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nmac/lex_fridman_podcast_semantic_search

sourceHugging Faceupdated 2y agoView on Hugging Face
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App README

lex-semantic-search

Gradio application for performing semantic search on Lex Fridman podcast transcripts.

Dataset

The Gradio application is pre-loaded with chunks (chunk size is 25 contiguous entries) and embeddings for dataset nmac/lex_fridman_podcast.

Usage

  1. 1.Set up virtual environment with the required dependencies:
bash
python -m venv lex-semantic-search
source lex-semantic-search/bin/activate 
pip install -r requirements.txt     # for GPU
pip install -r requirements_cpu.txt # for CPU
  1. 1.Run the application locally using the following command:
bash
python app.py
  1. 1.Access the application by opening your web browser and navigating to http://localhost:7860.
  1. 1.In the application interface, adjust the input settings according to your needs:
  2. 2.Query: Enter a query to search for relevant podcast transcript chunks related to it.
  3. 3.Chunk Size: Adjust the chunk size. (Fixed to 25)
  4. 4.Embeddings Generator: Select the embeddings generator to use. (Fixed to `sentence-transformers/multi-qa-mpnet-base-dot-v1`)
  5. 5.Retriever Method: Select the retriever method. (Fixed to `FAISS`)
  6. 6.Number of Chunks to Retrieve: Set the number of chunks to retrieve.
  1. 1.Click the "Submit" button to retrieve the chunks that match your settings and query. The results will be displayed in a table.