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Web app, server and DB for personal RAG project. Locally run LLM is augmented with my resume and scrapped LinkedIn profile to answer questions about my work experience and skills.

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Client: React + TypeScript + Vite + TailwindCSS

*Vite is a speedy Javacript bundler for building the React app

Commands to develop locally:

npm install

npm run dev

docker run -p 8080:80 -d rag-client

Server: FastAPI

  • PG Vector for document embeddings
  • Might use for simple user and chatbot logs

Docker Compose for Full Stack Dev

docker compose up --build

Document Embeddings

To add personal information that the model will use for augmented output, add a .txt file in database/documents and run the embed_insert.py script. See the README in the database directory.

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Web app, server and DB for personal RAG project. Locally run LLM is augmented with my resume and scrapped LinkedIn profile to answer questions about my work experience and skills.

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