feat(download): fill model metadata from the source API on download

A ModelScope or Hugging Face download landed as a bare filename, hash and
source link; the model card stayed empty until the user ran "Enrich
Metadata with AI" by hand. But everything that makes a CivitAI download
useful — the display name, the description, the tags, the trigger words,
the example images, the preview — is already published by those sites'
public APIs, so asking for it at download time is deterministic work, not
model work.

Add `py/services/model_sources/hydration.py`, called by
`_save_source_metadata()` once the sidecar exists and the file is in the
scanner cache. It fetches the model card plus the site's card extras and
hands them to the same `PostProcessor` the AI skill uses, with an empty
`llm_output`, so the two paths cannot drift apart. What lands:

* `model_name` from the site's own display name (ModelScope's `Name`), so
  the card stops showing the local filename — written only while the value
  still equals the file stem, since once a user renames a model that
  choice is theirs to keep
* `civitai.name` from the matched version's label (`showName`), which the
  card renders as the version chip
* `civitai.description` / `modelDescription` from the author summary plus
  the README as HTML
* `civitai.images` / `preview_url` from the per-file example images
* `civitai.trainedWords` from the per-file trigger words
* `base_model`, `tags` and `usage_tips` as before

Provenance stays honest: the pass records
`metadata_source = "source:<platform>"` rather than the skill's
`agent:enrich_hf_metadata`, and — because no provider ran — it no longer
stamps `llm_enriched_at`; that stamp is now conditional on the LLM
actually answering, which is what the field means. The five hand-rolled
`civitai` dict merges in the post-processor collapse into one
`_merge_civitai()` helper.

Two guards keep it safe. Only a model whose stored
`source_platform`/`source_url` match the repository being downloaded is
updated, so a local file that merely shares a name never receives another
model's card; and a file already on disk is topped up too, which
back-fills models downloaded before this existed. READMEs and detail
payloads describe the repository rather than the file, so a short-lived
process-wide `ModelSourceCache` (300 s, 32 entries) keeps a batch over one
repository to two HTTP requests. Every failure is logged and swallowed:
hydration can never fail a download.

Fix the hash policy while here. `_save_source_metadata()` went straight to
`MetadataManager.create_default_metadata()`, bypassing the per-type
factory on the owning scanner, so a checkpoint paid a full SHA256 inside
the download request — `CheckpointScanner`/`OtherScanner` deliberately
record `hash_status="pending"` with an empty `sha256` for their multi-GB
files. Metadata is now created through `scanner._create_default_metadata()`.
Hydration copes with the empty hash: `_matching_versions()` falls back to
the repository basename, which is exactly what the download just wrote.

Report both post-transfer stages, which advance no byte counter and so
read as a stall: the bar sat at 100% showing `0 B/s` for the seconds spent
hashing and fetching. `_report_phase()` broadcasts
`{"status": "metadata", "stage": "indexing" | "source", "platform": ...}`,
and `LoadingManager` names the stage in the status line (keeping the batch
position), retitles the item line, replaces the dead speed figure and runs
a sheen over the bar. `stage`/`platform` are machine-readable; the wording
is localised in the frontend.

Finally, `modelscope.ai` is its own catalogue rather than an alias of
`modelscope.cn` — `referall13/EM1` exists only on `.ai` and
`jj3550945163/Krea-2-LORA` only on `.cn` — so its URLs were rejected with
"Invalid model URL format". Register it as `ModelScopeIntlSource`
(`platform="modelscope-ai"`, `msai:` group prefix, its own default
download directory) and derive every URL either deployment builds from a
per-class `base_url`. `modelscope.com` stays an alias of `.cn`, which is
what it redirects to. The frontend source table, the link dialog hints and
the docs mirror the split.

Verified against the live APIs: both reported `.ai` repositories list
their files, read their READMEs and yield name / version / base model /
trigger words / example images. Backend 3092 passed; frontend 1259 JS +
91 Vue passed. The nine locales carry the new progress copy in the next
commit.

py/services/model_sources/hydration.py

@@ -0,0 +1,235 @@
+"""Deterministic metadata hydration for freshly downloaded source models.
+
+A CivitAI download writes a fully-populated metadata sidecar as part of the
+download itself: the name, the description, the tags, the trigger words and
+the example images all arrive with the file.  A download from an external
+model source (ModelScope, Hugging Face) has the same information behind a
+public API, but historically landed as a bare filename plus a source URL that
+the user had to enrich by hand ("Enrich Metadata with AI").
+
+This module closes that gap without involving an LLM.  It fetches the linked
+site's model card, hands it to the same :class:`~py.services.agent.post_processor.PostProcessor`
+the AI skill uses, and writes the result.  Everything it applies is data the
+site published, so it is safe to run automatically on every download and to
+treat as a fallback for the gaps the LLM would otherwise fill.
+
+Nothing here may break a download: every failure is logged and normalised to
+"the site had nothing to contribute".
+"""
+
+from __future__ import annotations
+
+import logging
+import os
+import time
+from typing import TYPE_CHECKING, Optional
+
+from .base import ModelCardContext, ModelSourceCache
+from .registry import get_source, resolve_source_ref
+
+if TYPE_CHECKING:  # pragma: no cover - typing only
+    from .base import ModelSource, SourceRef
+
+logger = logging.getLogger(__name__)
+
+#: How long a fetched repository payload stays usable.  A download batch walks
+#: a repository's files one HTTP request at a time, and the README plus the
+#: detail payload describe the *repository*, not the file, so re-fetching them
+#: per file would be pure waste.  They expire so an edited model card is still
+#: picked up by the next batch.
+SHARED_CACHE_TTL = 300.0
+
+#: Upper bound on memoised repositories; a long-running server must not grow
+#: without limit.
+SHARED_CACHE_MAX_ENTRIES = 32
+
+#: ``"<platform>:<source_id>"`` → ``(expiry, memo)``.
+_shared_caches: dict[str, tuple[float, ModelSourceCache]] = {}
+
+
+def shared_source_cache(platform: str, source_id: str) -> ModelSourceCache:
+    """Return a short-lived per-repository memo for download-time hydration."""
+
+    now = time.monotonic()
+    key = f"{platform}:{source_id}"
+    entry = _shared_caches.get(key)
+    if entry is not None and entry[0] > now:
+        return entry[1]
+
+    for expired in [k for k, (expiry, _) in _shared_caches.items() if expiry <= now]:
+        _shared_caches.pop(expired, None)
+    if len(_shared_caches) >= SHARED_CACHE_MAX_ENTRIES:
+        oldest = min(_shared_caches, key=lambda k: _shared_caches[k][0])
+        _shared_caches.pop(oldest, None)
+
+    cache = ModelSourceCache()
+    _shared_caches[key] = (now + SHARED_CACHE_TTL, cache)
+    return cache
+
+
+def reset_shared_caches() -> None:
+    """Drop every memoised repository — used by tests."""
+
+    _shared_caches.clear()
+
+
+async def load_model_card(
+    source: "ModelSource",
+    source_id: str,
+    cache: Optional[ModelSourceCache] = None,
+) -> str:
+    """Return *source_id*'s README, reusing *cache* when one is supplied.
+
+    Only successful reads are memoised, leaving a transient failure to be
+    retried for the next file of the same repository.
+    """
+
+    key = f"{source.platform}:{source_id}"
+    if cache is not None:
+        cached = cache.readmes.get(key)
+        if cached is not None:
+            return cached
+
+    readme = await source.fetch_model_card(source_id)
+    if cache is not None and readme:
+        cache.readmes[key] = readme
+    return readme or ""
+
+
+async def resolve_site_base_model(context: ModelCardContext) -> str:
+    """Resolve the site's base-model hints to a canonical name, or ``""``.
+
+    Sites name base models in their own vocabulary (ModelScope publishes both
+    ``krea/Krea-2-Turbo`` and the ``KREA_2_TURBO`` enum).  The resolver is
+    strict and only ever returns a name the canonical vocabulary already
+    contains, so an uncertain hint yields ``""`` rather than a plausible-looking
+    wrong value.
+    """
+
+    hints = [*context.base_model_aliases, context.base_model]
+    if not any(hints):
+        return ""
+
+    # Imported lazily: pulling in the agent package at module scope would make
+    # the model-source package import itself while it is still initialising.
+    try:
+        from ...metadata_ops import list_base_models
+        from ..agent.base_model_resolver import resolve_base_model
+
+        known_names = await list_base_models()
+    except Exception as exc:
+        logger.warning("Could not resolve a site base model: %s", exc)
+        return ""
+    return resolve_base_model(hints, known_names)
+
+
+async def hydrate_from_source(
+    file_path: str,
+    *,
+    ref: "SourceRef",
+    cache: Optional[ModelSourceCache] = None,
+) -> list[str]:
+    """Apply the linked site's published metadata to a downloaded model.
+
+    This is the deterministic counterpart of the ``enrich_hf_metadata`` skill:
+    it produces the same populated model card a CivitAI download produces,
+    without an LLM and without user action.
+
+    Args:
+        file_path: The just-downloaded model file, whose sidecar already
+            carries the SHA256 used to match the right file in a collection
+            repository.
+        ref: The source the file came from.
+        cache: Optional per-call memo; defaults to a short-lived shared one so
+            a batch over one repository fetches its card only once.
+
+    Returns:
+        The names of the metadata fields that changed.  Never raises — a site
+        that is down, or an API that changed shape, must not fail a download.
+    """
+
+    try:
+        source = get_source(ref.platform)
+        if source is None or not source.supports_enrichment:
+            return []
+
+        from ...metadata_ops import read_metadata
+
+        metadata = await read_metadata(file_path)
+        if not metadata:
+            logger.debug("No metadata to hydrate for %s", file_path)
+            return []
+
+        # Only a model that is actually linked to this repository may be
+        # updated.  The download path writes those fields just before calling
+        # us; a file that merely shares a name with the requested one must not
+        # be given another model's card.
+        linked = resolve_source_ref(metadata)
+        if linked is None or (linked.platform, linked.source_id) != (
+            ref.platform,
+            ref.source_id,
+        ):
+            logger.debug(
+                "Not hydrating %s: linked to %s, not %s",
+                file_path, linked.url if linked else "no model source", ref.url,
+            )
+            return []
+
+        memo = cache if cache is not None else shared_source_cache(
+            ref.platform, ref.source_id
+        )
+        readme = await load_model_card(source, ref.source_id, memo)
+        context = await source.fetch_model_card_context(
+            ref.source_id,
+            os.path.basename(file_path),
+            sha256=(metadata.get("sha256") or "").strip(),
+            cache=memo,
+        )
+        if context.is_empty() and not readme:
+            logger.debug(
+                "No published metadata for %s on %s", ref.source_id, ref.platform
+            )
+            return []
+
+        resolved_base_model = await resolve_site_base_model(context)
+
+        from ..agent.post_processor import PostProcessor
+
+        result = await PostProcessor().process(
+            skill_name="enrich_hf_metadata",
+            model_path=file_path,
+            llm_output={},
+            metadata=metadata,
+            readme_content=readme,
+            source_context=context,
+            resolved_base_model=resolved_base_model,
+            metadata_source=f"source:{ref.platform}",
+        )
+        if not result.get("success", True):
+            logger.debug(
+                "Hydration reported failure for %s: %s",
+                file_path, result.get("errors"),
+            )
+            return []
+
+        updated = list(result.get("updated_fields") or [])
+        logger.info(
+            "Hydrated %s from %s (%s): %s",
+            file_path, source.label or ref.platform, ref.source_id,
+            ", ".join(updated) or "nothing to change",
+        )
+        return updated
+    except Exception as exc:  # pragma: no cover - defensive by design
+        logger.warning("Source hydration failed for %s: %s", file_path, exc)
+        return []
+
+
+__all__ = [
+    "SHARED_CACHE_MAX_ENTRIES",
+    "SHARED_CACHE_TTL",
+    "hydrate_from_source",
+    "load_model_card",
+    "reset_shared_caches",
+    "resolve_site_base_model",
+    "shared_source_cache",
+]