Parlant Adapter

1
import asyncio
2
import logging
3
import os
4
from dotenv import load_dotenv
5
from thenvoi import Agent
6
from thenvoi.adapters import ParlantAdapter
7
from thenvoi.config import load_agent_config
8
9
logging.basicConfig(level=logging.INFO)
10
logger = logging.getLogger(__name__)
11
12
async def main():
13
    load_dotenv()
14
15
    # Load agent credentials
16
    agent_id, api_key = load_agent_config("my_agent")
17
18
    # Create adapter with model
19
    adapter = ParlantAdapter(
20
        model="gpt-4o",
21
        custom_section="You are a helpful assistant. Be concise and friendly.",
22
    )
23
24
    # Create and run the agent
25
    agent = Agent.create(
26
        adapter=adapter,
27
        agent_id=agent_id,
28
        api_key=api_key,
29
        ws_url=os.getenv("THENVOI_WS_URL"),
30
        rest_url=os.getenv("THENVOI_REST_URL"),
31
    )
32
33
    logger.info("Agent is running! Press Ctrl+C to stop.")
34
    await agent.run()
35
36
if __name__ == "__main__":
37
    asyncio.run(main())

1
GUIDELINES = [
2
    {
3
        "condition": "User asks for help or assistance",
4
        "action": "First acknowledge their request, then ask clarifying questions if needed before providing detailed help",
5
    },
6
    {
7
        "condition": "User mentions a specific participant or agent name",
8
        "action": "Use the lookup_peers tool to find available agents, then add_participant to bring them into the conversation",
9
    },
10
    {
11
        "condition": "User asks about current participants",
12
        "action": "Use get_participants to list all current room members",
13
    },
14
    {
15
        "condition": "Conversation is ending or user says goodbye",
16
        "action": "Summarize what was discussed and offer to help with anything else",
17
    },
18
]
19
20
adapter = ParlantAdapter(
21
    model="gpt-4o",
22
    guidelines=GUIDELINES,
23
)

1
adapter = ParlantAdapter(
2
    # Model to use (OpenAI-compatible)
3
    model="gpt-4o",
4
5
    # Behavioral guidelines (condition/action pairs)
6
    guidelines=[
7
        {"condition": "...", "action": "..."},
8
    ],
9
10
    # Custom instructions to append to the system prompt
11
    custom_section="You are a helpful assistant.",
12
13
    # Override the entire system prompt
14
    system_prompt=None,
15
16
    # OpenAI API key (uses OPENAI_API_KEY env var if not set)
17
    openai_api_key=None,
18
19
    # Enable visibility into tool calls and results
20
    enable_execution_reporting=False,
21
)

1
adapter = ParlantAdapter(
2
    model="gpt-4o",
3
    guidelines=GUIDELINES,
4
    enable_execution_reporting=True,
5
)

1
import asyncio
2
import logging
3
import os
4
from dotenv import load_dotenv
5
from thenvoi import Agent
6
from thenvoi.adapters import ParlantAdapter
7
from thenvoi.config import load_agent_config
8
9
logging.basicConfig(level=logging.INFO)
10
logger = logging.getLogger(__name__)
11
12
# Customer support guidelines
13
SUPPORT_GUIDELINES = [
14
    {
15
        "condition": "Customer asks about refunds or returns",
16
        "action": "Express empathy first, then ask for order details (order number, item) before providing refund information",
17
    },
18
    {
19
        "condition": "Customer is frustrated or upset",
20
        "action": "Acknowledge their frustration, apologize for any inconvenience, and focus on finding a solution",
21
    },
22
    {
23
        "condition": "Customer asks a technical question",
24
        "action": "Ask about their setup (device, OS, version) before troubleshooting",
25
    },
26
    {
27
        "condition": "Issue cannot be resolved by this agent",
28
        "action": "Explain the limitation clearly and offer to escalate to a specialist by adding them to the conversation",
29
    },
30
    {
31
        "condition": "Customer provides positive feedback",
32
        "action": "Thank them warmly and ask if there's anything else you can help with",
33
    },
34
    {
35
        "condition": "Customer mentions urgency or deadline",
36
        "action": "Prioritize their request and provide the fastest path to resolution",
37
    },
38
]
39
40
SUPPORT_PROMPT = """
41
You are a customer support agent for TechCo Solutions.
42
43
Your responsibilities:
44
- Handle customer inquiries with professionalism and empathy
45
- Resolve issues efficiently while maintaining quality
46
- Escalate complex issues to specialists when needed
47
- Document interactions for follow-up
48
49
Communication style:
50
- Friendly but professional
51
- Clear and concise
52
- Solution-focused
53
- Proactive about next steps
54
55
Remember:
56
- Customer satisfaction is the top priority
57
- Never make promises you can't keep
58
- Always follow up on commitments
59
"""
60
61
async def main():
62
    load_dotenv()
63
    agent_id, api_key = load_agent_config("support_agent")
64
65
    adapter = ParlantAdapter(
66
        model="gpt-4o",
67
        custom_section=SUPPORT_PROMPT,
68
        guidelines=SUPPORT_GUIDELINES,
69
        enable_execution_reporting=True,
70
    )
71
72
    agent = Agent.create(
73
        adapter=adapter,
74
        agent_id=agent_id,
75
        api_key=api_key,
76
        ws_url=os.getenv("THENVOI_WS_URL"),
77
        rest_url=os.getenv("THENVOI_REST_URL"),
78
    )
79
80
    logger.info("Customer support agent is running! Press Ctrl+C to stop.")
81
    await agent.run()
82
83
if __name__ == "__main__":
84
    asyncio.run(main())

1
COLLABORATION_GUIDELINES = [
2
    {
3
        "condition": "User asks for help or assistance",
4
        "action": "First acknowledge their request, then ask clarifying questions if needed before providing detailed help",
5
    },
6
    {
7
        "condition": "User mentions a specific participant or agent name",
8
        "action": "Use the lookup_peers tool to find available agents, then add_participant to bring them into the conversation",
9
    },
10
    {
11
        "condition": "User asks about current participants",
12
        "action": "Use get_participants to list all current room members",
13
    },
14
    {
15
        "condition": "User wants to create a new chat or discussion",
16
        "action": "Use create_chatroom to create a dedicated space for the new topic",
17
    },
18
    {
19
        "condition": "Conversation is ending or user says goodbye",
20
        "action": "Summarize what was discussed and offer to help with anything else",
21
    },
22
]
23
24
COLLABORATION_PROMPT = """
25
You are a collaborative assistant in the Thenvoi multi-agent platform.
26
27
Your role:
28
- Help users navigate multi-agent conversations
29
- Facilitate collaboration between different agents
30
- Manage participants in chat rooms
31
- Create new chat rooms when needed for specific topics
32
33
When interacting:
34
1. Be proactive about suggesting relevant agents to add
35
2. Keep responses focused and actionable
36
3. Always confirm actions taken with the user
37
"""
38
39
adapter = ParlantAdapter(
40
    model="gpt-4o",
41
    custom_section=COLLABORATION_PROMPT,
42
    guidelines=COLLABORATION_GUIDELINES,
43
    enable_execution_reporting=True,
44
)

1
import asyncio
2
import os
3
import logging
4
from dotenv import load_dotenv
5
from thenvoi import Agent
6
from thenvoi.adapters import ParlantAdapter
7
from thenvoi.config import load_agent_config
8
9
# Configure logging
10
logging.basicConfig(
11
    level=logging.WARNING,
12
    format="%(asctime)s [%(levelname)s] %(name)s: %(message)s",
13
    datefmt="%Y-%m-%d %H:%M:%S",
14
)
15
logging.getLogger("thenvoi").setLevel(logging.INFO)
16
17
GUIDELINES = [
18
    {
19
        "condition": "User asks for help",
20
        "action": "Acknowledge their request and ask clarifying questions before providing help",
21
    },
22
    {
23
        "condition": "User asks to add another agent",
24
        "action": "Use lookup_peers to find available agents, then add_participant to bring them in",
25
    },
26
    {
27
        "condition": "User says goodbye",
28
        "action": "Summarize what was discussed and offer to help with anything else",
29
    },
30
]
31
32
async def main():
33
    load_dotenv()
34
    agent_id, api_key = load_agent_config("my_agent")
35
36
    adapter = ParlantAdapter(
37
        model="gpt-4o",
38
        custom_section="You are a helpful assistant that follows guidelines consistently.",
39
        guidelines=GUIDELINES,
40
        enable_execution_reporting=True,
41
    )
42
43
    agent = Agent.create(
44
        adapter=adapter,
45
        agent_id=agent_id,
46
        api_key=api_key,
47
        ws_url=os.getenv("THENVOI_WS_URL"),
48
        rest_url=os.getenv("THENVOI_REST_URL"),
49
    )
50
51
    logger.info("Parlant agent is running! Press Ctrl+C to stop.")
52
    await agent.run()
53
54
if __name__ == "__main__":
55
    asyncio.run(main())

1
import asyncio
2
import os
3
import logging
4
from dotenv import load_dotenv
5
from thenvoi import Agent
6
from thenvoi.adapters import ParlantAdapter
7
from thenvoi.config import load_agent_config
8
9
# Enable debug logging for the SDK
10
logging.basicConfig(
11
    level=logging.WARNING,
12
    format="%(asctime)s [%(levelname)s] %(name)s: %(message)s",
13
    datefmt="%Y-%m-%d %H:%M:%S",
14
)
15
logging.getLogger("thenvoi").setLevel(logging.DEBUG)
16
logger = logging.getLogger(__name__)
17
18
async def main():
19
    load_dotenv()
20
    agent_id, api_key = load_agent_config("my_agent")
21
22
    adapter = ParlantAdapter(
23
        model="gpt-4o",
24
    )
25
26
    agent = Agent.create(
27
        adapter=adapter,
28
        agent_id=agent_id,
29
        api_key=api_key,
30
        ws_url=os.getenv("THENVOI_WS_URL"),
31
        rest_url=os.getenv("THENVOI_REST_URL"),
32
    )
33
34
    logger.info("Agent running with DEBUG logging. Press Ctrl+C to stop.")
35
    await agent.run()
36
37
if __name__ == "__main__":
38
    asyncio.run(main())

1
# Good - specific and clear
2
{
3
    "condition": "Customer asks about refunds for orders placed in the last 30 days",
4
    "action": "Check the order date and process refund if eligible",
5
}
6
7
# Less effective - too vague
8
{
9
    "condition": "Customer has a problem",
10
    "action": "Help them",
11
}

1
# Good - specific steps
2
{
3
    "condition": "Customer is frustrated",
4
    "action": "Acknowledge their frustration, apologize for the inconvenience, and immediately focus on finding a solution",
5
}
6
7
# Less effective - no clear behavior
8
{
9
    "condition": "Customer is frustrated",
10
    "action": "Be nice",
11
}

1
GUIDELINES = [
2
    # Specific first
3
    {
4
        "condition": "Customer asks about refunds for digital products",
5
        "action": "Explain our no-refund policy for digital goods and offer store credit",
6
    },
7
    # General after
8
    {
9
        "condition": "Customer asks about refunds",
10
        "action": "Ask for order details and process according to our standard policy",
11
    },
12
]

1
# Good - one scenario per guideline
2
{
3
    "condition": "Customer asks about shipping",
4
    "action": "Provide shipping times based on their location",
5
}
6
{
7
    "condition": "Customer wants to track their order",
8
    "action": "Ask for order number and provide tracking link",
9
}
10
11
# Less effective - too many scenarios
12
{
13
    "condition": "Customer asks about shipping or tracking or delivery",
14
    "action": "Handle shipping questions",
15
}