abdullahalioo commited on
Commit
525c517
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1 Parent(s): 0b55d13

Update app.py

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Files changed (1) hide show
  1. app.py +16 -33
app.py CHANGED
@@ -1,20 +1,11 @@
1
  import gradio as gr
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  from huggingface_hub import InferenceClient
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- """
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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("HuggingFaceH4/zephyr-7b-beta")
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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:
@@ -26,7 +17,6 @@ def respond(
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  messages.append({"role": "user", "content": message})
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  response = ""
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-
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  for message in client.chat_completion(
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  messages,
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  max_tokens=max_tokens,
@@ -35,31 +25,24 @@ def respond(
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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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- 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=[
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- gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
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  gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
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  gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
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- gr.Slider(
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- minimum=0.1,
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- maximum=1.0,
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- value=0.95,
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- step=0.05,
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- label="Top-p (nucleus sampling)",
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- ),
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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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-
 
1
  import gradio as gr
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  from huggingface_hub import InferenceClient
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+ # Set up the client for Hugging Face Inference
 
 
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  client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
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+ # Define the respond function
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+ def respond(message, history, system_message, max_tokens, temperature, top_p):
 
 
 
 
 
 
 
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  messages = [{"role": "system", "content": system_message}]
10
 
11
  for val in history:
 
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  messages.append({"role": "user", "content": message})
18
 
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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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  top_p=top_p,
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  ):
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  token = message.choices[0].delta.content
 
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  response += token
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+ return response
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+ # Gradio interface function for the chatbot
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+ def gradio_interface(message, history, system_message, max_tokens, temperature, top_p):
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+ return respond(message, history, system_message, max_tokens, temperature, top_p)
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+ # Define the Gradio interface
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+ demo = gr.Interface(
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+ fn=gradio_interface,
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+ inputs=[
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+ gr.Textbox(value="You are a friendly Chatbot.", label="System Message"),
 
 
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  gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
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  gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
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+ gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
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+ gr.Chatbot(label="Chat History"),
 
 
 
 
 
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  ],
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+ outputs=gr.Textbox(),
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  )
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+ demo.launch(share=True)