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Add local Rerank microservice for VideoRAGQnA (opea-project#496)
* initial commit Signed-off-by: BaoHuiling <[email protected]> * save Signed-off-by: BaoHuiling <[email protected]> * add readme, test script, fix bug Signed-off-by: BaoHuiling <[email protected]> * update video URL Signed-off-by: BaoHuiling <[email protected]> * use default Signed-off-by: BaoHuiling <[email protected]> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * update core dependency Signed-off-by: BaoHuiling <[email protected]> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * use p 5000 Signed-off-by: BaoHuiling <[email protected]> * use 5037 Signed-off-by: BaoHuiling <[email protected]> * update ctnr name Signed-off-by: BaoHuiling <[email protected]> * remove langsmith Signed-off-by: BaoHuiling <[email protected]> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * add rerank algo desc in readme Signed-off-by: BaoHuiling <[email protected]> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Signed-off-by: BaoHuiling <[email protected]> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: chen, suyue <[email protected]>
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# Rerank Microservice | ||
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This is a Docker-based microservice that do result rerank for VideoRAGQnA use case. Local rerank is used rather than rerank model. | ||
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For the `VideoRAGQnA` 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. | ||
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# 🚀1. Start Microservice with Docker | ||
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## 1.1 Build Images | ||
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```bash | ||
cd GenAIComps | ||
docker build --no-cache -t opea/reranking-videoragqna:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/reranks/video-rag-qna/docker/Dockerfile . | ||
``` | ||
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## 1.2 Start Rerank Service | ||
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```bash | ||
docker compose -f comps/reranks/video-rag-qna/docker/docker_compose_reranking.yaml up -d | ||
# wait until ready | ||
until docker logs reranking-videoragqna-server 2>&1 | grep -q "Uvicorn running on"; do | ||
sleep 2 | ||
done | ||
``` | ||
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Available configuration by environment variable: | ||
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- CHUNK_DURATION: target chunk duration, should be aligned with VideoRAGQnA dataprep. Default 10s. | ||
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# ✅ 2. Test | ||
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```bash | ||
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"} | ||
] | ||
}' | ||
``` | ||
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The result should be: | ||
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```bash | ||
{"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} | ||
``` | ||
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# ♻️ 3. Clean | ||
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```bash | ||
# remove the container | ||
cid=$(docker ps -aq --filter "name=reranking-videoragqna-server") | ||
if [[ ! -z "$cid" ]]; then docker stop $cid && docker rm $cid && sleep 1s; fi | ||
``` |
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# Copyright (C) 2024 Intel Corporation | ||
# SPDX-License-Identifier: Apache-2.0 | ||
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FROM python:3.11-slim | ||
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ENV LANG=C.UTF-8 | ||
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RUN useradd -m -s /bin/bash user && \ | ||
mkdir -p /home/user && \ | ||
chown -R user /home/user/ | ||
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USER user | ||
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COPY comps /home/user/comps | ||
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RUN pip install --no-cache-dir --upgrade pip && \ | ||
pip install --no-cache-dir -r /home/user/comps/reranks/video-rag-qna/requirements.txt | ||
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ENV PYTHONPATH=$PYTHONPATH:/home/user | ||
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WORKDIR /home/user/comps/reranks/video-rag-qna | ||
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ENTRYPOINT ["python", "local_reranking.py"] |
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comps/reranks/video-rag-qna/docker/docker_compose_reranking.yaml
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# Copyright (C) 2024 Intel Corporation | ||
# SPDX-License-Identifier: Apache-2.0 | ||
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services: | ||
reranking: | ||
image: opea/reranking-videoragqna:latest | ||
container_name: reranking-videoragqna-server | ||
ports: | ||
- "8000:8000" | ||
ipc: host | ||
environment: | ||
no_proxy: ${no_proxy} | ||
http_proxy: ${http_proxy} | ||
https_proxy: ${https_proxy} | ||
CHUNK_DURATION: ${CHUNK_DURATION} | ||
FILE_SERVER_ENDPOINT: ${FILE_SERVER_ENDPOINT} | ||
restart: unless-stopped | ||
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networks: | ||
default: | ||
driver: bridge |
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# Copyright (C) 2024 Intel Corporation | ||
# SPDX-License-Identifier: Apache-2.0 | ||
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import logging | ||
import os | ||
import time | ||
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from comps import ( | ||
LVMVideoDoc, | ||
SearchedMultimodalDoc, | ||
ServiceType, | ||
opea_microservices, | ||
register_microservice, | ||
register_statistics, | ||
statistics_dict, | ||
) | ||
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chunk_duration = os.getenv("CHUNK_DURATION", "10") or "10" | ||
chunk_duration = float(chunk_duration) if chunk_duration.isdigit() else 10.0 | ||
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file_server_endpoint = os.getenv("FILE_SERVER_ENDPOINT") or "http://0.0.0.0:6005" | ||
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logging.basicConfig( | ||
level=logging.INFO, format="%(levelname)s: [%(asctime)s] %(message)s", datefmt="%d/%m/%Y %I:%M:%S" | ||
) | ||
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def get_top_doc(top_n, videos) -> list: | ||
hit_score = {} | ||
if videos is None: | ||
return None | ||
for video_name in videos: | ||
try: | ||
if video_name not in hit_score.keys(): | ||
hit_score[video_name] = 0 | ||
hit_score[video_name] += 1 | ||
except KeyError as r: | ||
logging.info(f"no video name {r}") | ||
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x = dict(sorted(hit_score.items(), key=lambda item: -item[1])) # sorted dict of video name and score | ||
top_n_names = list(x.keys())[:top_n] | ||
logging.info(f"top docs = {x}") | ||
logging.info(f"top n docs names = {top_n_names}") | ||
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return top_n_names | ||
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def find_timestamp_from_video(metadata_list, video): | ||
return next( | ||
(metadata["timestamp"] for metadata in metadata_list if metadata["video"] == video), | ||
None, | ||
) | ||
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@register_microservice( | ||
name="opea_service@reranking_visual_rag", | ||
service_type=ServiceType.RERANK, | ||
endpoint="/v1/reranking", | ||
host="0.0.0.0", | ||
port=8000, | ||
input_datatype=SearchedMultimodalDoc, | ||
output_datatype=LVMVideoDoc, | ||
) | ||
@register_statistics(names=["opea_service@reranking_visual_rag"]) | ||
def reranking(input: SearchedMultimodalDoc) -> LVMVideoDoc: | ||
start = time.time() | ||
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# get top video name from metadata | ||
video_names = [meta["video"] for meta in input.metadata] | ||
top_video_names = get_top_doc(input.top_n, video_names) | ||
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# only use the first top video | ||
timestamp = find_timestamp_from_video(input.metadata, top_video_names[0]) | ||
video_url = f"{file_server_endpoint.rstrip('/')}/{top_video_names[0]}" | ||
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result = LVMVideoDoc( | ||
video_url=video_url, | ||
prompt=input.initial_query, | ||
chunk_start=timestamp, | ||
chunk_duration=float(chunk_duration), | ||
max_new_tokens=512, | ||
) | ||
statistics_dict["opea_service@reranking_visual_rag"].append_latency(time.time() - start, None) | ||
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return result | ||
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if __name__ == "__main__": | ||
opea_microservices["opea_service@reranking_visual_rag"].start() |
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datasets | ||
docarray | ||
fastapi | ||
opentelemetry-api | ||
opentelemetry-exporter-otlp | ||
opentelemetry-sdk | ||
Pillow | ||
prometheus-fastapi-instrumentator | ||
pydub | ||
shortuuid | ||
uvicorn |
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#!/bin/bash | ||
# Copyright (C) 2024 Intel Corporation | ||
# SPDX-License-Identifier: Apache-2.0 | ||
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set -xe | ||
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WORKPATH=$(dirname "$PWD") | ||
ip_address=$(hostname -I | awk '{print $1}') | ||
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function build_docker_images() { | ||
cd $WORKPATH | ||
docker build --no-cache -t opea/reranking-videoragqna:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/reranks/video-rag-qna/docker/Dockerfile . | ||
} | ||
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function start_service() { | ||
docker run -d --name "test-comps-reranking-videoragqna-server" \ | ||
-p 5037:8000 \ | ||
--ipc=host \ | ||
-e no_proxy=${no_proxy} \ | ||
-e http_proxy=${http_proxy} \ | ||
-e https_proxy=${https_proxy} \ | ||
-e CHUNK_DURATION=${CHUNK_DURATION} \ | ||
-e FILE_SERVER_ENDPOINT=${FILE_SERVER_ENDPOINT} \ | ||
opea/reranking-videoragqna:latest | ||
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until docker logs test-comps-reranking-videoragqna-server 2>&1 | grep -q "Uvicorn running on"; do | ||
sleep 2 | ||
done | ||
} | ||
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function validate_microservice() { | ||
result=$(\ | ||
http_proxy="" \ | ||
curl -X 'POST' \ | ||
"http://${ip_address}:5037/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"} | ||
] | ||
}') | ||
if [[ $result == *"this is the query"* ]]; then | ||
echo "Result correct." | ||
else | ||
echo "Result wrong." | ||
exit 1 | ||
fi | ||
} | ||
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function stop_docker() { | ||
cid=$(docker ps -aq --filter "name=test-comps-reranking*") | ||
if [[ ! -z "$cid" ]]; then docker stop $cid && docker rm $cid && sleep 1s; fi | ||
} | ||
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function main() { | ||
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stop_docker | ||
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build_docker_images | ||
start_service | ||
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validate_microservice | ||
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stop_docker | ||
echo y | docker system prune | ||
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} | ||
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main |