Topic Extraction

1. The extraction graph creates an endpoint which accepts audio files and transcribes them using OpenAI's Whisper model
2. The transcription is fed into an LLM for Topic Extraction.
3. The transcription is fed into a summarization model to summarize the entire transcript.

Code Reference

Link to Code

1. graph.yaml - contains the extraction graph.
2. setup_graph.py - Sets up the extraction graph in Indexify Server
3. upload_and_retrieve.py - Uploads audio into the extraction graph, waits for extraction and finally retrieves from the endpoint.

Download & Start Indexify Server

Terminal 1

curl https://getindexify.ai | sh
./indexify server -d

Download & Join Indexify Extractors

Terminal 2

virtualenv ve
source ve/bin/activate

pip install indexify-extractor-sdk
indexify-extractor download tensorlake/whisper-asr
indexify-extractor download tensorlake/summarization
indexify-extractor download tensorlake/openai
indexify-extractor join-server

Setup the Graph

Terminal 3

python setup_graph.py

Upload Data and Retrieve

The next step is to upload an audio file and retrieve the transcript

Terminal 3

python upload_and_retrieve.py