| import torch |
| from transformers import pipeline |
| import gradio as gr |
|
|
|
|
| generator = pipeline( |
| "text-generation", |
| model="microsoft/Phi-4-mini-instruct", |
| torch_dtype="auto", |
| device_map="auto" |
| ) |
|
|
|
|
| def generate_text(prompt): |
| messages = [ |
| {"role": "system", "content": |
| "You are a knowledgeable and up-to-date AI & Data Science teacher. " |
| "You can explain complex AI and DS concepts clearly to beginners, " |
| "while also providing advanced insights for experts. " |
| "You also share the latest trends, tools, and breakthroughs in the field " |
| "in an engaging and accessible way."}, |
| {"role": "user", "content": prompt} |
| ] |
|
|
| outputs = generator( |
| messages, |
| max_new_tokens=500, |
| temperature=0.7, |
| return_full_text=False |
| ) |
|
|
| return outputs[0]["generated_text"] |
|
|
|
|
| demo = gr.Interface( |
| fn=generate_text, |
| inputs=gr.Textbox(label="What Do You Want To Learn Today?", lines=12), |
| outputs=gr.Textbox(label="ExplainAI Assistant🤖", lines=12), |
| title="ExplainAI" |
| ) |
|
|
| if __name__ == "__main__": |
| demo.launch(server_name="0.0.0.0", server_port=7860) |
|
|
