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import gradio as gr |
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import openai |
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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}] |
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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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client = OpenAI( |
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api_key="sk-Eqk19o6qqgk3i09tUkriFcESxqsQNsvdF18AaHaoxeHIv0oc", |
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base_url="https://api.moonshot.cn/v1", |
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) |
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response = client.ChatCompletion.create( |
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model="moonshot-v1-128k", |
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messages=messages, |
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max_tokens=max_tokens, |
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temperature=temperature, |
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top_p=top_p, |
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stream=True |
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) |
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final_response = "" |
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for message in response['choices'][0]['message']: |
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final_response += message['content'] |
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return final_response |
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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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if __name__ == "__main__": |
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demo.launch() |
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