| 1 | #!/usr/bin/env python3 |
| 2 | """ |
| 3 | Black Forest Labs FLUX image generation backend. |
| 4 | |
| 5 | Configuration keys: |
| 6 | BFL_API_KEY (required) |
| 7 | BFL_BASE_URL (optional) |
| 8 | BFL_MODEL (optional) |
| 9 | """ |
| 10 | |
| 11 | import sys |
| 12 | from pathlib import Path |
| 13 | |
| 14 | _SCRIPTS_DIR = Path(__file__).resolve().parents[1] |
| 15 | if str(_SCRIPTS_DIR) not in sys.path: |
| 16 | sys.path.insert(0, str(_SCRIPTS_DIR)) |
| 17 | |
| 18 | from console_encoding import configure_utf8_stdio # noqa: E402 |
| 19 | |
| 20 | configure_utf8_stdio() |
| 21 | |
| 22 | if __name__ == "__main__": |
| 23 | print(__doc__) |
| 24 | print("Use via: python3 skills/ppt-master/scripts/image_gen.py \"prompt\" --backend bfl") |
| 25 | raise SystemExit(0 if any(arg in {"-h", "--help", "help"} for arg in sys.argv[1:]) else 1) |
| 26 | |
| 27 | import os |
| 28 | import time |
| 29 | |
| 30 | import requests |
| 31 | |
| 32 | from image_backends.backend_common import ( |
| 33 | MAX_RETRIES, |
| 34 | download_image, |
| 35 | http_error, |
| 36 | is_permanent_error, |
| 37 | is_rate_limit_error, |
| 38 | normalize_image_size, |
| 39 | poll_json, |
| 40 | require_api_key, |
| 41 | resolve_output_path, |
| 42 | retry_delay, |
| 43 | ) |
| 44 | |
| 45 | |
| 46 | VALID_ASPECT_RATIOS = [ |
| 47 | "1:1", "2:3", "3:2", "3:4", "4:3", |
| 48 | "4:5", "5:4", "9:16", "16:9", "21:9", |
| 49 | ] |
| 50 | |
| 51 | DEFAULT_BASE_URL = "https://api.bfl.ai" |
| 52 | DEFAULT_MODEL = "flux-pro-1.1-ultra" |
| 53 | |
| 54 | MODEL_ENDPOINTS = { |
| 55 | "flux-pro-1.1": "/v1/flux-pro-1.1", |
| 56 | "flux-pro-1.1-ultra": "/v1/flux-pro-1.1-ultra", |
| 57 | "flux-dev": "/v1/flux-dev", |
| 58 | } |
| 59 | |
| 60 | ASPECT_RATIO_TO_DIMENSIONS = { |
| 61 | "1:1": (1024, 1024), |
| 62 | "2:3": (960, 1440), |
| 63 | "3:2": (1440, 960), |
| 64 | "3:4": (1056, 1408), |
| 65 | "4:3": (1408, 1056), |
| 66 | "4:5": (1024, 1280), |
| 67 | "5:4": (1280, 1024), |
| 68 | "9:16": (576, 1024), |
| 69 | "16:9": (1024, 576), |
| 70 | "21:9": (1344, 576), |
| 71 | } |
| 72 | |
| 73 | |
| 74 | def _resolve_request_options( |
| 75 | aspect_ratio: str, |
| 76 | image_size: str, |
| 77 | model: str, |
| 78 | ) -> tuple[str, str]: |
| 79 | """Validate request options and return the normalized model and endpoint.""" |
| 80 | if aspect_ratio not in VALID_ASPECT_RATIOS: |
| 81 | raise ValueError( |
| 82 | f"Unsupported aspect ratio '{aspect_ratio}' for BFL backend. " |
| 83 | f"Supported: {VALID_ASPECT_RATIOS}" |
| 84 | ) |
| 85 | normalized_model = model.strip().lower() |
| 86 | endpoint = MODEL_ENDPOINTS.get(normalized_model) |
| 87 | if not endpoint: |
| 88 | supported = sorted(MODEL_ENDPOINTS) |
| 89 | raise ValueError(f"Unsupported BFL model '{model}'. Supported: {supported}") |
| 90 | normalized_size = normalize_image_size(image_size) |
| 91 | if normalized_size != "1K": |
| 92 | raise ValueError( |
| 93 | f"BFL model '{normalized_model}' does not expose the unified image_size preset; " |
| 94 | f"only the default '1K' is supported, got '{image_size}'." |
| 95 | ) |
| 96 | return normalized_model, endpoint |
| 97 | |
| 98 | |
| 99 | def _submit_request(url: str, headers: dict, payload: dict) -> dict: |
| 100 | """Submit a BFL generation request and return the JSON response.""" |
| 101 | response = requests.post(url, headers=headers, json=payload, timeout=180) |
| 102 | if response.status_code != 200: |
| 103 | raise http_error(response, "BFL generation request") |
| 104 | return response.json() |
| 105 | |
| 106 | |
| 107 | def _generate_image(api_key: str, prompt: str, |
| 108 | aspect_ratio: str = "1:1", image_size: str = "1K", |
| 109 | output_dir: str = None, filename: str = None, |
| 110 | model: str = DEFAULT_MODEL, base_url: str = DEFAULT_BASE_URL) -> str: |
| 111 | """Generate one image with the Black Forest Labs backend.""" |
| 112 | normalized_model, endpoint = _resolve_request_options( |
| 113 | aspect_ratio, |
| 114 | image_size, |
| 115 | model, |
| 116 | ) |
| 117 | |
| 118 | headers = { |
| 119 | "x-key": api_key, |
| 120 | "accept": "application/json", |
| 121 | "Content-Type": "application/json", |
| 122 | } |
| 123 | |
| 124 | payload = { |
| 125 | "prompt": prompt, |
| 126 | "prompt_upsampling": False, |
| 127 | "output_format": "png", |
| 128 | } |
| 129 | |
| 130 | if normalized_model.endswith("-ultra"): |
| 131 | payload["aspect_ratio"] = aspect_ratio |
| 132 | payload["raw"] = False |
| 133 | else: |
| 134 | width, height = ASPECT_RATIO_TO_DIMENSIONS[aspect_ratio] |
| 135 | payload["width"] = width |
| 136 | payload["height"] = height |
| 137 | |
| 138 | url = base_url.rstrip("/") + endpoint |
| 139 | |
| 140 | print("[Black Forest Labs]") |
| 141 | print(f" Model: {normalized_model}") |
| 142 | print(f" Prompt: {prompt[:120]}{'...' if len(prompt) > 120 else ''}") |
| 143 | print(f" Aspect Ratio: {aspect_ratio}") |
| 144 | print() |
| 145 | print(" [..] Submitting request...", end="", flush=True) |
| 146 | start = time.time() |
| 147 | request_payload = _submit_request(url, headers, payload) |
| 148 | elapsed = time.time() - start |
| 149 | print(f"\n [DONE] Request accepted ({elapsed:.1f}s)") |
| 150 | |
| 151 | polling_url = request_payload.get("polling_url") |
| 152 | if not polling_url: |
| 153 | raise RuntimeError(f"BFL response missing polling_url: {request_payload}") |
| 154 | |
| 155 | print(" [..] Polling result...") |
| 156 | result_payload = poll_json( |
| 157 | polling_url, |
| 158 | {"x-key": api_key, "accept": "application/json"}, |
| 159 | status_label="status", |
| 160 | ready_values=["Ready"], |
| 161 | failed_values=[ |
| 162 | "Error", |
| 163 | "Failed", |
| 164 | "Task not found", |
| 165 | "Request Moderated", |
| 166 | "Content Moderated", |
| 167 | ], |
| 168 | ) |
| 169 | |
| 170 | image_url = ((result_payload.get("result") or {}).get("sample")) |
| 171 | if not image_url: |
| 172 | raise RuntimeError(f"BFL result missing sample URL: {result_payload}") |
| 173 | |
| 174 | path = resolve_output_path(prompt, output_dir, filename, ".png") |
| 175 | return download_image(image_url, path) |
| 176 | |
| 177 | |
| 178 | def generate(prompt: str, |
| 179 | aspect_ratio: str = "1:1", image_size: str = "1K", |
| 180 | output_dir: str = None, filename: str = None, |
| 181 | model: str = None, max_retries: int = MAX_RETRIES) -> str: |
| 182 | """Generate an image with retries using the BFL backend.""" |
| 183 | resolved_model = model or os.environ.get("BFL_MODEL") or DEFAULT_MODEL |
| 184 | _resolve_request_options(aspect_ratio, image_size, resolved_model) |
| 185 | api_key = require_api_key( |
| 186 | "BFL_API_KEY", |
| 187 | message="No API key found. Set BFL_API_KEY in the current environment or a .env file.", |
| 188 | ) |
| 189 | base_url = os.environ.get("BFL_BASE_URL") or DEFAULT_BASE_URL |
| 190 | |
| 191 | last_error = None |
| 192 | for attempt in range(max_retries + 1): |
| 193 | try: |
| 194 | return _generate_image( |
| 195 | api_key=api_key, |
| 196 | prompt=prompt, |
| 197 | aspect_ratio=aspect_ratio, |
| 198 | image_size=image_size, |
| 199 | output_dir=output_dir, |
| 200 | filename=filename, |
| 201 | model=resolved_model, |
| 202 | base_url=base_url, |
| 203 | ) |
| 204 | except Exception as exc: |
| 205 | last_error = exc |
| 206 | if is_permanent_error(exc): |
| 207 | raise |
| 208 | if attempt >= max_retries: |
| 209 | break |
| 210 | limited = is_rate_limit_error(exc) |
| 211 | delay = retry_delay(attempt, rate_limited=limited) |
| 212 | label = "Rate limit hit" if limited else f"Error: {exc}" |
| 213 | print(f"\n [WARN] {label}. Retrying in {delay}s...") |
| 214 | time.sleep(delay) |
| 215 | |
| 216 | raise RuntimeError(f"Failed after {max_retries + 1} attempts. Last error: {last_error}") |
| 217 |