RWKV Agent Kit

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About 876 wordsAbout 3 min

2025-09-08

RWKV Agent Kit provides an advanced memory system that supports semantic memory retrieval, knowledge graph construction, and memory compression. This chapter will detail how to use and configure these memory features.

🧠 Advanced Memory System

Semantic Memory Retrieval

The semantic memory system uses vector embedding technology to retrieve relevant memories based on semantic similarity:

use rwkv_agent_kit::memory::{SemanticMemory, MemoryQuery};
use rwkv_agent_kit::embeddings::SentenceTransformer;

// Initialize semantic memory system
let embedding_model = SentenceTransformer::new("all-MiniLM-L6-v2")?;
let mut memory = SemanticMemory::new(embedding_model);

// Store memories
memory.store("User likes coffee", "preference").await?;
memory.store("User lives in Beijing", "location").await?;
memory.store("User is a software engineer", "profession").await?;

// Semantic retrieval
let query = MemoryQuery::new("User's dietary preferences")
    .with_similarity_threshold(0.7)
    .with_max_results(5);

let memories = memory.search(query).await?;
for memory in memories {
    println!("Related memory: {} (similarity: {:.2})", memory.content, memory.similarity);
}

Knowledge Graph Construction

Build entity relationship graphs that support complex knowledge reasoning:

use rwkv_agent_kit::knowledge::{KnowledgeGraph, Entity, Relation};

// Create knowledge graph
let mut kg = KnowledgeGraph::new();

// Add entities
let user = kg.add_entity(Entity::new("User", "Person"));
let coffee = kg.add_entity(Entity::new("Coffee", "Beverage"));
let beijing = kg.add_entity(Entity::new("Beijing", "City"));

// Add relations
kg.add_relation(user, "likes", coffee)?;
kg.add_relation(user, "lives_in", beijing)?;

// Query relations
let preferences = kg.find_relations(user, "likes")?;
for (entity, relation) in preferences {
    println!("User {}: {}", relation, entity.name);
}

// Path query
let path = kg.find_path(user, coffee, 3)?;
if let Some(path) = path {
    println!("Relationship path: {:?}", path);
}

Memory Compression and Summarization

Automatically compress long-term memories and extract key information:

use rwkv_agent_kit::memory::{MemoryCompressor, CompressionStrategy};

// Create memory compressor
let compressor = MemoryCompressor::new(CompressionStrategy::Extractive);

// Compress memory
let long_conversation = "Very long conversation history...";
let summary = compressor.compress(long_conversation, 200).await?;

println!("Compressed summary: {}", summary);

// Hierarchical compression
let hierarchical_summary = compressor
    .hierarchical_compress(long_conversation)
    .with_levels(3)
    .with_compression_ratio(0.3)
    .execute().await?;

Memory Management Strategies

Memory Categorization

Categorize and manage memories based on different types:

use rwkv_agent_kit::memory::{MemoryCategory, MemoryManager};

// Create memory manager
let mut manager = MemoryManager::new();

// Define memory categories
let categories = vec![
    MemoryCategory::new("personal", "Personal Information"),
    MemoryCategory::new("preference", "User Preferences"),
    MemoryCategory::new("context", "Conversation Context"),
    MemoryCategory::new("knowledge", "Knowledge Information"),
];

for category in categories {
    manager.add_category(category);
}

// Store categorized memories
manager.store_memory("User likes coffee", "preference").await?;
manager.store_memory("User's name is John", "personal").await?;
manager.store_memory("Today we discussed machine learning", "context").await?;

// Retrieve by category
let preferences = manager.get_memories_by_category("preference").await?;
for memory in preferences {
    println!("Preference memory: {}", memory.content);
}

Memory Priority

Set memory importance and retention policies:

use rwkv_agent_kit::memory::{MemoryPriority, RetentionPolicy};

// Set memory priorities
let high_priority = MemoryPriority::High;
let medium_priority = MemoryPriority::Medium;
let low_priority = MemoryPriority::Low;

// Store memories with priority
memory.store_with_priority("Important user information", high_priority).await?;
memory.store_with_priority("General conversation content", medium_priority).await?;
memory.store_with_priority("Temporary context information", low_priority).await?;

// Configure retention policy
let retention_policy = RetentionPolicy::new()
    .with_max_memories(1000)
    .with_ttl_for_priority(MemoryPriority::Low, Duration::from_days(7))
    .with_ttl_for_priority(MemoryPriority::Medium, Duration::from_days(30))
    .with_ttl_for_priority(MemoryPriority::High, Duration::from_days(365));

memory.set_retention_policy(retention_policy);

Memory Retrieval Optimization

Optimize memory retrieval performance and accuracy:

use rwkv_agent_kit::memory::{SearchStrategy, RetrievalOptimizer};

// Create retrieval optimizer
let optimizer = RetrievalOptimizer::new()
    .with_strategy(SearchStrategy::Hybrid) // Hybrid retrieval strategy
    .with_reranking(true) // Enable reranking
    .with_cache_size(100); // Set cache size

// Optimized memory retrieval
let query = "User's work-related information";
let optimized_results = optimizer
    .search(&memory, query)
    .with_context_boost(0.2) // Context enhancement
    .with_recency_boost(0.1) // Recency enhancement
    .execute().await?;

for result in optimized_results {
    println!("Search result: {} (score: {:.3})", result.content, result.score);
}

Advanced Features

Memory Fusion

Fuse multiple related memories into more complete information:

use rwkv_agent_kit::memory::MemoryFusion;

// Create memory fusion
let fusion = MemoryFusion::new();

// Fuse related memories
let related_memories = vec![
    "User is a programmer",
    "User uses Python",
    "User works at a tech company",
    "User is interested in AI"
];

let fused_memory = fusion.fuse_memories(related_memories).await?;
println!("Fused memory: {}", fused_memory);

Memory Validation

Validate memory consistency and accuracy:

use rwkv_agent_kit::memory::MemoryValidator;

// Create memory validator
let validator = MemoryValidator::new();

// Validate memory consistency
let memories_to_validate = vec![
    "User lives in Beijing",
    "User works in Shanghai", // Potential conflict
    "User likes to travel"
];

let validation_result = validator.validate_consistency(memories_to_validate).await?;
if let Some(conflicts) = validation_result.conflicts {
    for conflict in conflicts {
        println!("Conflict found: {} vs {}", conflict.memory1, conflict.memory2);
    }
}

Memory Visualization

Generate visual representations of memory networks:

use rwkv_agent_kit::memory::MemoryVisualizer;

// Create memory visualizer
let visualizer = MemoryVisualizer::new();

// Generate memory network graph
let memory_graph = visualizer
    .create_graph(&memory)
    .with_clustering(true)
    .with_layout("force_directed")
    .generate().await?;

// Export to different formats
visualizer.export_as_svg(&memory_graph, "memory_network.svg").await?;
visualizer.export_as_json(&memory_graph, "memory_network.json").await?;

Best Practices

Memory Design Principles

  1. Structured Storage: Use consistent data structures to store memories
  2. Semantic Richness: Include sufficient contextual information
  3. Temporal Marking: Record memory creation and update times
  4. Associativity: Establish relationships between memories

Performance Optimization

  • Batch Operations: Batch store and retrieve memories
  • Index Optimization: Build indexes for common queries
  • Caching Strategy: Cache frequently accessed memories
  • Asynchronous Processing: Use async operations for better responsiveness

Privacy Protection

  • Sensitive Information Detection: Automatically identify and protect sensitive information
  • Access Control: Implement fine-grained memory access control
  • Data Encryption: Encrypt sensitive memories in storage
  • Regular Cleanup: Regularly clean up expired and unnecessary memories

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