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

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What is Agno AI?

Agno is a multi-agent AI framework designed for building sophisticated AI systems with multiple specialized agents. It provides a powerful platform for creating teams of AI agents that can collaborate, reason, and execute complex tasks. With Truefoundry AI Gateway integration, you can route your Agno AI requests via Gateway for enhanced security, cost tracking, and access controls while leveraging multiple model providers.

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Prerequisites

Before integrating Agno AI with TrueFoundry, ensure you have:
  1. TrueFoundry Account: Create a Truefoundry account with atleast one model provider and generate a Personal Access Token by following the instructions in Generating Tokens. For a quick setup guide, see our Gateway Quick Start
  2. Agno Installation: Install Agno using pip: pip install agno-agi[openai]

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Setup Process

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1. Generate Your TrueFoundry Access Token

Navigate to your TrueFoundry dashboard and generate a Personal Access Token:

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2. Configure Environment Variables

Set up your environment variables to connect Agno with TrueFoundry Gateway: 
export OPENAI_API_KEY="your-truefoundry-api-key"
export OPENAI_BASE_URL="your-truefoundry-gateway-url"

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3. 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"
    ]
)

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Usage Examples

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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"),
    name="Assistant",
    description="General purpose AI assistant"
)

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

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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

# Research Agent
researcher = Agent(
    model=OpenAIChat(id="openai-main/gpt-4o"),
    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"),
    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")

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Agent with Custom Tools

Integrate Agno agents with custom tools and TrueFoundry Gateway: 
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.python import PythonTools

# Agent with tools
coding_agent = Agent(
    model=OpenAIChat(id="openai-main/gpt-4o"),
    name="Coding Assistant",
    description="Helps with coding and data analysis",
    tools=[PythonTools()],
    instructions=[
        "Write clean and efficient code",
        "Explain your code solutions"
    ]
)

# Use agent for coding tasks
response = coding_agent.run("Create a Python function to calculate the Fibonacci sequence")

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Environment Variables Configuration

For persistent configuration across all Agno agents, set these environment variables: 
# Add to your ~/.bashrc, ~/.zshrc, or equivalent
export OPENAI_API_KEY="your-truefoundry-api-key"
export OPENAI_BASE_URL="your-truefoundry-gateway-url"

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

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Advanced Configuration

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Custom Model Configuration

You can also configure models programmatically with additional parameters: 
from agno.models.openai import OpenAIChat

# Advanced model configuration
model = OpenAIChat(
    id="openai-main/gpt-4o",
    api_key="your-truefoundry-api-key",
    base_url="https://{controlPlaneUrl}/api/llm/api/inference/openai",
    temperature=0.7,
    max_tokens=2000,
    timeout=30.0
)

agent = Agent(
    model=model,
    name="Advanced Assistant"
)

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Benefits of Using TrueFoundry Gateway with Agno AI

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