mirror of
https://github.com/hwchase17/langchain.git
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community[major], core[patch], langchain[patch], experimental[patch]: Create langchain-community (#14463)
Moved the following modules to new package langchain-community in a backwards compatible fashion: ``` mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community ``` Moved the following to core ``` mv langchain/langchain/utils/json_schema.py core/langchain_core/utils mv langchain/langchain/utils/html.py core/langchain_core/utils mv langchain/langchain/utils/strings.py core/langchain_core/utils cat langchain/langchain/utils/env.py >> core/langchain_core/utils/env.py rm langchain/langchain/utils/env.py ``` See .scripts/community_split/script_integrations.sh for all changes
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GitHub
159
libs/community/langchain_community/chat_loaders/langsmith.py
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159
libs/community/langchain_community/chat_loaders/langsmith.py
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from __future__ import annotations
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import logging
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from typing import TYPE_CHECKING, Dict, Iterable, Iterator, List, Optional, Union, cast
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from langchain_core.chat_sessions import ChatSession
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from langchain_core.load import load
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from langchain_community.chat_loaders.base import BaseChatLoader
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if TYPE_CHECKING:
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from langsmith.client import Client
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from langsmith.schemas import Run
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logger = logging.getLogger(__name__)
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class LangSmithRunChatLoader(BaseChatLoader):
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"""
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Load chat sessions from a list of LangSmith "llm" runs.
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Attributes:
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runs (Iterable[Union[str, Run]]): The list of LLM run IDs or run objects.
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client (Client): Instance of LangSmith client for fetching data.
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"""
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def __init__(
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self, runs: Iterable[Union[str, Run]], client: Optional["Client"] = None
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):
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"""
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Initialize a new LangSmithRunChatLoader instance.
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:param runs: List of LLM run IDs or run objects.
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:param client: An instance of LangSmith client, if not provided,
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a new client instance will be created.
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"""
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from langsmith.client import Client
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self.runs = runs
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self.client = client or Client()
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def _load_single_chat_session(self, llm_run: "Run") -> ChatSession:
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"""
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Convert an individual LangSmith LLM run to a ChatSession.
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:param llm_run: The LLM run object.
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:return: A chat session representing the run's data.
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"""
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chat_session = LangSmithRunChatLoader._get_messages_from_llm_run(llm_run)
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functions = LangSmithRunChatLoader._get_functions_from_llm_run(llm_run)
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if functions:
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chat_session["functions"] = functions
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return chat_session
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@staticmethod
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def _get_messages_from_llm_run(llm_run: "Run") -> ChatSession:
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"""
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Extract messages from a LangSmith LLM run.
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:param llm_run: The LLM run object.
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:return: ChatSession with the extracted messages.
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"""
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if llm_run.run_type != "llm":
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raise ValueError(f"Expected run of type llm. Got: {llm_run.run_type}")
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if "messages" not in llm_run.inputs:
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raise ValueError(f"Run has no 'messages' inputs. Got {llm_run.inputs}")
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if not llm_run.outputs:
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raise ValueError("Cannot convert pending run")
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messages = load(llm_run.inputs)["messages"]
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message_chunk = load(llm_run.outputs)["generations"][0]["message"]
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return ChatSession(messages=messages + [message_chunk])
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@staticmethod
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def _get_functions_from_llm_run(llm_run: "Run") -> Optional[List[Dict]]:
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"""
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Extract functions from a LangSmith LLM run if they exist.
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:param llm_run: The LLM run object.
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:return: Functions from the run or None.
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"""
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if llm_run.run_type != "llm":
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raise ValueError(f"Expected run of type llm. Got: {llm_run.run_type}")
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return (llm_run.extra or {}).get("invocation_params", {}).get("functions")
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def lazy_load(self) -> Iterator[ChatSession]:
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"""
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Lazy load the chat sessions from the iterable of run IDs.
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This method fetches the runs and converts them to chat sessions on-the-fly,
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yielding one session at a time.
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:return: Iterator of chat sessions containing messages.
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"""
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from langsmith.schemas import Run
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for run_obj in self.runs:
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try:
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if hasattr(run_obj, "id"):
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run = run_obj
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else:
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run = self.client.read_run(run_obj)
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session = self._load_single_chat_session(cast(Run, run))
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yield session
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except ValueError as e:
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logger.warning(f"Could not load run {run_obj}: {repr(e)}")
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continue
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class LangSmithDatasetChatLoader(BaseChatLoader):
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"""
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Load chat sessions from a LangSmith dataset with the "chat" data type.
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Attributes:
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dataset_name (str): The name of the LangSmith dataset.
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client (Client): Instance of LangSmith client for fetching data.
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"""
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def __init__(self, *, dataset_name: str, client: Optional["Client"] = None):
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"""
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Initialize a new LangSmithChatDatasetLoader instance.
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:param dataset_name: The name of the LangSmith dataset.
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:param client: An instance of LangSmith client; if not provided,
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a new client instance will be created.
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"""
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try:
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from langsmith.client import Client
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except ImportError as e:
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raise ImportError(
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"The LangSmith client is required to load LangSmith datasets.\n"
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"Please install it with `pip install langsmith`"
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) from e
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self.dataset_name = dataset_name
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self.client = client or Client()
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def lazy_load(self) -> Iterator[ChatSession]:
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"""
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Lazy load the chat sessions from the specified LangSmith dataset.
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This method fetches the chat data from the dataset and
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converts each data point to chat sessions on-the-fly,
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yielding one session at a time.
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:return: Iterator of chat sessions containing messages.
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"""
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from langchain_community.adapters import openai as oai_adapter # noqa: E402
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data = self.client.read_dataset_openai_finetuning(
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dataset_name=self.dataset_name
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)
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for data_point in data:
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yield ChatSession(
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messages=[
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oai_adapter.convert_dict_to_message(m)
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for m in data_point.get("messages", [])
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],
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functions=data_point.get("functions"),
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)
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