**TL;DR much of the provided `Makefile` targets were broken, and any
time I wanted to preview changes locally I either had to refer to a
command Chester gave me or try waiting on a Vercel preview deployment.
With this PR, everything should behave like normal.**
Significant updates to the `Makefile` and documentation files, focusing
on improving usability, adding clear messaging, and fixing/enhancing
documentation workflows.
### Updates to `Makefile`:
#### Enhanced build and cleaning processes:
- Added informative messages (e.g., "📚 Building LangChain
documentation...") to makefile targets like `docs_build`, `docs_clean`,
and `api_docs_build` for better user feedback during execution.
- Introduced a `clean-cache` target to the `docs` `Makefile` to clear
cached dependencies and ensure clean builds.
#### Improved dependency handling:
- Modified `install-py-deps` to create a `.venv/deps_installed` marker,
preventing redundant/duplicate dependency installations and improving
efficiency.
#### Streamlined file generation and infrastructure setup:
- Added caching for the LangServe README download and parallelized
feature table generation
- Added user-friendly completion messages for targets like `copy-infra`
and `render`.
#### Documentation server updates:
- Enhanced the `start` target with messages indicating server start and
URL for local documentation viewing.
---
### Documentation Improvements:
#### Content clarity and consistency:
- Standardized section titles for consistency across documentation
files.
[[1]](diffhunk://#diff-9b1a85ea8a9dcf79f58246c88692cd7a36316665d7e05a69141cfdc50794c82aL1-R1)
[[2]](diffhunk://#diff-944008ad3a79d8a312183618401fcfa71da0e69c75803eff09b779fc8e03183dL1-R1)
- Refined phrasing and formatting in sections like "Dependency
management" and "Formatting and linting" for better readability.
[[1]](diffhunk://#diff-2069d4f956ab606ae6d51b191439283798adaf3a6648542c409d258131617059L6-R6)
[[2]](diffhunk://#diff-2069d4f956ab606ae6d51b191439283798adaf3a6648542c409d258131617059L84-R82)
#### Enhanced workflows:
- Updated instructions for building and viewing documentation locally,
including tips for specifying server ports and handling API reference
previews.
[[1]](diffhunk://#diff-048deddcfd44b242e5b23aed9f2e9ec73afc672244ce14df2a0a316d95840c87L60-R94)
[[2]](diffhunk://#diff-048deddcfd44b242e5b23aed9f2e9ec73afc672244ce14df2a0a316d95840c87L82-R126)
- Expanded guidance on cleaning documentation artifacts and using
linting tools effectively.
[[1]](diffhunk://#diff-048deddcfd44b242e5b23aed9f2e9ec73afc672244ce14df2a0a316d95840c87L82-R126)
[[2]](diffhunk://#diff-048deddcfd44b242e5b23aed9f2e9ec73afc672244ce14df2a0a316d95840c87L107-R142)
#### API reference documentation:
- Improved instructions for generating and formatting in-code
documentation, highlighting best practices for docstring writing.
[[1]](diffhunk://#diff-048deddcfd44b242e5b23aed9f2e9ec73afc672244ce14df2a0a316d95840c87L107-R142)
[[2]](diffhunk://#diff-048deddcfd44b242e5b23aed9f2e9ec73afc672244ce14df2a0a316d95840c87L144-R186)
---
### Minor Changes:
- Added support for a new package name (`langchain_v1`) in the API
documentation generation script.
- Fixed minor capitalization and formatting issues in documentation
files.
[[1]](diffhunk://#diff-2069d4f956ab606ae6d51b191439283798adaf3a6648542c409d258131617059L40-R40)
[[2]](diffhunk://#diff-2069d4f956ab606ae6d51b191439283798adaf3a6648542c409d258131617059L166-R160)
---------
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Follow up to https://github.com/langchain-ai/langsmith-sdk/pull/1696,
I've bumped the `langsmith` version where applicable in `uv.lock`.
Type checking problems here because deps have been updated in
`pyproject.toml` and `uv lock` hasn't been run - we should enforce that
in the future - goes with the other dependabot todos :).
Generally, this PR is CI performance focused + aims to clean up some
dependencies at the same time.
1. Unpins upper bounds for `numpy` in all `pyproject.toml` files where
`numpy` is specified
2. Requires `numpy >= 2.1.0` for Python 3.13 and `numpy > v1.26.0` for
Python 3.12, plus a `numpy` min version bump for `chroma`
3. Speeds up CI by minutes - linting on Python 3.13, installing `numpy <
2.1.0` was taking [~3
minutes](https://github.com/langchain-ai/langchain/actions/runs/14316342925/job/40123305868?pr=30713),
now the entire env setup takes a few seconds
4. Deleted the `numpy` test dependency from partners where that was not
used, specifically `huggingface`, `voyageai`, `xai`, and `nomic`.
It's a bit unfortunate that `langchain-community` depends on `numpy`, we
might want to try to fix that in the future...
Closes https://github.com/langchain-ai/langchain/issues/26026
Fixes https://github.com/langchain-ai/langchain/issues/30555
- Test if models support forcing tool calls via `tool_choice`. If they
do, they should support
- `"any"` to specify any tool
- the tool name as a string to force calling a particular tool
- Add `tool_choice` to signature of `BaseChatModel.bind_tools` in core
- Deprecate `tool_choice_value` in standard tests in favor of a boolean
`has_tool_choice`
Will follow up with PRs in external repos (tested in AWS and Google
already).
https://docs.x.ai/docs/guides/structured-outputs
Interface appears identical to OpenAI's.
```python
from langchain.chat_models import init_chat_model
from pydantic import BaseModel
class Joke(BaseModel):
setup: str
punchline: str
llm = init_chat_model("xai:grok-2").with_structured_output(
Joke, method="json_schema"
)
llm.invoke("Tell me a joke about cats.")
```
These are set in Github workflows, but forgot to add them to most
makefiles for convenience when developing locally.
`uv run` will automatically sync the lock file. Because many of our
development dependencies are local installs, it will pick up version
changes and update the lock file. Passing `--frozen` or setting this
environment variable disables the behavior.
## Goal
Solve the following problems with `langchain-openai`:
- Structured output with `o1` [breaks out of the
box](https://langchain.slack.com/archives/C050X0VTN56/p1735232400232099).
- `with_structured_output` by default does not use OpenAI’s [structured
output
feature](https://platform.openai.com/docs/guides/structured-outputs).
- We override API defaults for temperature and other parameters.
## Breaking changes:
- Default method for structured output is changing to OpenAI’s dedicated
[structured output
feature](https://platform.openai.com/docs/guides/structured-outputs).
For schemas specified via TypedDict or JSON schema, strict schema
validation is disabled by default but can be enabled by specifying
`strict=True`.
- To recover previous default, pass `method="function_calling"` into
`with_structured_output`.
- Models that don’t support `method="json_schema"` (e.g., `gpt-4` and
`gpt-3.5-turbo`, currently the default model for ChatOpenAI) will raise
an error unless `method` is explicitly specified.
- To recover previous default, pass `method="function_calling"` into
`with_structured_output`.
- Schemas specified via Pydantic `BaseModel` that have fields with
non-null defaults or metadata (like min/max constraints) will raise an
error.
- To recover previous default, pass `method="function_calling"` into
`with_structured_output`.
- `strict` now defaults to False for `method="json_schema"` when schemas
are specified via TypedDict or JSON schema.
- To recover previous behavior, use `with_structured_output(schema,
strict=True)`
- Schemas specified via Pydantic V1 will raise a warning (and use
`method="function_calling"`) unless `method` is explicitly specified.
- To remove the warning, pass `method="function_calling"` into
`with_structured_output`.
- Streaming with default structured output method / Pydantic schema no
longer generates intermediate streamed chunks.
- To recover previous behavior, pass `method="function_calling"` into
`with_structured_output`.
- We no longer override default temperature (was 0.7 in LangChain, now
will follow OpenAI, currently 1.0).
- To recover previous behavior, initialize `ChatOpenAI` or
`AzureChatOpenAI` with `temperature=0.7`.
- Note: conceptually there is a difference between forcing a tool call
and forcing a response format. Tool calls may have more concise
arguments vs. generating content adhering to a schema. Prompts may need
to be adjusted to recover desired behavior.
---------
Co-authored-by: Jacob Lee <jacoblee93@gmail.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
