Spaces:
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| title: Prompt Search Engine | |
| emoji: 👀 | |
| colorFrom: green | |
| colorTo: red | |
| sdk: streamlit | |
| sdk_version: 1.50.0 | |
| 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](http://127.0.0.1:8084/docs). 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 |