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import os
import time
from typing import TYPE_CHECKING
from PIL import Image
from logging_helper import log as _log, log_debug as _log_debug, _log_model_response
from common import MODELS_MAP
try:
# New google-genai client library
from google import genai
except ImportError: # pragma: no cover
genai = None # type: ignore
if TYPE_CHECKING: # pragma: no cover
# Kept for type-checkers; Image is also imported at runtime above
from PIL import Image as _ImageType
def _run_gemini_vision(image: Image.Image, prompt: str, model_choice: str) -> str:
if genai is None:
raise RuntimeError("google-genai package is not installed. Please install it to use Gemini backend.")
api_key = os.getenv("GEMINI_API_KEY")
if not api_key:
raise RuntimeError("GEMINI_API_KEY environment variable is not set.")
model_name = model_choice
# Instantiate the google-genai client and call the model
client = genai.Client(api_key=api_key)
_log_debug(f"Using Gemini model: {model_name}")
_log_debug(f"Input image size: {image.size}")
start_time = time.perf_counter()
# google-genai accepts mixed text and image content
response = client.models.generate_content(
model=model_name,
contents=[prompt, image],
)
duration = time.perf_counter() - start_time
print(f"Response: {response}")
print(f"Response text: {getattr(response, 'text', 'No text attribute')}")
content = response.text or ""
usage = getattr(response, "usage_metadata", None)
if usage is None:
usage = getattr(response, "usage", None)
_log_model_response(
model_name=model_name,
content=content,
duration=duration,
usage=usage,
pricing=MODELS_MAP,
)
return content
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