> [!IMPORTANT]
> **Behavior change on upgrade — minor bump (`1.1.16` → `1.2.0`).**
>
> Streaming calls now raise `StreamChunkTimeoutError` (a `TimeoutError`
subclass — existing `except TimeoutError:` / `except
asyncio.TimeoutError:` handlers catch it) after 120s of content silence
instead of hanging forever. Opt out with `stream_chunk_timeout=None` or
`LANGCHAIN_OPENAI_STREAM_CHUNK_TIMEOUT_S=0`.
>
> Kernel-level TCP keepalive / `TCP_USER_TIMEOUT` are applied via a
custom `httpx` transport. `httpx` disables its env-proxy auto-detection
(`HTTP_PROXY` / `HTTPS_PROXY` / `ALL_PROXY` / `NO_PROXY` and
macOS/Windows system proxy) whenever a transport is supplied, so to
avoid silently breaking enterprise proxy users, `ChatOpenAI` now detects
the "proxy-env-shadow" shape at construction and **skips the custom
transport entirely** when **all** of these hold:
>
> - `http_socket_options` left at default (`None`)
> - No `http_client` or `http_async_client` supplied
> - No `openai_proxy` supplied
> - A proxy env var / system proxy is visible to httpx
>
> On that shape the instance falls back to pre-PR behavior and env-proxy
auto-detection still applies. A one-time `INFO` records the bypass.
>
> Users who explicitly set `http_socket_options=[...]` alongside an env
proxy still get the shadowed behavior with a one-time `WARNING` log —
they opted in. Full opt-outs below.
---
Streaming chat completions can hang forever when the underlying TCP
connection silently dies mid-stream (idle NAT/LB timeouts, sandboxed
runtimes killing long-lived connections, peer gone without a FIN or
RST). httpx's read timeout doesn't help here because it's reset by any
bytes arriving on the socket, including OpenAI's SSE keepalive comments,
so a stream that's quiet on content but still producing keepalives looks
alive forever.
This PR adds two knobs to `ChatOpenAI`, both on by default with
opt-outs:
- `stream_chunk_timeout` (default 120s): wraps the async streaming
iterator in `asyncio.wait_for` per chunk. Measures the gap between
*parsed* SSE chunks, so keepalives don't reset it. Fires on genuine
content silence and raises `StreamChunkTimeoutError` — a `TimeoutError`
subclass carrying `timeout_s`, `model_name`, and `chunks_received` as
structured attributes (mirrored in the WARNING log's `extra=`) for
alerting without message-regex. Override with the kwarg or
`LANGCHAIN_OPENAI_STREAM_CHUNK_TIMEOUT_S`.
- `http_socket_options`: applies `SO_KEEPALIVE` + `TCP_KEEPIDLE` /
`TCP_KEEPINTVL` / `TCP_KEEPCNT` + `TCP_USER_TIMEOUT` on Linux (macOS
equivalents where available). On platforms missing some options, they're
dropped silently and the remaining set still does useful work.
Pool limits are set explicitly on the custom transport to mirror the
`openai` SDK — without that, passing `transport=` to `httpx.AsyncClient`
silently shrinks the connection pool.
## Behavior change
The default-shape proxy-env bypass (above) covers the common enterprise
case. Beyond that:
- Connections that would previously have hung forever will now error out
via `StreamChunkTimeoutError`.
- Users who explicitly opt into `http_socket_options` while also relying
on env proxies will see a one-time `WARNING` and lose env-proxy
auto-detection — the custom transport shadows it. This is the original
shipped behavior, retained for anyone who *wants* socket tuning on top
of an env-proxied setup.
Full opt-outs:
- `stream_chunk_timeout=None` or
`LANGCHAIN_OPENAI_STREAM_CHUNK_TIMEOUT_S=0`
- `http_socket_options=()` or `LANGCHAIN_OPENAI_TCP_KEEPALIVE=0`
- Supply your own `http_client` **and** `http_async_client`.
`http_socket_options` is applied per side: passing only one still leaves
the other side's default builder getting socket options. Supply both (or
combine with `http_socket_options=()`) to take full control.
Unparseable or negative values for the `LANGCHAIN_OPENAI_*` env vars
fall back to the default with a `WARNING` log rather than silently being
accepted, so a misconfigured environment still boots but the fallback is
discoverable.
---------
Co-authored-by: Mason Daugherty <github@mdrxy.com>
Co-authored-by: Mason Daugherty <mason@langchain.dev>
Python's `or` operator treats `0` as falsy, so
`token_usage.get("total_tokens") or fallback` silently replaces a
provider-reported `total_tokens=0` with the computed sum of input +
output tokens. Providers can legitimately report zero tokens (e.g.,
cached responses, empty completions).
The same pattern exists in the dual-key lookups for
`input_tokens`/`output_tokens` in Groq and OpenRouter. While current
APIs don't return both key formats simultaneously (making the `or`-chain
functionally correct today), the semantics are still wrong; `0` should
not fall through to a fallback.
## Changes
- Replace `x.get(key) or fallback` with explicit `is not None` checks in
`_create_usage_metadata` across `langchain-openai`, `langchain-groq`,
and `langchain-openrouter` for `input_tokens`, `output_tokens`, and
`total_tokens`
- Fix a concrete bug in the `total_tokens` path: a provider-reported `0`
was silently replaced by the computed sum
- Harden dual-key lookups in Groq and OpenRouter to correctly preserve
zero values from the preferred key, should both key formats ever coexist
- Update OpenAI's single-key extraction for consistency — the old `or 0`
pattern happened to produce correct results (`0 or 0 == 0`) but was
semantically wrong
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
Fixed typo in comment: "equivelent" -> "equivalent" in
libs/partners/openai/langchain_openai/chat_models/base.py
Co-authored-by: AI Assistant <assistant@example.com>
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
Just a small fix of some broken hyperlinks in the documentation of the
function `langchain_openai/chat_models/base.py#with_structured_output`
and a rephrase of the reference to supported models.
Co-authored-by: Thomas Reuhl <thomas.reuhl@telekom.de>
Fixed a bug where GPT-5 temperature validation was case-sensitive,
causing issues when users
specified Azure deployment names or model names in uppercase (e.g.,
`"GPT-5-2025-01-01"`, `"GPT-5-NANO"`). The validation now correctly
handles model names regardless of case.
Changes made:
- Updated `validate_temperature()` method in `BaseChatOpenAI` to perform
case-insensitive
model name comparisons
- Updated `_get_encoding_model()` method to use case-insensitive checks
for tiktoken encoder
selection
- Added comprehensive unit tests to verify case-insensitive behavior
with various case
combinations
**Issue:** Fixes#34003
**Dependencies:** None
**Test Coverage:**
- All existing tests pass
- New test `test_gpt_5_temperature_case_insensitive` covers uppercase,
lowercase, and
mixed-case model names
- Tests verify both non-chat GPT-5 models (temperature removed) and chat
models (temperature
preserved)
- Lint and format checks pass (`make lint`, `make format`)
---------
Co-authored-by: Mason Daugherty <github@mdrxy.com>
