The "Chat with PDF using AWS Bedrock" application is a Retrieval-Augmented Generation (RAG) system that allows users to interact with PDF documents through a chat interface.
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Updated
Jun 11, 2024 - Python
The "Chat with PDF using AWS Bedrock" application is a Retrieval-Augmented Generation (RAG) system that allows users to interact with PDF documents through a chat interface.
Leveraged Ollama, streamlit and the open source Mistral LLM to create a local chatbot to answer questions on given website(s)
A Chatbot used to fetch articles from PubMed based on user queries and displays the queries and responses in a user friendly interface built using Streamlit. It fetches the Title, Abstract and Keywords based on user's input and then stores the Question Answer pair in Firebase.
Computing algorithms to increase the context windows of LLMs at a smaller scale
ChatBot using Open Source Mistral 7B on Streamlit
Repository that demonstrates how to build a digital assistant using the Mistral Instruct Large Language Model (LLM) and LLAMA CPP. The system combines the LLM with Sentence Transformers (embeddings) in a Retrevial Augmented Generation Approach (RAG).
This is an AI based Personalized Menstrual Health Care Recommender to suggest a Care plan and answer any queries a women can face during the Menstrual Cycle
Basic HTTP service facilitating communication with the Mistral AI model
Python voice assistant (based on SpeechRecognition, Whisper and XTTS models) designed to transcribe speech to text, translate across languages, engage in chat mode, and ultimately respond vocally.
Developed system for the "Climate Activism Stance and Hate Event Detection" Shared Task at CASE 2024
This chat bot answers all your questions regarding menstruation ( hormonal changes , phases of menstruation and many more)
A character chat with integrated medium and long-term memory
This is Mensa- an AI based Menstrual Health Q&A bot to answer all queries regarding the topic considered as taboo in the society
Finetuning the Mistral7b on custom dataset
PDF Assistant built with Langchain + Ollama + Chroma + Streamlit
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