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import gradio as gr |
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import os |
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from pathlib import Path |
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import argparse |
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from huggingface_hub import snapshot_download |
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repo_name = 'HumanityFTW/so_rude' |
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model_file = "mistral-comedy-2.0-ckpt-600.Q6_K.gguf" |
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print('Fetching model:', repo_name, model_file) |
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snapshot_download(repo_id=repo_name, local_dir=".", allow_patterns=model_file) |
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print('Done fetching model:') |
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DEFAULT_MODEL_PATH = model_file |
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from llama_cpp import Llama |
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llm = Llama(model_path=model_file, model_type="mistral") |
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def predict(input, chatbot, max_length, top_p, temperature, history): |
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chatbot.append((input, "")) |
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response = "" |
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history.append(input) |
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for output in llm(input, stream=True, temperature=temperature, top_p=top_p, max_tokens=max_length, ): |
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piece = output['choices'][0]['text'] |
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response += piece |
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chatbot[-1] = (chatbot[-1][0], response) |
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yield chatbot, history |
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history.append(response) |
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yield chatbot, history |
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def reset_user_input(): |
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return gr.update(value="") |
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def reset_state(): |
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return [], [] |
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with gr.Blocks() as demo: |
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gr.HTML("""<h1 align="center">So Rude</h1>""") |
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chatbot = gr.Chatbot() |
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with gr.Row(): |
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with gr.Column(scale=4): |
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user_input = gr.Textbox(show_label=False, placeholder="Input...", lines=8, elem_id="user_input") |
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submitBtn = gr.Button("Submit", variant="primary", elem_id="submit_btn") |
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with gr.Column(scale=1): |
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max_length = gr.Slider(0, 256, value=64, step=1.0, label="Maximum Length", interactive=True) |
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top_p = gr.Slider(0, 1, value=0.7, step=0.01, label="Top P", interactive=True) |
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temperature = gr.Slider(0, 2.0, value=0.95, step=0.01, label="Temperature", interactive=True) |
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emptyBtn = gr.Button("Clear History") |
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history = gr.State([]) |
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submitBtn.click( |
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predict, [user_input, chatbot, max_length, top_p, temperature, history], [chatbot, history], show_progress=True |
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) |
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submitBtn.click(reset_user_input, [], [user_input]) |
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emptyBtn.click(reset_state, outputs=[chatbot, history], show_progress=True) |
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demo.queue().launch(share=False, inbrowser=True) |
