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fix(modelmgr): upsert Space-managed models instead of insert-only

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sync_new_models_from_space() skipped any model whose uuid already
existed. LangBot Space reuses a model's uuid across renames/re-specs
(e.g. the uuid that was claude-opus-4-6 later becomes claude-opus-4-7),
so renamed models never propagated locally — the stale local name was
also sent to the models gateway, causing model_not_found at inference.

Now upsert: create new uuids, and for existing models owned by the
Space provider, update name/abilities/ranking to track Space (models
from other providers are left untouched). Logs added/updated counts.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
Junyan Qin
2026-06-04 18:11:26 +08:00
parent 4889a3881b
commit 37b017459d
1 changed files with 65 additions and 31 deletions
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96
src/langbot/pkg/provider/modelmgr/modelmgr.py
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@@ -143,49 +143,83 @@ class ModelManager:
# get the latest models from space
space_models = await self.ap.space_service.get_models()
exists_llm_models_uuids = [m['uuid'] for m in await self.ap.llm_model_service.get_llm_models()]
exists_embedding_models_uuids = [
m['uuid'] for m in await self.ap.embedding_models_service.get_embedding_models()
]
# Index existing models by uuid. Space reuses a model's uuid across
# renames / re-specs (e.g. the uuid that used to be ``claude-opus-4-6``
# may later become ``claude-opus-4-7``). So for Space-managed models we
# upsert: create when the uuid is new, otherwise update name/abilities/
# ranking to track Space. Models owned by other providers are never
# touched, even on an (unexpected) uuid collision.
existing_llm_models = {m['uuid']: m for m in await self.ap.llm_model_service.get_llm_models()}
existing_embedding_models = {
m['uuid']: m for m in await self.ap.embedding_models_service.get_embedding_models()
}
created = 0
updated = 0
for space_model in space_models:
if space_model.category == 'chat':
uuid = space_model.uuid
if uuid in exists_llm_models_uuids:
continue
# model will be automatically loaded
await self.ap.llm_model_service.create_llm_model(
{
'uuid': space_model.uuid,
existing = existing_llm_models.get(space_model.uuid)
if existing is None:
# model will be automatically loaded
await self.ap.llm_model_service.create_llm_model(
{
'uuid': space_model.uuid,
'name': space_model.model_id,
'provider_uuid': space_model_provider.uuid,
'abilities': space_model.llm_abilities or [],
'extra_args': {},
'prefered_ranking': space_model.featured_order,
},
preserve_uuid=True,
auto_set_to_default_pipeline=False,
)
created += 1
elif existing.get('provider_uuid') == space_model_provider.uuid:
desired = {
'name': space_model.model_id,
'provider_uuid': space_model_provider.uuid,
'abilities': space_model.llm_abilities or [],
'extra_args': {},
'prefered_ranking': space_model.featured_order,
},
preserve_uuid=True,
auto_set_to_default_pipeline=False,
)
}
if (
existing.get('name') != desired['name']
or list(existing.get('abilities') or []) != list(desired['abilities'])
or existing.get('prefered_ranking') != desired['prefered_ranking']
):
await self.ap.llm_model_service.update_llm_model(space_model.uuid, dict(desired))
updated += 1
elif space_model.category == 'embedding':
uuid = space_model.uuid
if uuid in exists_embedding_models_uuids:
continue
# model will be automatically loaded
await self.ap.embedding_models_service.create_embedding_model(
{
'uuid': space_model.uuid,
existing = existing_embedding_models.get(space_model.uuid)
if existing is None:
# model will be automatically loaded
await self.ap.embedding_models_service.create_embedding_model(
{
'uuid': space_model.uuid,
'name': space_model.model_id,
'provider_uuid': space_model_provider.uuid,
'extra_args': {},
'prefered_ranking': space_model.featured_order,
},
preserve_uuid=True,
)
created += 1
elif existing.get('provider_uuid') == space_model_provider.uuid:
desired = {
'name': space_model.model_id,
'provider_uuid': space_model_provider.uuid,
'extra_args': {},
'prefered_ranking': space_model.featured_order,
},
preserve_uuid=True,
)
}
if (
existing.get('name') != desired['name']
or existing.get('prefered_ranking') != desired['prefered_ranking']
):
await self.ap.embedding_models_service.update_embedding_model(space_model.uuid, dict(desired))
updated += 1
if created or updated:
self.ap.logger.info(f'Synced models from LangBot Space: {created} added, {updated} updated.')
async def init_temporary_runtime_llm_model(
self,