import gradio as gr import yaml from huggingface_hub import hf_hub_download from huggingface_hub.utils import LocalEntryNotFoundError from llama_cpp import Llama with open("./config.yml", "r") as f: config = yaml.load(f, Loader=yaml.Loader) while True: try: load_config = config.copy() hub_config = load_config["hub"].copy() repo_id = hub_config.pop("repo_id") filename = hub_config.pop("filename") fp = hf_hub_download( repo_id=repo_id, filename=filename, **hub_config ) break except LocalEntryNotFoundError as e: if "Connection error" in str(e): print(str(e) + ", retrying...") else: raise(e) llm = Llama(model_path=fp, **config["llama_cpp"]) def user(message, history): history = history or [] # Append the user's message to the conversation history history.append([message, ""]) return "", history def chat(history, system_message, max_tokens, temperature, top_p, top_k, repeat_penalty): history = history or [] messages = system_message.strip() + "\n" + \ "\n".join(["\n".join(["Kullanıcı: "+item[0], "Asistan: "+item[1]]) for item in history]) # remove last space from assistant, some models output a ZWSP if you leave a space messages = messages[:-1] history[-1][1] = "" for output in llm( messages, echo=False, stream=True, max_tokens=max_tokens, temperature=temperature, top_p=top_p, top_k=top_k, repeat_penalty=repeat_penalty, **config['chat'] ): answer = output['choices'][0]['text'] history[-1][1] += answer # stream the response yield history, history def rp_chat(history, system_message, max_tokens, temperature, top_p, top_k, repeat_penalty): history = history or [] messages = "<|system|>" + system_message.strip() + "\n" + \ "\n".join(["\n".join(["<|user|>"+item[0], "<|model|>"+item[1]]) for item in history]) # remove last space from assistant, some models output a ZWSP if you leave a space messages = messages[:-1] history[-1][1] = "" for output in llm( messages, echo=False, stream=True, max_tokens=max_tokens, temperature=temperature, top_p=top_p, top_k=top_k, repeat_penalty=repeat_penalty, **config['chat'] ): answer = output['choices'][0]['text'] history[-1][1] += answer # stream the response yield history, history def clear_chat(chat_history_state, chat_message): chat_history_state = [] chat_message = '' return chat_history_state, chat_message start_message = """ - Akıllı, dürüst ve yardımsever bir asistansın. - Her türlü soruya dürüstçe cevap vereceksin. """ def generate_text_instruct(input_text): response = "" for output in llm(f"Kullanıcı: {input_text}\nAsistan:", echo=False, stream=True, **config['chat']): answer = output['choices'][0]['text'] response += answer yield response instruct_interface = gr.Interface( fn=generate_text_instruct, inputs=gr.inputs.Textbox(lines= 10, label="Enter your input text"), outputs=gr.outputs.Textbox(label="Output text"), ) with gr.Blocks() as demo: with gr.Row(): with gr.Column(): gr.Markdown(f""" ### This is the [{config["hub"]["repo_id"]}](https://huggingface.co/{config["hub"]["repo_id"]}) quantized model file [{config["hub"]["filename"]}](https://huggingface.co/{config["hub"]["repo_id"]}/blob/main/{config["hub"]["filename"]})
Duplicate the Space to skip the queue and run in a private space or to use your own GGUF models, simply update the config.yml
""") with gr.Tab("Chatbot"): gr.Markdown("# GGUF Spaces Chatbot Demo") chatbot = gr.Chatbot() with gr.Row(): message = gr.Textbox( label="Ne konuda konuşmak istersin?", placeholder="Bana bir şeyler sor.", lines=3, ) with gr.Row(): submit = gr.Button(value="Mesaj Gönder", variant="secondary").style(full_width=True) roleplay = gr.Button(value="Rol", variant="secondary").style(full_width=True) clear = gr.Button(value="Yeni Konu", variant="secondary").style(full_width=False) stop = gr.Button(value="Dur", variant="secondary").style(full_width=False) with gr.Row(): with gr.Column(): max_tokens = gr.Slider(20, 1000, label="Max Tokens", step=20, value=300) temperature = gr.Slider(0.2, 2.0, label="Temperature", step=0.1, value=0.8) top_p = gr.Slider(0.0, 1.0, label="Top P", step=0.05, value=0.95) top_k = gr.Slider(0, 100, label="Top K", step=1, value=40) repeat_penalty = gr.Slider(0.0, 2.0, label="Repetition Penalty", step=0.1, value=1.1) system_msg = gr.Textbox( start_message, label="System Message", interactive=True, visible=True, placeholder="system prompt, useful for RP", lines=5) chat_history_state = gr.State() clear.click(clear_chat, inputs=[chat_history_state, message], outputs=[chat_history_state, message], queue=False) clear.click(lambda: None, None, chatbot, queue=False) submit_click_event = submit.click( fn=user, inputs=[message, chat_history_state], outputs=[message, chat_history_state], queue=True ).then( fn=chat, inputs=[chat_history_state, system_msg, max_tokens, temperature, top_p, top_k, repeat_penalty], outputs=[chatbot, chat_history_state], queue=True ) roleplay_click_event = roleplay.click( fn=user, inputs=[message, chat_history_state], outputs=[message, chat_history_state], queue=True ).then( fn=rp_chat, inputs=[chat_history_state, system_msg, max_tokens, temperature, top_p, top_k, repeat_penalty], outputs=[chatbot, chat_history_state], queue=True ) # message_submit_event = message.submit( # fn=user, inputs=[message, chat_history_state], outputs=[message, chat_history_state], queue=True # ).then( # fn=chat, inputs=[chat_history_state, system_msg, max_tokens, temperature, top_p, top_k, repeat_penalty], outputs=[chatbot, chat_history_state], queue=True # ) stop.click(fn=None, inputs=None, outputs=None, cancels=[submit_click_event, roleplay_click_event], queue=False) with gr.Tab("Instruct"): gr.Markdown("# GGUF Spaces Instruct Demo") instruct_interface.render() demo.queue(**config["queue"]).launch(debug=True, server_name="0.0.0.0", server_port=7860)