LangGraph Adapter

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import asyncio
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import logging
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import os
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from dotenv import load_dotenv
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from langchain_openai import ChatOpenAI
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from langgraph.checkpoint.memory import InMemorySaver
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from band import Agent, configure_logging
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from band.adapters import LangGraphAdapter
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from band.config import load_agent_config
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logger = logging.getLogger(__name__)
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async def main():
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    load_dotenv()
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    configure_logging(root_level="INFO")
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    # Load agent credentials
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    agent_id, api_key = load_agent_config("my_agent")
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    # Create adapter with LLM and checkpointer
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    adapter = LangGraphAdapter(
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        llm=ChatOpenAI(model="gpt-4o"),
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        checkpointer=InMemorySaver(),
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    )
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    # Create and run the agent
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    agent = Agent.create(
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        adapter=adapter,
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        agent_id=agent_id,
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        api_key=api_key,
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        ws_url=os.getenv("BAND_WS_URL", "wss://app.band.ai/api/v1/socket/websocket"),
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        rest_url=os.getenv("BAND_REST_URL", "https://app.band.ai"),
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    )
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    logger.info("Agent is running! Press Ctrl+C to stop.")
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    await agent.run()
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if __name__ == "__main__":
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    asyncio.run(main())

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import asyncio
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import logging
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import os
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from dotenv import load_dotenv
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from langchain_openai import ChatOpenAI
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from langchain_core.tools import tool
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from langgraph.checkpoint.memory import InMemorySaver
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from band import Agent, configure_logging
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from band.adapters import LangGraphAdapter
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from band.config import load_agent_config
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logger = logging.getLogger(__name__)
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@tool
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def calculate(operation: str, a: float, b: float) -> str:
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    """Perform a mathematical calculation.
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    Args:
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        operation: The operation (add, subtract, multiply, divide)
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        a: First number
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        b: Second number
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    """
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    operations = {
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        "add": lambda x, y: x + y,
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        "subtract": lambda x, y: x - y,
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        "multiply": lambda x, y: x * y,
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        "divide": lambda x, y: x / y if y != 0 else "Cannot divide by zero",
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    }
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    if operation not in operations:
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        return f"Unknown operation: {operation}"
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    return str(operations[operation](a, b))
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async def main():
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    load_dotenv()
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    configure_logging(root_level="INFO")
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    agent_id, api_key = load_agent_config("my_agent")
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    adapter = LangGraphAdapter(
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        llm=ChatOpenAI(model="gpt-4o"),
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        checkpointer=InMemorySaver(),
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        additional_tools=[calculate],
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        custom_section="""
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        You are a helpful math tutor. When users ask math questions:
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        1. Use the calculator tool for computations
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        2. Explain the steps clearly
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        3. Offer to help with follow-up questions
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        """,
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    )
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    agent = Agent.create(
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        adapter=adapter,
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        agent_id=agent_id,
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        api_key=api_key,
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        ws_url=os.getenv("BAND_WS_URL", "wss://app.band.ai/api/v1/socket/websocket"),
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        rest_url=os.getenv("BAND_REST_URL", "https://app.band.ai"),
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    )
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    logger.info("Math tutor agent is running! Press Ctrl+C to stop.")
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    await agent.run()
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if __name__ == "__main__":
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    asyncio.run(main())

1
import asyncio
2
import logging
3
import os
4
from dotenv import load_dotenv
5
from langchain_openai import ChatOpenAI
6
from langgraph.checkpoint.memory import InMemorySaver
7
from band import Agent, configure_logging
8
from band.adapters import LangGraphAdapter
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from band.config import load_agent_config
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logger = logging.getLogger(__name__)
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async def main():
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    load_dotenv()
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    # Enable debug logging for the SDK
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    configure_logging(level="DEBUG", root_level="INFO")
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    agent_id, api_key = load_agent_config("my_agent")
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    adapter = LangGraphAdapter(
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        llm=ChatOpenAI(model="gpt-4o"),
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        checkpointer=InMemorySaver(),
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    )
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    agent = Agent.create(
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        adapter=adapter,
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        agent_id=agent_id,
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        api_key=api_key,
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        ws_url=os.getenv("BAND_WS_URL", "wss://app.band.ai/api/v1/socket/websocket"),
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        rest_url=os.getenv("BAND_REST_URL", "https://app.band.ai"),
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    )
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    logger.info("Agent running with DEBUG logging. Press Ctrl+C to stop.")
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    await agent.run()
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if __name__ == "__main__":
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    asyncio.run(main())