Update app.py

app.py

@@ -94,42 +94,30 @@ def predict_test(model, tokenizer, embedding_model, context, question, index):
     question_vector = prepare_sentences_vector([question_vector])
     distances, indices = faiss_search(index, question_vector, 3)  # Retrieve top 3 indices
 
-    # most_similar_contexts = []
     most_similar_contexts = ''
     for i in range(3):  # Loop through top 3 indices
         most_sim_context = context[indices[0][i]].strip()
         # most_similar_contexts.append(most_sim_context)
         most_similar_contexts += str(i)+': '+most_sim_context + "\n\n"
 
-    _time = time.time() - t
-    output = {
-        "user_question": question,
-        "answer": most_similar_contexts,
-        # "answer": Answer,
-        "totaltime": round(_time, 3),
-        "distance": round(distances[0][0], 4)
-    }
-    # print('\nAnswer:',Answer)
-
     return most_similar_contexts
 
-def chat_interface(question, history):
-    response = predict_test(model, tokenizer, embedding_model, context, question, index)
-    return response
-
-examples=['ภูมิทัศน์สื่อไทยในปี 2567 มีแนวโน้มว่า ',
-           'Fragmentation คือ',
-           'ติ๊กต๊อก คือ',
-           'รายงานจาก Reuters Institute'
-          ]
-interface = gr.ChatInterface(fn=chat_interface,
-                                examples=examples)
 
 
 if __name__ == "__main__":
-    # Load your model, tokenizer, data, and index here...
-    # model, tokenizer = load_model('wangchanberta-hyp')
     embedding_model = load_embedding_model()
-    # df = load_data()
     index = set_index(prepare_sentences_vector(get_embeddings(embedding_model, context)))
+
+    def chat_interface(question, history):
+        response = predict_test(model, tokenizer, embedding_model, context, question, index)
+        return response
+
+    examples=['ภูมิทัศน์สื่อไทยในปี 2567 มีแนวโน้มว่า ',
+               'Fragmentation คือ',
+               'ติ๊กต๊อก คือ',
+               'รายงานจาก Reuters Institute'
+              ]
+    interface = gr.ChatInterface(fn=chat_interface,
+                                    examples=examples)
+
     interface.launch()