7960158ee8
This PR updates the LangChain Arcade integration to v1.0.0, making the following key changes: • Bumped the package version in pyproject.toml from 0.2.0 to 1.0.0. • Changed the default parameter in ArcadeToolManager from langgraph=False to langgraph=True. • Updated dependencies to require langgraph≥0.2.67,<0.3.0 and simplified extras. • Adjusted example scripts to remove explicit authorization_url references in favor of a unified URL field. • Updated docs and environment references to align with new usage patterns and emphasize environment variables. These changes unify and streamline the LangGraph-based tooling while ensuring compatibility with the latest 1.0.0 release.
59 lines
1.9 KiB
Python
59 lines
1.9 KiB
Python
import os
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from arcadepy import Arcade
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from google.oauth2.credentials import Credentials
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from langchain_google_community import GmailToolkit
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from langchain_google_community.gmail.utils import (
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build_resource_service,
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)
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from langchain_openai import ChatOpenAI
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from langgraph.prebuilt import create_react_agent
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# Get the API key from the environment variable
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api_key = os.getenv("ARCADE_API_KEY")
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# Initialize the Arcade client
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client = Arcade(api_key=api_key)
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# Start the authorization process for Gmail
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# see all possible gmail scopes here:
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# https://developers.google.com/gmail/api/auth/scopes
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user_id = "user@example.com"
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auth_response = client.auth.start(
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user_id=user_id, provider="google", scopes=["https://www.googleapis.com/auth/gmail.readonly"]
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)
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# Prompt the user to authorize if not already completed
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if auth_response.status != "completed":
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print("Please authorize the application in your browser:")
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print(auth_response.url)
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# Wait for the user to complete the authorization process, if necessary...
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auth_response = client.auth.wait_for_completion(auth_response)
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# Obtain credentials using the authorization context
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creds = Credentials(auth_response.context.token)
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api_resource = build_resource_service(credentials=creds)
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# Initialize the Gmail toolkit with the authorized API resource
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toolkit = GmailToolkit(api_resource=api_resource)
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# Retrieve the tools from the langchain gmail toolkit
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tools = toolkit.get_tools()
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# Initialize the language model and create an agent
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llm = ChatOpenAI(model="gpt-4o")
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agent_executor = create_react_agent(llm, tools)
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# Define the user query
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example_query = "Read my latest emails and summarize them."
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# Execute the agent with the user query
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events = agent_executor.stream(
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{"messages": [("user", example_query)]},
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stream_mode="values",
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)
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# Display the agent's response
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for event in events:
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event["messages"][-1].pretty_print()
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