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import openai |
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import os |
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import gradio as gr |
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openai.api_key=os.getenv('openai_appkey') |
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def get_chatgpt(input_text): |
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chat_completion = openai.ChatCompletion.create( |
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model="gpt-3.5-turbo", |
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messages=[ |
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{"role": "system", "content": "You are a helpful assistant."}, |
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{"role": "user", "content": input_text}, |
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], |
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) |
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return chat_completion.choices[0].message.content |
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with gr.Blocks( |
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css=""" |
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.message.svelte-w6rprc.svelte-w6rprc.svelte-w6rprc {font-size: 20px; margin-top: 20px} |
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#component-21 > div.wrap.svelte-w6rprc {height: 600px;} |
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""" |
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) as iface: |
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state = gr.State([]) |
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with gr.Row(): |
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with gr.Column(scale=1): |
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with gr.Row(): |
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with gr.Column(scale=1): |
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chat_input = gr.Textbox(lines=1, label="Quesiton Input") |
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with gr.Row(): |
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clear_button = gr.Button(value="Clear", interactive=True) |
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submit_button = gr.Button( |
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value="提问", interactive=True, variant="primary" |
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) |
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with gr.Column(): |
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caption_output_v1 = gr.Textbox(lines=0, label="答案") |
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submit_button.click( |
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get_chatgpt, |
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[ |
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chat_input, |
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], |
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[caption_output_v1], |
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) |
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examples=[["毛主席是什么时候出生的?"]] |
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examples = gr.Examples( |
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examples=examples, |
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inputs=[ chat_input], |
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) |
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iface.queue(concurrency_count=1, api_open=False, max_size=10) |
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iface.launch(enable_queue=True) |
