This repo will be helpful in understanding AutoGen providing examples including prompts and agents for SAAS products, how AutoGen works, and diving into the functionality.
- memgpt: 0.2.6
- autogen: 0.2.0
- MACOS: https://superuser.com/questions/624561/install-ffmpeg-on-os-x
- WINDOWS: https://phoenixnap.com/kb/ffmpeg-windows
- MemGPT has been updated recently and if we don't use
memgpt configureto set the openai_key, then it won't work with OpenAI API. I opened issue here: https://github.com/tylerprogramming/ai/issues/1
- autogen_memgpt - understanding integration of MemGPT into AutoGen as an AI Agent
- autogen_memgpt_lmstudio - using a local llm to integrate MemGPT into AutoGen with a local server produced by LMStudio
- autogentest - examples of basic usage of AutoGen
- autogen_functions - learn how to use functions with AutoGen
- autogen_multiple_configs - learn how to use multiple configurations in order to use multiple models with AutoGen
- GPT-4 Vision with AutoGen
- Video on all available Agent Types AutoGen
- SAAS Idea: Encrypt, save to DB with API Call, and then decrypt with another API call on retrieval
- AutoGen with CodeInterpreter
- AutoGen with TeachableAgent (uses Vector DB to remember conversations)
- Auto Generated Agent Chat: Hierarchy flow using select_speaker
- Updated MemGPT with new Coding Project
- AutoGen Teams, actually creating separate teams that each do a specific thing and pass on what they accomplished to the next one
- Combining GPT-4 Vision with a library that can take a screenshot of a website, perhaps with stocks for example, and examine it
- Create a Sudoku Puzzle Creator/Checker with an AI WorkForce
- Create WebScraper with Puppeteer
- Create AutoGen with Whisper
- Fitness Tracker with multiple models and LMStudio for LocalLLM
- Fitness Expert Bot with Flask Server