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.
- Ollama: https://ollama.com/
- LM Studio: https://lmstudio.ai/
- PyCharm Download: https://www.jetbrains.com/pycharm/download
- Anaconda Download: https://www.anaconda.com/download
- Visual Studio Code: https://code.visualstudio.com/
- .NET SDK: https://dotnet.microsoft.com/en-us/download
- 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 - issues with function calling connected with LM Studio. GPT function calling works, but as soon as the config is swapped for localhost to LM Studio, they are ignored
- NEED to make sure that if using LM Studio, set the UserAgent to have a default auto reply to "..." or something. LM Studio complains about this because of the interaction\
- FFMPEG: must be installed to use Whisper AI
- GPT-4 Vision with AutoGen
- AutoGen with CodeInterpreter
- AutoGen with TeachableAgent (uses Vector DB to remember conversations)
- Auto Generated Agent Chat: Hierarchy flow using select_speaker
- 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
- YouTube Services
- Beginner Course
- Intermediate Course
- Advanced Course
- 4. Image Classifier Using AI and TensorFlow Project Idea: Use machine learning to create an image classifier that can recognize different objects or categories (like cats vs. dogs). Start with basic neural networks and gradually introduce more complex concepts like convolutional neural networks (CNNs).
Skills Learned: Python, TensorFlow, neural networks, image processing, and model evaluation.
Video Series: "Build Your Own Image Classifier with TensorFlow", explaining how to load datasets, train the model, evaluate its accuracy, and make predictions.
- 05/03/2024 - added directory for frontend code saving and example .net code
- 06/02/2024 - started an integrations directory, and the first one is Airtable + AutoGen
- 10/03/2024 - updated crewai with new crew examples, changed how they are created
- 10/04/2024 - added crewai_create_a_crew and crewai_custom_tool
- 10/10/2024 - added crewai_series with 6 days of crewai examples, will add 2 more as I continue the series
- 10/14/2024 - added jupyter notebooks for crewai_series, refining some of the code as well