README.md

metadata

title: Search Engine
emoji: 🔥
colorFrom: green
colorTo: red
sdk: streamlit
sdk_version: 1.39.0
app_file: app.py
pinned: false
short_description: Semantic Search engine with Faiss

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-

For local deployment run

fast_api.py

Script creates swagger app with endpoints on localhost:8084. First endpoint return the top k semanticaly most similar prompts with query prompt. Second endpoint returns all similarites with query (only applicable for very small datasets).

Data Ingestion

data_reader.py

creates data of various prompts for encoding into vector database, from prompt-picture dataset. Local database encoded only 11000 prompts. Faiss index that is used is small and not optimized, used for experimental datasets. Search is brute force, not optimised.

Streamlit

streamlit run app.py

Should be run for streamlit app, it can be assessed locally on http://localhost:8501.

Docker

docker build -t my-streamlit-app .

from main dir