import gradio as gr from openai import OpenAI import os from fpdf import FPDF import docx css = ''' .gradio-container{max-width: 890px !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, ) # Function to save generated text to a file def save_file(content, filename, 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 line in content.split("\n"): pdf.multi_cell(0, 10, line) pdf.output(f"{filename}.pdf") return f"{filename}.pdf" elif file_format == "docx": doc = docx.Document() doc.add_paragraph(content) doc.save(f"{filename}.docx") return f"{filename}.docx" elif file_format == "txt": with open(f"{filename}.txt", "w") as f: f.write(content) return f"{filename}.txt" else: raise ValueError("Unsupported file format") # Respond function with file saving 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-3.1-70B-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 return response, history + [(message, response)] # Function to handle file saving after generation def save_generated_file(response, filename, file_format): saved_file = save_file(response, filename, file_format) return saved_file # Gradio interface using Blocks with gr.Blocks(css=css) as demo: system_message = gr.Textbox(value="", label="System message") max_tokens = gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens") temperature = gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature") top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-P") filename = gr.Textbox(value="output", label="Filename") file_format = gr.Radio(["pdf", "docx", "txt"], label="File Format", value="pdf") message = gr.Textbox(label="User Message") chat_history = gr.State(value=[]) response_output = gr.Textbox(label="Generated Response") file_output = gr.File(label="Download File") generate_button = gr.Button("Generate") save_button = gr.Button("Save to File") generate_button.click( respond, inputs=[message, chat_history, system_message, max_tokens, temperature, top_p], outputs=[response_output, chat_history] ) save_button.click( save_generated_file, inputs=[response_output, filename, file_format], outputs=[file_output] ) if __name__ == "__main__": demo.launch()