Remove the redundant `lc_attributes` override from `ChatXAI`. The
`xai_api_base` field is a declared Pydantic `Field`, so
`Serializable.to_json()` already picks it up via its standard field
iteration loop (line 225-232 in `serializable.py`). The override was a
no-op — it re-inserted the same key with the same value that the base
serialization already included.
Add `base_url` alias and `XAI_API_BASE` env variable support to
`ChatXAI.xai_api_base`, aligning the xAI integration with the pattern
used across other partner packages (OpenAI, Groq, Fireworks, etc.).
Previously the base URL was a plain string field with no alias or
env-var lookup, making it inconsistent with the rest of the ecosystem
and harder to configure in deployment environments.
## Changes
- Add `alias="base_url"` and `default_factory=from_env("XAI_API_BASE",
default="https://api.x.ai/v1/")` to `ChatXAI.xai_api_base`, matching the
convention in `langchain_openai`, `langchain_groq`, and
`langchain_fireworks`
Extract additional fields from models.dev into `_model_data_to_profile`:
`name`, `status`, `release_date`, `last_updated`, `open_weights`,
`attachment`, `temperature`
Move the model profile refresh logic from an inline bash script in the
GitHub Actions workflow into a `make refresh-profiles` target in
`libs/model-profiles/Makefile`. This makes it runnable locally with a
single command and keeps the provider map in one place instead of
duplicated between CI and developer docs.
Automated refresh of model profile data for all in-monorepo partner
integrations via `langchain-profiles refresh`.
🤖 Generated by the `refresh_model_profiles` workflow.
Co-authored-by: mdrxy <61371264+mdrxy@users.noreply.github.com>
- Sort model profiles alphabetically by model ID (the top-level
`_PROFILES` dictionary keys, e.g. `claude-3-5-haiku-20241022`,
`gpt-4o-mini`) before writing `_profiles.py`, so that regenerating
profiles only shows actual data changes in diffs — not random reordering
from the models.dev API response order
- Regenerate all 10 partner profile files with the new sorted ordering
- Add `text_inputs` and `text_outputs` fields to `ModelProfile`
- Regenerate `_profiles.py` for all providers
## Why
models.dev data includes `'text'` as both an input and output modality,
but we didn't capture it.
models.dev broadly contains models without text input (Whisper/ASR) and
without text output (image generators, TTS).
Without this, downstream consumers can't filter on model text support
(e.g. preventing users from passing text input to an audio-only model).
---
We'd need to also run for Google, AWS and cut releases for all to
propagate
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)
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.")
```
## 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>
