Refactor predict function to clean up history logging and improve pixel value logging

app.py

@@ -195,12 +195,11 @@ def predict(message,
             repetition_penalty=2.5,
             do_sample=False):
         
-        history = state.get_prompt()[:-1]
-        logger.info(f"==== History ====\n{history}")
+        # history = state.get_prompt()[:-1]
+        # logger.info(f"==== History ====\n{history}")
 
         generation_config = dict(temperature=temperature, max_new_tokens= max_output_tokens, top_p=top_p, do_sample=do_sample, num_beams = 3, repetition_penalty=repetition_penalty)
 
-        question = message
         pixel_values = None
         if image_path is not None:
             pixel_values = load_image(image_path, max_num=max_input_tiles).to(torch.bfloat16).cuda()
@@ -211,11 +210,13 @@ def predict(message,
                     DEFAULT_IMAGE_TOKEN not in first_user_message:
                     state.messages[index]['content'] = DEFAULT_IMAGE_TOKEN + "\n" + first_user_message
 
-                    history = state.get_prompt()[:-1]
-                    logger.info(f"==== Modified History ====\n{history}")
+        history = state.get_prompt()[:-1]
+        logger.info(f"====  History ====\n{history}")
 
         logger.info(f"==== Lenght Pixel values ====\n{len(pixel_values)}")
-        response, conv_history = model.chat(tokenizer, pixel_values, question, generation_config, history=history, return_history=True)
+        
+        response, conv_history = model.chat(tokenizer, pixel_values, message, generation_config, history=history, return_history=True)
+        logger.info(f"==== Conv History ====\n{conv_history}")
         return response, conv_history
 
 def ai_bot(