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import gradio as gr |
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import os |
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import json |
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import requests |
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API_URL = "https://api.openai.com/v1/chat/completions" |
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OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") |
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def predict(system_msg, inputs, top_p, temperature, chat_counter, chatbot=[], history=[]): |
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headers = { |
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"Content-Type": "application/json", |
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"Authorization": f"Bearer {OPENAI_API_KEY}" |
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} |
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print(f"system message is ^^ {system_msg}") |
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initial_message = [{"role": "user", "content": f"{inputs}"},] |
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multi_turn_message = [ |
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{"role": "system", "content": "你是一个中文AI专家,你是用远见科技公司开发和维护的,你可以回答所有的问题,除了涉黄涉政的问题,你就是一个中国人,切记"} |
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] |
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messages=multi_turn_message |
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for data in chatbot: |
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user = {} |
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user["role"] = "user" |
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user["content"] = data[0] |
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assistant = {} |
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assistant["role"] = "assistant" |
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assistant["content"] = data[1] |
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messages.append(user) |
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messages.append(assistant) |
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temp = {} |
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temp["role"] = "user" |
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temp["content"] = inputs |
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messages.append(temp) |
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payload = {"model": "gpt-3.5-turbo", "messages": messages, "temperature" : 1, "top_p": 1.0, "n" : 1, "stream": True, "presence_penalty":0, "frequency_penalty":0,} |
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chat_counter+=1 |
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history.append(inputs) |
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print(f"Logging : payload is - {payload}") |
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response = requests.post(API_URL, headers=headers, json=payload, stream=True) |
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print(f"Logging : response code - {response}") |
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token_counter = 0 |
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partial_words = "" |
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counter=0 |
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for chunk in response.iter_lines(): |
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if counter == 0: |
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counter+=1 |
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continue |
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if chunk.decode() : |
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chunk = chunk.decode() |
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if len(chunk) > 12 and "content" in json.loads(chunk[6:])['choices'][0]['delta']: |
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partial_words = partial_words + json.loads(chunk[6:])['choices'][0]["delta"]["content"] |
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if token_counter == 0: |
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history.append(" " + partial_words) |
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else: |
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history[-1] = partial_words |
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chat = [(history[i], history[i + 1]) for i in range(0, len(history) - 1, 2) ] |
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token_counter+=1 |
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yield chat, history, chat_counter, response |
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def reset_textbox(): |
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return gr.update(value='') |
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def set_visible_false(): |
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return gr.update(visible=False) |
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def set_visible_true(): |
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return gr.update(visible=False) |
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theme_addon_msg = "" |
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system_msg_info = "" |
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theme = gr.themes.Soft(primary_hue="zinc", secondary_hue="green", neutral_hue="blue", |
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text_size=gr.themes.sizes.text_md) |
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with gr.Blocks(css = """#col_container { margin-left: auto; margin-right: auto;} #chatbot {height: 450px; overflow: auto;}""", |
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theme=theme) as demo: |
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with gr.Column(elem_id = "col_container"): |
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with gr.Accordion("", open=False, visible=False): |
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system_msg = gr.Textbox(value="") |
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accordion_msg = gr.HTML(value="", visible=False) |
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chatbot = gr.Chatbot(label='chat', elem_id="chatbot") |
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inputs = gr.Textbox(placeholder= "请输入", show_label= False) |
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state = gr.State([]) |
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with gr.Accordion("", open=False, visible=False): |
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top_p = gr.Slider( minimum=-0, maximum=1.0, value=1.0, step=0.05, interactive=False, visible=False) |
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temperature = gr.Slider( minimum=-0, maximum=5.0, value=1.0, step=0.1, interactive=False, visible=False) |
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chat_counter = gr.Number(value=0, visible=False, precision=0) |
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inputs.submit( predict, [system_msg, inputs, top_p, temperature, chat_counter, chatbot, state], [chatbot, state, chat_counter],) |
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inputs.submit(reset_textbox, [], [inputs]) |
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demo.queue(max_size=20, concurrency_count=20).launch(debug=True) |
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