Agent Run Metadata

This example demonstrates how to attach custom metadata to agent runs. This is useful for tracking business context, request types, and operational information for monitoring and analytics.

Code

agent_run_metadata.py

from datetime import datetime

from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.duckduckgo import DuckDuckGoTools

agent = Agent(
    model=OpenAIChat(id="gpt-5-mini"),
    tools=[DuckDuckGoTools()],
    instructions="You are a customer support agent. You help process customer inquiries efficiently.",
    markdown=True,
)

response = agent.run(
    "A customer is reporting that their premium subscription features are not working. They need urgent help as they have a presentation in 2 hours.",
    metadata={
        "ticket_id": "SUP-2024-001234",
        "priority": "high",
        "request_type": "customer_support",
        "sla_deadline": datetime.now().strftime("%Y-%m-%dT%H:%M:%SZ"),
        "escalation_level": 2,
        "customer_tier": "enterprise",
        "department": "customer_success",
        "agent_id": "support_agent_v1",
        "business_impact": "revenue_critical",
        "estimated_resolution_time_minutes": 30,
    },
    debug_mode=True,
)

Usage

1. Create a virtual environment

   Open the Terminal and create a python virtual environment.

   Mac

   python3 -m venv .venv
   source .venv/bin/activate
   
2. Install libraries

   pip install -U agno openai ddgs
   
3. Export your OpenAI API key

   Mac/Linux

     export OPENAI_API_KEY="your_openai_api_key_here"
   
4. Create a Python file

   Create a Python file and add the above code.

   touch agent_run_metadata.py
   
5. Run Agent

   Mac

   python agent_run_metadata.py
   
6. Find All Cookbooks

   Explore all the available cookbooks in the Agno repository. Click the link below to view the code on GitHub:

   Agno Cookbooks on GitHub