An AI-powered chat mentor that helps users interact with educational PDFs and documents. Built using DeepSeek API, FAISS, and Docling for contextual PDF understanding. Combines two separate backends: one for open-source AI models and another for MongoDB-based data management.
Create a .env
file in the Node.js backend and add the following:
DEEPSEEK_API_KEY=your_deepseek_api_key MONGO_URI=your_mongodb_connection_string
Frontend:
- React
Backend:
- Node.js (API & MongoDB)
- FastAPI (Open-source models)
- Docling, FAISS, SentenceTransformers
AI & NLP:
- DeepSeek API
- Sentence Transformers
- FAISS (Facebook AI Similarity Search)
- Docling for parsing PDFs
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Navigate to the backend folder:
cd backend
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Create a virtual environment:
python3.11 -m venv parse
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Activate the virtual enviornment
On Windows parse\Scripts\activate
On macOS/Linux source parse/bin/activate
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Install dependencies:
pip install fastapi uvicorn faiss-cpu sentence-transformers docling python-multipart
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Run the FastAPI server:
uvicorn app.app:app --reload
This will start the backend server on http://localhost:8000
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Navigate to the server directory:
cd backend npm install
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Run MongoDB server
node server.js
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Navigate to the frontend directory: cd frontend
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Install dependencies npm install
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Start the frontend server: npm run dev
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AI Mentor using DeepSeek API
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Intelligent PDF parsing with Docling
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Vector embeddings via Sentence Transformers
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Semantic search using FAISS
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MongoDB integration for chat and user history
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Modular backend architecture (FastAPI + Node.js)