calvana/scripts/generate-fidya-images.py

#!/usr/bin/env python3
"""
Generate on-brand photography for the Charity Right Fidya/Kaffarah page
using Gemini Nano Banana Pro (Gemini 3 Pro Image Preview).

Brand style reference (from Ramadan homepage):
- Documentary/photojournalistic style
- Warm earth tones (sandy, ochre, warm brown palette)
- Natural golden hour lighting
- Shallow depth of field (subject sharp, background softly blurred)
- Dignified portraits of people in need (children, elderly, families)
- High quality, professional look
- Wide aspect ratio (~16:9)
"""

import os
import json
import base64
import sys
import time
from pathlib import Path

# Load from .env
from dotenv import load_dotenv
load_dotenv()

API_KEY = os.getenv("GEMINI_API_KEY")
MODEL = os.getenv("GEMINI_IMAGE_MODEL", "nano-banana-pro-preview")

if not API_KEY:
    print("ERROR: GEMINI_API_KEY not set in .env")
    sys.exit(1)

print(f"Using model: {MODEL}")
print(f"API Key: {API_KEY[:10]}...")

import requests

OUTPUT_DIR = Path("screenshots/fidya-kaffarah")
OUTPUT_DIR.mkdir(parents=True, exist_ok=True)

# Image prompts designed to match the CR brand photography style for fidya/kaffarah context
PROMPTS = [
    {
        "name": "fidya-hero",
        "prompt": (
            "Documentary photography, wide shot. An elderly South Asian grandmother "
            "sitting peacefully in a modest home, warm golden hour light streaming through "
            "a window, she has gentle wrinkles and wise eyes, wearing a simple white cotton "
            "dupatta over her head. A plate of simple food (rice and lentils) sits beside her. "
            "Warm earth tones, shallow depth of field, photojournalistic style, "
            "shot on 85mm lens, natural lighting. Dignified and compassionate mood. "
            "16:9 aspect ratio, high resolution professional photograph."
        )
    },
    {
        "name": "fidya-feeding",
        "prompt": (
            "Documentary photography. A warm scene of food being served to people in need "
            "at a community feeding program in rural Bangladesh. Focus on hands gently "
            "placing a plate of rice and curry in front of a grateful elderly person. "
            "Golden warm lighting, earth tones, shallow depth of field with other people "
            "softly blurred in background. Photojournalistic style, authentic, dignified. "
            "Shot on 50mm lens, natural light. 16:9 aspect ratio, professional photograph."
        )
    },
    {
        "name": "kaffarah-community",
        "prompt": (
            "Documentary photography. A community meal distribution scene in a rural village. "
            "Several children and elderly people receiving meals from volunteers. "
            "The scene is outdoors with dusty earth ground and simple structures in background. "
            "Warm golden hour sunlight, rich earth tones (ochre, sand, brown). "
            "Focus on a child holding a bowl of food, looking up with hopeful eyes. "
            "Shallow depth of field, photojournalistic authenticity. "
            "Shot on 35mm lens. 16:9 aspect ratio, professional photograph."
        )
    },
    {
        "name": "fidya-quran-elder",
        "prompt": (
            "Documentary photography, intimate portrait. An elderly Muslim man with a white beard "
            "and simple prayer cap, sitting cross-legged on the floor in a humble room, "
            "holding prayer beads (tasbih). Soft warm natural light from a side window "
            "illuminating his weathered, peaceful face. Warm earth tone palette, "
            "shallow depth of field, background is a simple mud-colored wall. "
            "Dignified, contemplative, spiritual mood. Shot on 85mm lens. "
            "16:9 aspect ratio, high resolution professional photograph."
        )
    },
    {
        "name": "fidya-child-meal",
        "prompt": (
            "Documentary photography. A young child in South Asia or East Africa, "
            "around 6-8 years old, sitting at a simple wooden table eating a plate of food "
            "(rice and vegetables). The child has a subtle, content smile. "
            "Warm golden natural light, earth tones (sandy, ochre), background is softly "
            "blurred showing a simple classroom or community center. "
            "Shallow depth of field, photojournalistic style. Dignified, hopeful. "
            "Shot on 50mm lens. 16:9 aspect ratio, professional photograph."
        )
    },
]


def generate_image(prompt_data):
    """Generate an image using Gemini Nano Banana Pro."""
    name = prompt_data["name"]
    prompt = prompt_data["prompt"]
    
    url = f"https://generativelanguage.googleapis.com/v1beta/models/{MODEL}:generateContent?key={API_KEY}"
    
    payload = {
        "contents": [
            {
                "parts": [
                    {"text": prompt}
                ]
            }
        ],
        "generationConfig": {
            "responseModalities": ["TEXT", "IMAGE"],
            "temperature": 1.0,
        }
    }
    
    headers = {"Content-Type": "application/json"}
    
    print(f"\n[*] Generating: {name}")
    print(f"   Prompt: {prompt[:80]}...")
    
    try:
        response = requests.post(url, json=payload, headers=headers, timeout=120)
        
        if response.status_code != 200:
            print(f"   [ERR] Error {response.status_code}: {response.text[:300]}")
            return None
        
        data = response.json()
        
        # Extract image from response
        candidates = data.get("candidates", [])
        if not candidates:
            print(f"   [ERR] No candidates in response")
            print(f"   Response: {json.dumps(data, indent=2)[:500]}")
            return None
        
        parts = candidates[0].get("content", {}).get("parts", [])
        
        for part in parts:
            if "inlineData" in part:
                image_data = part["inlineData"]
                mime_type = image_data.get("mimeType", "image/png")
                b64_data = image_data["data"]
                
                # Determine extension
                ext = "png" if "png" in mime_type else "jpg"
                output_path = OUTPUT_DIR / f"{name}.{ext}"
                
                # Decode and save
                img_bytes = base64.b64decode(b64_data)
                output_path.write_bytes(img_bytes)
                
                size_kb = len(img_bytes) / 1024
                print(f"   [OK] Saved: {output_path} ({size_kb:.0f} KB)")
                return str(output_path)
        
        # If we get here, no image was found
        print(f"   [ERR] No image in response parts")
        for part in parts:
            if "text" in part:
                print(f"   Text response: {part['text'][:200]}")
        return None
        
    except Exception as e:
        print(f"   [ERR] Exception: {e}")
        return None


def main():
    print("=" * 60)
    print("Charity Right — Fidya/Kaffarah Photography Generator")
    print(f"Model: {MODEL}")
    print("=" * 60)
    
    results = []
    for i, prompt_data in enumerate(PROMPTS):
        result = generate_image(prompt_data)
        results.append((prompt_data["name"], result))
        
        # Small delay between requests to avoid rate limiting
        if i < len(PROMPTS) - 1:
            print("   ... Waiting 3s before next generation...")
            time.sleep(3)
    
    print("\n" + "=" * 60)
    print("RESULTS SUMMARY")
    print("=" * 60)
    for name, path in results:
        status = f"[OK] {path}" if path else "[FAIL] Failed"
        print(f"  {name}: {status}")
    
    successful = sum(1 for _, p in results if p)
    print(f"\n  {successful}/{len(results)} images generated successfully")


if __name__ == "__main__":
    main()