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import os
import json
import google.generativeai as genai
from dotenv import load_dotenv
load_dotenv()
class VisualAnalyst:
def __init__(self):
self.api_key = os.getenv("GEMINI_API_KEY")
if not self.api_key:
raise ValueError("GEMINI_API_KEY not found")
genai.configure(api_key=self.api_key)
self.model_name = "models/gemini-flash-latest"
self.model = genai.GenerativeModel(self.model_name)
print(f"✅ VisualAnalyst stored Gemini model: {self.model_name}")
async def analyze_image(self, image_path: str):
try:
# Upload the file to Gemini
# Note: For efficiency in production, files should be managed (uploads/deletes)
# but for this agentic flow, we'll upload per request or assume local path usage helper if needed.
# However, the standard `model.generate_content` can take PIL images or file objects directly for some sdk versions,
# but using the File API is cleaner for 1.5 Flash multi-modal.
# Let's use the simpler PIL integration if available, or just path if the SDK supports it.
# actually, standard genai usage for images usually involves PIL or uploading.
# Let's try the PIL approach first as it's often more direct for local scripts.
import PIL.Image
img = PIL.Image.open(image_path)
user_prompt = (
"Analyze this product image. "
"Return ONLY valid JSON with keys: main_color, product_type, design_style, visual_features."
)
# Gemini 1.5 Flash supports JSON response schema, but simple prompting often works well too.
# We'll stick to prompt engineering for now to match the "Return ONLY valid JSON" instruction.
response = self.model.generate_content([user_prompt, img])
response_text = response.text
# Clean up potential markdown code fences
cleaned_content = response_text
if "```json" in cleaned_content:
cleaned_content = cleaned_content.replace("```json", "").replace("```", "")
elif "```" in cleaned_content:
cleaned_content = cleaned_content.replace("```", "")
return json.loads(cleaned_content.strip())
except Exception as e:
print(f"❌ Analysis Failed: {e}")
return {
"main_color": "Unknown",
"product_type": "Unknown",
"design_style": "Unknown",
"visual_features": [f"Error: {str(e)}"]
}
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