vizra-ai/vizra-adk/vizra-memory

Claude Code and agent skill by vizra-ai/vizra-adk

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Implement persistent memory, session context, and vector memory (RAG) for AI agents

Install

npx vskill@latest install vizra-ai/vizra-adk/vizra-memory

SKILL.md

Vizra ADK Memory System

Vizra ADK provides multiple memory types for agents to maintain context across conversations and sessions.

Memory Types

TypePurposePersistence
Session MemoryConversation history within a sessionSession lifetime
User MemoryInformation tied to a specific userPermanent
Vector MemorySemantic search and RAGPermanent

Basic Memory Usage

Session-Based Memory

Conversation history persists within a session:

php
use App\Agents\MyAgent;
$sessionId = 'conversation-123';
// First message in session
$response1 = MyAgent::run('My name is John')
->forUser($user)
->withSession($sessionId)
->go();
// Later in the same session - agent remembers context
$response2 = MyAgent::run('What is my name?')
->forUser($user)
->withSession($sessionId)
->go(); // Will remember "John"
User-Based Memory

Memory persists across all sessions for a user:

php
// First conversation
$response1 = MyAgent::run('I prefer dark mode and short responses')
->forUser($user)
->go();
// New conversation - user preferences are remembered
$response2 = MyAgent::run('Help me with my project')
->forUser($user)
->go(); // Agent remembers preferences

Memory Tools

MemoryTool

Allow agents to explicitly store and retrieve memories:

php
use Vizra\VizraADK\Tools\MemoryTool;
class PersonalAssistantAgent extends BaseLlmAgent
{
protected string $name = 'personal_assistant';
protected string $instructions = <<<'INSTRUCTIONS'
You are a personal assistant. Use the memory tool to:
- Remember important facts the user tells you
- Recall information when asked
- Update memories when information changes
INSTRUCTIONS;
protected array $tools = [
MemoryTool::class,
];
}

The agent can then use commands like:

  • remember: User's birthday is March 15
  • recall: birthday
  • forget: old address
VectorMemoryTool

Enable semantic search for RAG (Retrieval Augmented Generation):

php
use Vizra\VizraADK\Tools\VectorMemoryTool;
class KnowledgeAgent extends BaseLlmAgent
{
protected string $name = 'knowledge_agent';
protected string $instructions = <<<'INSTRUCTIONS'
You are a knowledge assistant with access to the company documentation.
Use the vector memory tool to search for relevant information before answering questions.
Always cite the source of information.
INSTRUCTIONS;
protected array $tools = [
VectorMemoryTool::class,
];
}

Programmatic Memory Access

Storing Memories
php
use Vizra\VizraADK\Services\MemoryManager;
$memoryManager = app(MemoryManager::class);
// Store a memory for a user
$memoryManager->store(
userId: $user->id,
key: 'preferences',
value: [
'theme' => 'dark',
'language' => 'en',
'notifications' => true
]
);
// Store with tags for organization
$memoryManager->store(
userId: $user->id,
key: 'project_alpha_notes',
value: $notes,
tags: ['projects', 'alpha', 'notes']
);
Retrieving Memories
php
// Get specific memory
$preferences = $memoryManager->get($user->id, 'preferences');
// Get all memories with a tag
$projectMemories = $memoryManager->getByTag($user->id, 'projects');
// Search memories
$results = $memoryManager->search($user->id, 'project deadline');
Updating and Deleting
php
// Update existing memory
$memoryManager->update(
userId: $user->id,
key: 'preferences',
value: array_merge($currentPrefs, ['theme' => 'light'])
);
// Delete specific memory
$memoryManager->delete($user->id, 'old_data');
// Clear all user memories
$memoryManager->clearUser($user->id);

Vector Memory for RAG

Storing Documents
php
use Vizra\VizraADK\Services\VectorMemoryManager;
$vectorManager = app(VectorMemoryManager::class);
// Store a document with automatic chunking
$vectorManager->store(
content: $documentContent,
metadata: [
'source' => 'company_handbook',
'section' => 'policies',
'updated_at' => now()
]
);
// Store multiple documents
$vectorManager->storeMany([
['content' => $doc1, 'metadata' => ['type' => 'policy']],
['content' => $doc2, 'metadata' => ['type' => 'guide']],
]);
Searching Vector Memory
php
// Semantic search
$results = $vectorManager->search(
query: 'What is the vacation policy?',
limit: 5
);
// Search with metadata filter
$results = $vectorManager->search(
query: 'onboarding process',
limit: 5,
filter: ['type' => 'guide']
);
CLI Commands
bash
# Store documents from file
php artisan vizra:vector:store --file=handbook.pdf
# Store directory of documents
php artisan vizra:vector:store --directory=docs/
# Search vector memory
php artisan vizra:vector:search "vacation policy"
# View statistics
php artisan vizra:vector:stats

Memory Patterns

Building User Profiles
php
class ProfileBuildingAgent extends BaseLlmAgent
{
protected string $instructions = <<<'INSTRUCTIONS'
Build a comprehensive user profile by:
1. Asking about their preferences gradually
2. Remembering details they share
3. Inferring preferences from behavior
4. Updating profile as preferences change
INSTRUCTIONS;
protected array $tools = [
MemoryTool::class,
];
public function afterExecution($response, $context)
{
// Extract and store any preferences mentioned
$this->extractAndStorePreferences($response, $context);
}
}
Context-Aware Responses
php
class ContextAwareAgent extends BaseLlmAgent
{
public function beforeExecution($input, $context)
{
// Load relevant memories before processing
$memories = $this->loadRelevantMemories($context);
// Inject into context
$context->setParameter('user_context', $memories);
return $input;
}
protected function loadRelevantMemories($context)
{
$memoryManager = app(MemoryManager::class);
return [
'preferences' => $memoryManager->get($context->getUserId(), 'preferences'),
'recent_topics' => $memoryManager->getByTag($context->getUserId(), 'recent'),
'important' => $memoryManager->getByTag($context->getUserId(), 'important'),
];
}
}
Conversation Summarization
php
class SummarizingAgent extends BaseLlmAgent
{
protected int $maxHistoryLength = 50;
public function beforeExecution($input, $context)
{
$history = $context->getHistory();
if (count($history) > $this->maxHistoryLength) {
// Summarize older messages
$toSummarize = array_slice($history, 0, -20);
$summary = $this->summarize($toSummarize);
// Store summary and trim history
$context->setParameter('conversation_summary', $summary);
$context->setHistory(array_slice($history, -20));
}
return $input;
}
protected function summarize($messages)
{
return SummarizerAgent::run(json_encode($messages))
->withParameters(['style' => 'concise'])
->go();
}
}

Memory Configuration

Config File Settings
php
// config/vizra-adk.php
return [
'memory' => [
// Default memory driver
'driver' => env('VIZRA_MEMORY_DRIVER', 'database'),
// Memory TTL (time to live)
'ttl' => env('VIZRA_MEMORY_TTL', 86400 * 30), // 30 days
// Maximum memories per user
'max_per_user' => env('VIZRA_MAX_MEMORIES', 1000),
],
'vector_memory' => [
// Embedding provider
'provider' => env('VIZRA_EMBEDDING_PROVIDER', 'openai'),
// Embedding model
'model' => env('VIZRA_EMBEDDING_MODEL', 'text-embedding-3-small'),
// Vector store
'store' => env('VIZRA_VECTOR_STORE', 'meilisearch'),
// Chunk size for documents
'chunk_size' => env('VIZRA_CHUNK_SIZE', 500),
// Chunk overlap
'chunk_overlap' => env('VIZRA_CHUNK_OVERLAP', 50),
],
];
Environment Variables
env
# Memory settings
VIZRA_MEMORY_DRIVER=database
VIZRA_MEMORY_TTL=2592000
# Vector memory / Embeddings
VIZRA_EMBEDDING_PROVIDER=openai
VIZRA_EMBEDDING_MODEL=text-embedding-3-small
VIZRA_VECTOR_STORE=meilisearch
MEILISEARCH_HOST=http://localhost:7700
MEILISEARCH_KEY=your-master-key

Best Practices

1. Scope Memories Appropriately
php
// Good: User-specific memory
$memoryManager->store($user->id, 'preferences', $prefs);
// Good: Session-specific for temporary data
$context->setSessionData('current_task', $task);
// Bad: Global memory without user scope
$memoryManager->store(null, 'data', $data);
2. Clean Up Old Memories
php
// Periodic cleanup
$memoryManager->deleteOlderThan($user->id, now()->subMonths(6));
// Or use TTL on store
$memoryManager->store($user->id, 'temp_data', $data, ttl: 3600);
3. Structure Memory Keys
php
// Good: Hierarchical keys
$memoryManager->store($user->id, 'projects.alpha.deadline', $date);
$memoryManager->store($user->id, 'projects.alpha.status', 'active');
// Good: Use tags for cross-cutting concerns
$memoryManager->store($user->id, 'note_123', $note, tags: ['notes', 'project_alpha']);
4. Handle Memory Limits
php
class MemoryAwareAgent extends BaseLlmAgent
{
public function beforeExecution($input, $context)
{
$history = $context->getHistory();
// Limit token usage
if ($this->estimateTokens($history) > 4000) {
$history = $this->trimHistory($history, 4000);
$context->setHistory($history);
}
return $input;
}
}

Database Tables

Memories are stored in these tables:

  • agent_memories - Key-value persistent memories
  • agent_sessions - Session data
  • agent_messages - Conversation history
  • agent_vector_memories - Vector embeddings

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewNot runA model review is scheduled for the next rescan.

Quality evaluation

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Source

Popularity

Repository stars
291
Repository forks
36
7-day trend score
28

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 8 Apr 2026, 6 months ago.

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