[SD] Fix vicuna response

Signed-Off-by: Gaurav Shukla <gaurav@nod-labs.com>

apps/language_models/scripts/sharded_vicuna_fp32_web.py

@@ -621,13 +621,7 @@ def user(message, history):
 
 def chat(curr_system_message, history):
     global sharded_model
-    prompt_history = "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions.\n"
-    prologue_prompt = "ASSISTANT:\n"
     past_key_values = None
-    #  user_prompt = input("User: ")
-    #  prompt_history = (
-    #      prompt_history + "USER:\n" + user_prompt + prologue_prompt
-    #  )
     messages = curr_system_message + "".join(
         [
             "".join(["<|USER|>" + item[0], "<|ASSISTANT|>" + item[1]])
@@ -635,14 +629,11 @@ def chat(curr_system_message, history):
         ]
     )
     print(messages)
-    #  prompt = prompt_history.strip()
     prompt = messages.strip()
     input_ids = tokenizer(prompt).input_ids
     tokens = input_ids
-    #  prompt = print("Robot:", end=" ")
     new_sentence = []
     max_response_len = 1000
-    new_sentence_str = ""
     for iteration in range(max_response_len):
         original_input_ids = input_ids
         input_id_len = len(input_ids)
@@ -660,10 +651,6 @@ def chat(curr_system_message, history):
         new_token = int(torch.argmax(logits[:, -1, :], dim=1)[0])
         if new_token == 2:
             break
-        new_text = tokenizer.decode(new_token)
-        new_sentence_str += new_text
-        history[-1][1] = new_sentence_str
-        yield history
         new_sentence += [new_token]
         tokens.append(new_token)
         original_input_ids.append(new_token)
@@ -672,10 +659,10 @@ def chat(curr_system_message, history):
     for i in range(len(tokens)):
         if type(tokens[i]) != int:
             tokens[i] = int(tokens[i][0])
-    new_sentence_str2 = tokenizer.decode(new_sentence)
-    print(new_sentence_str2)
-    prompt_history += f"\n{new_sentence_str}\n"
-    return new_sentence_str2
+    new_sentence_str = tokenizer.decode(new_sentence)
+    print(new_sentence_str)
+    history[-1][1] = new_sentence_str
+    return history
 
 
 system_msg = "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions.\n"