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backend_replicate.py
根目录 / skills / ppt-master / scripts / image_backends / backend_replicate.py
1 #!/usr/bin/env python3
2 """
3 Replicate image generation backend.
4
5 Configuration keys:
6 REPLICATE_API_KEY / REPLICATE_API_TOKEN (required)
7 REPLICATE_BASE_URL (optional)
8 REPLICATE_MODEL (optional; FLUX 1.1 Pro only)
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 replicate")
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 = ["1:1", "16:9", "9:16", "3:4", "4:3", "3:2", "2:3", "4:5", "5:4", "21:9"]
47 DEFAULT_BASE_URL = "https://api.replicate.com/v1"
48 DEFAULT_MODEL = "black-forest-labs/flux-1.1-pro"
49 SUPPORTED_MODELS = {DEFAULT_MODEL}
50
51
52 def _split_model(model: str) -> tuple[str, str]:
53 """Split a Replicate model reference into owner and name."""
54 parts = [part for part in model.strip().split("/") if part]
55 if len(parts) != 2:
56 raise ValueError(
57 f"Replicate model must be in 'owner/name' format, got '{model}'."
58 )
59 return parts[0], parts[1]
60
61
62 def _resolve_request_options(
63 aspect_ratio: str,
64 image_size: str,
65 model: str,
66 ) -> tuple[str, str]:
67 """Validate request options and return the Replicate model path."""
68 resolved_model = model.strip()
69 if resolved_model not in SUPPORTED_MODELS:
70 raise ValueError(
71 f"Unsupported Replicate model '{model}'. Supported: {sorted(SUPPORTED_MODELS)}"
72 )
73 if aspect_ratio not in VALID_ASPECT_RATIOS:
74 raise ValueError(
75 f"Unsupported aspect ratio '{aspect_ratio}' for Replicate backend. "
76 f"Supported: {VALID_ASPECT_RATIOS}"
77 )
78 normalized_size = normalize_image_size(image_size)
79 if normalized_size != "1K":
80 raise ValueError(
81 "Replicate FLUX 1.1 Pro does not expose the unified image_size preset; "
82 f"only the default '1K' is supported, got '{image_size}'."
83 )
84 return _split_model(resolved_model)
85
86
87 def _extract_output_url(payload: dict) -> str | None:
88 """Extract an output URL from a Replicate prediction payload."""
89 output = payload.get("output")
90 if isinstance(output, str):
91 return output
92 if isinstance(output, list) and output:
93 first = output[0]
94 if isinstance(first, str):
95 return first
96 if isinstance(first, dict):
97 return first.get("url")
98 if isinstance(output, dict):
99 return output.get("url")
100 return None
101
102
103 def _generate_image(api_key: str, prompt: str,
104 aspect_ratio: str = "1:1", image_size: str = "1K",
105 output_dir: str = None, filename: str = None,
106 model: str = DEFAULT_MODEL, base_url: str = DEFAULT_BASE_URL) -> str:
107 """Generate one image with the Replicate backend."""
108 owner, name = _resolve_request_options(aspect_ratio, image_size, model)
109 url = f"{base_url.rstrip('/')}/models/{owner}/{name}/predictions"
110 headers = {
111 "Authorization": f"Bearer {api_key}",
112 "Content-Type": "application/json",
113 "Prefer": "wait=60",
114 }
115
116 payload = {
117 "input": {
118 "prompt": prompt,
119 "aspect_ratio": aspect_ratio,
120 "output_format": "png",
121 }
122 }
123
124 print("[Replicate]")
125 print(f" Model: {model}")
126 print(f" Prompt: {prompt[:120]}{'...' if len(prompt) > 120 else ''}")
127 print(f" Aspect Ratio: {aspect_ratio}")
128 print()
129 print(" [..] Generating...", end="", flush=True)
130 start = time.time()
131 response = requests.post(url, headers=headers, json=payload, timeout=180)
132 elapsed = time.time() - start
133 print(f"\n [DONE] Initial response received ({elapsed:.1f}s)")
134
135 if response.status_code not in (200, 201):
136 raise http_error(response, "Replicate generation request")
137
138 data = response.json()
139 status = str(data.get("status", "")).lower()
140 if status != "succeeded":
141 poll_url = ((data.get("urls") or {}).get("get"))
142 if not poll_url:
143 prediction_id = data.get("id")
144 if prediction_id:
145 poll_url = f"{base_url.rstrip('/')}/predictions/{prediction_id}"
146 if not poll_url:
147 raise RuntimeError(f"Replicate response missing poll URL: {data}")
148
149 print(" [..] Polling result...")
150 data = poll_json(
151 poll_url,
152 {"Authorization": f"Bearer {api_key}"},
153 status_label="status",
154 ready_values=["succeeded"],
155 failed_values=["failed", "canceled"],
156 )
157
158 image_url = _extract_output_url(data)
159 if not image_url:
160 raise RuntimeError(f"Replicate response missing output URL: {data}")
161
162 path = resolve_output_path(prompt, output_dir, filename, ".png")
163 return download_image(image_url, path)
164
165
166 def generate(prompt: str,
167 aspect_ratio: str = "1:1", image_size: str = "1K",
168 output_dir: str = None, filename: str = None,
169 model: str = None, max_retries: int = MAX_RETRIES) -> str:
170 """Generate an image with retries using the Replicate backend."""
171 resolved_model = model or os.environ.get("REPLICATE_MODEL") or DEFAULT_MODEL
172 _resolve_request_options(aspect_ratio, image_size, resolved_model)
173 api_key = require_api_key(
174 "REPLICATE_API_KEY",
175 "REPLICATE_API_TOKEN",
176 message="No API key found. Set REPLICATE_API_KEY or REPLICATE_API_TOKEN in the current environment or a .env file.",
177 )
178 base_url = os.environ.get("REPLICATE_BASE_URL") or DEFAULT_BASE_URL
179
180 last_error = None
181 for attempt in range(max_retries + 1):
182 try:
183 return _generate_image(
184 api_key=api_key,
185 prompt=prompt,
186 aspect_ratio=aspect_ratio,
187 image_size=image_size,
188 output_dir=output_dir,
189 filename=filename,
190 model=resolved_model,
191 base_url=base_url,
192 )
193 except Exception as exc:
194 last_error = exc
195 if is_permanent_error(exc):
196 raise
197 if attempt >= max_retries:
198 break
199 limited = is_rate_limit_error(exc)
200 delay = retry_delay(attempt, rate_limited=limited)
201 label = "Rate limit hit" if limited else f"Error: {exc}"
202 print(f"\n [WARN] {label}. Retrying in {delay}s...")
203 time.sleep(delay)
204
205 raise RuntimeError(f"Failed after {max_retries + 1} attempts. Last error: {last_error}")
206
206 lines PYTHON