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1 Parent(s): 3846deb

Update app.py

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  1. app.py +12 -59
app.py CHANGED
@@ -1,64 +1,17 @@
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  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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- 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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-
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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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-
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- messages.append({"role": "user", "content": message})
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-
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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,
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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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- """
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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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-
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- if __name__ == "__main__":
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- demo.launch()
 
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  import gradio as gr
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+ from transformers import pipeline
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+ # بارگذاری مدل DeepSeek-Coder
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+ coder = pipeline("text-generation", model="deepseek-ai/deepseek-coder-33b-instruct")
 
 
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+ def respond(message, history):
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+ prompt = f"<|system|>You are an expert programming assistant. Use Persian when needed.</s><|user|>{message}</s><|assistant|>"
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+ response = coder(prompt, max_new_tokens=200)[0]['generated_text']
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+ return response.split("<|assistant|>")[-1].strip()
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+ # استفاده از تمپلت آماده Chat Interface
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+ gr.ChatInterface(
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  respond,
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+ title="👨‍💻 دستیار کدنویسی شما",
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+ examples=["چطوری در React از useState استفاده کنم؟", "خطای SyntaxError در پایتون را رفع کن"]
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+ ).launch()