ai: publish tooling + real model hashes in the bundled catalog

publish_ai_models.py produces the CDN artifacts for every AI_MODELS
entry — GPG-signed .meta4 sidecars (reusing the map trust chain) and
the signed ai/models.json manifest — and uploads them with s3cmd.
The bundled catalog now carries the real sha256/size of the two Qwen
GGUFs, which match Hugging Face's LFS records for the Apache 2.0
unsloth quants, and whose signed meta4s verify against the committed
public key.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

modules/ai/catalog.py

@@ -17,15 +17,15 @@ logger = logger.getChild(__name__)
 CDN = 'https://wrolpi.nyc3.cdn.digitaloceanspaces.com'
 MODELS_MANIFEST_URL = f'{CDN}/ai/models.json'
 
-# Sizes are bytes; sha256 values are filled from the published manifest at release time.  The
-# meta4 sidecar (GPG-verified at download time) is what actually enforces the hash.
+# Sizes are bytes; sha256 values match the published manifest (wrolpi/scripts/publish_ai_models.py
+# refreshes both).  The meta4 sidecar (GPG-verified at download time) is what enforces the hash.
 AI_MODELS = [
     dict(
         name='Qwen3-1.7B-Q4_K_M.gguf',
         tier='small',
         url=f'{CDN}/ai/Qwen3-1.7B-Q4_K_M.gguf',
-        sha256='',
-        size=1_200_000_000,
+        sha256='b139949c5bd74937ad8ed8c8cf3d9ffb1e99c866c823204dc42c0d91fa181897',
+        size=1_107_409_472,
         min_ram_gb=4,
         default_context=8_192,
         license='Apache 2.0',
@@ -35,8 +35,8 @@ AI_MODELS = [
         name='Qwen3-4B-Instruct-2507-Q4_K_M.gguf',
         tier='medium',
         url=f'{CDN}/ai/Qwen3-4B-Instruct-2507-Q4_K_M.gguf',
-        sha256='',
-        size=2_600_000_000,
+        sha256='3605803b982cb64aead44f6c1b2ae36e3acdb41d8e46c8a94c6533bc4c67e597',
+        size=2_497_281_120,
         min_ram_gb=8,
         default_context=16_384,
         license='Apache 2.0',

wrolpi/scripts/publish_ai_models.py

@@ -0,0 +1,95 @@
+#!/usr/bin/env python3
+"""Publish the AI model catalog to the WROLPi CDN.
+
+For every model in modules/ai/catalog.py AI_MODELS this expects the GGUF file in MODELS_DIR,
+then produces and uploads (the same trust chain the maps use):
+  - <model>.gguf.meta4   Metalink4 with size, sha-256, and a GPG signature of the hash
+                         (aria2c enforces the hash; WROLPi GPG-verifies it before download)
+  - ai/models.json       the manifest, with the real sha256/size values
+  - ai/models.json.sig   detached GPG signature of the manifest
+
+Run on a machine with the roland@learningselfreliance.com secret key and an s3cmd configured
+for the wrolpi Spaces bucket:
+
+    python3 wrolpi/scripts/publish_ai_models.py <models_dir> [--upload]
+
+Afterwards, copy the printed sha256/size values into AI_MODELS (the bundled offline catalog).
+"""
+import argparse
+import json
+import pathlib
+import subprocess
+import sys
+
+PROJECT_DIR = pathlib.Path(__file__).parent.parent.parent
+sys.path.insert(0, str(PROJECT_DIR))
+
+from modules.ai.catalog import AI_MODELS, MODELS_MANIFEST_URL  # noqa: E402
+from wrolpi.scripts.build_map_regions import generate_meta4, sha256_file, sign_hash  # noqa: E402
+
+BUCKET = 's3://wrolpi/ai'
+GPG_UID = 'roland@learningselfreliance.com'
+
+
+def sign_file(path: pathlib.Path) -> pathlib.Path:
+    sig_path = path.with_suffix(path.suffix + '.sig')
+    sig_path.unlink(missing_ok=True)
+    subprocess.run(['gpg', '--batch', '-u', GPG_UID, '--detach-sign', '--armor',
+                    '-o', str(sig_path), str(path)], check=True)
+    return sig_path
+
+
+def upload(path: pathlib.Path):
+    subprocess.run(['s3cmd', 'put', '--acl-public', str(path), f'{BUCKET}/{path.name}'], check=True)
+
+
+def main():
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument('models_dir', type=pathlib.Path)
+    parser.add_argument('--upload', action='store_true', help='Upload to the CDN with s3cmd')
+    args = parser.parse_args()
+
+    manifest_models = []
+    artifacts = []
+    for model in AI_MODELS:
+        path = args.models_dir / model['name']
+        if not path.is_file():
+            print(f'MISSING: {path} — download it first', file=sys.stderr)
+            return 1
+
+        size = path.stat().st_size
+        print(f'Hashing {model["name"]} ({size:,} bytes)...')
+        sha256 = sha256_file(str(path))
+        signature = sign_hash(sha256)
+        meta4_path = pathlib.Path(f'{path}.meta4')
+        meta4_path.write_text(generate_meta4(model['name'], model['url'], sha256, size, signature))
+        print(f'  sha256 {sha256}')
+
+        manifest_models.append(dict(model, sha256=sha256, size=size,
+                                    meta4_url=f'{model["url"]}.meta4'))
+        artifacts += [path, meta4_path]
+
+    manifest_path = args.models_dir / 'models.json'
+    manifest_path.write_text(json.dumps(dict(version=1, models=manifest_models), indent=2) + '\n')
+    sig_path = sign_file(manifest_path)
+    artifacts += [manifest_path, sig_path]
+    print(f'Manifest written: {manifest_path} (URL: {MODELS_MANIFEST_URL})')
+
+    if args.upload:
+        for path in artifacts:
+            print(f'Uploading {path.name}...')
+            upload(path)
+        print('Upload complete.')
+    else:
+        print('\nDry run (no --upload).  Artifacts ready:')
+        for path in artifacts:
+            print(f'  {path}')
+
+    print('\nCopy these real values into modules/ai/catalog.py AI_MODELS:')
+    for model in manifest_models:
+        print(f'  {model["name"]}: sha256={model["sha256"]} size={model["size"]}')
+    return 0
+
+
+if __name__ == '__main__':
+    sys.exit(main())