Update FastPLMs files

fastplms/registry.py

@@ -22,6 +22,10 @@ from urllib.parse import urlparse
 
 _HEX_RE = re.compile(r"^[0-9a-f]+$")
 _WANDB_RUN_URL_RE = re.compile(r"^https://wandb\.ai/[^/?#]+/[^/?#]+/runs/[^/?#]+$")
+_CONFIDENCE_DATASET_URL_RE = re.compile(
+    r"https://huggingface\.co/datasets/Synthyra/[A-Za-z0-9][A-Za-z0-9_.-]*/"
+    r"(?P<view>tree|blob)/[0-9a-f]{40}(?:/(?P<path>[A-Za-z0-9_./-]+))?"
+)
 _IDENTIFIER_RE = re.compile(r"^[a-z0-9][a-z0-9_-]*$")
 _HUB_LICENSE_NAME_RE = re.compile(r"[^a-z0-9.]+")
 _WINDOWS_INVALID_PATH_CHARACTERS = frozenset('<>:"|?*')
@@ -400,6 +404,8 @@ class ConfidenceAdaptation:
     training_url: str
     evaluation_url: str
     evidence_path: str
+    release: Literal["pilot", "v1"] = "pilot"
+    frozen_base: CheckpointSource | None = None
 
 
 @dataclass(frozen=True, slots=True)
@@ -441,6 +447,17 @@ class ModelSpec:
 
         return self.fast if self.artifact_source == "fast" else self.official
 
+    @property
+    def confidence_training_base(self) -> CheckpointSource:
+        """Keep confidence training tied to its original base after release repinning."""
+
+        if (
+            self.confidence_adaptation is not None
+            and self.confidence_adaptation.frozen_base is not None
+        ):
+            return self.confidence_adaptation.frozen_base
+        return self.fast
+
     @property
     def oracle_asset_map(self) -> Mapping[str, OracleAsset]:
         """Return native oracle assets keyed by their declared role."""
@@ -1293,16 +1310,42 @@ def _parse_confidence_adaptation(
             "training_url",
             "evaluation_url",
             "evidence_path",
+            "release",
+            "frozen_base",
         }
     )
     _reject_unknown_fields(raw, fields, f"{context}.confidence_adaptation")
     adaptation_context = f"{context}.confidence_adaptation"
+    release = raw.get("release", "pilot")
+    if release not in ("pilot", "v1"):
+        raise RegistryError(f"{adaptation_context}.release must be pilot or v1.")
     digests: dict[str, str] = {}
     for key in ("head_sha256", "base_weight_sha256", "donor_weight_sha256"):
         digest = _require_str(raw, key, adaptation_context)
         if len(digest) != 64 or _HEX_RE.fullmatch(digest) is None:
             raise RegistryError(f"{adaptation_context}.{key} must be a SHA-256 digest.")
         digests[key] = digest
+    frozen_base = None
+    if "frozen_base" in raw:
+        base_context = f"{adaptation_context}.frozen_base"
+        raw_base = raw["frozen_base"]
+        if not isinstance(raw_base, dict):
+            raise RegistryError(f"{base_context} must be a table.")
+        _reject_unknown_fields(raw_base, {"repo", "revision", "files"}, base_context)
+        frozen_base = _parse_checkpoint(
+            {f"base_{key}": value for key, value in raw_base.items()},
+            "base",
+            base_context,
+        )
+        weight = frozen_base.file_map.get("model.safetensors")
+        if (
+            weight is None
+            or weight.algorithm != "sha256"
+            or weight.digest != digests["base_weight_sha256"]
+        ):
+            raise RegistryError(f"{base_context} model.safetensors must match base_weight_sha256.")
+    if release == "v1" and frozen_base is None:
+        raise RegistryError(f"{adaptation_context}.frozen_base is required for v1.")
     donor_repo = _require_str(raw, "donor_repo", adaptation_context)
     if _REPOSITORY_ID_RE.fullmatch(donor_repo) is None:
         raise RegistryError(f"{adaptation_context}.donor_repo must be a repository ID.")
@@ -1311,9 +1354,21 @@ def _parse_confidence_adaptation(
     urls: dict[str, str] = {}
     for key in ("training_url", "evaluation_url"):
         url = _require_str(raw, key, adaptation_context)
-        if _WANDB_RUN_URL_RE.fullmatch(url) is None:
+        dataset_match = (
+            _CONFIDENCE_DATASET_URL_RE.fullmatch(url) if key == "evaluation_url" else None
+        )
+        if dataset_match is not None:
+            dataset_path = dataset_match["path"]
+            if dataset_match["view"] == "blob" and dataset_path is None:
+                raise RegistryError(f"{adaptation_context}.{key} blob URL requires a file path.")
+            if dataset_path is not None:
+                _portable_relative_path(dataset_path, f"{adaptation_context}.{key}")
+        elif _WANDB_RUN_URL_RE.fullmatch(url) is None:
+            accepted_urls = "a W&B run URL"
+            if key == "evaluation_url":
+                accepted_urls += " or an immutable Synthyra Hugging Face dataset URL"
             raise RegistryError(
-                f"{adaptation_context}.{key} must be a W&B run URL without query or fragment."
+                f"{adaptation_context}.{key} must be {accepted_urls} without query or fragment."
             )
         urls[key] = url
     evidence_path = _portable_relative_path(
@@ -1331,6 +1386,8 @@ def _parse_confidence_adaptation(
         training_url=urls["training_url"],
         evaluation_url=urls["evaluation_url"],
         evidence_path=evidence_path.as_posix(),
+        release=cast(Literal["pilot", "v1"], release),
+        frozen_base=frozen_base,
     )
 
 

fastplms_bundle.py

@@ -1,6 +1,6 @@
 """Generated deterministic archive of unchanged FastPLMs runtime sources."""
 
-RUNTIME_HASH = "403000fd007daa13a239be98e33a40322522a2eb319e3b22ac1d29059cd68020"
+RUNTIME_HASH = "c7fe3e9f04c64f825e675745adfa3d7c3b565874d175d67c2390d9d21a0e86cf"
 RUNTIME_DATA = (
     'P)h>@6aWAK2mk;8ApjK1*rl8T002P;000yK003rTb98WQZF4VQUukY>bYEXCaCwcDT~FIE6o&8fE6#kCOkKrpD{WG>fiw*S0w!&%'
     'ka3ff)~XXnw!<ih|Gr}<E=?(v+%(O3-uHYsJ!OoY2<t9R&nz_UT*(|7k*~x8LDmjUDRLYq$@LPU(nYHfT8kExcvu78H`+K0R)ehk'
@@ -1205,221 +1205,230 @@ RUNTIME_DATA = (
     'a4<Z~YYk=Ad%WEcKK3?ZKH?YzWNXIM(e2-Xm=cd_WH{RcJB2%ETv_S#PFQ>|j^v1(jKN@2yhk=Ykf77a&mitsJxL6&_enzjY_+c0'
     'da6C+=7pj*5>imL^4Z#&NNgf%gJNp!0bqfbNAAkf{eiWCV>}6kTxtk>!2K(8!$?W{xdX(V@BiF0&t*ObjpjF(JNLZWpAC%v)Mu)m'
     'UBed-2F~sEMZ1J=E77eSno;*oi^|7s#{c^gxg`##ST%D^7{3QnjX$ZI*MhCt);mt71J=E%PF)r_L^Pe~L~XJWwTE#igvspePyl;^'
-    'ZBAJUq%1FI#X;jAOsQ~RUSgR*&oA+i;1})oE76B9+v`9-c$fblP)h>@6aWAK2mk;8Apo>GQ9}kf002}C0RR*L003rTb98WQZF4Vj'
-    'WoKz~baHtvaCzl@X?Nqs5#V?I3K-tEB4dhkIPuFeh7*lMd9>C@dJ@M+WCejpP(p?T833FaMbUrXs=liah?JCLcm1A61kguyb#--J'
-    'T^+~q=ysV;qHH|Q>pE%{QFD_=2U*>m9=)rh`C^jKqO6=m%WCm4FSBx-NAs*Krg`1;x3)%5xXQ1Kx~XoXqK=BP$;+l#l-X<sFUm>2'
-    '%;BH1i5Amnw5Y~6tg%s*mGyK{&GV}6!~4aoD6gY&R&GJ>RSsWrs9Z1eaTC?6<#JIq0OR;3AAeXbppUv2&5Che);avb2B8krL*VMg'
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+    'FJ*0FWn^S&ZfA2Zb98TVVP|D7aCuNm0Rj{N6aWAK2mk;8Aplw52h=eK002K3000~S0000000000005+c#@qk^W?^%5aBOXJFJ*0F'
+    'Wn^S&ZfA2Zba`-Pb1rasP)h*<6aW+e000O8001EXUCm{gi&FpqAVvWI6aWAK0000000000q=7Ny003rTb98WQZF4VeZ)9a`b1rmm'
+    'ZER3W0Rj{N6aWAK2mk;8Apn+gw*2q_002+{000{R0000000000005+c?l%DdW?^%5aBOXJFKusRWo&aVUtei%X>?y-E^v8JO928D'
+    '02BZK00;m803iUUb9%Sz1pokD5dZ)l00000000000001_ffqRe0A^uxbZ~5Kb1!XgWMyn~FJEPIZC`S4bYXINE^v8JO928D02BZK'
+    '00;m803iT{<4%QJ5dZ*<PXGWX00000000000001_fj>V10A^uxbZ~5Kb1!XgWMyn~FJo+Bb8~5CX=7n@X>V>{aB^>AWiD`eP)h*<'
+    '6aW+e000O8001EX000000ssI200000BLDyZ0000000000q=Da10RU!Ub98WQZF4VeZ)9a`b1!9cZDwz5WG`P|X>MtBUtcb8c~DCM'
+    '0u%rg000080000X09v)V->4=400y%F05AXm00000000000HlE;Q2_vEVRLkFY;AKdZEs{{Y;!MVb8TjCY-BHOZ)9a`X>Mm<W?^%5'
+    'UuAP`W^Zg{E^v8JO928D02BZK00;m803iT_E!@tYI{*Nh7Xbhi00000000000001_ff#rJ0A^uxbZ~5Kb1!mbXK8bEa(OOrc~DCM'
+    '0u%rg000080000X0E@x_u22I20PP6?022TJ00000000000HlHFvjG5RVRLkFY;AKda&>NWX>DaLaCuNm1qJ{B000*N7XZZu003#X'
+    '0RR91'
 )

modeling_fastplms.py

@@ -13,7 +13,7 @@ from zipfile import ZIP_DEFLATED, ZipFile
 
 from .fastplms_bundle import RUNTIME_DATA, RUNTIME_HASH
 
-if RUNTIME_HASH != "403000fd007daa13a239be98e33a40322522a2eb319e3b22ac1d29059cd68020":
+if RUNTIME_HASH != "c7fe3e9f04c64f825e675745adfa3d7c3b565874d175d67c2390d9d21a0e86cf":
     raise RuntimeError("FastPLMs runtime identity differs from the bridge.")
 
 _RUNTIME_TEMPORARIES = []