import os
import time
import json
from pathlib import Path
from dotenv import load_dotenv
import requests
from datetime import datetime
import gradio as gr

# Configuration
QUOTA_FILE = "api_quota.json"
RATE_LIMIT_DELAY = 1.0
DEFAULT_MODEL = "facebook/bart-large-cnn"
MAX_RETRIES = 3
RETRY_DELAY = 5

# --- Core Functions ---
def load_quota():
    try:
        if Path(QUOTA_FILE).exists():
            with open(QUOTA_FILE, "r") as f:
                return json.load(f)
    except:
        pass
    return {"remaining": 600, "last_updated": datetime.now().isoformat()}

def save_quota(quota):
    with open(QUOTA_FILE, "w") as f:
        json.dump(quota, f)

def summarize_text(text, model=DEFAULT_MODEL):
    try:
        load_dotenv()
        token = os.getenv("HF_API_TOKEN")
        if not token:
            return "⚠️ Add your Hugging Face token to .env file", "0/600"
    except Exception as e:
        return f"⚠️ Config error: {str(e)}", "0/600"

    api_url = f"https://api-inference.huggingface.co/models/{model}"
    headers = {"Authorization": f"Bearer {token}"}
    payload = {"inputs": text, "parameters": {"max_length": 50, "min_length": 20}}

    for attempt in range(MAX_RETRIES):
        try:
            time.sleep(RATE_LIMIT_DELAY)
            response = requests.post(api_url, headers=headers, json=payload, timeout=10)
            
            quota = load_quota()
            quota["remaining"] = max(0, quota.get("remaining", 600) - 1)
            save_quota(quota)

            if response.status_code == 200:
                result = response.json()
                if isinstance(result, list):
                    return result[0].get("summary_text", "⚠️ No summary generated"), f"{quota['remaining']}/600"
            if response.status_code == 503:
                time.sleep(RETRY_DELAY)
                continue
            return f"⚠️ API Error: {response.text[:200]}", f"{quota['remaining']}/600"
        except requests.exceptions.RequestException as e:
            if attempt == MAX_RETRIES - 1:
                return f"⚠️ Network error: {str(e)}", "0/600"
            time.sleep(RETRY_DELAY)
    return "⚠️ Failed after multiple attempts", "0/600"

# --- Gradio Interface ---
css = """
button {
    background: #A41F13 !important;
    color: white !important;
    border: none !important;
    border-radius: 8px !important;
    padding: 12px 24px !important;
    font-weight: bold !important;
    transition: transform 0.2s ease-in-out;
}
button:hover {
    transform: scale(1.05);
    cursor: pointer;
}
"""

with gr.Blocks(theme=gr.themes.Soft(), css=css, title="My AI Summarizer") as app:
    gr.Markdown("# ✨ My Text Summarizer")
    gr.Markdown("Paste any text and get a concise summary using AI!")

    with gr.Row():
        input_text = gr.Textbox(label="Input Text", lines=8, placeholder="Paste your article/story here...")
        output_text = gr.Textbox(label="Summary", lines=8, interactive=False)

    with gr.Row():
        submit_btn = gr.Button("Summarize", variant="primary")
        quota_display = gr.Textbox(label="API Status", interactive=False)

    submit_btn.click(
        fn=summarize_text,
        inputs=input_text,
        outputs=[output_text, quota_display]
    )

    gr.Examples(
        examples=[
            "He prayed Fajr half-asleep...",
            "Scientists discovered octopuses can edit their RNA...",
            "The quick brown fox jumps over the lazy dog."
        ],
        inputs=input_text
    )

if __name__ == "__main__":
    app.launch()