Rerank Microservice with VideoQnA

This README provides set-up instructions and comprehensive details regarding the reranking microservice with VideoQnA. This microservice is designed that do result rerank for VideoQnA use case. Local rerank is used rather than rerank model.

For the VideoQnA usecase, during the data preparation phase, frames are extracted from videos and stored in a vector database. To identify the most relevant video, we count the occurrences of each video source among the retrieved data with rerank function get_top_doc. This sorts the video as a descending list of names, ranked by their degree of match with the query. Then we could send the top_n videos to the downstream LVM.

---

🚀1. Start Microservice with Docker

1.1 Build Images

cd GenAIComps
docker build --no-cache -t opea/reranking-videoqna:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy  -f comps/reranks/videoqna/Dockerfile .

1.2 Start Rerank Service

docker compose -f comps/reranks/videoqna/docker_compose_reranking.yaml up -d
# wait until ready
until docker logs reranking-videoqna-server 2>&1 | grep -q "Uvicorn running on"; do
    sleep 2
done

1.3 Configuration available by setting environment variable

Configuration that available by setting environment variable:

• CHUNK_DURATION: target chunk duration, should be aligned with VideoQnA dataprep. Default 10s.

---

✅ 2. Invoke Reranking Microservice

The Reranking microservice exposes following API endpoints:

export ip_address=$(hostname -I | awk '{print $1}')

curl -X 'POST' \
"http://${ip_address}:8000/v1/reranking" \
-H 'accept: application/json' \
-H 'Content-Type: application/json' \
-d '{
  "retrieved_docs": [{"doc": [{"text": "this is the retrieved text"}]}],
  "initial_query": "this is the query",
  "top_n": 1,
  "metadata": [
      {"other_key": "value", "video":"top_video_name", "timestamp":"20"},
      {"other_key": "value", "video":"second_video_name", "timestamp":"40"},
      {"other_key": "value", "video":"top_video_name", "timestamp":"20"}
  ]
}'

# Expected output result:
# {"id":"random number","video_url":"http://0.0.0.0:6005/top_video_name","chunk_start":20.0,"chunk_duration":10.0,"prompt":"this is the query","max_new_tokens":512}

---

♻️ 3. Cleaning the Container

# remove the container
cid=$(docker ps -aq --filter "name=reranking-videoqna-server")
if [[ ! -z "$cid" ]]; then docker stop $cid && docker rm $cid && sleep 1s; fi