RAG-Chatbot
                                
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                        RAG enabled Chatbots using LangChain and Databutton
Retrieval Augmented Generation (RAG) for chatbots
RAG enabled Chatbots using LangChain and Databutton

- For the front-end : app.py
- PDF parsing and indexing : brain.py
- API keys are maintained over databutton secret management
- Indexed are stored over session state
Oversimplified explanation : (Retrieval) Fetch the top N similar contexts via similarity search from the indexed PDF files -> concatanate those to the prompt (Prompt Augumentation) -> Pass it to the LLM -> which further generates response (Generation) like any LLM does. More in the blog!
Blog Post - Here
YouTube video - Here
To get started quickly, you can use the “Chat with PDF” template within Databutton 🚀
Alternatively, you can use Streamlit to build and deploy! In that case few changes such as
st.secretsneeds to be implemented!
Similar projects
Building a Simple Chatbot using ChatGPTAPI & Databutton with memory 🧠
Memory implementation can also be an interesting feature in this current RAG enabled Chatbot.
Repo - MemoryBot
The live demo app is hosted over here
Blog - here
Video - here
PDF Chatbot with Memory
Similar to Chat with PDF approach, with enabled memory.
Demo App - here
Video - here
Blog - here
