Update app.py

app.py

@@ -147,7 +147,7 @@ import torch
 device = "cpu"
 
 # Load models once
-embedding_model = SentenceTransformer("all-MiniLM-L6-v2-int8", device=device, normalize_embeddings=True)
+embedding_model = SentenceTransformer("all-MiniLM-L6-v2-int8", device=device)  # Removed normalize_embeddings
 summarizer = pipeline("summarization", model="facebook/bart-large-cnn", device=-1)
 
 # Load API Key
@@ -156,6 +156,7 @@ api_key = os.getenv("API_KEY")
 genai.configure(api_key=api_key)
 gemini_model = genai.GenerativeModel(model_name="gemini-2.0-flash")
 
+# Cache FAISS index & document texts
 @st.cache_resource
 def load_faiss_index():
     if not os.path.exists("faiss_index.idx") or not os.path.exists("doc_texts.npy"):
@@ -173,6 +174,8 @@ def query_legal_documents(query: str, top_k=3):
         return []
 
     query_embedding = embedding_model.encode([query])
+    faiss.normalize_L2(query_embedding)  # Normalize embeddings manually
+
     distances, indices = faiss_index.search(query_embedding, top_k)
 
     return [doc_texts[i] for i in indices[0] if i < len(doc_texts)]