Parlant Adapter

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# Load environment FIRST - Parlant checks OPENAI_API_KEY on import
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from dotenv import load_dotenv; load_dotenv()
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import asyncio
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import logging
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import os
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import parlant.sdk as p
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from band import Agent, configure_logging
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from band.adapters import ParlantAdapter
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from band.config import load_agent_config
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configure_logging(root_level="INFO")
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logger = logging.getLogger(__name__)
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AGENT_DESCRIPTION = """You are a helpful assistant in the Band multi-agent platform.
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## Your Tools
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- band_send_message: Send messages to users (requires @mentions)
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- band_send_event: Share thoughts, errors, or task progress
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- band_lookup_peers: Find available agents
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- band_add_participant: Add agents/users to room
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- band_remove_participant: Remove participants
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- band_get_participants: List current participants
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- band_create_chatroom: Create new rooms
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"""
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async def main():
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    # Load agent credentials
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    agent_id, api_key = load_agent_config("my_agent")
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    # The adapter boots and owns the Parlant server
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    adapter = ParlantAdapter(
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        name="Band Assistant",
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        description=AGENT_DESCRIPTION,
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        nlp_service=p.NLPServices.openai,
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    )
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    # Declare guidelines before starting. Band's platform tools are attached
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    # to each one by default.
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    adapter.add_guideline(
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        condition="User asks a question or needs help",
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        action="Use band_send_message to respond with the user's name in mentions",
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    )
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    # Create and run the Band 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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from dotenv import load_dotenv; load_dotenv()
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import asyncio
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import os
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import parlant.sdk as p
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from band import Agent
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from band.adapters import ParlantAdapter
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from band.config import load_agent_config
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async def main():
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    agent_id, api_key = load_agent_config("my_agent")
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    async with p.Server(nlp_service=p.NLPServices.openai) as server:
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        parlant_agent = await server.create_agent(
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            name="Band Assistant",
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            description="You are a helpful assistant in a Band room.",
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        )
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        adapter = ParlantAdapter(server=server, parlant_agent=parlant_agent)
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        adapter.add_guideline(
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            condition="User asks a question",
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            action="Answer with band_send_message, mentioning the user",
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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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        await agent.run()
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if __name__ == "__main__":
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    asyncio.run(main())

1
# Load environment FIRST - Parlant checks OPENAI_API_KEY on import
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from dotenv import load_dotenv; load_dotenv()
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import asyncio
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import logging
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import os
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import parlant.sdk as p
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from band import Agent, configure_logging
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from band.adapters import ParlantAdapter
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from band.config import load_agent_config
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configure_logging(root_level="INFO")
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logger = logging.getLogger(__name__)
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SUPPORT_DESCRIPTION = """
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You are a customer support agent for TechCo Solutions.
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Your responsibilities:
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- Handle customer inquiries with professionalism and empathy
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- Resolve issues efficiently while maintaining quality
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- Escalate complex issues to specialists when needed
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Communication style:
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- Friendly but professional
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- Clear and concise
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- Solution-focused
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"""
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def build_support_adapter() -> ParlantAdapter:
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    """Build a customer support adapter with its guidelines."""
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    adapter = ParlantAdapter(
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        name="TechCo Support",
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        description=SUPPORT_DESCRIPTION,
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        nlp_service=p.NLPServices.openai,
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    )
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    # Guidelines that do not call platform tools opt out with tools=[]
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    adapter.add_guideline(
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        condition="Customer asks about refunds or returns",
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        action="Express empathy first, then ask for order details (order number, item) before providing refund information",
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        tools=[],
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    )
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    adapter.add_guideline(
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        condition="Customer is frustrated or upset",
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        action="Acknowledge their frustration, apologize for any inconvenience, and focus on finding a solution",
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        tools=[],
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    )
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    adapter.add_guideline(
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        condition="Customer asks a technical question",
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        action="Ask about their setup (device, OS, version) before troubleshooting",
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        tools=[],
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    )
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    # This one calls platform tools, so it keeps the default attachment
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    adapter.add_guideline(
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        condition="Issue cannot be resolved by this agent",
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        action="Explain the limitation clearly, then use band_lookup_peers to find a specialist and band_add_participant to add them to the conversation",
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    )
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    adapter.add_guideline(
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        condition="Customer provides positive feedback",
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        action="Thank them warmly and ask if there's anything else you can help with",
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        tools=[],
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    )
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    adapter.add_guideline(
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        condition="Customer mentions urgency or deadline",
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        action="Prioritize their request and provide the fastest path to resolution",
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        tools=[],
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    )
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    return adapter
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async def main():
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    agent_id, api_key = load_agent_config("my_agent")
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    adapter = build_support_adapter()
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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("Customer support 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
# Load environment FIRST - Parlant checks OPENAI_API_KEY on import
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from dotenv import load_dotenv; load_dotenv()
3
4
import asyncio
5
import logging
6
import os
7
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import parlant.sdk as p
9
from band import Agent, configure_logging
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from band.adapters import ParlantAdapter
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from band.config import load_agent_config
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configure_logging(root_level="INFO")
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logger = logging.getLogger(__name__)
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COLLABORATION_DESCRIPTION = """
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You are a collaborative assistant in the Band multi-agent platform.
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Your role:
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- Help users navigate multi-agent conversations
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- Facilitate collaboration between different agents
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- Manage participants in chat rooms
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- Create new chat rooms when needed for specific topics
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## Your Tools
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- band_send_message: Respond to users (requires mentions)
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- band_send_event: Share thoughts, errors, or task progress
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- band_lookup_peers: Find available agents
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- band_add_participant: Add agents/users to room
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- band_remove_participant: Remove participants
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- band_get_participants: List current participants
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- band_create_chatroom: Create new rooms
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"""
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def build_collaboration_adapter() -> ParlantAdapter:
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    """Build a collaborative adapter with its guidelines."""
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    adapter = ParlantAdapter(
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        name="Collaborative Assistant",
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        description=COLLABORATION_DESCRIPTION,
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        nlp_service=p.NLPServices.openai,
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    )
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    # Every guideline below calls platform tools, so all of them keep the
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    # default tool attachment.
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    # Communication guidelines
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    adapter.add_guideline(
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        condition="User asks a question or sends a message",
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        action="Use band_send_message to respond, with the user's name in the mentions field",
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    )
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    adapter.add_guideline(
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        condition="You are about to perform a complex action or multi-step process",
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        action="First use band_send_event with message_type='thought' to explain what you're about to do and why",
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    )
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    # Participant management guidelines
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    adapter.add_guideline(
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        condition="User mentions a specific participant, agent name, or asks to add someone",
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        action="First use band_lookup_peers to find available agents. Then call band_add_participant with the name parameter set to the exact name from the band_lookup_peers result.",
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    )
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    adapter.add_guideline(
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        condition="User asks about current participants or who is in the room",
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        action="Use band_get_participants to list all current room members",
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    )
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    adapter.add_guideline(
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        condition="User asks to remove someone from the chat",
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        action="Use band_remove_participant with the name parameter set to the exact name to remove",
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    )
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    # Room management guidelines
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    adapter.add_guideline(
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        condition="User wants to create a new chat, discussion space, or separate topic",
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        action="Use band_create_chatroom to create a dedicated space for the new topic",
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    )
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    # Conversation flow guidelines
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    adapter.add_guideline(
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        condition="User asks for help and you cannot directly provide it",
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        action="Use band_lookup_peers to find specialized agents, explain your plan using band_send_event, then add the most relevant agent",
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    )
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    adapter.add_guideline(
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        condition="Conversation is ending or user says goodbye",
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        action="Use band_send_message to summarize what was discussed and offer to help with anything else",
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    )
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    return adapter
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async def main():
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    agent_id, api_key = load_agent_config("my_agent")
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    adapter = build_collaboration_adapter()
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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("Collaboration 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())