import gradio as gr import os import time import torch from transformers import pipeline pipe = pipeline("text-generation", model="TinyLlama/TinyLlama-1.1B-Chat-v1.0", torch_dtype=torch.bfloat16, device_map="auto") messages = [ { "role": "system", "content": "You are a friendly chatbot who always responds in the style of a pirate", }, # {"role": "user", "content": "How many helicopters can a human eat in one sitting?"}, ] def greet(name): return "Hello " + name + "!!" #iface = gr.Interface(fn=greet, inputs="text", outputs="text") #iface.launch() # Chatbot demo with multimodal input (text, markdown, LaTeX, code blocks, image, audio, & video). Plus shows support for streaming text. def print_like_dislike(x: gr.LikeData): print(x.index, x.value, x.liked) def add_ia_text(history, text): messages.append({"role": "user", "content": text}) print(messages) prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) print("prompt") outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95) print("output") response = (outputs[0]["generated_text"])# type: ignore print(response) history = history + [response, None] def add_text(history, text): history = history + [(text, None)] add_ia_text(history, text) return history, gr.Textbox(value="", interactive=False) def add_file(history, file): history = history + [((file.name,), None)] return history def bot(history): response = "**That's cool!**" history[-1][1] = "" for character in response: history[-1][1] += character time.sleep(0.05) yield history with gr.Blocks() as demo: chatbot = gr.Chatbot( [], elem_id="chatbot", bubble_full_width=False, avatar_images=(None, (os.path.join(os.path.dirname(__file__), "avatar.png"))), ) with gr.Row(): txt = gr.Textbox( scale=4, show_label=False, placeholder="Enter text and press enter, or upload an image", container=False, ) btn = gr.UploadButton("📁", file_types=["image", "video", "audio"]) txt_msg = txt.submit(add_text, [chatbot, txt], [chatbot, txt], queue=False).then( bot, chatbot, chatbot, api_name="bot_response" ) txt_msg.then(lambda: gr.Textbox(interactive=True), None, [txt], queue=False) file_msg = btn.upload(add_file, [chatbot, btn], [chatbot], queue=False).then( bot, chatbot, chatbot ) chatbot.like(print_like_dislike, None, None) demo.queue() if __name__ == "__main__": demo.launch()