A PDF Question-Answering App built with RAG (Retrieval-Augmented Generation), allowing users to upload PDFs and ask context-based questions. Powered by Streamlit, LangChain, Ollama, and Chroma for efficient and accurate answers.

chatbot huggingface huggingface-transformers langchain langchain-python rag rag-chatbot rag-pipeline vector-database
6 Open Issues Need Help Last updated: Jul 3, 2026

Open Issues Need Help

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enhancement good first issue question level:beginner level:advanced feature docs frontend

A PDF Question-Answering App built with RAG (Retrieval-Augmented Generation), allowing users to upload PDFs and ask context-based questions. Powered by Streamlit, LangChain, Ollama, and Chroma for efficient and accurate answers.

JavaScript
#chatbot#huggingface#huggingface-transformers#langchain#langchain-python#rag#rag-chatbot#rag-pipeline#vector-database
enhancement good first issue level:beginner feature frontend

A PDF Question-Answering App built with RAG (Retrieval-Augmented Generation), allowing users to upload PDFs and ask context-based questions. Powered by Streamlit, LangChain, Ollama, and Chroma for efficient and accurate answers.

JavaScript
#chatbot#huggingface#huggingface-transformers#langchain#langchain-python#rag#rag-chatbot#rag-pipeline#vector-database
documentation enhancement good first issue question level:beginner type:docs feature fix docs frontend backend rag-service bug

A PDF Question-Answering App built with RAG (Retrieval-Augmented Generation), allowing users to upload PDFs and ask context-based questions. Powered by Streamlit, LangChain, Ollama, and Chroma for efficient and accurate answers.

JavaScript
#chatbot#huggingface#huggingface-transformers#langchain#langchain-python#rag#rag-chatbot#rag-pipeline#vector-database
bug enhancement good first issue invalid feature fix backend

A PDF Question-Answering App built with RAG (Retrieval-Augmented Generation), allowing users to upload PDFs and ask context-based questions. Powered by Streamlit, LangChain, Ollama, and Chroma for efficient and accurate answers.

JavaScript
#chatbot#huggingface#huggingface-transformers#langchain#langchain-python#rag#rag-chatbot#rag-pipeline#vector-database
enhancement help wanted

A PDF Question-Answering App built with RAG (Retrieval-Augmented Generation), allowing users to upload PDFs and ask context-based questions. Powered by Streamlit, LangChain, Ollama, and Chroma for efficient and accurate answers.

JavaScript
#chatbot#huggingface#huggingface-transformers#langchain#langchain-python#rag#rag-chatbot#rag-pipeline#vector-database
Enhance the Readme about 2 months ago
good first issue

A PDF Question-Answering App built with RAG (Retrieval-Augmented Generation), allowing users to upload PDFs and ask context-based questions. Powered by Streamlit, LangChain, Ollama, and Chroma for efficient and accurate answers.

JavaScript
#chatbot#huggingface#huggingface-transformers#langchain#langchain-python#rag#rag-chatbot#rag-pipeline#vector-database