title | emoji | colorFrom | colorTo | sdk | sdk_version | app_file | pinned | short_description |
---|---|---|---|---|---|---|---|---|
Search Engine |
🔥 |
green |
red |
streamlit |
1.39.0 |
app.py |
false |
Semantic Search engine with Faiss |
Check out the API of Search engine at https://huggingface.co/spaces/Vitomir/search_engine
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_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 run app.py
Should be run for streamlit app, it can be assessed locally on http://localhost:8501.
docker build -t my-streamlit-app .
from main dir