Rollback rerank and e5-large-v2 to all-MiniLM-L6-v2

.env

@@ -12,10 +12,10 @@ HF_API_URL=https://api-inference.huggingface.co/models/mistralai/Mistral-7B-Inst
 HF_TOKEN=your_huggingface_token_here
 
 # Embedding Model
-#EMBEDDING_MODEL=sentence-transformers/all-MiniLM-L6-v2
+EMBEDDING_MODEL=sentence-transformers/all-MiniLM-L6-v2
 #EMBEDDING_MODEL=sentence-transformers/multi-qa-MiniLM-L6-cos-v1
 #EMBEDDING_MODEL=BAAI/bge-small-en-v1.5
-EMBEDDING_MODEL=intfloat/e5-large-v2
+#EMBEDDING_MODEL=intfloat/e5-large-v2
 
 
 # Server Configuration
@@ -24,4 +24,4 @@ PORT=7860
 LOG_LEVEL=debug
 
 # CORS
-ALLOWED_ORIGINS=http://localhost:5173,https://your-frontend.pages.dev
+ALLOWED_ORIGINS=http://localhost:5173,https://your-frontend.pages.dev, https://VcRlAgent-workwise-backend.hf.space/api

app/routes/ask_routes.py

@@ -4,7 +4,7 @@ from fastapi import APIRouter, HTTPException
 from app.models.jira_schema import QueryRequest, QueryResponse
 from app.services.retriever import retriever
 from app.services.generator import generator
-from app.services.reranker import reranker
+#from app.services.reranker import reranker
 from app.utils.response_builder import build_query_response, extract_chart_intent
 from app.utils.logger import setup_logger
 from collections import Counter
@@ -33,15 +33,15 @@ async def ask_question(request: QueryRequest):
                 sources=[]
             )
         
-        # 🧠 Re-rank results
-        logger.info("[RERANKER] Starting re-ranking process...")
-        reranked_results = reranker.rerank(request.query, results, top_k=5)
+        
+        # Format context                
+        context = retriever.format_context(results)
 
-        # Format context
-        #context = retriever.format_context(results)
-        # Use reranked results for context
-        ## Bug IO Error
-        context = retriever.format_context(reranked_results)
+        # 🧠 Re-rank results        
+        #logger.info("[RERANKER] Starting re-ranking process...")        
+        #reranked_results = reranker.rerank(request.query, results, top_k=5)
+        # Format context, Use reranked results for context
+        #context = retriever.format_context(reranked_results) # ## Bug IO Error
         
         # Generate answer
         answer = generator.generate_rag_response(request.query, context)

requirements.txt

@@ -8,7 +8,6 @@ pandas==2.2.0
 numpy==1.26.3
 requests==2.31.0
 pydantic==2.5.3
-python-multipart==0.0.6
 tqdm==4.66.4                  # progress bars
 loguru==0.7.2                 # clean logging