Persistent Memory API

The Persistent Memory API provides configurable memory retrieval and storage capabilities, enabling agents to access and utilize persistent knowledge across sessions through customizable pipelines.

Overview

The persistent memory module enables you to:

• Memory Configurations: Create configurable memory access patterns
• Retrieval Pipelines: Define how data is retrieved from various sources
• Contribution Formats: Control how data is formatted and returned
• Multi-Source: Access vector databases, KV stores, event logs, and knowledge graphs
• Validation: Test and validate memory configurations before deployment

Quick Start Example

// Wait for connection
await codebolt.waitForReady();

// Create a persistent memory configuration
const memory = await codebolt.persistentMemory.create({
    label: 'Code Context Memory',
    description: 'Retrieves relevant code context for development tasks',
    inputs_scope: ['codebolt.project', 'codebolt.file'],
    retrieval: {
        source_type: 'vectordb',
        source_id: 'code-vectors',
        query_template: 'Find relevant code for {context}',
        limit: 10
    },
    contribution: {
        format: 'markdown',
        template: '## Relevant Code\n\n{results}',
        max_tokens: 2000
    }
});

// Execute retrieval with context
const result = await codebolt.persistentMemory.executeRetrieval(
    memory.data.memory.id,
    {
        query: 'How is authentication implemented?',
        context: { task: 'code_review' }
    }
);

console.log('Retrieved memory:', result.data.result);

Response Structure

All persistent memory API functions return responses with a consistent structure:

{
    type: string,
    success: boolean,
    data?: {
        memory: {
            id: string,
            label: string,
            description?: string,
            status: 'active' | 'disabled' | 'draft',
            inputs_scope: string[],
            retrieval: RetrievalConfig,
            contribution: ContributionConfig,
            createdAt: string,
            updatedAt: string
        },
        result?: any
    },
    message?: string,
    error?: string,
    timestamp: string,
    requestId: string
}

Key Concepts

Memory Configuration

Defines how agents access persistent knowledge through configurable pipelines.

Retrieval Sources

• vectordb: Vector similarity search
• kv: Key-value store lookup
• eventlog: Event log queries
• kg: Knowledge graph queries

Input Scope

Defines which inputs the memory configuration applies to (e.g., specific project types).

Contribution Format

Controls how retrieved data is formatted:

• text: Plain text output
• json: Structured JSON
• markdown: Markdown formatted

Pipeline Execution

Retrieval is triggered by execution intents with context, keywords, and queries.

Validation

Test configurations before activating to ensure they work correctly.

• create - Creates a new persistent memory configuration.
• get - Gets a persistent memory by ID.
• list - Lists persistent memories with optional filters.
• update - Updates a persistent memory configuration.
• delete - Deletes a persistent memory.
• executeRetrieval - Executes memory retrieval pipeline.
• validate - Validates a memory configuration.
• getStepSpecs - Gets available step specifications.