Dhahlan2000 commited on
Commit
e56158c
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1 Parent(s): 4f33e12

Update app.py

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Files changed (1) hide show
  1. app.py +18 -17
app.py CHANGED
@@ -4,45 +4,47 @@ from huggingface_hub import InferenceClient
4
  """
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  For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
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  """
 
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  client = InferenceClient("cognitivecomputations/TinyDolphin-2.8.2-1.1b-laser")
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-
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  def respond(
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- message,
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  history: list[tuple[str, str]],
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- system_message,
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- max_tokens,
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- temperature,
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- top_p,
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  ):
 
 
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  messages = [{"role": "system", "content": system_message}]
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- for val in history:
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- if val[0]:
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- messages.append({"role": "user", "content": val[0]})
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- if val[1]:
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- messages.append({"role": "assistant", "content": val[1]})
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  messages.append({"role": "user", "content": message})
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  response = ""
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  for message in client.chat_completion(
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- messages,
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  max_tokens=max_tokens,
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  stream=True,
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  temperature=temperature,
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  top_p=top_p,
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  ):
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- token = message.choices[0].delta.content
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-
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  response += token
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  yield response
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-
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  """
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- For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
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  """
 
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  demo = gr.ChatInterface(
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  respond,
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  additional_inputs=[
@@ -59,6 +61,5 @@ demo = gr.ChatInterface(
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  ],
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  )
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-
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  if __name__ == "__main__":
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  demo.launch()
 
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  """
5
  For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
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  """
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+ # Initialize the inference client with the model repo
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  client = InferenceClient("cognitivecomputations/TinyDolphin-2.8.2-1.1b-laser")
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  def respond(
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+ message: str,
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  history: list[tuple[str, str]],
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+ system_message: str,
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+ max_tokens: int,
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+ temperature: float,
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+ top_p: float,
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  ):
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+ """Generate a response for the chatbot using the InferenceClient."""
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+ # Prepare the messages in the correct format for the API
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  messages = [{"role": "system", "content": system_message}]
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+ for user_input, assistant_reply in history:
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+ if user_input:
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+ messages.append({"role": "user", "content": user_input})
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+ if assistant_reply:
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+ messages.append({"role": "assistant", "content": assistant_reply})
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  messages.append({"role": "user", "content": message})
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  response = ""
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+ # Stream response tokens from the chat completion API
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  for message in client.chat_completion(
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+ messages=messages,
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  max_tokens=max_tokens,
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  stream=True,
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  temperature=temperature,
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  top_p=top_p,
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  ):
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+ token = message["choices"][0]["delta"].get("content", "")
 
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  response += token
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  yield response
43
 
 
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  """
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+ For information on how to customize the ChatInterface, peruse the Gradio docs: https://www.gradio.app/docs/chatinterface
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  """
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+
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  demo = gr.ChatInterface(
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  respond,
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  additional_inputs=[
 
61
  ],
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  )
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  if __name__ == "__main__":
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  demo.launch()