Refactor reranking (#1113)

Signed-off-by: WenjiaoYue <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>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: ZePan110 <[email protected]>

.github/CODEOWNERS

@@ -21,7 +21,7 @@
 /comps/lvms/ [email protected] [email protected]
 /comps/prompt_registry/ [email protected] [email protected]
 /comps/ragas/ [email protected] [email protected]
-/comps/reranks/ [email protected] [email protected]
+/comps/rerankings/ [email protected] [email protected]
 /comps/retrievers/ [email protected] [email protected]
 /comps/text2image/ [email protected] [email protected]
 /comps/text2sql/ [email protected] [email protected]

.github/workflows/docker/compose/reranks-compose.yaml → .github/workflows/docker/compose/rerankings-compose.yaml

@@ -5,5 +5,5 @@
 services:
   reranking:
     build:
-      dockerfile: comps/reranks/src/Dockerfile
+      dockerfile: comps/rerankings/src/Dockerfile
     image: ${REGISTRY:-opea}/reranking:${TAG:-latest}

.github/workflows/manual-comps-test.yml

@@ -7,7 +7,7 @@ on:
     inputs:
       services:
         default: "asr"
-        description: "List of services to test [agent,asr,chathistory,dataprep,embeddings,feedback_management,finetuning,guardrails,intent_detection,knowledgegraphs,llms,lvms,nginx,prompt_registry,ragas,reranks,retrievers,tts,vectorstores,web_retrievers]"
+        description: "List of services to test [agent,asr,chathistory,dataprep,embeddings,feedback_management,finetuning,guardrails,intent_detection,knowledgegraphs,llms,lvms,nginx,prompt_registry,ragas,rerankings,retrievers,tts,vectorstores,web_retrievers]"
         required: true
         type: string
       build:

.github/workflows/manual-docker-publish.yml

@@ -7,7 +7,7 @@ on:
     inputs:
       services:
         default: ""
-        description: "List of services to test [agent,asr,chathistory,dataprep,embeddings,feedback_management,finetuning,guardrails,intent_detection,knowledgegraphs,llms,lvms,nginx,prompt_registry,ragas,reranks,retrievers,tts,vectorstores,web_retrievers]"
+        description: "List of services to test [agent,asr,chathistory,dataprep,embeddings,feedback_management,finetuning,guardrails,intent_detection,knowledgegraphs,llms,lvms,nginx,prompt_registry,ragas,rerankings,retrievers,tts,vectorstores,web_retrievers]"
         required: false
         type: string
       images:

.github/workflows/manual-docker-scan.yml

@@ -7,7 +7,7 @@ on:
     inputs:
       services:
         default: "asr"
-        description: "List of services to test [agent_langchain,asr,chathistory_mongo,dataprep_milvus...]" #,embeddings,guardrails,llms,lvms,prompt_registry,ragas,reranks,retrievers,tts,vectorstores,web_retrievers]"
+        description: "List of services to test [agent_langchain,asr,chathistory_mongo,dataprep_milvus...]" #,embeddings,guardrails,llms,lvms,prompt_registry,ragas,rerankings,retrievers,tts,vectorstores,web_retrievers]"
         required: false
         type: string
       images:

README.md

@@ -41,8 +41,8 @@ The initially supported `Microservices` are described in the below table. More `
 | [Embedding](./comps/embeddings/src/README.md)     | [LangChain](https://www.langchain.com)/[LlamaIndex](https://www.llamaindex.ai) | [BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5)                                   | [TEI-Gaudi](https://github.com/huggingface/tei-gaudi)           | Gaudi2 | Embedding on Gaudi2                   |
 | [Embedding](./comps/embeddings/src/README.md)     | [LangChain](https://www.langchain.com)/[LlamaIndex](https://www.llamaindex.ai) | [BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5)                                   | [TEI](https://github.com/huggingface/text-embeddings-inference) | Xeon   | Embedding on Xeon CPU                 |
 | [Retriever](./comps/retrievers/src/README.md)     | [LangChain](https://www.langchain.com)/[LlamaIndex](https://www.llamaindex.ai) | [BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5)                                   | [TEI](https://github.com/huggingface/text-embeddings-inference) | Xeon   | Retriever on Xeon CPU                 |
-| [Reranking](./comps/reranks/src/README.md)        | [LangChain](https://www.langchain.com)/[LlamaIndex](https://www.llamaindex.ai) | [BAAI/bge-reranker-base](https://huggingface.co/BAAI/bge-reranker-base)                                 | [TEI-Gaudi](https://github.com/huggingface/tei-gaudi)           | Gaudi2 | Reranking on Gaudi2                   |
-| [Reranking](./comps/reranks/src/README.md)        | [LangChain](https://www.langchain.com)/[LlamaIndex](https://www.llamaindex.ai) | [BBAAI/bge-reranker-base](https://huggingface.co/BAAI/bge-reranker-base)                                | [TEI](https://github.com/huggingface/text-embeddings-inference) | Xeon   | Reranking on Xeon CPU                 |
+| [Reranking](./comps/rerankings/src/README.md)     | [LangChain](https://www.langchain.com)/[LlamaIndex](https://www.llamaindex.ai) | [BAAI/bge-reranker-base](https://huggingface.co/BAAI/bge-reranker-base)                                 | [TEI-Gaudi](https://github.com/huggingface/tei-gaudi)           | Gaudi2 | Reranking on Gaudi2                   |
+| [Reranking](./comps/rerankings/src/README.md)     | [LangChain](https://www.langchain.com)/[LlamaIndex](https://www.llamaindex.ai) | [BBAAI/bge-reranker-base](https://huggingface.co/BAAI/bge-reranker-base)                                | [TEI](https://github.com/huggingface/text-embeddings-inference) | Xeon   | Reranking on Xeon CPU                 |
 | [ASR](./comps/asr/src/README.md)                  | NA                                                                             | [openai/whisper-small](https://huggingface.co/openai/whisper-small)                                     | NA                                                              | Gaudi2 | Audio-Speech-Recognition on Gaudi2    |
 | [ASR](./comps/asr/src/README.md)                  | NA                                                                             | [openai/whisper-small](https://huggingface.co/openai/whisper-small)                                     | NA                                                              | Xeon   | Audio-Speech-RecognitionS on Xeon CPU |
 | [TTS](./comps/tts/src/README.md)                  | NA                                                                             | [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts)                                 | NA                                                              | Gaudi2 | Text-To-Speech on Gaudi2              |

comps/finetuning/README.md

@@ -244,7 +244,7 @@ curl http://${your_ip}:8015/v1/finetune/list_checkpoints -X POST -H "Content-Typ
 
 ### 3.4 Leverage fine-tuned model
 
-After fine-tuning job is done, fine-tuned model can be chosen from listed checkpoints, then the fine-tuned model can be used in other microservices. For example, fine-tuned reranking model can be used in [reranks](../reranks/src/README.md) microservice by assign its path to the environment variable `RERANK_MODEL_ID`, fine-tuned embedding model can be used in [embeddings](../embeddings/src/README.md) microservice by assign its path to the environment variable `model`, LLMs after instruction tuning can be used in [llms](../llms/src/text-generation/README.md) microservice by assign its path to the environment variable `your_hf_llm_model`.
+After fine-tuning job is done, fine-tuned model can be chosen from listed checkpoints, then the fine-tuned model can be used in other microservices. For example, fine-tuned reranking model can be used in [rerankings](../rerankings/src/README.md) microservice by assign its path to the environment variable `RERANK_MODEL_ID`, fine-tuned embedding model can be used in [embeddings](../embeddings/src/README.md) microservice by assign its path to the environment variable `model`, LLMs after instruction tuning can be used in [llms](../llms/src/text-generation/README.md) microservice by assign its path to the environment variable `your_hf_llm_model`.
 
 ## 🚀4. Descriptions for Finetuning parameters
 

comps/lvms/llama-vision/transformers_generation_utils.py

@@ -4238,7 +4238,7 @@ def _ranking_fast(
     alpha: float,
     beam_width: int,
 ) -> torch.FloatTensor:
-    """Reranks the top_k candidates based on a degeneration penalty (cosine similarity with previous tokens), as described
+    """Rerankings the top_k candidates based on a degeneration penalty (cosine similarity with previous tokens), as described
     in the paper "A Contrastive Framework for Neural Text Generation".
 
     Returns the index of the best candidate for each

comps/reranks/deployment/docker_compose/rerank_tei.yaml → comps/rerankings/deployment/docker_compose/rerank_tei.yaml

@@ -29,6 +29,7 @@ services:
       http_proxy: ${http_proxy}
       https_proxy: ${https_proxy}
       TEI_RERANKING_ENDPOINT: ${TEI_RERANKING_ENDPOINT}
+      RERANK_COMPONENT_NAME: "OPEA_TEI_RERANKING"
       HF_TOKEN: ${HF_TOKEN}
     depends_on:
       tei_reranking_service:

comps/rerankings/deployment/docker_compose/rerank_videoqna.yaml

@@ -0,0 +1,22 @@
+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+services:
+  reranking:
+    image: opea/reranking:latest
+    container_name: reranking-videoqna-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}
+      RERANK_COMPONENT_NAME: "OPEA_VIDEO_RERANKING"
+    restart: unless-stopped
+
+networks:
+  default:
+    driver: bridge

comps/rerankings/src/Dockerfile

@@ -0,0 +1,46 @@
+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+FROM python:3.11-slim
+
+ENV LANG=C.UTF-8
+
+ARG ARCH="cpu"
+ARG SERVICE="all"
+
+RUN apt-get update -y && apt-get install -y --no-install-recommends --fix-missing \
+    git \
+    libgl1-mesa-glx \
+    libjemalloc-dev
+
+RUN useradd -m -s /bin/bash user && \
+    mkdir -p /home/user && \
+    chown -R user /home/user/
+
+USER user
+
+COPY comps /home/user/comps
+
+RUN if [ ${ARCH} = "cpu" ]; then \
+    pip install --no-cache-dir torch --index-url https://download.pytorch.org/whl/cpu; \
+fi && \
+if [ ${SERVICE} = "videoqna" ]; then \
+    pip install --no-cache-dir --upgrade pip setuptools && \
+    pip install --no-cache-dir -r /home/user/comps/rerankings/src/requirements_videoqna.txt; \
+elif [ ${SERVICE} = "all" ]; then \
+    git clone https://github.com/IntelLabs/fastRAG.git /home/user/fastRAG && \
+    cd /home/user/fastRAG && \
+    pip install --no-cache-dir --upgrade pip && \
+    pip install --no-cache-dir . && \
+    pip install --no-cache-dir .[intel] && \
+    pip install --no-cache-dir -r /home/user/comps/rerankings/src/requirements_videoqna.txt; \
+fi && \
+pip install --no-cache-dir --upgrade pip setuptools && \
+pip install --no-cache-dir -r /home/user/comps/rerankings/src/requirements.txt;
+
+
+ENV PYTHONPATH=$PYTHONPATH:/home/user
+
+WORKDIR /home/user/comps/rerankings/src
+
+ENTRYPOINT ["python", "opea_reranking_microservice.py"]

comps/reranks/src/integrations/opea_tei.py → comps/rerankings/src/integrations/tei.py

@@ -18,7 +18,7 @@
     RerankingResponseData,
 )
 
-logger = CustomLogger("reranking_tei")
+logger = CustomLogger("tei_reranking")
 logflag = os.getenv("LOGFLAG", False)
 
 # Environment variables
@@ -27,8 +27,8 @@
 CLIENT_SECRET = os.getenv("CLIENT_SECRET")
 
 
-@OpeaComponentRegistry.register("OPEA_RERANK_TEI")
-class OPEATEIReranking(OpeaComponent):
+@OpeaComponentRegistry.register("OPEA_TEI_RERANKING")
+class OpeaTEIReranking(OpeaComponent):
     """A specialized reranking component derived from OpeaComponent for TEI reranking services.
 
     Attributes:

comps/rerankings/src/integrations/videoqna.py

@@ -0,0 +1,121 @@
+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+import logging
+import os
+import re
+
+from fastapi import HTTPException
+
+from comps import CustomLogger, LVMVideoDoc, OpeaComponentRegistry, SearchedMultimodalDoc, ServiceType
+from comps.cores.common.component import OpeaComponent
+
+logger = CustomLogger("video_reranking")
+logflag = os.getenv("LOGFLAG", False)
+
+chunk_duration = os.getenv("CHUNK_DURATION", "10") or "10"
+chunk_duration = float(chunk_duration) if chunk_duration.isdigit() else 10.0
+
+file_server_endpoint = os.getenv("FILE_SERVER_ENDPOINT") or "http://0.0.0.0:6005"
+
+logging.basicConfig(
+    level=logging.INFO, format="%(levelname)s:     [%(asctime)s] %(message)s", datefmt="%d/%m/%Y %I:%M:%S"
+)
+
+
+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}")
+
+    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}")
+
+    return top_n_names
+
+
+def find_timestamp_from_video(metadata_list, video):
+    return next(
+        (metadata["timestamp"] for metadata in metadata_list if metadata["video"] == video),
+        None,
+    )
+
+
+def format_video_name(video_name):
+    # Check for an existing file extension
+    match = re.search(r"\.(\w+)$", video_name)
+
+    if match:
+        extension = match.group(1)
+        # If the extension is not 'mp4', raise an error
+        if extension != "mp4":
+            raise ValueError(f"Invalid file extension: .{extension}. Only '.mp4' is allowed.")
+
+    # Use regex to remove any suffix after the base name (e.g., '_interval_0', etc.)
+    base_name = re.sub(r"(_interval_\d+)?(\.mp4)?$", "", video_name)
+
+    # Add the '.mp4' extension
+    formatted_name = f"{base_name}.mp4"
+
+    return formatted_name
+
+
+@OpeaComponentRegistry.register("OPEA_VIDEO_RERANKING")
+class OpeaVideoReranking(OpeaComponent):
+    """A specialized reranking component derived from OpeaComponent for OPEA Video native reranking services."""
+
+    def __init__(self, name: str, description: str, config: dict = None):
+        super().__init__(name, ServiceType.RERANK.name.lower(), description, config)
+
+    async def invoke(self, input: SearchedMultimodalDoc) -> LVMVideoDoc:
+        """Invokes the reranking service to generate reranking for the provided input.
+
+        Args:
+            input (SearchedMultimodalDoc): The input in OpenAI reranking format.
+
+        Returns:
+            LVMVideoDoc: The response in OpenAI reranking format.
+        """
+        try:
+            # 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)
+
+            # only use the first top video
+            timestamp = find_timestamp_from_video(input.metadata, top_video_names[0])
+            formatted_video_name = format_video_name(top_video_names[0])
+            video_url = f"{file_server_endpoint.rstrip('/')}/{formatted_video_name}"
+
+            result = LVMVideoDoc(
+                video_url=video_url,
+                prompt=input.initial_query,
+                chunk_start=timestamp,
+                chunk_duration=float(chunk_duration),
+                max_new_tokens=512,
+            )
+        except ValueError as e:
+            raise HTTPException(status_code=400, detail=str(e))
+        except Exception as e:
+            logging.error(f"Unexpected error in reranking: {str(e)}")
+            # Handle any other exceptions with a generic server error response
+            raise HTTPException(status_code=500, detail="An unexpected error occurred.")
+
+        return result
+
+    def check_health(self) -> bool:
+        """Checks the health of the reranking service.
+
+        Returns:
+            bool: True if the service is reachable and healthy, False otherwise.
+        """
+
+        return True

comps/reranks/src/opea_reranking_microservice.py → comps/rerankings/src/opea_reranking_microservice.py

@@ -5,7 +5,8 @@
 import time
 from typing import Union
 
-from integrations.opea_tei import OPEATEIReranking
+from integrations.tei import OpeaTEIReranking
+from integrations.videoqna import OpeaVideoReranking
 
 from comps import (
     CustomLogger,
@@ -22,7 +23,7 @@
 logger = CustomLogger("opea_reranking_microservice")
 logflag = os.getenv("LOGFLAG", False)
 
-rerank_component_name = os.getenv("RERANK_COMPONENT_NAME", "OPEA_RERANK_TEI")
+rerank_component_name = os.getenv("RERANK_COMPONENT_NAME", "OPEA_TEI_RERANKING")
 # Initialize OpeaComponentLoader
 loader = OpeaComponentLoader(rerank_component_name, description=f"OPEA RERANK Component: {rerank_component_name}")
 

comps/rerankings/src/requirements_videoqna.txt

@@ -0,0 +1,7 @@
+datasets
+haystack-ai
+langchain  --extra-index-url https://download.pytorch.org/whl/cpu
+langchain_community  --extra-index-url https://download.pytorch.org/whl/cpu
+openai
+Pillow
+pydub

comps/text2sql/src/Dockerfile

@@ -30,4 +30,4 @@ ENV PYTHONPATH=$PYTHONPATH:/home/user
 
 WORKDIR /home/user/comps/text2sql/src/
 
-ENTRYPOINT ["python", "opea_text2sql_microservice.py"]
+ENTRYPOINT ["python", "opea_text2sql_microservice.py"]

tests/reranks/test_reranks_opea_tei.sh → tests/rerankings/test_rerankings_tei.sh

@@ -9,7 +9,12 @@ ip_address=$(hostname -I | awk '{print $1}')
 
 function build_docker_images() {
     cd $WORKPATH
-    docker build --no-cache -t opea/reranking:comps --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/reranks/src/Dockerfile .
+    docker build --no-cache \
+          -t opea/reranking:comps \
+          --build-arg https_proxy=$https_proxy \
+          --build-arg http_proxy=$http_proxy \
+          --build-arg SERVICE=tei \
+          -f comps/rerankings/src/Dockerfile .
     if [ $? -ne 0 ]; then
         echo "opea/reranking built fail"
         exit 1
@@ -30,7 +35,7 @@ function start_service() {
     export TEI_RERANKING_ENDPOINT="http://${ip_address}:${tei_endpoint}"
     tei_service_port=5007
     unset http_proxy
-    docker run -d --name="test-comps-reranking-server" -e LOGFLAG=True  -p ${tei_service_port}:8000 --ipc=host -e http_proxy=$http_proxy -e https_proxy=$https_proxy -e TEI_RERANKING_ENDPOINT=$TEI_RERANKING_ENDPOINT -e HF_TOKEN=$HF_TOKEN -e RERANK_TYPE="tei" opea/reranking:comps
+    docker run -d --name="test-comps-reranking-server" -e LOGFLAG=True  -p ${tei_service_port}:8000 --ipc=host -e http_proxy=$http_proxy -e https_proxy=$https_proxy -e TEI_RERANKING_ENDPOINT=$TEI_RERANKING_ENDPOINT -e HF_TOKEN=$HF_TOKEN  -e RERANK_COMPONENT_NAME="OPEA_TEI_RERANKING"  opea/reranking:comps
     sleep 15
 }
 
@@ -52,7 +57,7 @@ function validate_microservice() {
 }
 
 function stop_docker() {
-    cid=$(docker ps -aq --filter "name=test-comps-rerank*")
+    cid=$(docker ps -aq --filter "name=test-comps-reranking*")
     if [[ ! -z "$cid" ]]; then docker stop $cid && docker rm $cid && sleep 1s; fi
 }