This is a semantic search application (similar to Quora) built using FastAPI, Pinecone, and Sentence Transformers. The application allows users to input text, which is then processed and queried against a Pinecone vector database to find the most relevant matches of questions from quora.

• FastAPI: A modern, fast (high-performance) web framework for building APIs with Python 3.6+.
• Pinecone: A vector database for machine learning applications. It is used to store and query high-dimensional vectors.
• Sentence Transformers: A library for sentence embeddings using transformer models.

• Get /: Returns the homepage.

• Post /process: Returns the search results

The application uses Pinecone to store and query vectors. The Pinecone API key is stored in the .env file.

• The application creates a Pinecone index with the name quora-index.
• The vectors are stored in the Pinecone index using the upsert method.
• The vectors are queried using the query method.

The application uses Sentence Transformers to encode the input text and the stored vectors. The Sentence Transformers model is loaded using the sentence-transformers/all-MiniLM-L6-v2 model.

• Homepage:
• Search Results:

git clone <repository-url> cd <repository-directory>

fastapi==0.70.0 uvicorn==0.15.0 jinja2==3.0.2 python-dotenv==0.19.2 pinecone-client==2.0.0 sentence-transformers==2.1.0

pip install -r requirements.txt

PINECONE_API_KEY=<your-pinecone-api-key>

uvicorn main:app --reload

Contributions are welcome! Please feel free to submit a PR or open an issue if you encounter any problems.