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core: BaseChatModel modify chat message before passing to run_manager (#19939)
Thank you for contributing to LangChain! - [ ] **PR title**: "package: description" - Where "package" is whichever of langchain, community, core, experimental, etc. is being modified. Use "docs: ..." for purely docs changes, "templates: ..." for template changes, "infra: ..." for CI changes. - Example: "community: add foobar LLM" - [ ] **PR message**: ***Delete this entire checklist*** and replace with - **Description:** a description of the change - **Issue:** the issue # it fixes, if applicable - **Dependencies:** any dependencies required for this change - **Twitter handle:** if your PR gets announced, and you'd like a mention, we'll gladly shout you out! - [ ] **Add tests and docs**: If you're adding a new integration, please include 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. It lives in `docs/docs/integrations` directory. - [ ] **Lint and test**: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. See contribution guidelines for more: https://python.langchain.com/docs/contributing/ Additional guidelines: - Make sure optional dependencies are imported within a function. - Please do not add dependencies to pyproject.toml files (even optional ones) unless they are required for unit tests. - Most PRs should not touch more than one package. - Changes should be backwards compatible. - If you are adding something to community, do not re-import it in langchain. If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, hwchase17.
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@ -221,12 +221,12 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
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generation: Optional[ChatGenerationChunk] = None
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generation: Optional[ChatGenerationChunk] = None
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try:
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try:
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for chunk in self._stream(messages, stop=stop, **kwargs):
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for chunk in self._stream(messages, stop=stop, **kwargs):
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run_manager.on_llm_new_token(
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cast(str, chunk.message.content), chunk=chunk
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)
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if chunk.message.id is None:
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if chunk.message.id is None:
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chunk.message.id = f"run-{run_manager.run_id}"
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chunk.message.id = f"run-{run_manager.run_id}"
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chunk.message.response_metadata = _gen_info_and_msg_metadata(chunk)
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chunk.message.response_metadata = _gen_info_and_msg_metadata(chunk)
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run_manager.on_llm_new_token(
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cast(str, chunk.message.content), chunk=chunk
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)
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yield chunk.message
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yield chunk.message
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if generation is None:
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if generation is None:
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generation = chunk
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generation = chunk
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@ -293,12 +293,12 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
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stop=stop,
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stop=stop,
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**kwargs,
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**kwargs,
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):
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):
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await run_manager.on_llm_new_token(
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cast(str, chunk.message.content), chunk=chunk
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)
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if chunk.message.id is None:
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if chunk.message.id is None:
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chunk.message.id = f"run-{run_manager.run_id}"
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chunk.message.id = f"run-{run_manager.run_id}"
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chunk.message.response_metadata = _gen_info_and_msg_metadata(chunk)
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chunk.message.response_metadata = _gen_info_and_msg_metadata(chunk)
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await run_manager.on_llm_new_token(
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cast(str, chunk.message.content), chunk=chunk
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)
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yield chunk.message
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yield chunk.message
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if generation is None:
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if generation is None:
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generation = chunk
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generation = chunk
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@ -610,13 +610,13 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
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):
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):
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chunks: List[ChatGenerationChunk] = []
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chunks: List[ChatGenerationChunk] = []
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for chunk in self._stream(messages, stop=stop, **kwargs):
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for chunk in self._stream(messages, stop=stop, **kwargs):
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chunk.message.response_metadata = _gen_info_and_msg_metadata(chunk)
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if run_manager:
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if run_manager:
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if chunk.message.id is None:
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if chunk.message.id is None:
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chunk.message.id = f"run-{run_manager.run_id}"
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chunk.message.id = f"run-{run_manager.run_id}"
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run_manager.on_llm_new_token(
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run_manager.on_llm_new_token(
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cast(str, chunk.message.content), chunk=chunk
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cast(str, chunk.message.content), chunk=chunk
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)
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)
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chunk.message.response_metadata = _gen_info_and_msg_metadata(chunk)
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chunks.append(chunk)
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chunks.append(chunk)
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result = generate_from_stream(iter(chunks))
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result = generate_from_stream(iter(chunks))
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else:
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else:
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@ -691,13 +691,13 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
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):
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):
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chunks: List[ChatGenerationChunk] = []
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chunks: List[ChatGenerationChunk] = []
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async for chunk in self._astream(messages, stop=stop, **kwargs):
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async for chunk in self._astream(messages, stop=stop, **kwargs):
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chunk.message.response_metadata = _gen_info_and_msg_metadata(chunk)
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if run_manager:
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if run_manager:
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if chunk.message.id is None:
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if chunk.message.id is None:
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chunk.message.id = f"run-{run_manager.run_id}"
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chunk.message.id = f"run-{run_manager.run_id}"
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await run_manager.on_llm_new_token(
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await run_manager.on_llm_new_token(
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cast(str, chunk.message.content), chunk=chunk
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cast(str, chunk.message.content), chunk=chunk
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)
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)
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chunk.message.response_metadata = _gen_info_and_msg_metadata(chunk)
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chunks.append(chunk)
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chunks.append(chunk)
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result = generate_from_stream(iter(chunks))
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result = generate_from_stream(iter(chunks))
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else:
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else:
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