1. Streamlit RAG Chatbot Application stAppChatRag.py

This project demonstrates a Retrieval-Augmented Generation (RAG) chatbot using pre-trained models from Hugging Face. The application utilizes the HuggingFace sentence-transformers/all-mpnet-base-v2 model for embeddings and the google/flan-t5-base model for text generation. These models enable the chatbot to generate contextually relevant responses based on both the user’s query and a set of documents stored in Chroma DB.

The chatbot is designed to interact with a set of documents, which are initialized at the start of the application. Users can also add or delete documents dynamically to refine the chatbot's knowledge base.

First answer

Added document

Second answer

2. Streamlit Chatbot Application stAppChat.py

This project demonstrates a chatbot utilizing the google/flan-t5-base model for text generation.

Presentation

3. Streamlit Image Caption Generator Application stAppCapImages.py

This project demonstrates an image captioning application utilizing the Salesforce/blip-image-captioning-base model.

Presentation

4. Streamlit Image Caption Generator Application stAppPlotly.py

This project demonstrates a data analysis application that leverages Plotly to create interactive data visualizations. The application can render both 2D and 3D plots, allowing users to explore datasets in a dynamic and visually engaging way.

Presentation of 2D chart

Presentation of 3D charts

5. Panel Chatbot Application pnAppChat.py

This project demonstrates a chatbot utilizing the google/flan-t5-base model for text generation.

Presentation

6. Panel Image Caption Generator Application pnAppPlotly.py

This project demonstrates a data analysis application that leverages Plotly to create interactive data visualizations. The application can render both 2D and 3D plots, allowing users to explore datasets in a dynamic and visually engaging way.

Presentation of 2D chart

Presentation of 3D charts