#!/usr/bin/env python3 """ Free Image Generation Tool Uses Hugging Face Free Inference API (no auth required for public models) to generate images via CLI. Falls back to Pollinations.ai if HF fails. """ import argparse import hashlib import json import os import sys import urllib.request import urllib.parse import urllib.error from pathlib import Path # Hugging Face free inference endpoint (public models, no auth needed) HF_INFERENCE_URL = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0" def generate_image_hf(prompt: str, output_dir: str = None) -> dict: """ Generate image using Hugging Face Inference API (free tier). Uses stabilityai/stable-diffusion-xl-base-1.0 model. """ if output_dir is None: output_dir = os.getcwd() output_path = Path(output_dir) output_path.mkdir(parents=True, exist_ok=True) prompt_hash = hashlib.md5(prompt.encode()).hexdigest()[:8] filename = f"hf_{prompt_hash}.png" file_path = output_path / filename # Hugging Face expects JSON payload payload = json.dumps({ "inputs": prompt, "parameters": { "negative_prompt": "blurry, low quality, distorted", "guidance_scale": 7.5, "num_inference_steps": 30 } }).encode('utf-8') req = urllib.request.Request( HF_INFERENCE_URL, data=payload, headers={ "Content-Type": "application/json", "Authorization": "Bearer hf_", # Empty token for public models "x-wait-for-model": "true" # Wait for model to load if cold } ) try: with urllib.request.urlopen(req, timeout=300) as response: if response.status != 200: raise Exception(f"API returned status {response.status}") # HF returns image binary data image_data = response.read() if len(image_data) < 100: raise Exception("Response too small - likely error") with open(file_path, 'wb') as f: f.write(image_data) file_size = file_path.stat().st_size return { "file_path": str(file_path.absolute()), "model": "stabilityai/stable-diffusion-xl-base-1.0", "prompt": prompt, "file_size_bytes": file_size, "provider": "huggingface" } except urllib.error.HTTPError as e: if e.code == 401: raise Exception("Hugging Face API requires authentication for this model") elif e.code == 503: raise Exception("Model is loading - try again in a moment") raise Exception(f"HTTP error {e.code}: {e.reason}") except urllib.error.URLError as e: raise Exception(f"Network error: {e.reason}") except Exception as e: raise Exception(f"HF generation failed: {str(e)}") def generate_image_pollinations(prompt: str, width: int = 1024, height: int = 1024, output_dir: str = None) -> dict: """ Generate image using Pollinations.ai free API. """ if output_dir is None: output_dir = os.getcwd() output_path = Path(output_dir) output_path.mkdir(parents=True, exist_ok=True) prompt_hash = hashlib.md5(prompt.encode()).hexdigest()[:8] filename = f"pollinations_{prompt_hash}.png" file_path = output_path / filename # Build URL - Pollinations expects prompt in URL path encoded_prompt = urllib.parse.quote(prompt) api_url = f"https://image.pollinations.ai/prompt/{encoded_prompt}" # Add query params params = urllib.parse.urlencode({ "width": width, "height": height, "nologo": "true", "nofeed": "true", "seed": "random" }) api_url = f"{api_url}?{params}" try: req = urllib.request.Request(api_url) req.add_header('User-Agent', 'FreeImageGen/1.0') with urllib.request.urlopen(req, timeout=60) as response: if response.status != 200: raise Exception(f"API returned status {response.status}") image_data = response.read() if len(image_data) < 100: raise Exception("Response too small") # Check if it's actually an image (PNG starts with PNG signature) if image_data[:8] != b'\x89PNG\r\n\x1a\n': # Might be JSON error try: error = json.loads(image_data.decode('utf-8')) raise Exception(f"API error: {error.get('error', 'Unknown')}") except: raise Exception("Response is not a valid image") with open(file_path, 'wb') as f: f.write(image_data) file_size = file_path.stat().st_size return { "file_path": str(file_path.absolute()), "model": "pollinations.ai", "prompt": prompt, "width": width, "height": height, "file_size_bytes": file_size, "provider": "pollinations" } except urllib.error.HTTPError as e: raise Exception(f"HTTP error {e.code}: {e.reason}") except urllib.error.URLError as e: raise Exception(f"Network error: {e.reason}") except Exception as e: raise Exception(f"Pollinations generation failed: {str(e)}") def generate_image(prompt: str, width: int = 1024, height: int = 1024, output_dir: str = None, prefer: str = "hf") -> dict: """ Generate an image using free APIs. Tries Hugging Face first (higher quality), then falls back to Pollinations. Args: prompt: The image generation prompt width: Image width (for Pollinations fallback) height: Image height (for Pollinations fallback) output_dir: Directory to save the image prefer: "hf" or "pollinations" Returns: JSON dict with file_path, model, and prompt """ if prefer == "pollinations": return generate_image_pollinations(prompt, width, height, output_dir) # Try Hugging Face first try: result = generate_image_hf(prompt, output_dir) print(f"# Using Hugging Face: stabilityai/stable-diffusion-xl-base-1.0", file=sys.stderr) return result except Exception as e: print(f"# HF failed: {e}. Falling back to Pollinations...", file=sys.stderr) # Fall back to Pollinations try: result = generate_image_pollinations(prompt, width, height, output_dir) print(f"# Using Pollinations.ai", file=sys.stderr) return result except Exception as e: raise Exception(f"All free APIs failed: {str(e)}") def main(): parser = argparse.ArgumentParser( description="Generate images using free APIs (Hugging Face or Pollinations.ai)" ) parser.add_argument("--prompt", type=str, required=True, help="Image generation prompt") parser.add_argument("--width", type=int, default=1024, help="Image width (Pollinations)") parser.add_argument("--height", type=int, default=1024, help="Image height (Pollinations)") parser.add_argument("--output_dir", type=str, default=None, help="Output directory") parser.add_argument("--prefer", type=str, choices=["hf", "pollinations"], default="hf", help="Preferred API: hf (default) or pollinations") args = parser.parse_args() try: result = generate_image( prompt=args.prompt, width=args.width, height=args.height, output_dir=args.output_dir, prefer=args.prefer ) print(json.dumps(result, indent=2)) except Exception as e: print(json.dumps({"error": str(e), "provider": "none"}, indent=2)) sys.exit(1) if __name__ == "__main__": main()