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e23172f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 | #!/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() |