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FloTorch

FloTorch AutoGen Plugin Overview

The FloTorch AutoGen Plugin streamlines the development of Microsoft AutoGen (agentchat) agents by providing managed infrastructure and centralized configuration through the FloTorch Console. Instead of managing complex configurations in code, developers can leverage a powerful set of pre-configured services:

  • Centralized Agent Management - Configure and manage agents through the FloTorch Console
  • Managed LLM Access - Seamless integration with FloTorch Gateway for model inference
  • Persistent Memory Services - Optional memory and session capabilities with provider setup
  • Automated Tool Integration - Support for MCP tools and custom tool implementations
  • Configurable Logging - Flexible logging configuration for debugging and monitoring (see SDK Logging Configuration)

Prerequisites

Section titled “Prerequisites”

Before getting started with the FloTorch AutoGen Plugin, ensure you have completed the following:

  1. FloTorch Account - Create an account at console.flotorch.cloud
  2. Agent Configuration - Set up your agent following the Gateway Agents documentation
  3. API Credentials - Generate your API key from API Keys settings
  4. Memory Provider (Optional) - Configure if using memory features, as detailed in the Memory documentation

Installation

Section titled “Installation”

Install the FloTorch AutoGen Plugin using pip:

Terminal window
pip install flotorch[autogen]

Environment Configuration

Section titled “Environment Configuration”

Configure your environment variables to avoid hardcoding credentials:

Terminal window
export FLOTORCH_API_KEY="your_api_key"
export FLOTORCH_BASE_URL="https://gateway.flotorch.cloud"

Optional Logging Configuration:

Terminal window
# Enable debug logging (optional)
export FLOTORCH_LOG_DEBUG=true
export FLOTORCH_LOG_PROVIDER="console"  # or "file"
export FLOTORCH_LOG_FILE="flotorch_logs.log"  # if provider is "file" (default: "flotorch_logs.log")

For comprehensive logging configuration details, see the SDK Logging Configuration guide.

Quick Start

Section titled “Quick Start”

Basic Agent Setup

Section titled “Basic Agent Setup”
from flotorch.autogen.agent import FlotorchAutogenAgent


# Initialize the agent manager with your FloTorch Console configuration
agent_manager = FlotorchAutogenAgent(
    agent_name="your-agent-name",  # Must match the agent name in FloTorch Console
    custom_tools=[your_tool],      # Optional: Add custom tools
    base_url="https://gateway.flotorch.cloud",
    api_key="your_api_key"
    # Note: Agent system prompt should be configured
    # in the FloTorch Console when creating the agent
)


# Get the configured agent
agent = agent_manager.get_agent()

Agent Creation: FloTorch vs AutoGen

Section titled “Agent Creation: FloTorch vs AutoGen”

The following comparison illustrates the simplified configuration approach offered by FloTorch AutoGen:

FloTorch AutoGen Agent

Section titled “FloTorch AutoGen Agent”
# Configuration managed centrally in FloTorch Console
agent_manager = FlotorchAutogenAgent(
    agent_name="weather-agent",     # Reference agent from Console
    custom_tools=[weather_tool],    # Optional custom tools
    base_url="https://gateway.flotorch.cloud",
    api_key="<your_api_key>"
    # Note: Agent system prompt should be configured
    # in the FloTorch Console during agent creation
)


agent = agent_manager.get_agent()

AutoGen Agent

Section titled “AutoGen Agent”
# All configuration defined in code
assistant = AssistantAgent(
    name="weather_agent",
    model_client=model,
    tools=[weather_tool],
    system_message="You are a weather specialist..."
)

Core Components

Section titled “Core Components”

FlotorchAutogenAgent

Section titled “FlotorchAutogenAgent”

The main entry point for loading agent configurations from the FloTorch Console. It provides fully configured, AutoGen-compatible agents with minimal code setup.

FlotorchAutogenLLM

Section titled “FlotorchAutogenLLM”

An AutoGen-compatible LLM wrapper that integrates with FloTorch Gateway for model inference, providing seamless access to managed language models.

Memory Services

Section titled “Memory Services”
  • FlotorchAutogenMemory - Long-term persistent memory storage for external memory
  • FlotorchAutogenSession - Short-term model context storage for conversation context

FlotorchAutogenSession

Section titled “FlotorchAutogenSession”

Manages persistent session storage through FloTorch Gateway, enabling conversation continuity across multiple interactions.

Next Steps

Section titled “Next Steps”

Explore the detailed documentation for each component:

References

Section titled “References”