"""
Gradio app: Instagram Comments Downloader → XLSX
- Accepts single or multiple post URLs
- Resolves Media ID automatically
- Fetches comments using official Instagram Graph API
- Provides XLSX files for download
- Shows estimated API calls (credit usage)
"""

import os
import requests
import pandas as pd
import gradio as gr
from io import BytesIO
from urllib.parse import urlparse

# Instagram API token stored as HF Space secret
ACCESS_TOKEN = os.environ.get("INSTAGRAM_API_TOKEN")
if not ACCESS_TOKEN:
    raise ValueError("Set the Instagram API token in Space secrets as INSTAGRAM_API_TOKEN")

def resolve_shortcode_to_media_id(shortcode: str):
    """Resolve Instagram post shortcode to media ID via Graph API OEmbed"""
    url = "https://graph.facebook.com/v19.0/instagram_oembed"
    params = {
        "url": f"https://www.instagram.com/p/{shortcode}/",
        "access_token": ACCESS_TOKEN
    }
    resp = requests.get(url, params=params)
    if resp.status_code != 200:
        raise ValueError(f"Error resolving URL {shortcode}: {resp.status_code} {resp.text}")
    data = resp.json()
    media_id = data.get("media_id")
    if not media_id:
        raise ValueError(f"Could not resolve media ID for shortcode {shortcode}")
    return media_id

def fetch_instagram_comments(media_id: str, max_comments: int = 200):
    """Fetch comments for a single post; returns DataFrame and API calls used"""
    columns = ["id", "username", "text", "timestamp"]
    comments_list = []
    count = 0
    api_calls = 0
    url = f"https://graph.facebook.com/v19.0/{media_id}/comments"
    params = {"fields": "id,username,text,timestamp", "limit": 100, "access_token": ACCESS_TOKEN}
    next_url = url

    while next_url and count < max_comments:
        resp = requests.get(next_url, params=params)
        api_calls += 1
        if resp.status_code != 200:
            raise ValueError(f"Error fetching comments: {resp.status_code} {resp.text}")
        data = resp.json()
        for c in data.get("data", []):
            comments_list.append({
                "id": c.get("id"),
                "username": c.get("username"),
                "text": c.get("text"),
                "timestamp": c.get("timestamp")
            })
            count += 1
            if count >= max_comments:
                break
        next_url = data.get("paging", {}).get("next")

    df = pd.DataFrame(comments_list, columns=columns)
    return df, api_calls

def process_instagram_urls(urls_text, max_comments=200):
    """Process multiple URLs, return list of (filename, BytesIO) and total API calls"""
    urls = [u.strip() for u in urls_text.replace(",", "\n").split("\n") if u.strip()]
    files = []
    total_api_calls = 0

    for url in urls:
        try:
            parsed = urlparse(url)
            path_parts = parsed.path.strip("/").split("/")
            if len(path_parts) < 2 or path_parts[0] != "p":
                return [], f"Invalid Instagram post URL: {url}"
            shortcode = path_parts[1]
            media_id = resolve_shortcode_to_media_id(shortcode)
            df, api_calls = fetch_instagram_comments(media_id, max_comments)
            total_api_calls += api_calls
            output = BytesIO()
            df.to_excel(output, index=False, engine='openpyxl')
            output.seek(0)
            filename = f"instagram_{shortcode}_comments.xlsx"
            files.append((filename, output))
        except Exception as e:
            return [], f"Error processing {url}: {e}"

    return files, f"Estimated API calls used: {total_api_calls}"

# --- Gradio UI ---
with gr.Blocks(title="Instagram Comments Downloader") as demo:
    gr.Markdown(
        "## Instagram Comments → XLSX\n"
        "Paste one or multiple Instagram post URLs (newline or comma separated) and fetch comments."
    )

    urls_input = gr.Textbox(
        label="Instagram Post URLs",
        lines=5,
        placeholder="https://www.instagram.com/p/CODE1/\nhttps://www.instagram.com/p/CODE2/"
    )
    max_comments_input = gr.Number(value=200, label="Max comments per post")
    run_btn = gr.Button("Fetch Comments")
    download_files = gr.Files(label="Download XLSX files", file_types=[".xlsx"])
    api_info = gr.Textbox(label="Estimated API Calls / Status", interactive=False)

    def on_fetch(urls_text, max_comments):
        files, api_estimate = process_instagram_urls(urls_text, int(max_comments))
        return files, api_estimate

    run_btn.click(
        fn=on_fetch,
        inputs=[urls_input, max_comments_input],
        outputs=[download_files, api_info]
    )

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