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import os |
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import urllib.request |
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import gradio as gr |
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from llama_cpp import Llama |
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def download_file(file_link, filename): |
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if not os.path.isfile(filename): |
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urllib.request.urlretrieve(file_link, filename) |
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print("File downloaded successfully.") |
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else: |
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print("File already exists.") |
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ggml_model_path = "https://huggingface.co/TheBloke/CodeLlama-7B-Instruct-GGML/blob/main/codellama-7b-instruct.ggmlv3.Q4_1.bin" |
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filename = "codellama-7b-instruct.ggmlv3.Q4_1.bin" |
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download_file(ggml_model_path, filename) |
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llm = Llama(model_path=filename, n_ctx=512, n_batch=126) |
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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 llm( |
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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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if __name__ == "__main__": |
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demo.launch() |
