update reranker source code (#1082)

python/reranker/bge-reranker-base/Dockerfile

@@ -3,8 +3,10 @@ FROM pytorch/pytorch:2.0.1-cuda11.7-cudnn8-runtime
 # please download the model from https://huggingface.co/BAAI/bge-reranker-base and put it in the same directory as Dockerfile
 COPY ./bge-reranker-base ./bge-reranker-base
 
-COPY app.py Dockerfile requirement.txt .
+COPY requirement.txt .
 
-RUN python3 -m pip install -r requirement.txt
+RUN python3 -m pip install -r requirement.txt -i https://pypi.tuna.tsinghua.edu.cn/simple
+
+COPY app.py Dockerfile .
 
 ENTRYPOINT python3 app.py

python/reranker/bge-reranker-base/README.md

@@ -38,7 +38,7 @@
 
 **镜像和端口**
 
-+ 镜像名: `luanshaotong/reranker:v0.1`  
++ 镜像名: `luanshaotong/reranker:v0.2`  
 + 端口号: 6006
 
 ```

python/reranker/bge-reranker-base/app.py

@@ -4,7 +4,7 @@
 @Time: 2023/11/7 22:45
 @Author: zhidong
 @File: reranker.py
-@Desc: 
+@Desc:
 """
 import os
 import numpy as np
@@ -30,17 +30,11 @@ def response(code, msg, data=None):
     return result
 
 def success(data=None, msg=''):
-    return 
-
-
-class Inputs(BaseModel):
-    id: str
-    text: Optional[str]
-
+    return
 
 class QADocs(BaseModel):
     query: Optional[str]
-    inputs: Optional[List[Inputs]]
+    documents: Optional[List[str]]
 
 
 class Singleton(type):
@@ -72,23 +66,24 @@ class Chat(object):
         self.reranker = Reranker(rerank_model_path)
 
     def fit_query_answer_rerank(self, query_docs: QADocs) -> List:
-        if query_docs is None or len(query_docs.inputs) == 0:
+        if query_docs is None or len(query_docs.documents) == 0:
             return []
         new_docs = []
         pair = []
-        for answer in query_docs.inputs:
-            pair.append([query_docs.query, answer.text])
+        for answer in query_docs.documents:
+            pair.append([query_docs.query, answer])
         scores = self.reranker.compute_score(pair)
         for index, score in enumerate(scores):
-            new_docs.append({"id": query_docs.inputs[index].id, "score": 1 / (1 + np.exp(-score))})
-        new_docs = list(sorted(new_docs, key=lambda x: x["score"], reverse=True))
-        return new_docs
+            new_docs.append({"index": index, "text": query_docs.documents[index], "score": 1 / (1 + np.exp(-score))})
+        #results = [{"document": {"text": documents["text"]}, "index": documents["index"], "relevance_score": documents["score"]} for documents in list(sorted(new_docs, key=lambda x: x["score"], reverse=True))]
+        results = [{"index": documents["index"], "relevance_score": documents["score"]} for documents in list(sorted(new_docs, key=lambda x: x["score"], reverse=True))]
+        return {"results": results}
 
 app = FastAPI()
 security = HTTPBearer()
 env_bearer_token = 'ACCESS_TOKEN'
 
-@app.post('/api/v1/rerank')
+@app.post('/v1/rerank')
 async def handle_post_request(docs: QADocs, credentials: HTTPAuthorizationCredentials = Security(security)):
     token = credentials.credentials
     if env_bearer_token is not None and token != env_bearer_token:
@@ -104,4 +99,4 @@ if __name__ == "__main__":
     try:
         uvicorn.run(app, host='0.0.0.0', port=6006)
     except Exception as e:
-        print(f"API启动失败！\n报错：\n{e}")
\ No newline at end of file
+        print(f"API启动失败！\n报错：\n{e}")

python/reranker/bge-reranker-base/requirement.txt → python/reranker/bge-reranker-base/requirements.txt

 fastapi==0.104.1
+transformers[sentencepiece]
 FlagEmbedding==1.1.5
 pydantic==1.10.13
 uvicorn==0.17.6