| import gradio as gr |
| from transformers import AutoTokenizer, AutoModelForCausalLM |
|
|
| model_id = "Luzika01883/AI" |
|
|
| tokenizer = AutoTokenizer.from_pretrained(model_id) |
| model = AutoModelForCausalLM.from_pretrained(model_id) |
|
|
| history = [] |
|
|
| def chat(message): |
| global history |
|
|
| history.append("User: " + message) |
|
|
| prompt = "\n".join(history) + "\nAssistant:" |
|
|
| inputs = tokenizer(prompt, return_tensors="pt") |
|
|
| output = model.generate(**inputs, max_new_tokens=120) |
|
|
| reply = tokenizer.decode(output[0], skip_special_tokens=True) |
| reply = reply.split("Assistant:")[-1].strip() |
|
|
| history.append("Assistant: " + reply) |
|
|
| return reply |
|
|
|
|
| with gr.Blocks() as app: |
| gr.Markdown("# 💬 My AI Chatbot") |
|
|
| chatbot = gr.Chatbot() |
| msg = gr.Textbox() |
|
|
| def respond(msg, chat_history): |
| reply = chat(msg) |
| chat_history.append((msg, reply)) |
| return "", chat_history |
|
|
| msg.submit(respond, [msg, chatbot], [msg, chatbot]) |
|
|
| app.launch() |
