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@@ -329,16 +329,23 @@ def create_qdrant_indexes():
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model_name=dataset.embedding_model
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)
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except Exception:
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- provider = Provider(
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- id='provider_id',
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- tenant_id=dataset.tenant_id,
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- provider_name='openai',
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- provider_type=ProviderType.CUSTOM.value,
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- encrypted_config=json.dumps({'openai_api_key': 'TEST'}),
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- is_valid=True,
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- )
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- model_provider = OpenAIProvider(provider=provider)
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- embedding_model = OpenAIEmbedding(name="text-embedding-ada-002", model_provider=model_provider)
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+ try:
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+ embedding_model = ModelFactory.get_embedding_model(
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+ tenant_id=dataset.tenant_id
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+ )
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+ dataset.embedding_model = embedding_model.name
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+ dataset.embedding_model_provider = embedding_model.model_provider.provider_name
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+ except Exception:
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+ provider = Provider(
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+ id='provider_id',
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+ tenant_id=dataset.tenant_id,
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+ provider_name='openai',
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+ provider_type=ProviderType.SYSTEM.value,
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+ encrypted_config=json.dumps({'openai_api_key': 'TEST'}),
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+ is_valid=True,
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+ )
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+ model_provider = OpenAIProvider(provider=provider)
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+ embedding_model = OpenAIEmbedding(name="text-embedding-ada-002", model_provider=model_provider)
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embeddings = CacheEmbedding(embedding_model)
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from core.index.vector_index.qdrant_vector_index import QdrantVectorIndex, QdrantConfig
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