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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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from new_chat import Conversation, ChatgptAPI |
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chat_api = ChatgptAPI() |
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def predict(system_input, password_input, user_in_file, user_input, conversation): |
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if password_input != '112233': |
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return [(None, "Wrong password!")], conversation, user_input |
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if conversation.is_initialized() == False: |
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conversation = Conversation(system_input, 5) |
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conversation = chat_api.get_single_round_completion(user_in_file, user_input, conversation) |
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return conversation, conversation, None |
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def clear_history(conversation): |
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conversation.clear() |
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return None, conversation |
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with gr.Blocks(css="#chatbot{height:350px} .overflow-y-auto{height:600px}") as demo: |
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chatbot = gr.Chatbot(elem_id="chatbot") |
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conversation = gr.State(value=Conversation()) |
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with gr.Row(): |
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system_in_txt = gr.Textbox(lines=1, label="System role content:", placeholder="Enter system role content") |
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password_in_txt = gr.Textbox(lines=1, label="Password:", placeholder="Enter password") |
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with gr.Row(): |
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user_in_file = gr.File(label="Upload File") |
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user_in_txt = gr.Textbox(lines=3, label="User role content:", placeholder="Enter text...").style(container=False) |
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with gr.Row(): |
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submit_button = gr.Button("Submit") |
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reset_button = gr.Button("Reset") |
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submit_button.click(predict, [system_in_txt, password_in_txt, user_in_file, user_in_txt, conversation], [chatbot, conversation, user_in_txt]) |
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reset_button.click(clear_history, [conversation], [chatbot, conversation], queue=False) |
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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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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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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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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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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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