Update app.py

app.py

@@ -495,7 +495,7 @@ def get_query_embedding_together(query):
     response.raise_for_status()
     return response.json()["data"][0]["embedding"]
 
-def find_most_similar_chunks(query_embedding, data, top_n=3):
+def find_most_similar_chunks(query_embedding, data, top_n=10):
     query_vec = np.array(query_embedding).reshape(1, -1)
     similarities = []
     for item in data:
@@ -523,7 +523,6 @@ if query:
         query_embedding = get_query_embedding_together(query)
         data = load_embeddings(EMBEDDING_FILE)
         top_chunks = find_most_similar_chunks(query_embedding, data, top_n=10)
-        st.write("Top Chunks:", top_chunks)
 
         context = "\n".join(top_chunks)
         prompt = f"""