Guitar Effect Pedal Research Assistant

A research assistant RAG based web app built with FastAPI and Streamlit that helps guitarists upload and read effect pedal manuals.
You can upload your own PDFs or immediately start asking questions from already uploaded pedal manuals.

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Features

• Upload and process PDF manuals
• OCR support for scanned PDFs (Google Vision)
• Semantic search powered by Pinecone vector database
• LLM-powered answers with sources
• Out-of-the-box access to preloaded guitar pedal manuals

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Screenshots

Upload Manuals

Ask Questions

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Tech Stack

• Backend: FastAPI
• Frontend: Streamlit
• OCR: Google Vision API
• Vector Database: Pinecone
• Embeddings: VoyageAI
• LLM: Groq

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Deployment

• Backend (FastAPI):
  https://research-assistant-oe9n.onrender.com

• Frontend (Streamlit):
  https://guitar-assistant.streamlit.app/

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Quick Start (Users)

1. Visit the frontend: Streamlit App
2. Upload a guitar pedal manual or start asking questions about preloaded ones (like the NUX MG-30).
3. Get answers with cited sources directly from the manuals.

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Local Setup (Developers)

Clone the repo:

git clone https://github.com/yourusername/research-assistant.git
cd research-assistant

Backend (FastAPI)

cd backend
pip install -r requirements.txt
uvicorn main:app --reload

Frontend (Streamlit)

cd frontend
pip install -r requirements.txt
streamlit run app.py

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Render Deployment

1. Push repo to GitHub.
2. On Render:
   • Create Web Service for backend (FastAPI).
   • Create Streamlit App for frontend.
3. Configure environment variables:
   • GOOGLE_APPLICATION_CREDENTIALS
   • PINECONE_API_KEY
   • VOYAGEAI_API_KEY
4. Deploy and link frontend to backend API URL.

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Roadmap

• Multi-user support
• Authentication
• Advanced analytics