twitter.com/langchain_oss.svg?style=social&label=Follow%20%40LangChain" alt="Twitter / X"></a>
|
||||
</div>
|
||||
Looking for the JS/TS version? Check out [LangGraph.js](https://github.com/langchain-ai/langgraphjs).
|
||||
|
||||
<br>
|
||||
To help you ship LangGraph apps to production faster, check out [LangSmith](https://www.langchain.com/langsmith).
|
||||
[LangSmith](https://www.langchain.com/langsmith) is a unified developer platform for building, testing, and monitoring LLM applications.
|
||||
|
||||
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.
|
||||
## Quick Install
|
||||
|
||||
## Get started
|
||||
|
||||
Install LangGraph:
|
||||
|
||||
```
|
||||
pip install -U langgraph
|
||||
```bash
|
||||
uv add langgraph
|
||||
```
|
||||
|
||||
Create a simple workflow:
|
||||
## 🤔 What is this?
|
||||
|
||||
```python
|
||||
from langgraph.graph import START, StateGraph
|
||||
from typing_extensions import TypedDict
|
||||
LangGraph is a low-level orchestration framework for building, managing, and deploying long-running, stateful agents. LangGraph provides the infrastructure for durable execution, streaming, human-in-the-loop, persistence, memory, and more.
|
||||
|
||||
We recommend you use LangGraph when you have advanced needs that require a combination of deterministic and agentic workflows, heavy customization, and carefully controlled latency. Use [LangChain](https://docs.langchain.com/oss/python/langchain/overview) when you want to quickly build agents and applications powered by LLMs using pre-built agent architectures and model integrations.
|
||||
|
||||
class State(TypedDict):
|
||||
text: str
|
||||
LangChain [agents](https://docs.langchain.com/oss/python/langchain/agents) are built on top of LangGraph in order to provide durable execution, streaming, human-in-the-loop, persistence, and more. (You do not need to know LangGraph for basic LangChain agent usage.)
|
||||
|
||||
Trusted by companies shaping the future of agents – including Klarna, Replit, Elastic, and more – LangGraph is used to ship AI applications at scale.
|
||||
|
||||
def node_a(state: State) -> dict:
|
||||
return {"text": state["text"] + "a"}
|
||||
## 📖 Documentation
|
||||
|
||||
For full documentation, see the [API reference](https://reference.langchain.com/python/langgraph/). For conceptual guides, tutorials, and examples on using LangGraph, see the [LangGraph Docs](https://docs.langchain.com/oss/python/langgraph/overview). Get started with the [LangGraph Quickstart](https://docs.langchain.com/oss/python/langgraph/quickstart).
|
||||
|
||||
def node_b(state: State) -> dict:
|
||||
return {"text": state["text"] + "b"}
|
||||
## 📕 Releases & Versioning
|
||||
|
||||
See our [Releases](https://docs.langchain.com/oss/python/release-policy) and [Versioning](https://docs.langchain.com/oss/python/versioning) policies.
|
||||
|
||||
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")
|
||||
## 💁 Contributing
|
||||
|
||||
print(graph.compile().invoke({"text": ""}))
|
||||
# {'text': 'ab'}
|
||||
```
|
||||
As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.
|
||||
|
||||
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).
|
||||
|
||||
## Core benefits
|
||||
|
||||
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:
|
||||
|
||||
- [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.
|
||||
|
||||
## LangGraph’s 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.
|
||||
|
||||
> [!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/langgraph/guides): 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.
|
||||
For detailed information on how to contribute, see the [Contributing Guide](https://docs.langchain.com/oss/python/contributing/overview).
|
||||
|
||||
## Acknowledgements
|
||||
|
||||
|
||||
+37
-7
@@ -1,16 +1,36 @@
|
||||
# LangGraph Prebuilt
|
||||
|
||||
This library defines high-level APIs for creating and executing LangGraph agents and tools.
|
||||
[](https://pypi.org/project/langgraph-prebuilt/#history)
|
||||
[](https://opensource.org/licenses/MIT)
|
||||
[](https://pypistats.org/packages/langgraph-prebuilt)
|
||||
[](https://x.com/langchain_oss)
|
||||
|
||||
To help you ship LangGraph apps to production faster, check out [LangSmith](https://www.langchain.com/langsmith).
|
||||
[LangSmith](https://www.langchain.com/langsmith) is a unified developer platform for building, testing, and monitoring LLM applications.
|
||||
|
||||
## Quick Install
|
||||
|
||||
```bash
|
||||
uv add langgraph
|
||||
```
|
||||
|
||||
## 🤔 What is this?
|
||||
|
||||
This library defines high-level APIs for creating and executing LangGraph agents and tools. It includes prebuilt components such as `create_react_agent`, `ToolNode`, validation helpers, and Agent Inbox schemas.
|
||||
|
||||
## 📖 Documentation
|
||||
|
||||
For full documentation, see the [API reference](https://reference.langchain.com/python/langgraph.prebuilt/). For conceptual guides and tutorials, see the [LangGraph Docs](https://docs.langchain.com/oss/python/langgraph/overview).
|
||||
|
||||
> [!IMPORTANT]
|
||||
> This library is meant to be bundled with `langgraph`, don't install it directly
|
||||
> This library is bundled with `langgraph`; most users should install `langgraph` instead of installing `langgraph-prebuilt` directly.
|
||||
|
||||
## Agents
|
||||
|
||||
`langgraph-prebuilt` provides an [implementation](https://langchain-ai.github.io/langgraph/reference/prebuilt/#langgraph.prebuilt.chat_agent_executor.create_react_agent) of a tool-calling [ReAct-style](https://langchain-ai.github.io/langgraph/concepts/agentic_concepts/#react-implementation) agent - `create_react_agent`:
|
||||
`langgraph-prebuilt` provides an [implementation](https://reference.langchain.com/python/langgraph.prebuilt/chat_agent_executor/create_react_agent) of a tool-calling ReAct-style agent - `create_react_agent`:
|
||||
|
||||
```bash
|
||||
pip install langchain-anthropic
|
||||
uv add langchain-anthropic
|
||||
```
|
||||
|
||||
```python
|
||||
@@ -39,7 +59,7 @@ app.invoke(
|
||||
|
||||
### ToolNode
|
||||
|
||||
`langgraph-prebuilt` provides an [implementation](https://langchain-ai.github.io/langgraph/reference/prebuilt/#langgraph.prebuilt.tool_node.ToolNode) of a node that executes tool calls - `ToolNode`:
|
||||
`langgraph-prebuilt` provides an [implementation](https://reference.langchain.com/python/langgraph.prebuilt/tool_node/ToolNode) of a node that executes tool calls - `ToolNode`:
|
||||
|
||||
```python
|
||||
from langgraph.prebuilt import ToolNode
|
||||
@@ -61,7 +81,7 @@ tool_node.invoke({"messages": [ai_message]})
|
||||
|
||||
### ValidationNode
|
||||
|
||||
`langgraph-prebuilt` provides an [implementation](https://langchain-ai.github.io/langgraph/reference/prebuilt/#langgraph.prebuilt.tool_validator.ValidationNode) of a node that validates tool calls against a pydantic schema - `ValidationNode`:
|
||||
`langgraph-prebuilt` provides an [implementation](https://reference.langchain.com/python/langgraph.prebuilt/tool_validator/ValidationNode) of a node that validates tool calls against a pydantic schema - `ValidationNode`:
|
||||
|
||||
```python
|
||||
from pydantic import BaseModel, field_validator
|
||||
@@ -114,4 +134,14 @@ def my_graph_function():
|
||||
if response['type'] == "response":
|
||||
# Do something with the response
|
||||
...
|
||||
```
|
||||
```
|
||||
|
||||
## 📕 Releases & Versioning
|
||||
|
||||
See our [Releases](https://docs.langchain.com/oss/python/release-policy) and [Versioning](https://docs.langchain.com/oss/python/versioning) policies.
|
||||
|
||||
## 💁 Contributing
|
||||
|
||||
As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.
|
||||
|
||||
For detailed information on how to contribute, see the [Contributing Guide](https://docs.langchain.com/oss/python/contributing/overview).
|
||||
|
||||
+11
-1
@@ -1 +1,11 @@
|
||||
This repository has been moved to [langchain-ai/langgraphjs](https://github.com/langchain-ai/langgraphjs/tree/main/libs/sdk).
|
||||
# LangGraph JavaScript SDK
|
||||
|
||||
Looking for the JS/TS version? Check out [LangGraph.js](https://github.com/langchain-ai/langgraphjs).
|
||||
|
||||
## 🤔 What is this?
|
||||
|
||||
This package has moved to [langchain-ai/langgraphjs](https://github.com/langchain-ai/langgraphjs/tree/main/libs/sdk).
|
||||
|
||||
## 📖 Documentation
|
||||
|
||||
For JavaScript and TypeScript documentation, see the [LangGraph.js docs](https://docs.langchain.com/oss/javascript/langgraph/overview).
|
||||
|
||||
+30
-9
@@ -1,17 +1,30 @@
|
||||
# LangGraph Python SDK
|
||||
|
||||
This repository contains the Python SDK for interacting with the LangSmith Deployment REST API.
|
||||
[](https://pypi.org/project/langgraph-sdk/#history)
|
||||
[](https://opensource.org/licenses/MIT)
|
||||
[](https://pypistats.org/packages/langgraph-sdk)
|
||||
[](https://x.com/langchain_oss)
|
||||
|
||||
## Quick Start
|
||||
To help you ship LangGraph apps to production faster, check out [LangSmith](https://www.langchain.com/langsmith).
|
||||
[LangSmith](https://www.langchain.com/langsmith) is a unified developer platform for building, testing, and monitoring LLM applications.
|
||||
|
||||
To get started with the Python SDK, [install the package](https://pypi.org/project/langgraph-sdk/)
|
||||
## Quick Install
|
||||
|
||||
```bash
|
||||
pip install -U langgraph-sdk
|
||||
uv add langgraph-sdk
|
||||
```
|
||||
|
||||
You will need a running LangGraph API server. If you're running a server locally using `langgraph-cli`, SDK will automatically point at `http://localhost:8123`, otherwise
|
||||
you would need to specify the server URL when creating a client.
|
||||
## 🤔 What is this?
|
||||
|
||||
This library provides the Python SDK for interacting with the LangGraph API. Use it to connect to a running LangGraph API server, manage assistants and threads, and stream runs from Python applications.
|
||||
|
||||
You will need a running LangGraph API server. If you're running a server locally using `langgraph-cli`, the SDK will automatically point at `http://localhost:8123`; otherwise, specify the server URL when creating a client.
|
||||
|
||||
## 📖 Documentation
|
||||
|
||||
For full documentation, see the [API reference](https://reference.langchain.com/python/langgraph-sdk/). For conceptual guides and tutorials, see the [LangGraph Docs](https://docs.langchain.com/oss/python/langgraph/overview).
|
||||
|
||||
## Quick Start
|
||||
|
||||
```python
|
||||
from langgraph_sdk import get_client
|
||||
@@ -43,9 +56,7 @@ async for chunk in client.runs.stream(thread['thread_id'], agent['assistant_id']
|
||||
|
||||
## Thread-Centric Streaming (v3)
|
||||
|
||||
`client.threads.stream()` returns a context manager that owns the SSE session for one
|
||||
thread. Typed projections — values snapshots, message streams, tool calls, custom
|
||||
events — all share the same underlying connection.
|
||||
`client.threads.stream()` returns a context manager that owns the SSE session for one thread. Typed projections — values snapshots, message streams, tool calls, custom events — all share the same underlying connection.
|
||||
|
||||
```python
|
||||
from langgraph_sdk import get_client
|
||||
@@ -73,3 +84,13 @@ async with client.threads.stream(
|
||||
|
||||
final = await thread.output # terminal state values
|
||||
```
|
||||
|
||||
## 📕 Releases & Versioning
|
||||
|
||||
See our [Releases](https://docs.langchain.com/oss/python/release-policy) and [Versioning](https://docs.langchain.com/oss/python/versioning) policies.
|
||||
|
||||
## 💁 Contributing
|
||||
|
||||
As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.
|
||||
|
||||
For detailed information on how to contribute, see the [Contributing Guide](https://docs.langchain.com/oss/python/contributing/overview).
|
||||
|
||||
Reference in New Issue
Block a user