mirror of
https://github.com/langbot-app/LangBot.git
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Merge branch 'rc/new-plugin' into refactor/new-plugin-system
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@@ -10,7 +10,7 @@ from ....provider.modelmgr import requester as model_requester
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from langbot_plugin.api.entities.builtin.provider import message as provider_message
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class ModelsService:
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class LLMModelsService:
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ap: app.Application
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def __init__(self, ap: app.Application) -> None:
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@@ -109,5 +109,91 @@ class ModelsService:
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model=runtime_llm_model,
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messages=[provider_message.Message(role='user', content='Hello, world!')],
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funcs=[],
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extra_args=model_data.get('extra_args', {}),
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)
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class EmbeddingModelsService:
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ap: app.Application
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def __init__(self, ap: app.Application) -> None:
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self.ap = ap
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async def get_embedding_models(self) -> list[dict]:
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result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_model.EmbeddingModel))
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models = result.all()
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return [self.ap.persistence_mgr.serialize_model(persistence_model.EmbeddingModel, model) for model in models]
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async def create_embedding_model(self, model_data: dict) -> str:
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model_data['uuid'] = str(uuid.uuid4())
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await self.ap.persistence_mgr.execute_async(
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sqlalchemy.insert(persistence_model.EmbeddingModel).values(**model_data)
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)
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embedding_model = await self.get_embedding_model(model_data['uuid'])
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await self.ap.model_mgr.load_embedding_model(embedding_model)
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return model_data['uuid']
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async def get_embedding_model(self, model_uuid: str) -> dict | None:
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result = await self.ap.persistence_mgr.execute_async(
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sqlalchemy.select(persistence_model.EmbeddingModel).where(
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persistence_model.EmbeddingModel.uuid == model_uuid
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)
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)
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model = result.first()
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if model is None:
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return None
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return self.ap.persistence_mgr.serialize_model(persistence_model.EmbeddingModel, model)
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async def update_embedding_model(self, model_uuid: str, model_data: dict) -> None:
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if 'uuid' in model_data:
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del model_data['uuid']
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await self.ap.persistence_mgr.execute_async(
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sqlalchemy.update(persistence_model.EmbeddingModel)
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.where(persistence_model.EmbeddingModel.uuid == model_uuid)
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.values(**model_data)
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)
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await self.ap.model_mgr.remove_embedding_model(model_uuid)
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embedding_model = await self.get_embedding_model(model_uuid)
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await self.ap.model_mgr.load_embedding_model(embedding_model)
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async def delete_embedding_model(self, model_uuid: str) -> None:
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await self.ap.persistence_mgr.execute_async(
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sqlalchemy.delete(persistence_model.EmbeddingModel).where(
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persistence_model.EmbeddingModel.uuid == model_uuid
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)
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)
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await self.ap.model_mgr.remove_embedding_model(model_uuid)
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async def test_embedding_model(self, model_uuid: str, model_data: dict) -> None:
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runtime_embedding_model: model_requester.RuntimeEmbeddingModel | None = None
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if model_uuid != '_':
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for model in self.ap.model_mgr.embedding_models:
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if model.model_entity.uuid == model_uuid:
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runtime_embedding_model = model
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break
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if runtime_embedding_model is None:
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raise Exception('model not found')
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else:
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runtime_embedding_model = await self.ap.model_mgr.init_runtime_embedding_model(model_data)
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await runtime_embedding_model.requester.invoke_embedding(
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model=runtime_embedding_model,
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input_text=['Hello, world!'],
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extra_args={},
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)
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