Update app.py

app.py

@@ -62,8 +62,8 @@ async def lifespan(app: FastAPI):
     
         # Load models into the shared dictionary
         ml_models["embedder"] = HuggingFaceEmbeddings(
-                                                      # model_name="BAAI/bge-base-en-v1.5", #better but lil slower
-                                                      model_name="intfloat/e5-large-v2", #lil faster 
+                                                      model_name="BAAI/bge-base-en-v1.5", #better but lil slower
+                                                      # model_name="intfloat/e5-large-v2", #lil faster 
                                                       encode_kwargs={
                                                           "batch_size": 64,
                                                           # "normalize_embeddings": True
@@ -167,7 +167,7 @@ async def run_hackrx(req: RunRequest):
     )
 
     # dense_retriever = vectorstore.as_retriever(search_type="mmr",search_kwargs={"k": 8})
-    dense_retriever = vectorstore.as_retriever(search_type="mmr",search_kwargs={"k": 7 ,"lambda_mult": 0.5})
+    dense_retriever = vectorstore.as_retriever(search_type="mmr",search_kwargs={"k": 8 ,"lambda_mult": 0.5})
     
 
     # Create retrievers using the pre-loaded models from our ml_models dictionary