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