mirror of
https://github.com/hwchase17/langchain
synced 2024-11-04 06:00:26 +00:00
ed58eeb9c5
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
49 lines
1.5 KiB
Python
49 lines
1.5 KiB
Python
from typing import Dict, Optional, Type
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from langchain_core.callbacks import CallbackManagerForToolRun
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from langchain_core.pydantic_v1 import BaseModel, Field
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from langchain_community.tools.gmail.base import GmailBaseTool
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class GetThreadSchema(BaseModel):
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"""Input for GetMessageTool."""
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# From https://support.google.com/mail/answer/7190?hl=en
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thread_id: str = Field(
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...,
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description="The thread ID.",
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)
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class GmailGetThread(GmailBaseTool):
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"""Tool that gets a thread by ID from Gmail."""
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name: str = "get_gmail_thread"
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description: str = (
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"Use this tool to search for email messages."
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" The input must be a valid Gmail query."
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" The output is a JSON list of messages."
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)
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args_schema: Type[GetThreadSchema] = GetThreadSchema
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def _run(
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self,
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thread_id: str,
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run_manager: Optional[CallbackManagerForToolRun] = None,
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) -> Dict:
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"""Run the tool."""
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query = self.api_resource.users().threads().get(userId="me", id=thread_id)
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thread_data = query.execute()
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if not isinstance(thread_data, dict):
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raise ValueError("The output of the query must be a list.")
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messages = thread_data["messages"]
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thread_data["messages"] = []
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keys_to_keep = ["id", "snippet", "snippet"]
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# TODO: Parse body.
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for message in messages:
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thread_data["messages"].append(
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{k: message[k] for k in keys_to_keep if k in message}
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)
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return thread_data
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