import gradio as gr
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline

model_name = "King-8/confidence-feedback"  # Replace with your actual path if needed

tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)

generator = pipeline("text2text-generation", model=model, tokenizer=tokenizer)

def generate_feedback(prompt):
    result = generator(prompt, max_length=50, do_sample=False)[0]["generated_text"]
    return result

examples = [
    "I don't think I can do this.",
    "I'm proud of what I accomplished.",
    "I believe I'm ready for the challenge.",
]

description = """
## Confidence Feedback Generator ✨

Enter a statement — confident or not — and the model will give supportive, personalized feedback.

Try examples like:
- “I always doubt myself.”
- “I'm proud of how I handled that.”
- “I feel nervous before presenting.”

"""

iface = gr.Interface(
    fn=generate_feedback,
    inputs=gr.Textbox(lines=2, placeholder="Enter your statement here..."),
    outputs="text",
    examples=examples,
    title="Confidence Feedback Generator",
    description=description
)

iface.launch()