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
194
libs/community/langchain_community/callbacks/context_callback.py
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194
libs/community/langchain_community/callbacks/context_callback.py
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"""Callback handler for Context AI"""
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import os
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from typing import Any, Dict, List
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from uuid import UUID
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from langchain_core.callbacks import BaseCallbackHandler
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from langchain_core.messages import BaseMessage
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from langchain_core.outputs import LLMResult
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def import_context() -> Any:
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"""Import the `getcontext` package."""
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try:
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import getcontext # noqa: F401
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from getcontext.generated.models import (
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Conversation,
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Message,
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MessageRole,
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Rating,
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)
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from getcontext.token import Credential # noqa: F401
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except ImportError:
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raise ImportError(
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"To use the context callback manager you need to have the "
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"`getcontext` python package installed (version >=0.3.0). "
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"Please install it with `pip install --upgrade python-context`"
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)
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return getcontext, Credential, Conversation, Message, MessageRole, Rating
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class ContextCallbackHandler(BaseCallbackHandler):
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"""Callback Handler that records transcripts to the Context service.
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(https://context.ai).
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Keyword Args:
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token (optional): The token with which to authenticate requests to Context.
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Visit https://with.context.ai/settings to generate a token.
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If not provided, the value of the `CONTEXT_TOKEN` environment
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variable will be used.
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Raises:
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ImportError: if the `context-python` package is not installed.
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Chat Example:
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>>> from langchain_community.llms import ChatOpenAI
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>>> from langchain_community.callbacks import ContextCallbackHandler
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>>> context_callback = ContextCallbackHandler(
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... token="<CONTEXT_TOKEN_HERE>",
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... )
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>>> chat = ChatOpenAI(
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... temperature=0,
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... headers={"user_id": "123"},
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... callbacks=[context_callback],
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... openai_api_key="API_KEY_HERE",
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... )
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>>> messages = [
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... SystemMessage(content="You translate English to French."),
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... HumanMessage(content="I love programming with LangChain."),
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... ]
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>>> chat(messages)
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Chain Example:
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>>> from langchain.chains import LLMChain
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>>> from langchain_community.chat_models import ChatOpenAI
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>>> from langchain_community.callbacks import ContextCallbackHandler
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>>> context_callback = ContextCallbackHandler(
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... token="<CONTEXT_TOKEN_HERE>",
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... )
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>>> human_message_prompt = HumanMessagePromptTemplate(
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... prompt=PromptTemplate(
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... template="What is a good name for a company that makes {product}?",
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... input_variables=["product"],
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... ),
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... )
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>>> chat_prompt_template = ChatPromptTemplate.from_messages(
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... [human_message_prompt]
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... )
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>>> callback = ContextCallbackHandler(token)
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>>> # Note: the same callback object must be shared between the
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... LLM and the chain.
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>>> chat = ChatOpenAI(temperature=0.9, callbacks=[callback])
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>>> chain = LLMChain(
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... llm=chat,
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... prompt=chat_prompt_template,
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... callbacks=[callback]
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... )
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>>> chain.run("colorful socks")
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"""
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def __init__(self, token: str = "", verbose: bool = False, **kwargs: Any) -> None:
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(
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self.context,
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self.credential,
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self.conversation_model,
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self.message_model,
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self.message_role_model,
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self.rating_model,
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) = import_context()
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token = token or os.environ.get("CONTEXT_TOKEN") or ""
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self.client = self.context.ContextAPI(credential=self.credential(token))
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self.chain_run_id = None
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self.llm_model = None
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self.messages: List[Any] = []
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self.metadata: Dict[str, str] = {}
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def on_chat_model_start(
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self,
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serialized: Dict[str, Any],
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messages: List[List[BaseMessage]],
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*,
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run_id: UUID,
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**kwargs: Any,
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) -> Any:
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"""Run when the chat model is started."""
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llm_model = kwargs.get("invocation_params", {}).get("model", None)
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if llm_model is not None:
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self.metadata["model"] = llm_model
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if len(messages) == 0:
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return
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for message in messages[0]:
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role = self.message_role_model.SYSTEM
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if message.type == "human":
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role = self.message_role_model.USER
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elif message.type == "system":
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role = self.message_role_model.SYSTEM
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elif message.type == "ai":
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role = self.message_role_model.ASSISTANT
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self.messages.append(
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self.message_model(
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message=message.content,
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role=role,
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)
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)
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def on_llm_end(self, response: LLMResult, **kwargs: Any) -> None:
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"""Run when LLM ends."""
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if len(response.generations) == 0 or len(response.generations[0]) == 0:
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return
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if not self.chain_run_id:
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generation = response.generations[0][0]
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self.messages.append(
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self.message_model(
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message=generation.text,
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role=self.message_role_model.ASSISTANT,
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)
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)
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self._log_conversation()
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def on_chain_start(
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self, serialized: Dict[str, Any], inputs: Dict[str, Any], **kwargs: Any
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) -> None:
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"""Run when chain starts."""
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self.chain_run_id = kwargs.get("run_id", None)
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def on_chain_end(self, outputs: Dict[str, Any], **kwargs: Any) -> None:
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"""Run when chain ends."""
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self.messages.append(
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self.message_model(
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message=outputs["text"],
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role=self.message_role_model.ASSISTANT,
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)
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)
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self._log_conversation()
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self.chain_run_id = None
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def _log_conversation(self) -> None:
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"""Log the conversation to the context API."""
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if len(self.messages) == 0:
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return
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self.client.log.conversation_upsert(
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body={
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"conversation": self.conversation_model(
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messages=self.messages,
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metadata=self.metadata,
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)
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}
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)
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self.messages = []
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self.metadata = {}
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