Add generics tests

Signed-off-by: William Fu-Hinthorn <13333726+hinthornw@users.noreply.github.com>

docs/_scripts/prepare_notebooks_for_ci.py

@@ -20,7 +20,6 @@ BLOCKLIST_COMMANDS = (
 
 NOTEBOOKS_NO_CASSETTES = (
     "docs/how-tos/visualization.ipynb",
-    "docs/how-tos/many-tools.ipynb"
 )
 
 NOTEBOOKS_NO_EXECUTION = [
@@ -49,7 +48,10 @@ NOTEBOOKS_NO_EXECUTION = [
     "docs/how-tos/map-reduce.ipynb",  # flakiness from structured output, only when running with VCR
     "docs/tutorials/tot/tot.ipynb",
     "docs/how-tos/visualization.ipynb",
-    "docs/tutorials/llm-compiler/LLMCompiler.ipynb"
+    "docs/how-tos/streaming-specific-nodes.ipynb",
+    "docs/tutorials/llm-compiler/LLMCompiler.ipynb",
+    "docs/tutorials/customer-support/customer-support.ipynb",  # relies on openai embeddings, doesn't play well w/ VCR
+    "docs/how-tos/many-tools.ipynb",  # relies on openai embeddings, doesn't play well w/ VCR
 ]
 
 
@@ -86,6 +88,12 @@ def has_blocklisted_command(code: str, metadata: dict) -> bool:
             return True
     return False
 
+def add_mermaid_retries(code: str) -> str:
+    return code.replace(
+        "draw_mermaid_png()",
+        "draw_mermaid_png(max_retries=10, retry_delay=2.0)"
+    )
+
 
 def add_vcr_to_notebook(
     notebook: nbformat.NotebookNode, cassette_prefix: str
@@ -180,6 +188,15 @@ def add_vcr_to_notebook(
     return notebook
 
 
+def add_mermaid_retries_to_notebook(notebook: nbformat.NotebookNode) -> nbformat.NotebookNode:
+    for cell in notebook.cells:
+        if cell.cell_type != "code":
+            continue
+
+        cell.source = add_mermaid_retries(cell.source)
+    return notebook
+
+
 def process_notebooks(should_comment_install_cells: bool) -> None:
     for directory in NOTEBOOK_DIRS:
         for root, _, files in os.walk(directory):
@@ -201,6 +218,8 @@ def process_notebooks(should_comment_install_cells: bool) -> None:
                             notebook, cassette_prefix=cassette_prefix
                         )
 
+                    notebook = add_mermaid_retries_to_notebook(notebook)
+
                     if notebook_path in NOTEBOOKS_NO_EXECUTION:
                         # Add a cell at the beginning to indicate that this notebook should not be executed
                         warning_cell = nbformat.v4.new_markdown_cell(

docs/docs/cloud/reference/env_var.md

@@ -55,6 +55,14 @@ Set `LANGSMITH_TRACING` to `false` to disable tracing to LangSmith.
 
 Configure [log level](https://docs.python.org/3/library/logging.html#logging-levels). Defaults to `INFO`.
 
+## `LOG_JSON`
+
+Set `LOG_JSON` to `true` to render all log messages as JSON objects using the configured `JSONRenderer`. This produces structured logs that can be easily parsed or ingested by log management systems. Defaults to `false`.
+
+## `LOG_COLOR`
+
+This is mainly relevant in the context of using the dev server via the `langgraph dev` command. Set `LOG_COLOR` to `true` to enable ANSI-colored console output when using the default console renderer. Disabling color output by setting this variable to `false` produces monochrome logs. Defaults to `true`.
+
 ## `N_JOBS_PER_WORKER`
 
 Number of jobs per worker for the LangGraph Server task queue. Defaults to `10`.

docs/docs/tutorials/sql-agent.ipynb

@@ -741,13 +741,7 @@
     "from IPython.display import Image, display\n",
     "from langchain_core.runnables.graph import MermaidDrawMethod\n",
     "\n",
-    "display(\n",
-    "    Image(\n",
-    "        app.get_graph().draw_mermaid_png(\n",
-    "            draw_method=MermaidDrawMethod.API,\n",
-    "        )\n",
-    "    )\n",
-    ")"
+    "display(Image(app.get_graph().draw_mermaid_png()))"
    ]
   },
   {

docs/poetry.lock

@@ -3387,14 +3387,14 @@ tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<10"
 
 [[package]]
 name = "langchain-core"
-version = "0.3.52"
+version = "0.3.54"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.9"
 groups = ["docs", "test"]
 files = [
-    {file = "langchain_core-0.3.52-py3-none-any.whl", hash = "sha256:cd137109c1e3d04f5a582c2cae9539b2cd5e4b795f486b58969dbc3d0387fe7c"},
-    {file = "langchain_core-0.3.52.tar.gz", hash = "sha256:f1981ec9efa4fceb11ff5ca57f5f9c8e22859cea3a94f8a044e6de8815afbd57"},
+    {file = "langchain_core-0.3.54-py3-none-any.whl", hash = "sha256:cd42155d9089e2fd4695ee02a4b2bc6daf55b9d4e1a37639647cf2455ed4fa04"},
+    {file = "langchain_core-0.3.54.tar.gz", hash = "sha256:55ce38939038e19b1271f36f512335462d7f64057b531598b3651d2b403e1b42"},
 ]
 
 [package.dependencies]
@@ -3530,7 +3530,7 @@ langchain-core = ">=0.3.45,<1.0.0"
 
 [[package]]
 name = "langgraph"
-version = "0.3.30"
+version = "0.3.31"
 description = "Building stateful, multi-actor applications with LLMs"
 optional = false
 python-versions = ">=3.9.0,<4.0"
@@ -3541,7 +3541,7 @@ develop = true
 [package.dependencies]
 langchain-core = ">=0.1,<0.4"
 langgraph-checkpoint = "^2.0.10"
-langgraph-prebuilt = ">=0.1.1,<0.2"
+langgraph-prebuilt = ">=0.1.8,<0.2"
 langgraph-sdk = "^0.1.42"
 xxhash = "^3.5.0"
 
@@ -5987,7 +5987,6 @@ optional = false
 python-versions = ">=3.8"
 groups = ["test"]
 files = [
-    {file = "pyasn1-0.6.1-py3-none-any.whl", hash = "sha256:0d632f46f2ba09143da3a8afe9e33fb6f92fa2320ab7e886e2d0f7672af84629"},
     {file = "pyasn1-0.6.1.tar.gz", hash = "sha256:6f580d2bdd84365380830acf45550f2511469f673cb4a5ae3857a3170128b034"},
 ]
 
@@ -5999,7 +5998,6 @@ optional = false
 python-versions = ">=3.8"
 groups = ["test"]
 files = [
-    {file = "pyasn1_modules-0.4.1-py3-none-any.whl", hash = "sha256:49bfa96b45a292b711e986f222502c1c9a5e1f4e568fc30e2574a6c7d07838fd"},
     {file = "pyasn1_modules-0.4.1.tar.gz", hash = "sha256:c28e2dbf9c06ad61c71a075c7e0f9fd0f1b0bb2d2ad4377f240d33ac2ab60a7c"},
 ]
 
@@ -8902,4 +8900,4 @@ cffi = ["cffi (>=1.11)"]
 [metadata]
 lock-version = "2.1"
 python-versions = "^3.10"
-content-hash = "45bbc644a3b878063f5cbb75eed56540423315784f8dd42cfd3937c910dfc9c5"
+content-hash = "36d7e4c4eba50d5e4dfb2e99964d7b51fe17d36238a912765cca8fc360216079"

docs/pyproject.toml

@@ -43,6 +43,7 @@ langchain-cohere = "^0.4.2"
 
 [tool.poetry.group.test.dependencies]
 langchain = "^0.3.8"
+langchain-core = "^0.3.54"
 langchain-openai = "^0.3.7"
 langchain-anthropic = "^0.3.8"
 langchain-nomic = "^0.1.3"

libs/checkpoint-postgres/langgraph/store/postgres/base.py

@@ -1320,7 +1320,7 @@ def _ensure_index_config(
     index_config = index_config.copy()
     tokenized: list[tuple[str, Union[Literal["$"], list[str]]]] = []
     tot = 0
-    text_fields = index_config.get("text_fields") or ["$"]
+    text_fields = index_config.get("fields") or ["$"]
     if isinstance(text_fields, str):
         text_fields = [text_fields]
     if not isinstance(text_fields, list):

libs/checkpoint-postgres/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langgraph-checkpoint-postgres"
-version = "2.0.20"
+version = "2.0.21"
 description = "Library with a Postgres implementation of LangGraph checkpoint saver."
 authors = []
 license = "MIT"

libs/checkpoint-postgres/tests/test_async_store.py

@@ -377,7 +377,7 @@ async def _create_vector_store(
             "vector_type": vector_type,
         },
         "distance_type": distance_type,
-        "text_fields": text_fields,
+        "fields": text_fields,
     }
 
     async with await AsyncConnection.connect(

libs/checkpoint-postgres/tests/test_store.py

@@ -401,7 +401,7 @@ def _create_vector_store(
             "vector_type": vector_type,
         },
         "distance_type": distance_type,
-        "text_fields": text_fields,
+        "fields": text_fields,
     }
 
     with Connection.connect(admin_conn_string, autocommit=True) as conn:

libs/langgraph/langgraph/graph/schema_utils.py

@@ -70,6 +70,17 @@ class SchemaCoercionMapper:
                 for n, f in schema.__fields__.items()
             }
             self._construct = schema.construct
+            unhandled_attrs = (
+                "__pre_root_validators__",
+                "__post_root_validators__",
+                "__validators__",
+            )
+            if any(getattr(schema, c, None) for c in unhandled_attrs):
+                self.coerce: Callable[[Any, Any], Union[BaseModelV1, BaseModel]] = (
+                    lambda v, _: schema(**v)
+                )
+            else:
+                self.coerce = self._coerce
 
         elif issubclass(schema, BaseModel):
             self._fields = {
@@ -77,6 +88,13 @@ class SchemaCoercionMapper:
                 for n, f in schema.model_fields.items()
             }
             self._construct: Callable[..., Any] = schema.model_construct  # type: ignore
+            unhandled_attrs = ("validators", "field_validators", "root_validators")
+            if (decorators := getattr(schema, "__pydantic_decorators__", None)) and any(
+                getattr(decorators, attr, None) for attr in unhandled_attrs
+            ):
+                self.coerce = lambda v, _: schema.model_validate(v)
+            else:
+                self.coerce = self._coerce
 
         else:
             raise TypeError("Schema is neither a Pydantic v1 nor v2 model.")
@@ -86,7 +104,7 @@ class SchemaCoercionMapper:
     def __call__(self, input_data: Any, depth: Optional[int] = None) -> Any:
         return self.coerce(input_data, depth)
 
-    def coerce(self, input_data: Any, depth: Optional[int] = None) -> Any:
+    def _coerce(self, input_data: Any, depth: Optional[int] = None) -> Any:
         if depth is None:
             depth = self.max_depth
         if not isinstance(input_data, dict) or depth <= 0:

libs/langgraph/tests/test_pregel.py

@@ -24,12 +24,14 @@ from typing import (
     Any,
     Dict,
     Generator,
+    Generic,
     Iterator,
     List,
     Literal,
     Optional,
     Sequence,
     Tuple,
+    TypeVar,
     Union,
     get_type_hints,
 )
@@ -37,11 +39,7 @@ from typing import (
 import httpx
 import pytest
 from langchain_core.language_models import GenericFakeChatModel
-from langchain_core.runnables import (
-    RunnableConfig,
-    RunnableLambda,
-    RunnablePassthrough,
-)
+from langchain_core.runnables import RunnableConfig, RunnableLambda, RunnablePassthrough
 from langchain_core.runnables.graph import Edge
 from langsmith import traceable
 from pytest_mock import MockerFixture
@@ -1339,22 +1337,26 @@ def test_pending_writes_resume(
             "configurable": {
                 "thread_id": "1",
                 "checkpoint_ns": "",
-                "checkpoint_id": checkpoints[2].config["configurable"]["checkpoint_id"]
-                if checkpoint_during
-                else AnyStr(),
+                "checkpoint_id": (
+                    checkpoints[2].config["configurable"]["checkpoint_id"]
+                    if checkpoint_during
+                    else AnyStr()
+                ),
             }
         },
-        pending_writes=UnsortedSequence(
-            (AnyStr(), "value", 2),
-            (AnyStr(), "__error__", 'ConnectionError("I\'m not good")'),
-            (AnyStr(), "value", 3),
-        )
-        if checkpoint_during
-        else UnsortedSequence(
-            (AnyStr(), "value", 2),
-            (AnyStr(), "__error__", 'ConnectionError("I\'m not good")'),
-            # the write against the previous checkpoint is not saved, as it is
-            # produced in a run where only the next checkpoint (the last) is saved
+        pending_writes=(
+            UnsortedSequence(
+                (AnyStr(), "value", 2),
+                (AnyStr(), "__error__", 'ConnectionError("I\'m not good")'),
+                (AnyStr(), "value", 3),
+            )
+            if checkpoint_during
+            else UnsortedSequence(
+                (AnyStr(), "value", 2),
+                (AnyStr(), "__error__", 'ConnectionError("I\'m not good")'),
+                # the write against the previous checkpoint is not saved, as it is
+                # produced in a run where only the next checkpoint (the last) is saved
+            )
         ),
     )
     if not checkpoint_during:
@@ -3105,10 +3107,10 @@ def test_nested_pydantic_models(version: str) -> None:
     # Import necessary modules
 
     if version == "v1":
-        from pydantic.v1 import (  # type: ignore
+        from pydantic.v1 import (
             BaseModel,
             ByteSize,
-            Field,
+            Field,  # type: ignore
             SecretStr,
             confloat,
             conint,
@@ -3116,10 +3118,10 @@ def test_nested_pydantic_models(version: str) -> None:
             constr,
         )
     else:
-        from pydantic import (  # type: ignore
+        from pydantic import (
             BaseModel,
             ByteSize,
-            Field,
+            Field,  # type: ignore
             SecretStr,
             confloat,
             conint,
@@ -3355,6 +3357,107 @@ def test_nested_pydantic_models(version: str) -> None:
     assert {**new_inputs, **update} == graph.invoke(new_inputs.copy())
 
 
+def test_pydantic_state_field_validator():
+    from pydantic import BaseModel, field_validator, model_validator
+
+    class State(BaseModel):
+        name: str
+        text: str = ""
+        only_root: int = 13
+
+        @field_validator("name", mode="after")
+        @classmethod
+        def validate_name(cls, value):
+            if value[0].islower():
+                raise ValueError("Name must start with a capital letter")
+            return "Validated " + value
+
+        @model_validator(mode="before")
+        @classmethod
+        def validate_amodel(cls, values: "State"):
+            return values | {"only_root": 392}
+
+    input_state = {"name": "John"}
+
+    def process_node(state: State):
+        assert State.model_validate(input_state) == state
+        return {"text": "Hello, " + state.name + "!"}
+
+    builder = StateGraph(state_schema=State)
+    builder.add_node("process", process_node)
+    builder.add_edge(START, "process")
+    builder.add_edge("process", END)
+    g = builder.compile()
+    res = g.invoke(input_state)
+    assert res["text"] == "Hello, Validated John!"
+
+
+def test_pydantic_v1_state_root_validator():
+    from pydantic.v1 import BaseModel, root_validator
+
+    class State(BaseModel):
+        name: str
+        text: str = ""
+        only_root: int = 13
+
+        @root_validator(pre=True)
+        @classmethod
+        def validate(cls, values: dict):
+            values["name"] = "Validated " + values["name"]
+            return values | {"only_root": 396}
+
+    input_state = {"name": "John"}
+
+    def process_node(state: State):
+        assert State(**input_state) == state
+        return {"text": "Hello, " + state.name + "!"}
+
+    builder = StateGraph(state_schema=State)
+    builder.add_node("process", process_node)
+    builder.add_edge(START, "process")
+    builder.add_edge("process", END)
+    g = builder.compile()
+    res = g.invoke(input_state)
+    assert res["text"] == "Hello, Validated John!"
+
+
+def test_pydantic_generics():
+    from pydantic import BaseModel
+
+    class A(BaseModel):
+        a: str
+
+    class B(BaseModel):
+        b: str
+
+    AorB = TypeVar("AorB", A, B)
+
+    class C(BaseModel, Generic[AorB]):
+        c: AorB
+
+    class State(BaseModel):
+        text: str
+        count: int
+        c: C[A]
+
+    input_state = {"text": "1", "count": 0, "c": {"c": {"a": "1"}}}
+    expected_input = State.model_validate(input_state)
+
+    def process_node(state: State):
+        assert state == expected_input
+        new_text = ", the type of c is " + str(type(state.c.c))
+
+        return {"text": state.text + new_text, "count": state.count + 1}
+
+    builder = StateGraph(State)
+    builder.add_node("process", process_node)
+    builder.add_edge(START, "process")
+    g = builder.compile()
+
+    g.invoke(input_state)
+    g.invoke(expected_input)
+
+
 @pytest.mark.parametrize("checkpointer_name", ALL_CHECKPOINTERS_SYNC)
 def test_in_one_fan_out_state_graph_waiting_edge_plus_regular(
     request: pytest.FixtureRequest, checkpointer_name: str

libs/sdk-js/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@langchain/langgraph-sdk",
-  "version": "0.0.67",
+  "version": "0.0.69",
   "description": "Client library for interacting with the LangGraph API",
   "type": "module",
   "packageManager": "yarn@1.22.19",

libs/sdk-js/src/client.ts

@@ -1,42 +1,41 @@
 import {
   Assistant,
   AssistantGraph,
+  AssistantVersion,
   CancelAction,
+  Checkpoint,
   Config,
+  Cron,
+  CronCreateForThreadResponse,
+  CronCreateResponse,
   DefaultValues,
   GraphSchema,
+  Item,
+  ListNamespaceResponse,
   Metadata,
   Run,
   RunStatus,
+  SearchItemsResponse,
+  Subgraphs,
   Thread,
   ThreadState,
-  Cron,
-  AssistantVersion,
-  Subgraphs,
-  Checkpoint,
-  SearchItemsResponse,
-  ListNamespaceResponse,
-  Item,
   ThreadStatus,
-  CronCreateResponse,
-  CronCreateForThreadResponse,
 } from "./schema.js";
-import { AsyncCaller, AsyncCallerParams } from "./utils/async_caller.js";
-import { IterableReadableStream } from "./utils/stream.js";
 import type {
+  Command,
+  CronsCreatePayload,
+  OnConflictBehavior,
   RunsCreatePayload,
   RunsStreamPayload,
   RunsWaitPayload,
   StreamEvent,
-  CronsCreatePayload,
-  OnConflictBehavior,
-  Command,
 } from "./types.js";
-import { mergeSignals } from "./utils/signals.js";
+import type { StreamMode, TypedAsyncGenerator } from "./types.stream.js";
+import { AsyncCaller, AsyncCallerParams } from "./utils/async_caller.js";
 import { getEnvironmentVariable } from "./utils/env.js";
-import { _getFetchImplementation } from "./singletons/fetch.js";
-import type { TypedAsyncGenerator, StreamMode } from "./types.stream.js";
+import { mergeSignals } from "./utils/signals.js";
 import { BytesLineDecoder, SSEDecoder } from "./utils/sse.js";
+import { IterableReadableStream } from "./utils/stream.js";
 /**
  * Get the API key from the environment.
  * Precedence:
@@ -619,6 +618,15 @@ export class ThreadsClient<
      * Must be one of 'idle', 'busy', 'interrupted' or 'error'.
      */
     status?: ThreadStatus;
+    /**
+     * Sort by.
+     */
+    sortBy?: "id" | "status" | "created_at" | "updated_at";
+    /**
+     * Sort order.
+     * Must be one of 'asc' or 'desc'.
+     */
+    sortOrder?: "asc" | "desc";
   }): Promise<Thread<ValuesType>[]> {
     return this.fetch<Thread<ValuesType>[]>("/threads/search", {
       method: "POST",
@@ -627,6 +635,8 @@ export class ThreadsClient<
         limit: query?.limit ?? 10,
         offset: query?.offset ?? 0,
         status: query?.status,
+        sort_by: query?.sortBy,
+        sort_order: query?.sortOrder,
       },
     });
   }

libs/sdk-js/src/react-ui/client.tsx

@@ -175,7 +175,11 @@ export function LoadExternalComponent({
   }, [uiClient, uiNamespace, message.name, shadowRootId, hasClientComponent]);
 
   if (hasClientComponent) {
-    return React.createElement(clientComponent, message.props);
+    return (
+      <UseStreamContext.Provider value={{ stream, meta }}>
+        {React.createElement(clientComponent, message.props)}
+      </UseStreamContext.Provider>
+    );
   }
 
   return (

libs/sdk-py/langgraph_sdk/client.py

@@ -1043,6 +1043,8 @@ class ThreadsClient:
         status: Optional[ThreadStatus] = None,
         limit: int = 10,
         offset: int = 0,
+        sort_by: Literal["id", "status", "created_at", "updated_at"] = "created_at",
+        sort_order: Literal["asc", "desc"] = "asc",
         headers: Optional[dict[str, str]] = None,
     ) -> list[Thread]:
         """Search for threads.
@@ -1079,6 +1081,10 @@ class ThreadsClient:
             payload["values"] = values
         if status:
             payload["status"] = status
+        if sort_by:
+            payload["sort_by"] = sort_by
+        if sort_order:
+            payload["sort_order"] = sort_order
         return await self.http.post(
             "/threads/search",
             json=payload,

libs/sdk-py/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langgraph-sdk"
-version = "0.1.61"
+version = "0.1.62"
 description = "SDK for interacting with LangGraph API"
 authors = []
 license = "MIT"