import os
import gradio as gr
from groq import Groq

api_key = os.getenv("GROQ_API_KEY")
if not api_key:
    raise ValueError("Missing GROQ_API_KEY. Please set it in Hugging Face Space Settings → Secrets.")

client = Groq(api_key=api_key)

def summarize_abstract(text):
    try:
        response = client.chat.completions.create(
            model="openai/gpt-oss-120b",   # replace with a valid model from client.models.list()
            messages=[
                {"role": "system", "content": "Summarize the abstract into two parts: Main Idea and Findings."},
                {"role": "user", "content": text}
            ],
            max_tokens=250
        )
        summary = response.choices[0].message.content

        # Simple parsing: look for "Main Idea:" and "Findings:"
        main_html, findings_html = "", ""
        for line in summary.split("\n"):
            if line.lower().startswith("main idea"):
                main_html = f"<span style='color:pink; font-weight:bold'>{line}</span>"
            elif line.lower().startswith("findings"):
                findings_html = f"<span style='color:gold; font-weight:bold'>{line}</span>"

        return main_html + "<br>" + findings_html if (main_html or findings_html) else summary
    except Exception as e:
        return f"<span style='color:red'>Error: {str(e)}</span>"

demo = gr.Interface(
    fn=summarize_abstract,
    inputs=gr.Textbox(lines=10, label="Paste Abstract"),
    outputs=gr.HTML(label="Summary"),
    title="📄 Scientific Abstract Summarizer",
    description="Main Idea appears in pink, Findings in yellow."
)

demo.launch()