When a langsmith `@traceable` function invokes a LangChain Runnable or
LangGraph subgraph, the callback manager's `_configure` function injects
the `@traceable` RunTree into the `LangChainTracer`'s `run_map` so that
child runs can resolve their parent for trace nesting. However, since
the RunTree was created outside the tracer's callback lifecycle,
`_end_trace` never removes it. The entry persists in `run_map`
indefinitely, retaining the full RunTree and its entire child tree.
In applications with nested subgraph invocations (e.g. an outer
investigation graph delegating to skill agent subgraphs, each compiled
as their own `StateGraph`), this causes RunTree objects to accumulate
linearly with every call.
**Fix:** Track which `run_map` entries were injected externally via a
shared `_external_run_ids` refcount dict on `_TracerCore`. When
`_start_trace` adds a child under an external parent, it increments the
count. When `_end_trace` finishes a child, it decrements — and evicts
the external parent from `run_map` once the last child completes.
The refcount (rather than a simple set) is necessary because a single
external parent may have multiple sibling children in the callback chain
(e.g. a `prompt | llm` `RunnableSequence`). Only truly external runs are
tracked — the `_configure` guard `if run_id_str not in handler.run_map`
prevents tracer-managed runs from being misclassified.
it looks scary but i promise it is not
improving documentation consistency across core. primarily update
docstrings and comments for better formatting, readability, and
accuracy, as well as add minor clarifications and formatting
improvements to user-facing documentation.
# Add `tool_call_id` to `on_tool_error` event data
## Summary
This PR addresses issue #33597 by adding `tool_call_id` to the
`on_tool_error` callback event data. This enables users to link tool
errors to specific tool calls in stateless agent implementations, which
is essential for building OpenAI-compatible APIs and tracking tool
execution flows.
## Problem
When streaming events using `astream_events` with `version="v2"`, the
`on_tool_error` event only included the error and input data, but lacked
the `tool_call_id`. This made it difficult to:
- Link errors to specific tool calls in stateless agent scenarios
- Implement OpenAI-compatible APIs that require tool call tracking
- Track tool execution flows when using `run_id` is not sufficient
## Solution
The fix adds `tool_call_id` propagation through the callback chain:
1. **Pass `tool_call_id` to callbacks**: Updated `BaseTool.run()` and
`BaseTool.arun()` to pass `tool_call_id` to both `on_tool_start` and
`on_tool_error` callbacks
2. **Store in event stream handler**: Modified
`_AstreamEventsCallbackHandler` to store `tool_call_id` in run info
during `on_tool_start`
3. **Include in error events**: Updated `on_tool_error` handler to
extract and include `tool_call_id` in the event data
## Changes
- **`libs/core/langchain_core/tools/base.py`**:
- Pass `tool_call_id` to `on_tool_start` in both sync and async methods
- Pass `tool_call_id` to `on_tool_error` when errors occur
- **`libs/core/langchain_core/tracers/event_stream.py`**:
- Store `tool_call_id` in run info during `on_tool_start`
- Extract `tool_call_id` from kwargs or run info in `on_tool_error`
- Include `tool_call_id` in the `on_tool_error` event data
## Testing
The fix was verified by:
1. Direct tool invocation: Confirmed `tool_call_id` appears in
`on_tool_error` event data when calling tools directly
2. Agent integration: Tested with `create_agent` to ensure
`tool_call_id` is present in error events during agent execution
```python
# Example verification
async for event in agent.astream_events(
{"messages": "Please demonstrate a tool error"},
version="v2",
):
if event["event"] == "on_tool_error":
assert "tool_call_id" in event["data"] # ✓ Now passes
print(event["data"]["tool_call_id"])
```
## Backward Compatibility
- ✅ Fully backward compatible: `tool_call_id` is optional (can be
`None`)
- ✅ No breaking changes: All changes are additive
- ✅ Existing code continues to work without modification
## Related Issues
Fixes#33597
---------
Co-authored-by: Mason Daugherty <github@mdrxy.com>
* FIxed where possible
* Used `cast` when not possible to fix
---------
Co-authored-by: Mason Daugherty <github@mdrxy.com>
Co-authored-by: Mason Daugherty <mason@langchain.dev>
## Problem
The `draw_mermaid_png()` function fails with HTTP 400 when using named
background colors like `white`. This is because named colors get
prefixed with `!` (e.g., `!white`) but this special character is not
URL-encoded before being added to the API URL.
As reported in #34444, the URL parameter `bgColor=!white` causes
mermaid.ink to return a 400 Bad Request error.
## Solution
URL-encode the `background_color` parameter using `urllib.parse.quote()`
before constructing the API URL. This ensures special characters like
`!` are properly encoded as `%21`.
## Changes
- Added `import urllib.parse`
- URL-encode `background_color` value with
`urllib.parse.quote(str(background_color), safe="")`
- Added 2 unit tests:
- `test_mermaid_bgcolor_url_encoding`: Verifies named colors are
properly encoded
- `test_mermaid_bgcolor_hex_not_encoded`: Verifies hex colors work
correctly
## Testing
```bash
pytest tests/unit_tests/runnables/test_graph.py::test_mermaid_bgcolor_url_encoding -v
pytest tests/unit_tests/runnables/test_graph.py::test_mermaid_bgcolor_hex_not_encoded -v
```
Both tests pass.
Fixes#34444
---
*This contribution was made with AI assistance (Claude).*
Co-authored-by: Mr-Neutr0n <mrneutron@users.noreply.github.com>
Co-authored-by: Mason Daugherty <mason@langchain.dev>
# Description
This submission is a part of a school project from our team of 4
@EminGul @williamzhu54 @annay54 @donttouch22.
Our pull request fixes the issue with RunnableParallel scheme being
empty by returning the correct schema output when children runnable
input schemas use TypedDicts.
# Issue
Fixes#24326
# Dependencies
No extra dependencies required for this fix.
# Feedback
Any feedback and advice is gladly welcomed. Please feel free to let us
know what we can change or improve upon regarding this issue.
---------
Co-authored-by: Mason Daugherty <mason@langchain.dev>
Co-authored-by: Mason Daugherty <github@mdrxy.com>
* Fix detection of support of context in `asyncio.create_task`
* Fix: in Python 3.14 `asyncio.get_event_loop()` raises an exception if
there's no running loop
* Bump pydantic to version 2.12
* Skips tests with pydantic v1 models as they are not supported with
Python 3.14
* Run core tests with Python 3.14 in CI.
---------
Co-authored-by: Mason Daugherty <mason@langchain.dev>
Co-authored-by: Sydney Runkle <54324534+sydney-runkle@users.noreply.github.com>
Largely:
- Remove explicit `"Default is x"` since new refs show default inferred
from sig
- Inline code (useful for eventual parsing)
- Fix code block rendering (indentations)
Removed:
- `libs/core/langchain_core/chat_history.py`: `add_user_message` and
`add_ai_message` in favor of `add_messages` and `aadd_messages`
- `libs/core/langchain_core/language_models/base.py`: `predict`,
`predict_messages`, and async versions in favor of `invoke`. removed
`_all_required_field_names` since it was a wrapper on
`get_pydantic_field_names`
- `libs/core/langchain_core/language_models/chat_models.py`:
`callback_manager` param in favor of `callbacks`. `__call__` and
`call_as_llm` method in favor of `invoke`
- `libs/core/langchain_core/language_models/llms.py`: `callback_manager`
param in favor of `callbacks`. `__call__`, `predict`, `apredict`, and
`apredict_messages` methods in favor of `invoke`
- `libs/core/langchain_core/prompts/chat.py`: `from_role_strings` and
`from_strings` in favor of `from_messages`
- `libs/core/langchain_core/prompts/pipeline.py`: removed
`PipelinePromptTemplate`
- `libs/core/langchain_core/prompts/prompt.py`: `input_variables` param
on `from_file` as it wasn't used
- `libs/core/langchain_core/tools/base.py`: `callback_manager` param in
favor of `callbacks`
- `libs/core/langchain_core/tracers/context.py`: `tracing_enabled` in
favor of `tracing_enabled_v2`
- `libs/core/langchain_core/tracers/langchain_v1.py`: entire module
- `libs/core/langchain_core/utils/loading.py`: entire module,
`try_load_from_hub`
- `libs/core/langchain_core/vectorstores/in_memory.py`: `upsert` in
favor of `add_documents`
- `libs/standard-tests/langchain_tests/integration_tests/chat_models.py`
and `libs/standard-tests/langchain_tests/unit_tests/chat_models.py`:
`tool_choice_value` as models should accept `tool_choice="any"`
- `langchain` will consequently no longer expose these items if it was
previously
---------
Co-authored-by: Mohammad Mohtashim <45242107+keenborder786@users.noreply.github.com>
Co-authored-by: Caspar Broekhuizen <caspar@langchain.dev>
Co-authored-by: ccurme <chester.curme@gmail.com>
Co-authored-by: Christophe Bornet <cbornet@hotmail.com>
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
Co-authored-by: Sadra Barikbin <sadraqazvin1@yahoo.com>
Co-authored-by: Vadym Barda <vadim.barda@gmail.com>
### Description
* Replace the Mermaid graph node label escaping logic
(`_escape_node_label`) with `_to_safe_id`, which converts a string into
a unique, Mermaid-compatible node id. Ensures nodes with special
characters always render correctly.
**Before**
* Invalid characters (e.g. `开`) replaced with `_`. Causes collisions
between nodes with names that are the same length and contain all
non-safe characters:
```python
_escape_node_label("开") # '_'
_escape_node_label("始") # '_' same as above, but different character passed in. not a unique mapping.
```
**After**
```python
_to_safe_id("开") # \5f00
_to_safe_id("始") # \59cb unique!
```
### Tests
* Rename `test_graph_mermaid_escape_node_label()` to
`test_graph_mermaid_to_safe_id()` and update function logic to use
`_to_safe_id`
* Add `test_graph_mermaid_special_chars()`
### Issue
Fixeslangchain-ai/langgraph#6036
Description: Fixes a bug in RunnableRetry where .batch / .abatch could
return misordered outputs (e.g. inputs [0,1,2] yielding [1,1,2]) when
some items succeeded on an earlier attempt and others were retried. Root
cause: successful results were stored keyed by the index within the
shrinking “pending” subset rather than the original input index, causing
collisions and reordered/duplicated outputs after retries. Fix updates
_batch and _abatch to:
- Track remaining original indices explicitly.
- Call underlying batch/abatch only on remaining inputs.
- Map results back to original indices.
- Preserve final ordering by reconstructing outputs in original
positional order.
Issue: Fixes#21326
Tests:
- Added regression tests: test_retry_batch_preserves_order and
test_async_retry_batch_preserves_order asserting correct ordering after
a single controlled failure + retry.
- Existing retry tests still pass.
Dependencies:
- None added or changed.
---------
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
- **Description:** Currently,
`langchain_core.runnables.graph_mermaid.py` is hardcoded to use
mermaid.ink to render graph diagrams. It would be nice to allow users to
specify a custom URL, e.g. for self-hosted instances of the Mermaid
server.
- **Issue:** [Langchain Forum: allow custom mermaid API
URL](https://forum.langchain.com/t/feature-request-allow-custom-mermaid-api-url/1472)
- **Dependencies:** None
- [X] **Add tests and docs**: Added unit tests using mock requests.
- [X] **Lint and test**: Run `make format`, `make lint` and `make test`.
Minimal example using the feature:
```python
import os
import operator
from pathlib import Path
from typing import Any, Annotated, TypedDict
from langgraph.graph import StateGraph
class State(TypedDict):
messages: Annotated[list[dict[str, Any]], operator.add]
def hello_node(state: State) -> State:
return {"messages": [{"role": "assistant", "content": "pong!"}]}
builder = StateGraph(State)
builder.add_node("hello_node", hello_node)
builder.add_edge("__start__", "hello_node")
builder.add_edge("hello_node", "__end__")
graph = builder.compile()
# Run graph
output = graph.invoke({"messages": [{"role": "user", "content": "ping?"}]})
# Draw graph
Path("graph.png").write_bytes(graph.get_graph().draw_mermaid_png(base_url="https://custom-mermaid.ink"))
```
---------
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
