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Closes #37172 --- Bumps `langchain-fireworks` to the rewritten `fireworks-ai` 1.x SDK (currently 1.2.0a*; Stainless-generated, pure-httpx, no `grpcio`/`protobuf`/`googleapis-common-protos`). The motivating bug is a startup crash in self-hosted LangGraph environments that also import `langchain-google-vertexai`. Importing `fireworks-ai` 0.19.x eagerly loads vendored grpcio protobuf modules under `fireworks.control_plane.generated.protos_grpcio.*`, which register `google/rpc/status.proto`, `google/api/*.proto`, and `google/longrunning/*.proto` in the default protobuf descriptor pool. When `langchain-google-vertexai` later triggers `google.api_core.exceptions` → `grpc_status.rpc_status` → `google.rpc.status_pb2`, the pool already holds a byte-different descriptor for `google/rpc/status.proto` and startup dies with: ``` TypeError: Couldn't build proto file into descriptor pool: duplicate file name google/rpc/status.proto ``` Fleet has been pinning around this by routing Fireworks through `ChatOpenAI` against the OpenAI-compat endpoint, which works for inference but means Fireworks `ModelProfile` data never loads — so Kimi K2.6's ~262k context window goes unrecognized and summarization triggers below limit. The 1.x SDK does not vendor protobuf at all. The control-plane gRPC code path is gone; chat inference goes over httpx. Verified locally that `import langchain_fireworks` and `from langchain_fireworks import ChatFireworks` load zero `_pb2` / `google.*` modules. ## What changed in `ChatFireworks` - Imports switch from `fireworks.client` to the top-level `fireworks` package. - Async path now `await client.chat.completions.create(...)`; the 0.x `acreate` shim is no longer used. - Error classes remapped to the 1.x hierarchy. `InvalidRequestError` → `BadRequestError`. `BadGatewayError` and `ServiceUnavailableError` no longer exist (1.x maps all `>=500` to `InternalServerError`) and were dropped from the retryable set with no loss of coverage. `FireworksContextOverflowError`'s parent class becomes `BadRequestError`. - `stream_options` is moved into the SDK's `extra_body` because the Stainless-generated `create()` signature does not model it as a typed kwarg. Top-level `stream_options` is preserved as a caller convenience; if a caller supplies both `extra_body["stream_options"]` and a top-level value, `extra_body` wins and the discarded value is logged. - The 0.x `(connect, read)` tuple form of `request_timeout` is normalized to an `httpx.Timeout` so existing user code keeps working. - The SDK's built-in retry layer is suppressed via `max_retries=0` on client construction so retries remain owned by `create_base_retry_decorator` and surface through the LangChain `run_manager`. ## Lifecycle methods Adds `close()` and `aclose()` on `ChatFireworks`. The 1.x `AsyncFireworks` client defaults to `httpx_aiohttp.HttpxAiohttpClient`, whose underlying aiohttp `ClientSession` is created lazily on first request. Sync-only paths therefore never open a session — which fixes the "Unclosed client session" warnings from #37172 at the source. Callers using async paths can now release the connector deterministically rather than relying on GC after the event loop has stopped. An autouse fixture in the integration `conftest.py` calls `aclose()` between tests to silence the corresponding `Unclosed connector` warning that surfaces under `pytest-asyncio`. ## Relation to #37227 Supersedes #37227. That PR monkey-patched `fireworks._util.is_running_in_async_context` and `fireworks.client.api_client.is_running_in_async_context` to suppress the 0.x SDK's eager `aiohttp.ClientSession` creation in async contexts. Both module paths are removed in 1.x; the SDK's lazy-session behavior makes the suppression unnecessary, and the explicit `aclose()` provides the cleaner long-term lifecycle hook. Thanks to @keenborder786 for surfacing the failure mode. ## Installation note `fireworks-ai` 1.x is currently published as an alpha (`1.2.0a*`); a stable 1.x is not yet out. `pip install langchain-fireworks` / `uv pip install langchain-fireworks` will need `--pre` (or `--prerelease=allow`) until Fireworks GAs 1.x. The `pyproject.toml` adds `[tool.uv] prerelease = "allow"` so the in-repo dev environment resolves cleanly. The package version is bumped to `1.4.0` — the public surface (`ChatFireworks`, `Fireworks`, `FireworksEmbeddings`) is unchanged; the breakage is confined to internal error classes and the transitive SDK.
The agent engineering platform.
LangChain is a framework for building agents and LLM-powered applications. It helps you chain together interoperable components and third-party integrations to simplify AI application development — all while future-proofing decisions as the underlying technology evolves.
Tip
Just getting started? Check out Deep Agents — a higher-level package built on LangChain for agents that have built-in capabilites for common usage patterns such as planning, subagents, file system usage, and more.
Quickstart
pip install langchain
# or
uv add langchain
from langchain.chat_models import init_chat_model
model = init_chat_model("openai:gpt-5.4")
result = model.invoke("Hello, world!")
If you're looking for more advanced customization or agent orchestration, check out LangGraph, our framework for building controllable agent workflows.
For an equivalent JS/TS library, check out LangChain.js.
Tip
For developing, debugging, and deploying AI agents and LLM applications, see LangSmith.
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