import random
import os
import sys
import json
import csv
from huggingface_hub import hf_hub_download, HfApi

# Force UTF-8 for console output (Windows fix)
sys.stdout.reconfigure(encoding='utf-8')

# Add backend directory to sys.path so imports work
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))

from config import AppConfig

def main():
    repo_id = "toecm/PureChain_Dataset"
    filename = "pending_tx_queue.json"
    queue = []
    
    from huggingface_hub import get_token
    hf_token = getattr(AppConfig, 'HF_TOKEN', None) or get_token()
    if not hf_token:
        print("❌ Missing HF_TOKEN in config and Hugging Face CLI.")
        return

    print("☁️ Downloading existing pending_tx_queue.json from Hugging Face...")
    try:
        downloaded_path = hf_hub_download(
            repo_id=repo_id,
            repo_type="dataset",
            filename=filename,
            token=hf_token
        )
        with open(downloaded_path, "r", encoding='utf-8') as f:
            queue = json.load(f)
        print(f"✅ Downloaded existing queue with {len(queue)} items.")
    except Exception as e:
        print(f"ℹ️ Could not download existing queue (it may not exist). Starting fresh. ({e})")
        queue = []

    korean_dialects = [
        "Gyeongsangdo Satoori",
        "Jeju Satoori",
        "Gangwon Satoori",
        "Chungcheong Satoori",
        "Seoul Satoori",
        "Jeolla Satoori",
    ]

    print("🎲 Generating 60 Korean↔Korean interactions...")
    for i in range(60):
        d1 = random.choice(korean_dialects)
        d2 = random.choice(korean_dialects)
        payload = {
            "original": f"Simulated utterance from {d1} to {d2}",
            "dialect": d2,
            "Data_Origin": f"Simulation: {d1}",
            "user": "System Auto-Simulation"
        }
        queue.append(payload)

    print("🎲 Generating 30 interactions for each Korean Satoori with American English...")
    for dialect in korean_dialects:
        for i in range(30):
            payload = {
                "original": f"Simulated utterance from {dialect} to American English",
                "dialect": "American English",
                "Data_Origin": f"Simulation: {dialect}",
                "user": "System Auto-Simulation"
            }
            queue.append(payload)

    print(f"✅ Generated simulations. Total queue size: {len(queue)}")
    
    local_path = "pending_tx_queue.json"
    with open(local_path, "w", encoding="utf-8") as f:
        json.dump(queue, f, indent=2, ensure_ascii=False)
        
    # Write CSV version for pending approvals
    csv_path = "pending_approvals.csv"
    with open(csv_path, "w", newline="", encoding="utf-8") as csvfile:
        fieldnames = ["original", "dialect", "Data_Origin", "user"]
        writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
        writer.writeheader()
        for item in queue:
            writer.writerow({k: item.get(k, "") for k in fieldnames})
        
    print("☁️ Uploading updated queue back to Hugging Face...")
    api = HfApi(token=hf_token)
    # Upload JSON queue
    api.upload_file(
        path_or_fileobj=local_path,
        path_in_repo=filename,
        repo_id=repo_id,
        repo_type="dataset",
        commit_message="🤖 Auto-queued 240 simulated interactions (JSON)"
    )
    # Upload CSV approvals
    api.upload_file(
        path_or_fileobj=csv_path,
        path_in_repo="pending_approvals.csv",
        repo_id=repo_id,
        repo_type="dataset",
        commit_message="🤖 Auto-queued 240 simulated interactions (CSV)"
    )
    print("✅ Successfully uploaded JSON and CSV! The UI should see the new pending items shortly.")

if __name__ == "__main__":
    main()