Fixes a bug introduced with commit 85f1ba2 (released in `langchain ==
1.2.1`).
Whenever the index embedding of the langgraph-server is configured with
`azure_openai` provider, the wrong class is going to be initialized (and
fails to do so if the now unexpected credentials in environment variable
`OPENAI_API_KEY` is not provided).
Example configuration file `langgraph.json` that will reproduce the
issue:
(see
https://docs.langchain.com/langsmith/cli#adding-semantic-search-to-the-store)
```json
{
"dependencies": ["."],
"graphs": {
"chat": "src/agents/chat/graph.py:graph",
},
"store": {
"index": {
"embed": "azure_openai:text-embedding-3-small",
"dims": 1536
}
},
"python_version": "3.13",
"image_distro": "wolfi"
}
```
The agent should only make a single call to update the todo list at a
time. A parallel call doesn't make sense, but also cannot work as
there's no obvious reducer to use.
On parallel calls of the todo tool, we return ToolMessage containing to
guide the LLM to not call the tool in parallel.
---------
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
Fixes#34517
Supersedes #34557, #34570
Fixes token inflation in `SummarizationMiddleware` that caused context
window overflow during summarization.
**Root cause:** When formatting messages for the summary prompt,
`str(messages)` was implicitly called, which includes all Pydantic
metadata fields (`usage_metadata`, `response_metadata`,
`additional_kwargs`, etc.). This caused the stringified representation
to use ~2.5x more tokens than `count_tokens_approximately` estimates.
**Problem:**
- Summarization triggers at 85% of context window based on
`count_tokens_approximately`
- But `str(messages)` in the prompt uses 2.5x more tokens
- Results in `ContextLengthExceeded`
**Fix:** Use `get_buffer_string()` to format messages, which produces
compact output:
```
Human: What's the weather?
AI: Let me check...[tool_calls]
Tool: 72°F and sunny
```
Instead of verbose Pydantic repr:
```python
[HumanMessage(content='What's the weather?', additional_kwargs={}, response_metadata={}), ...]
```
Fixed typo in ImportError messages where "langchain experiment" should
be "langchain_experimental" for consistency with the actual package
name.
This helps improve clarity for users who encounter these error messages
when trying to use deprecated tools that have moved to the
langchain_experimental package.
Related issues: #13858, #13859
Co-authored-by: Ademola <ademicho@gmail>
**Description:**
*Closes
#[33883](https://github.com/langchain-ai/langchain/issues/33883)*
Chat model cache keys are generated by serializing messages via
`dumps(messages)`. The optional `BaseMessage.id` field (a UUID used
solely for tracing/threading) is included in this serialization, causing
functionally identical messages to produce different cache keys. This
results in repeated API calls, cache bloat, and degraded performance in
production workloads (e.g., agents, RAG chains, long conversations).
This change normalizes messages **only for cache key generation** by
stripping the nonsemantic `id` field using Pydantic V2’s
`model_copy(update={"id": None})`. The normalization is applied in both
synchronous and asynchronous cache paths (`_generate_with_cache` /
`_agenerate_with_cache`) immediately before `dumps()`.
```python
normalized_messages = [
msg.model_copy(update={"id": None})
if getattr(msg, "id", None) is not None
else msg
for msg in messages
]
prompt = dumps(normalized_messages)
---------
Co-authored-by: Mason Daugherty <mason@langchain.dev>
Co-authored-by: Mason Daugherty <github@mdrxy.com>
Summary
Fixes an issue where HTMLSemanticPreservingSplitter failed to preserve
elements nested inside non-container tags. With these changes, preserved
elements are now correctly detected and handled at any nesting depth.
Root Cause
`_process_element()` only recursed into a small set of hard-coded
container tags (`html`, `body`, `div`, `main`). For other tags, the
subtree was flattened into text, preventing nested preserved elements
(inside `<p>`, `<section>`, `<article>`, etc.) from being detected.
Fix
- Updated traversal logic in _process_element (html.py) to recursively
process child elements for any tag that contains nested elements
- Avoided duplicate text extraction
- Preserved correct placeholder ordering
- Treated leaf nodes as text only
Tests
Adds regression tests covering preserved elements nested inside
non-container tags, including:
- table inside section
- nested divs
- code inside paragraph
All existing tests pass (make lint, format, test, etc).
Breaking changes
None.
Fixes
Fixes#31569
Disclaimer
GitHub Copilot was used to assist with test case design in
test_text_splitters.py and documentation comments; all code logic was
manually implemented and reviewed.
---------
Co-authored-by: julih <julih@julihs-MacBook-Pro.local>
Co-authored-by: Mason Daugherty <github@mdrxy.com>
Co-authored-by: Mason Daugherty <mason@langchain.dev>
This PR updates an outdated GitHub Action version.
- Updated `astral-sh/setup-uv` from `v6` to `v7` in
`.github/actions/uv_setup/action.yml`
Looks like this was missed as part of
https://github.com/langchain-ai/langchain/pull/33457 so hopefully safe
to bring it into alignment.
Addresses a flaky test
When executing `exit 1` as a startup command, the shell process
terminates immediately. The code then tries to write a marker command
(`printf '...'`) to stdin, but the pipe is already broken because the
shell has exited, causing `BrokenPipeError`.
