import gradio as gr
import requests
import os
import json

PRIVATE_SPACE_URL = os.getenv("PRIVATE_SPACE_URL")
HF_TOKEN = os.getenv("HF_TOKEN")

def fetch_actor_data():
    if not PRIVATE_SPACE_URL:
        return "Error: PRIVATE_SPACE_URL not found. Check Secrets."
    if not HF_TOKEN:
        return "Error: HF_TOKEN not found. Check Secrets."

    headers = {
        "Authorization": f"Bearer {HF_TOKEN}"
    }

    try:
        response = requests.get(f"{PRIVATE_SPACE_URL}/api/actor", headers=headers)

        if response.status_code == 200:
            # 응답 JSON 파싱
            data = response.json()
            
            # 기대 구조: data["data"]["result"] => list of actor items
            actor_ids = []
            if (
                "data" in data
                and isinstance(data["data"], dict)
                and "result" in data["data"]
                and isinstance(data["data"]["result"], list)
            ):
                for item in data["data"]["result"]:
                    if "actor_id" in item:
                        actor_ids.append(item["actor_id"])
                    if len(actor_ids) >= 10:
                        break

            if actor_ids:
                return f"Found actor_ids: {actor_ids}"
            else:
                # actor_id가 없을 경우 구조 파악용 반환
                top_level_keys = list(data["data"].keys()) if "data" in data and isinstance(data["data"], dict) else []
                first_item = data["data"]["result"][0] if "data" in data and "result" in data["data"] and len(data["data"]["result"]) > 0 else {}
                return (
                    "No actor_id found.\n\n"
                    f"Keys in data['data']: {top_level_keys}\n\n"
                    "First item in data['data']['result']:\n" +
                    json.dumps(first_item, indent=2, ensure_ascii=False)
                )
        else:
            return f"Error {response.status_code}\nResponse Text:\n{response.text}"
    except Exception as e:
        return f"Request failed: {str(e)}"

iface = gr.Interface(
    fn=fetch_actor_data,
    inputs=None,
    outputs="text",
    title="Fetch Actor Data",
    description=(
        "Fetches actor data from the private Hugging Face Space.\n"
        "Assumes structure: {status_code:..., data:{count:..., result:[{actor_id:...}]}}\n"
        "If no actor_id found, shows partial keys for debugging."
    )
)

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