import gradio as gr from openai import OpenAI import os from fpdf import FPDF from docx import Document css = ''' .gradio-container{max-width: 1000px !important} h1{text-align:center} footer { visibility: hidden } ''' ACCESS_TOKEN = os.getenv("HF_TOKEN") client = OpenAI( base_url="https://api-inference.huggingface.co/v1/", api_key=ACCESS_TOKEN, ) def respond( message, history: list[tuple[str, str]], system_message, max_tokens, temperature, top_p, ): messages = [{"role": "system", "content": system_message}] for val in history: if val[0]: messages.append({"role": "user", "content": val[0]}) if val[1]: messages.append({"role": "assistant", "content": val[1]}) messages.append({"role": "user", "content": message}) response = "" for message in client.chat.completions.create( model="meta-llama/Meta-Llama-3.1-8B-Instruct", max_tokens=max_tokens, stream=True, temperature=temperature, top_p=top_p, messages=messages, ): token = message.choices[0].delta.content response += token yield response def save_to_file(history, file_format): if file_format == "PDF": pdf = FPDF() pdf.add_page() pdf.set_auto_page_break(auto=True, margin=15) pdf.set_font("Arial", size=12) for user_message, assistant_message in history: pdf.multi_cell(0, 10, f"User: {user_message}") pdf.multi_cell(0, 10, f"Assistant: {assistant_message}") file_name = "chat_history.pdf" pdf.output(file_name) elif file_format == "DOCX": doc = Document() for user_message, assistant_message in history: doc.add_paragraph(f"User: {user_message}") doc.add_paragraph(f"Assistant: {assistant_message}") file_name = "chat_history.docx" doc.save(file_name) elif file_format == "TXT": file_name = "chat_history.txt" with open(file_name, "w") as file: for user_message, assistant_message in history: file.write(f"User: {user_message}\n") file.write(f"Assistant: {assistant_message}\n") return file_name def save_conversation(history, file_format): file_name = save_to_file(history, file_format) return file_name demo = gr.ChatInterface( respond, additional_inputs=[ gr.Textbox(value="", label="System message"), gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"), gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"), gr.Slider(minimum=0.1, maximum 1.0, value=0.95, step=0.05, label="Top-P"), gr.Radio(["PDF", "DOCX", "TXT"], label="Save As"), ], button_fn=save_conversation, css=css, theme="allenai/gradio-theme", ) if __name__ == "__main__": demo.launch()