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# import logging
# from PIL import Image
# from io import BytesIO
# import requests, os, json, time
# from google import genai
# prompt_base_path = "src/llm_wrapper/prompt"
# client = genai.Client(api_key=os.getenv("GEMINI_API_KEY"))
# def encode_image(image_source):
# """
# ์ด๋ฏธ์ง ๊ฒฝ๋ก๊ฐ URL์ด๋ ๋ก์ปฌ ํ์ผ์ด๋ Pillow Image ๊ฐ์ฒด์ด๋ ๋์ผํ๊ฒ ์ฒ๋ฆฌํ๋ ํจ์.
# ์ด๋ฏธ์ง๋ฅผ ์ด์ด google.genai.types.Part ๊ฐ์ฒด๋ก ๋ณํํฉ๋๋ค.
# Pillow์์ ์ง์๋์ง ์๋ ํฌ๋งท์ ๋ํด์๋ ์์ธ๋ฅผ ๋ฐ์์ํต๋๋ค.
# """
# try:
# # ์ด๋ฏธ Pillow ์ด๋ฏธ์ง ๊ฐ์ฒด์ธ ๊ฒฝ์ฐ ๊ทธ๋๋ก ์ฌ์ฉ
# if isinstance(image_source, Image.Image):
# image = image_source
# else:
# # URL์์ ์ด๋ฏธ์ง ๋ค์ด๋ก๋
# if isinstance(image_source, str) and (
# image_source.startswith("http://")
# or image_source.startswith("https://")
# ):
# response = requests.get(image_source)
# image = Image.open(BytesIO(response.content))
# # ๋ก์ปฌ ํ์ผ์์ ์ด๋ฏธ์ง ์ด๊ธฐ
# else:
# image = Image.open(image_source)
# # ์ด๋ฏธ์ง ํฌ๋งท์ด None์ธ ๊ฒฝ์ฐ (๋ฉ๋ชจ๋ฆฌ์์ ์์ฑ๋ ์ด๋ฏธ์ง ๋ฑ)
# if image.format is None:
# image_format = "JPEG"
# else:
# image_format = image.format
# # ์ด๋ฏธ์ง ํฌ๋งท์ด ์ง์๋์ง ์๋ ๊ฒฝ์ฐ ์์ธ ๋ฐ์
# if image_format not in Image.registered_extensions().values():
# raise ValueError(f"Unsupported image format: {image_format}.")
# buffered = BytesIO()
# # PIL์์ ์ง์๋์ง ์๋ ํฌ๋งท์ด๋ ๋ค์ํ ์ฑ๋์ RGB๋ก ๋ณํ ํ ์ ์ฅ
# if image.mode in ("RGBA", "P", "CMYK"): # RGBA, ํ๋ ํธ, CMYK ๋ฑ์ RGB๋ก ๋ณํ
# image = image.convert("RGB")
# image.save(buffered, format="JPEG")
# return genai.types.Part.from_bytes(data=buffered.getvalue(), mime_type="image/jpeg")
# except requests.exceptions.RequestException as e:
# raise ValueError(f"Failed to download the image from URL: {e}")
# except IOError as e:
# raise ValueError(f"Failed to process the image file: {e}")
# except ValueError as e:
# raise ValueError(e)
# def run_gemini(
# target_prompt: str,
# prompt_in_path: str,
# img_in_data: str = None,
# model: str = "gemini-2.0-flash",
# ) -> str:
# """
# GEMINI API๋ฅผ ๋๊ธฐ ๋ฐฉ์์ผ๋ก ํธ์ถํ์ฌ ๋ฌธ์์ด ์๋ต์ ๋ฐ์ต๋๋ค.
# retry ๋
ผ๋ฆฌ๋ ์ ๊ฑฐ๋์์ต๋๋ค.
# """
# with open(os.path.join(prompt_base_path, prompt_in_path), "r", encoding="utf-8") as file:
# prompt_dict = json.load(file)
# system_prompt = prompt_dict["system_prompt"]
# user_prompt_head = prompt_dict["user_prompt"]["head"]
# user_prompt_tail = prompt_dict["user_prompt"]["tail"]
# user_prompt_text = "\n".join([user_prompt_head, target_prompt, user_prompt_tail])
# input_content = [user_prompt_text]
# if img_in_data is not None:
# encoded_image = encode_image(img_in_data)
# input_content.append(encoded_image)
# logging.info("Requested API for chat completion response (sync call)...")
# start_time = time.time()
# # ๋๊ธฐ ๋ฐฉ์: client.models.generate_content(...)
# chat_completion = client.models.generate_content(
# model=model,
# contents=input_content,
# )
# chat_output = chat_completion.parsed
# input_token = chat_completion.usage_metadata.prompt_token_count
# output_token = chat_completion.usage_metadata.candidates_token_count
# pricing = input_token / 1000000 * 0.1 * 1500 + output_token / 1000000 * 0.7 * 1500
# logging.info(
# f"[GEMINI] Request completed (sync). Time taken: {time.time()-start_time:.2f}s / Pricing(KRW): {pricing:.2f}"
# )
# return chat_output, chat_completion
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