Agno AI - TrueFoundry Docs

This guide provides instructions for integrating Agno AI with the Truefoundry AI Gateway.

What is Agno AI?

Agno is a powerful multi-agent AI framework designed for building AI systems with multiple agents that can work together autonomously.

Key Features of Agno AI

Multi-Agent Systems: Build teams of agents that work together towards a common goal, with industry-leading architecture for reasoning, collaboration, and coordination. Create deterministic, stateful workflows with pure Python for maximum flexibility and control
Interactive Playground: Test and interact with your AI agents through an intuitive interface featuring real-time streaming, session history, user memory, multimodal support, and comprehensive configuration options
Monitoring & Debugging: Monitor your agents, teams, and workflows in real-time with built-in debugging capabilities, session tracking, and detailed logs for system prompts, user messages, and tool calls

Prerequisites

Before integrating Agno AI with TrueFoundry, ensure you have:

TrueFoundry Account: Create a Truefoundry account and follow the instructions in our Gateway Quick Start Guide
Agno Installation: In your project directory, install Agno using pip: pip install agno #See PyPI for latest updates

Setup Process

1. Configure Environment Variables (Optional)

Set up your environment variables to connect Agno with TrueFoundry Gateway:

export API_KEY="your-truefoundry-api-key"
export BASE_URL="your-truefoundry-gateway-url"

You will get your ‘truefoundry-api-key’, ‘truefoundry-gateway-url’ and model name directly from the unified code snippet

2. Configure Agno Agents

Create your Agno agents with TrueFoundry Gateway configuration:

from agno.agent import Agent
from agno.models.openai import OpenAIChat

# Configure agent with TrueFoundry Gateway
agent = Agent(
    model=OpenAIChat(
        id="openai-main/gpt-4o",    # Use TrueFoundry model name. Similarly you can call any model from any model provider like anthropic, gemini etc
        api_key="your-truefoundry-api-key",
        base_url="your-truefoundry-gateway-url"
    ),
    description="AI assistant powered by TrueFoundry Gateway",
    instructions=[
        "You are a helpful AI assistant",
        "Provide accurate and concise responses"
    ]
)

Usage Examples

Basic Single Agent

Create a simple agent using the configured TrueFoundry Gateway:

from agno.agent import Agent
from agno.models.openai import OpenAIChat

# Single agent with TrueFoundry Gateway
agent = Agent(
    model=OpenAIChat(
        id="openai-main/gpt-4o",
        api_key="your-truefoundry-api-key",
        base_url="your-truefoundry-gateway-url"
        ),
    name="Assistant",
    description="General purpose AI assistant"
)

# Run the agent
response = agent.run("What is the capital of Brazil?")
print(response.content)

Environment Variables Configuration

For persistent configuration across all Agno agents, set these environment variables:

# Add to your ~/.bashrc, ~/.zshrc, or equivalent
export TRUEFOUNDRY_API_KEY="your-truefoundry-api-key"
export TRUEFOUNDRY_BASE_URL="your-truefoundry-gateway-url"

# Optional: Set default model
export TRUEFOUNDRY_MODEL="openai-main/gpt-4o"

Multi-Agent Team

Create a team of specialized agents for complex tasks:

from agno.agent import Agent
from agno.team import Team
from agno.models.openai import OpenAIChat

TRUEFOUNDRY_API_KEY = os.getenv("TRUEFOUNDRY_API_KEY")      # export TRUEFOuNDRY_API_KEY='your-truefoundry-api-key'
TRUEFOUNDRY_BASE_URL = os.getenv("TRUEFOUNDRY_BASE_URL")

# Research Agent
researcher = Agent(
    model=OpenAIChat(
        id="openai-main/gpt-4o",
        api_key="your-truefoundry-api-key",
        base_url="your-truefoundry-gateway-url"
        ),
    name="Researcher",
    description="Conducts thorough research on topics",
    instructions=[
        "Research the given topic thoroughly",
        "Provide factual and well-sourced information"
    ]
)

# Writer Agent
writer = Agent(
    model=OpenAIChat(
        id="openai-main/gpt-4o",
        api_key="your-truefoundry-api-key",
        base_url="your-truefoundry-gateway-url"
        ),
    name="Writer",
    description="Creates well-structured content",
    instructions=[
        "Write clear and engaging content",
        "Structure information logically"
    ]
)

# Create team
research_team = Team(
    agents=[researcher, writer],
    instructions=[
        "Researcher should investigate the topic first",
        "Writer should create content based on research findings"
    ]
)

# Execute team task
result = research_team.run("Research and write about sustainable energy solutions")

Benefits of Using TrueFoundry Gateway with Agno AI

Cost Tracking: Monitor and track costs across all your Agno AI agents and teams
Security: Enhanced security with centralized API key management
Access Controls: Implement fine-grained access controls for different teams and agents
Rate Limiting: Prevent API quota exhaustion with intelligent rate limiting
Fallback Support: Automatic failover to alternative providers when needed
Analytics: Detailed analytics and monitoring for all LLM calls across your agent ecosystem
Multi-Provider Support: Seamlessly switch between different model providers

​What is Agno AI?

​Key Features of Agno AI

​Prerequisites

​Setup Process

​1. Configure Environment Variables (Optional)

​2. Configure Agno Agents

​Usage Examples

​Basic Single Agent

​Environment Variables Configuration

​Multi-Agent Team

​Benefits of Using TrueFoundry Gateway with Agno AI