import os
import openai
from openai import OpenAI
import base64
from tqdm import tqdm
import time
import json
from pathlib import Path
from threading import Lock
from typing import Any


_json_write_lock = Lock()

def save_json_file(
    data: Any,
    file_path: str,
    indent: int = 4,
    temp_suffix: str = ".tmp"
) -> None:
    """

    """
    path = Path(file_path)
    path.parent.mkdir(parents=True, exist_ok=True)

    temp_path = f"{file_path}{temp_suffix}"

    with _json_write_lock:
        try:

            with open(temp_path, "w", encoding="utf-8") as f:
                json.dump(data, f, ensure_ascii=False, indent=indent)


                f.flush()
                os.fsync(f.fileno())


            os.replace(temp_path, file_path)

        except Exception as e:
            # 出错则删除临时文件
            try:
                if os.path.exists(temp_path):
                    os.remove(temp_path)
            except OSError:
                pass
            raise RuntimeError(f"save json failed: {e}") from e

def read_json_file(file_path):
    """
    Reads a JSON file and returns the parsed data as a Python object.

    :param file_path: The path to the JSON file
    :return: The data parsed from the JSON file
    """
    with open(file_path, 'r', encoding='utf-8') as f:
        data = json.load(f)
    return data

def encode_image(image_path):
    with open(image_path, "rb") as image_file:
        return base64.standard_b64encode(image_file.read()).decode("utf-8")

def merge_json_lists(folder_path):
    """
    """

    json_list = [
        os.path.join(folder_path, f)
        for f in os.listdir(folder_path)
        if f.lower().endswith('.json') and os.path.isfile(os.path.join(folder_path, f))
    ]

    merged_list = []

    for file_path in json_list:
        try:
            with open(file_path, 'r', encoding='utf-8') as f:
                data = json.load(f)
                if isinstance(data, list):
                    merged_list.extend(data)
                else:
                    print(f"waring: {file_path} is not list. skipped")
        except Exception as e:
            print(f"processing {file_path} error: {str(e)}")

    return merged_list


def openai_api(image_path, prompt = None):
    if prompt == None:
        prompt = "What's in this image?"

    base64_image = encode_image(image_path)
    client = OpenAI(
        base_url='your_url',
        api_key='your_key'
    )
    response = client.chat.completions.create(
        model="claude-3-7-sonnet-20250219",
        messages=[
            {
                "role": "user",
                "content": [
                    {"type": "text", "text": prompt},
                    {
                        "type": "image_url",
                        "image_url": {
                             "url": f"data:image/jpeg;base64,{base64_image}"
                        }
                    },
                ],
            }
        ],
        max_tokens=5000,
    )

    return response

if __name__ == "__main__":
    folder_path = r"your_path/poster/data"
    save_dir = r"your_path/poster/result"

    saved_josn = os.path.join(save_dir,"result.json")
    if not os.path.exists(saved_josn):
        tasks = merge_json_lists(folder_path)
        save_json_file(tasks, saved_josn)

    tasks = read_json_file(saved_josn)
    max_retries = 4
    retry_wait = 10
    for item in tqdm(tasks):
        if "response" in item: continue

        prompt = item["prompt"]
        image_path = os.path.join(folder_path, item["path"])
        for attempt in range(max_retries):
            try:
                response = openai_api(image_path, prompt)
                item["response"] = response.choices[0].message.content
                print(item["response"])
                save_json_file(tasks, saved_josn)
                break  
            except Exception as e:
                print(f"[Warning] Request failed: {e}")
                if attempt < max_retries - 1:
                    print(f"Retrying in {retry_wait} seconds... (attempt {attempt + 1})")
                    time.sleep(retry_wait)
                else:
                    print("[Error] Reached max retries. Skipping this item.")
                    item["error"] = str(e)