arad1367 commited on
Commit
ecd62fd
1 Parent(s): 770dcc9

Update app.py

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Files changed (1) hide show
  1. app.py +14 -12
app.py CHANGED
@@ -12,10 +12,7 @@ MODEL = os.environ.get("MODEL_ID")
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  PLACEHOLDER = """
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  <center>
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- <h1><center>MathΣtral - Your Math advisor</center></h1>
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- <p>Hi! I'm MisMath. A Math advisor. My model is based on mathstral-7B-v0.1. Feel free to ask your questions</p>
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- <p>Mathstral 7B is a model specializing in mathematical and scientific tasks, based on Mistral 7B.</p>
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- <p>mathstral-7B-v0.1 is first Mathstral model</p>
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  </center>
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  """
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@@ -64,19 +61,23 @@ def stream_chat(
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  print(f'message: {message}')
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  print(f'history: {history}')
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- conversation = [system_prompt]
 
 
 
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  for prompt, answer in history:
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- conversation.append(prompt)
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- conversation.append(answer)
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- conversation.append(message)
 
 
 
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- input_ids = tokenizer(conversation, return_tensors="pt").input_ids.to(model.device)
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-
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  streamer = TextIteratorStreamer(tokenizer, timeout=60.0, skip_prompt=True, skip_special_tokens=True)
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-
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  generate_kwargs = dict(
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- input_ids=input_ids,
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  max_new_tokens=max_new_tokens,
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  do_sample=False if temperature == 0 else True,
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  top_p=top_p,
@@ -95,6 +96,7 @@ def stream_chat(
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  buffer += new_text
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  yield buffer
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  chatbot = gr.Chatbot(height=600, placeholder=PLACEHOLDER)
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  PLACEHOLDER = """
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  <center>
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+ <p>MathΣtral - I'm MisMath,Your Math advisor</p>
 
 
 
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  </center>
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  """
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  print(f'message: {message}')
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  print(f'history: {history}')
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+ # Prepare the conversation list
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+ conversation = [
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+ {"role": "system", "content": system_prompt}
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+ ]
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  for prompt, answer in history:
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+ conversation.append({"role": "user", "content": prompt})
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+ conversation.append({"role": "assistant", "content": answer})
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+ conversation.append({"role": "user", "content": message})
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+
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+ # Tokenize the conversation
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+ input_ids = tokenizer(conversation, padding=True, truncation=True, return_tensors="pt").input_ids.to(model.device)
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  streamer = TextIteratorStreamer(tokenizer, timeout=60.0, skip_prompt=True, skip_special_tokens=True)
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+
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  generate_kwargs = dict(
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+ input_ids=input_ids,
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  max_new_tokens=max_new_tokens,
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  do_sample=False if temperature == 0 else True,
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  top_p=top_p,
 
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  buffer += new_text
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  yield buffer
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+
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  chatbot = gr.Chatbot(height=600, placeholder=PLACEHOLDER)
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