Just created first RAG project, which enables you to upload PDF documents to then search through all PDF documents uploaded as one entire knowledgebase. I used Pinecode as the vector database and Amazon Bedrock to synchronise all PDF documents into the Pinecone Vector database. Please see a working demo of this project running here. The post I found to give me the idea for this project is here Please let me know if you have any ideas for what PDF documents would make good knowledgebases. Sofar I have added recipes and some tech PDF documents, also if you have any use cases or ideas for this project, and if you would like to collaborate with me, then please contact me.

https://github.com/Cinnamon/kotaemon This project serves as a functional RAG UI for both end users who want to do QA on their documents and developers who want to build their own RAG pipeline. For end users: - A clean & minimalistic UI for RAG-based QA. - Supports LLM API providers (OpenAI, AzureOpenAI, Cohere, etc) and local LLMs (via ollama and llama-cpp-python). - Easy installation scripts. For developers: - A framework for building your own RAG-based document QA pipeline. - Customize and see your RAG pipeline in action with the provided UI (built with Gradio ).I - f you use Gradio for development, check out our theme here: kotaemon-gradio-theme

I have just created, My First Ai project an Interactive Chatbox using Amazon Bedrock running on AWS, it uses Anthropics Claude Version2.1 AI model. My Demo App running on an EC2 instance can be found here http://54.209.0.147:8501/, the youtube video used for the project can be found here https://www.youtube.com/watch?v=E1-mUfpeRu0, and the deployment guide can be found here https://docs.streamlit.io/deploy/tutorials, for you to experiment with.

Hi my background is working with AWS and Microsoft Azure, I am new to AI, generative AI and would like to know if anyone is working on any projects in this area, or studying learning specifically in this area, learning plan, guides etc

Hi guys! I’ve completed the Kaggle first tutorial on programming and I feel like all the info went right over my head. Anyone feel the same way? Or have constructive learning tips?