6d8e943c96
**PR Description** This update bumps the integration’s version to `0.2.0` and brings several important changes to how `langchain-arcade` interfaces with Arcade tools: 1. **Updated Tool Definition Imports** • Replaces `arcadepy.types.shared.ToolDefinition` with `arcadepy.types.ToolGetResponse as ToolDefinition`. • The parameter extraction is now done via `tool_def.input.parameters` instead of the previous `tool_def.inputs.parameters`. 2. **Authorization Flow Adjustments** • Uses `auth_response.url` instead of `auth_response.authorization_url`. • The `authorize` and `is_authorized` methods now rely on the Arcade client’s updated arguments (`client.auth.status(id=authorization_id)`). 3. **Tool Execution Parameter Renaming** • The `execute` method now expects `input=kwargs` instead of `inputs=kwargs`, aligning with Arcade’s new API spec. 4. **Tool Retrieval Enhancements** • `_retrieve_tool_definitions` is revised to better handle pagination and tool listing (including when no tools/toolkits are explicitly provided). 5. **Version & Dependency Updates** • Increases `langchain-arcade` to `0.2.0`. • Switches `arcadepy` dependency to `~1.0.0rc1`. • Updates example requirements to consume `langchain-arcade[langgraph]>=0.2.0`. These changes may affect existing code that relies on older parameter names (`inputs.parameters` → `input.parameters`) and the renamed execute argument. Please ensure any integrations or custom usage of Arcade tools is updated accordingly.
43 lines
1.4 KiB
Python
43 lines
1.4 KiB
Python
import os
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# Import necessary modules and classes
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from langchain_arcade import ArcadeToolManager
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from langchain_core.messages import HumanMessage
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from langchain_openai import ChatOpenAI
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from langgraph.prebuilt import create_react_agent
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arcade_api_key = os.environ["ARCADE_API_KEY"]
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openai_api_key = os.environ["OPENAI_API_KEY"]
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# Initialize the tool manager that fetches
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# tools from arcade and wraps them as langgraph tools
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tool_manager = ArcadeToolManager(api_key=arcade_api_key)
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tools = tool_manager.get_tools(langgraph=True)
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# Create an instance of the AI language model
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model = ChatOpenAI(model="gpt-4o", api_key=openai_api_key)
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# Init a prebuilt agent that can use tools
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# in a REACT style langgraph
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graph = create_react_agent(model, tools=tools)
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# Define the initial input message from the user
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inputs = {
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"messages": [HumanMessage(content="Star arcadeai/arcade-ai on GitHub!")],
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}
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# Configuration parameters for the agent and tools
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config = {
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"configurable": {
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"thread_id": "2",
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"user_id": "user@example.com",
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}
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}
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# Stream the assistant's responses by executing the graph
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for chunk in graph.stream(inputs, stream_mode="values", config=config):
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# Access the latest message from the conversation
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last_message = chunk["messages"][-1]
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# Print the assistant's message content
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if last_message.content:
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print(last_message.content)
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