Update app.py

app.py

@@ -27,36 +27,13 @@ def askme(symptoms, question):
     content = symptoms + " " + question
     messages = [{"role": "system", "content": sys_message}, {"role": "user", "content": content}]
     prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
-   # inputs = tokenizer(prompt, return_tensors="pt").to(device)  # Ensure inputs are on CUDA device
-   # outputs = model.generate(**inputs, max_new_tokens=200, use_cache=True)
-   # response_text = tokenizer.batch_decode(outputs)[0].strip()
-
-
-
-    # Tokenize all prompts and batch them
-    tokenized_inputs = tokenizer(prompts, return_tensors="pt", padding=True, truncation=True).to(device)
-    outputs = model.generate(**tokenized_inputs, max_new_tokens=200, use_cache=True)
-
-    # Decode responses
-    response_texts = tokenizer.batch_decode(outputs, skip_special_tokens=True)
-
-    
-    
+    inputs = tokenizer(prompt, return_tensors="pt").to(device)  # Ensure inputs are on CUDA device
+    outputs = model.generate(**inputs, max_new_tokens=200, use_cache=True)
+    response_text = tokenizer.batch_decode(outputs)[0].strip() #skip_special_tokens=True
     # Remove system messages and content
-    #response_text = response_text.replace(sys_message, "").replace(content, "").strip()
     # Extract only the assistant's response
-    #assistant_response = response_text.split("<|im_start|>assistant")[1].strip().replace('<|im_end', '')
-    # Extract only the assistant's response
-    
-    
-    
-    
-       # Extract assistant's responses
-    assistant_responses = []
-    for response_text in response_texts:
-        assistant_response = response_text.split("assistant")[1].strip().replace('<|im_end', '')
-        assistant_responses.append(assistant_response)
-
+    assistant_response = response_text.split("<|im_start|>assistant")[1].strip().replace('<|im_end', '')
+   #  Extract only the assistant's response
     return assistant_responses