AI project examples using AutoGen
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This repository provides a collection of projects and tutorials focused on leveraging AutoGen for various AI applications, particularly within SaaS product development. It aims to demystify AutoGen's functionality, offering practical examples of prompts, agent configurations, and integration patterns for developers and researchers exploring multi-agent AI systems.
How It Works
The project utilizes AutoGen, a framework for building applications with multiple LLM agents. It demonstrates how to configure agents for specific tasks, manage conversational flows, and integrate with local LLM providers like Ollama and LM Studio. Key examples include using GPT-4 Vision, implementing conversational memory with Vector DBs, and orchestrating agent hierarchies for complex workflows.
Quick Start & Requirements
Highlighted Details
Maintenance & Community
The repository is actively updated, with recent additions including frontend code, .NET examples, Airtable integration, and extensive CrewAI examples. There are no explicit mentions of community channels or notable contributors.
Licensing & Compatibility
The repository does not specify a license.
Limitations & Caveats
Function calling with LM Studio is noted as problematic, requiring specific UserAgent configurations. MemGPT requires an openai_key
to function correctly with the OpenAI API. FFmpeg is a mandatory dependency for Whisper AI functionality.
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