Anthropic Adapter

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import asyncio
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import os
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from dotenv import load_dotenv
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from thenvoi import Agent
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from thenvoi.adapters import AnthropicAdapter
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from thenvoi.config import load_agent_config
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async def main():
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    load_dotenv()
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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 Claude model
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    adapter = AnthropicAdapter(
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        model="claude-sonnet-4-5-20250929",
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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("THENVOI_WS_URL"),
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        rest_url=os.getenv("THENVOI_REST_URL"),
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    )
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    print("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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# Claude Sonnet (recommended for most use cases)
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adapter = AnthropicAdapter(model="claude-sonnet-4-5-20250929")
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# Claude Opus (most capable)
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adapter = AnthropicAdapter(model="claude-opus-4-5-20251215")
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# Claude Haiku (fastest)
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adapter = AnthropicAdapter(model="claude-3-5-haiku-20241022")

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adapter = AnthropicAdapter(
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    model="claude-sonnet-4-5-20250929",
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    custom_section="""
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    You are a helpful assistant that specializes in answering
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    questions about Python programming. Be concise and include
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    code examples when helpful.
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    """,
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)

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adapter = AnthropicAdapter(
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    # Model to use
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    model="claude-sonnet-4-5-20250929",
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    # API key (optional - uses ANTHROPIC_API_KEY env var by default)
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    anthropic_api_key="sk-ant-...",
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    # Custom instructions to append to the system prompt
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    custom_section="You are a helpful assistant.",
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    # Override the entire system prompt
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    system_prompt=None,
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    # Maximum output tokens per response
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    max_tokens=4096,
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    # Enable visibility into tool calls and results
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    enable_execution_reporting=False,
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)

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adapter = AnthropicAdapter(
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    model="claude-sonnet-4-5-20250929",
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    enable_execution_reporting=True,
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)

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custom_prompt = """You are a technical support agent.
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Guidelines:
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- Be patient and thorough
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- Ask clarifying questions before providing solutions
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- Always verify the user's environment
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- Escalate to humans if you cannot resolve the issue
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When helping users:
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1. Acknowledge their issue
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2. Ask for relevant details (OS, version, error messages)
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3. Provide step-by-step solutions
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4. Confirm the issue is resolved before closing"""
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adapter = AnthropicAdapter(
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    model="claude-sonnet-4-5-20250929",
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    system_prompt=custom_prompt,
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)

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import asyncio
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import os
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from dotenv import load_dotenv
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from thenvoi import Agent
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from thenvoi.adapters import AnthropicAdapter
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from thenvoi.config import load_agent_config
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async def main():
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    load_dotenv()
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    agent_id, api_key = load_agent_config("my_agent")
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    adapter = AnthropicAdapter(
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        model="claude-sonnet-4-5-20250929",
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        custom_section="""
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        You are a helpful data analysis expert. When users ask questions:
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        1. Analyze the problem carefully
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        2. Provide clear, step-by-step explanations
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        3. Include code examples in Python when relevant
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        4. Offer to help with follow-up questions
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        """,
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        enable_execution_reporting=True,
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        max_tokens=8192,
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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("THENVOI_WS_URL"),
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        rest_url=os.getenv("THENVOI_REST_URL"),
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    )
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    print("Data analysis 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 os
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import logging
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from dotenv import load_dotenv
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from thenvoi import Agent
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from thenvoi.adapters import AnthropicAdapter
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from thenvoi.config import load_agent_config
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# Enable debug logging for the SDK
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logging.basicConfig(
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    level=logging.WARNING,
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    format="%(asctime)s [%(levelname)s] %(name)s: %(message)s",
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    datefmt="%Y-%m-%d %H:%M:%S",
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)
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logging.getLogger("thenvoi").setLevel(logging.DEBUG)
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async def main():
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    load_dotenv()
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    agent_id, api_key = load_agent_config("my_agent")
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    adapter = AnthropicAdapter(
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        model="claude-sonnet-4-5-20250929",
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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("THENVOI_WS_URL"),
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        rest_url=os.getenv("THENVOI_REST_URL"),
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    )
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    print("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())