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NoOpVectorDatabase

symbi_runtime::context::vector_db

Struct NoOpVectorDatabase 

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pub struct NoOpVectorDatabase;
Expand description

No-op vector database for when no backend is configured

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impl VectorDatabase for NoOpVectorDatabase

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fn initialize<'life0, 'async_trait>( &'life0 self, ) -> Pin<Box<dyn Future<Output = Result<(), ContextError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait,

Initialize the vector database connection and collection
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fn store_knowledge_item<'life0, 'life1, 'async_trait>( &'life0 self, _item: &'life1 KnowledgeItem, _embedding: Vec<f32>, ) -> Pin<Box<dyn Future<Output = Result<VectorId, ContextError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Store a knowledge item with its embedding
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fn store_memory_item<'life0, 'life1, 'async_trait>( &'life0 self, _agent_id: AgentId, _memory: &'life1 MemoryItem, _embedding: Vec<f32>, ) -> Pin<Box<dyn Future<Output = Result<VectorId, ContextError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Store memory item with embedding
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fn batch_store<'life0, 'async_trait>( &'life0 self, batch: VectorBatchOperation, ) -> Pin<Box<dyn Future<Output = Result<Vec<VectorId>, ContextError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait,

Batch store multiple items for performance
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fn search_knowledge_base<'life0, 'async_trait>( &'life0 self, _agent_id: AgentId, _query_embedding: Vec<f32>, _limit: usize, ) -> Pin<Box<dyn Future<Output = Result<Vec<KnowledgeItem>, ContextError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait,

Search for similar knowledge items
Perform semantic search with text query
Advanced search with filters and metadata
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fn delete_knowledge_item<'life0, 'async_trait>( &'life0 self, _vector_id: VectorId, ) -> Pin<Box<dyn Future<Output = Result<(), ContextError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait,

Delete knowledge item by ID
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fn batch_delete<'life0, 'async_trait>( &'life0 self, _vector_ids: Vec<VectorId>, ) -> Pin<Box<dyn Future<Output = Result<(), ContextError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait,

Batch delete multiple items
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fn update_metadata<'life0, 'async_trait>( &'life0 self, _vector_id: VectorId, _metadata: HashMap<String, Value>, ) -> Pin<Box<dyn Future<Output = Result<(), ContextError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait,

Update knowledge item metadata
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fn get_stats<'life0, 'async_trait>( &'life0 self, ) -> Pin<Box<dyn Future<Output = Result<VectorDatabaseStats, ContextError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait,

Get collection statistics
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fn create_index<'life0, 'life1, 'async_trait>( &'life0 self, _field_name: &'life1 str, ) -> Pin<Box<dyn Future<Output = Result<(), ContextError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Create index for better performance
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fn optimize_collection<'life0, 'async_trait>( &'life0 self, ) -> Pin<Box<dyn Future<Output = Result<(), ContextError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait,

Optimize collection for better search performance
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impl VectorDb for NoOpVectorDatabase

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fn initialize<'life0, 'async_trait>( &'life0 self, ) -> Pin<Box<dyn Future<Output = Result<(), ContextError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait,

Initialize the backend (create collection/table if needed).
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fn store_knowledge_item<'life0, 'life1, 'async_trait>( &'life0 self, _item: &'life1 KnowledgeItem, _embedding: Vec<f32>, ) -> Pin<Box<dyn Future<Output = Result<VectorId, ContextError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Store a knowledge item with its embedding vector.
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fn store_memory_item<'life0, 'life1, 'async_trait>( &'life0 self, _agent_id: AgentId, _memory: &'life1 MemoryItem, _embedding: Vec<f32>, ) -> Pin<Box<dyn Future<Output = Result<VectorId, ContextError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Store a memory item with its embedding vector.
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fn batch_store<'life0, 'async_trait>( &'life0 self, batch: VectorBatchOperation, ) -> Pin<Box<dyn Future<Output = Result<Vec<VectorId>, ContextError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait,

Store multiple items in batch.
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fn search_knowledge_base<'life0, 'async_trait>( &'life0 self, _agent_id: AgentId, _query_embedding: Vec<f32>, _limit: usize, ) -> Pin<Box<dyn Future<Output = Result<Vec<KnowledgeItem>, ContextError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait,

Search the knowledge base by semantic similarity.
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fn semantic_search<'life0, 'async_trait>( &'life0 self, _agent_id: AgentId, _query_embedding: Vec<f32>, _limit: usize, _threshold: f32, ) -> Pin<Box<dyn Future<Output = Result<Vec<ContextItem>, ContextError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait,

Semantic similarity search returning context items.
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fn advanced_search<'life0, 'async_trait>( &'life0 self, _agent_id: AgentId, _query_embedding: Vec<f32>, _filters: HashMap<String, String>, _limit: usize, _threshold: f32, ) -> Pin<Box<dyn Future<Output = Result<Vec<VectorSearchResult>, ContextError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait,

Advanced search with metadata filters.
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fn delete_knowledge_item<'life0, 'async_trait>( &'life0 self, _vector_id: VectorId, ) -> Pin<Box<dyn Future<Output = Result<(), ContextError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait,

Delete a knowledge item by vector ID.
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fn batch_delete<'life0, 'async_trait>( &'life0 self, _vector_ids: Vec<VectorId>, ) -> Pin<Box<dyn Future<Output = Result<(), ContextError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait,

Delete multiple vectors by ID.
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fn update_metadata<'life0, 'async_trait>( &'life0 self, _vector_id: VectorId, _metadata: HashMap<String, Value>, ) -> Pin<Box<dyn Future<Output = Result<(), ContextError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait,

Update metadata on an existing vector.
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fn get_stats<'life0, 'async_trait>( &'life0 self, ) -> Pin<Box<dyn Future<Output = Result<VectorDatabaseStats, ContextError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait,

Get statistics about the vector database.
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fn create_index<'life0, 'life1, 'async_trait>( &'life0 self, _field_name: &'life1 str, ) -> Pin<Box<dyn Future<Output = Result<(), ContextError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Create an index on a field.
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fn optimize_collection<'life0, 'async_trait>( &'life0 self, ) -> Pin<Box<dyn Future<Output = Result<(), ContextError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait,

Optimize the collection (compact, reindex, etc.).
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fn health_check<'life0, 'async_trait>( &'life0 self, ) -> Pin<Box<dyn Future<Output = Result<bool, ContextError>> + Send + 'async_trait>>
where Self: 'async_trait, 'life0: 'async_trait,

Health check — can the backend be reached?

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