Update app.py

app.py

@@ -1,4 +1,4 @@
-from fastapi import FastAPI, HTTPException
+from fastapi import FastAPI, HTTPException, JSONResponse, Request
 from pydantic import BaseModel
 from sentence_transformers import SentenceTransformer, util
 from transformers import pipeline
@@ -14,9 +14,6 @@ nlp = pipeline('question-answering', model=question_model, tokenizer=question_mo
 
 summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
 
-# Request models
-class ModifyQueryRequest(BaseModel):
-    query_string: str
 
 class ModifyQueryRequest_v3(BaseModel):
     query_string_list: List[str]
@@ -29,9 +26,6 @@ class AnswerQuestionRequest(BaseModel):
 class T5QuestionRequest(BaseModel):
     context: str
 
-# Response models
-class ModifyQueryResponse(BaseModel):
-    embeddings: List[List[float]]
 
 class AnswerQuestionResponse(BaseModel):
     answer: str
@@ -41,20 +35,22 @@ class T5Response(BaseModel):
     answer: str
 
 # API endpoints
-@app.post("/modify_query", response_model=ModifyQueryResponse)
-async def modify_query(request: ModifyQueryRequest):
+@app.post("/modify_query")
+async def modify_query(request: Request):
     try:
-        binary_embeddings = model.encode([request.query_string], precision="binary")
-        return ModifyQueryResponse(embeddings=binary_embeddings[0].tolist())
+        raw_data = await request.json()
+        binary_embeddings = model.encode([raw_data['query_string']], precision="binary")
+        return JSONResponse(content={'embeddings':binary_embeddings[0].tolist()})
     except Exception as e:
         raise HTTPException(status_code=500, detail=str(e))
 
-@app.post("/modify_query_v3", response_model=ModifyQueryResponse)
-async def modify_query_v3(request: ModifyQueryRequest_v3):
+@app.post("/modify_query_v3")
+async def modify_query_v3(request: Request):
     try:
         # Generate embeddings for a list of query strings
-        embeddings = model.encode(request.query_string_list)
-        return ModifyQueryResponse(embeddings=[emb.tolist() for emb in embeddings])
+        raw_data = await request.json()
+        embeddings = model.encode(raw_data['query_string_list'])
+        return JSONResponse(content={'embeddings':[emb.tolist() for emb in embeddings]})
     except Exception as e:
         raise HTTPException(status_code=500, detail=f"Error in modifying query v3: {str(e)}")