Add support for the `X-OpenRouter-Categories` header via a new
`app_categories` field on `ChatOpenRouter`, and extract inline client
construction into a dedicated `_build_client` method.
PR #35788 added 7 new fields to the `langchain-profiles` CLI output
(`name`, `status`, `release_date`, `last_updated`, `open_weights`,
`attachment`, `temperature`) but didn't update `ModelProfile` in
`langchain-core`. Partner packages like `langchain-aws` that set
`extra="forbid"` on their Pydantic models hit `extra_forbidden`
validation errors when Pydantic encountered undeclared TypedDict keys at
construction time. This adds the missing fields, makes `ModelProfile`
forward-compatible, provides a base-class hook so partners can stop
duplicating model-profile validator boilerplate, migrates all in-repo
partners to the new hook, and adds runtime + CI-time warnings for schema
drift.
## Changes
### `langchain-core`
- Add `__pydantic_config__ = ConfigDict(extra="allow")` to
`ModelProfile` so unknown profile keys pass Pydantic validation even on
models with `extra="forbid"` — forward-compatibility for when the CLI
schema evolves ahead of core
- Declare the 7 missing fields on `ModelProfile`: `name`, `status`,
`release_date`, `last_updated`, `open_weights` (metadata) and
`attachment`, `temperature` (capabilities)
- Add `_warn_unknown_profile_keys()` in `model_profile.py` — emits a
`UserWarning` when a profile dict contains keys not in `ModelProfile`,
suggesting a core upgrade. Wrapped in a bare `except` so introspection
failures never crash model construction
- Add `BaseChatModel._resolve_model_profile()` hook that returns `None`
by default. Partners can override this single method instead of
redefining the full `_set_model_profile` validator — the base validator
calls it automatically
- Add `BaseChatModel._check_profile_keys` as a separate
`model_validator` that calls `_warn_unknown_profile_keys`. Uses a
distinct method name so partner overrides of `_set_model_profile` don't
inadvertently suppress the check
### `langchain-profiles` CLI
- Add `_warn_undeclared_profile_keys()` to the CLI (`cli.py`), called
after merging augmentations in `refresh()` — warns at profile-generation
time (not just runtime) when emitted keys aren't declared in
`ModelProfile`. Gracefully skips if `langchain-core` isn't installed
- Add guard test
`test_model_data_to_profile_keys_subset_of_model_profile` in
model-profiles — feeds a fully-populated model dict to
`_model_data_to_profile()` and asserts every emitted key exists in
`ModelProfile.__annotations__`. CI fails before any release if someone
adds a CLI field without updating the TypedDict
### Partner packages
- Migrate all 10 in-repo partners to the `_resolve_model_profile()`
hook, replacing duplicated `@model_validator` / `_set_model_profile`
overrides: anthropic, deepseek, fireworks, groq, huggingface, mistralai,
openai (base + azure), openrouter, perplexity, xai
- Anthropic retains custom logic (context-1m beta → `max_input_tokens`
override); all others reduce to a one-liner
- Add `pr_lint.yml` scope for the new `model-profiles` package
Streaming token usage was silently dropped for `ChatOpenRouter`. Both
`_stream` and `_astream` skipped any SSE chunk without a `choices` array
— which is exactly the shape OpenRouter uses for the final
usage-reporting chunk. This meant `usage_metadata` was never populated
on streamed responses, causing downstream consumers (like the Deep
Agents CLI) to show "unknown" model with 0 tokens.
## Changes
- Add `stream_usage: bool = True` field to `ChatOpenRouter`, which
passes `stream_options: {"include_usage": True}` to the OpenRouter API
when streaming — matching the pattern already established in
`langchain-openai`'s `BaseChatOpenAI`
- Handle usage-only chunks (no `choices`, just `usage`) in both
`_stream` and `_astream` by emitting a `ChatGenerationChunk` with
`usage_metadata` via `_create_usage_metadata`, instead of silently
`continue`-ing past them
Add a `model` property to `ChatFireworks`, `ChatGroq`, and
`ChatOpenRouter` that returns `model_name`. These partners use
Pydantic's `Field(alias="model")` on `model_name`, which means
`instance.model` doesn't work as a read accessor after construction — it
raises an `AttributeError` or returns the field descriptor. `ChatOpenAI`
already has this property; this brings the remaining in-repo partners to
parity.
## Description
OpenRouter returns `cost` and `cost_details` in its API response `usage`
object, providing the actual cost of each API call. Currently,
`_create_usage_metadata()` only extracts token counts and drops these
cost fields.
This PR surfaces both `cost` and `cost_details` in `response_metadata`
for both non-streaming and streaming paths, allowing users to access
actual API costs directly from the response without manual estimation
from token counts.
**Example response from OpenRouter:**
```json
{
"usage": {
"prompt_tokens": 100,
"completion_tokens": 50,
"cost": 0.000075,
"cost_details": {
"upstream_inference_cost": 0.00007745,
"upstream_inference_prompt_cost": 0.00000895,
"upstream_inference_completions_cost": 0.0000685
}
}
}
```
**After this change:**
```python
result = chat.invoke("hello")
result.response_metadata["cost"] # 0.000075
result.response_metadata["cost_details"] # {...}
```
## Changes
- **`_create_chat_result`**: Surface `cost` and `cost_details` from
`token_usage` into `response_metadata` (non-streaming)
- **`_convert_chunk_to_message_chunk`**: Same for streaming
`AIMessageChunk`
- Added `PLR0912` to `noqa` comments (new branches pushed count over
threshold)
- Added two unit tests: one verifying cost fields are present when
returned, one verifying they're absent when not in usage
## Issue
N/A — discovered while integrating OpenRouter in a production pipeline.
The cost data is already returned by the API but was being silently
dropped.
## Dependencies
None.
## Twitter handle
@hamza_kyamanywa
---------
Co-authored-by: Mason Daugherty <mason@langchain.dev>
