MemoriLabs/Memori
memori
SQL Native Memory Layer for LLMs, AI Agents & Multi-Agent Systems
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MemoriLabs
MemoriLabs • individual
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Created
Jul 24, 2025
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README Summary
Memori is a SQL-native memory layer designed specifically for LLMs, AI agents, and multi-agent systems. It provides a structured approach to storing and retrieving conversational context and agent memory using SQL databases. The system enables persistent memory management across AI interactions with query-based memory retrieval.
AI Dev Skills
Unmapped
Large Language Model IntegrationAI Agent Memory SystemsConversational AI State ManagementSQL-based Knowledge StorageMulti-Agent System ArchitectureLLM Context Management
Tags
Large Language Model IntegrationAI Agent Memory SystemsConversational AI State ManagementSQL-based Knowledge StorageMulti-Agent System ArchitectureLLM Context ManagementContextual Information RetrievalCompound AI SystemsStateful AI ApplicationsEnterprise SoftwareConversational AISQL Database IntegrationPersistent AI State ManagementMulti-Agent SystemsAgentic AIAI Assistant State ManagementCross-Session Knowledge RetentionMulti-Agent CoordinationTextPersistent Chat MemoryDeveloper ToolsSelf-hostedMemory Management for AI SystemsOn-premiseDatabase-Backed AI ApplicationsCloudPython
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Recent Activity
Updated 27 days ago
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Quality
prototype- Quality
- medium
- Maturity
- prototype
Categories
Dev Tools & AutomationPrimaryEdge & Mobile AISearch & KnowledgeOther AI / MLRAG & RetrievalEvals & BenchmarkingRoboticsFoundation ModelsAI Agents
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Developer Platform
Languages
Python100.0%
Timeline
- Project created
- Jul 24, 2025
- Forked
- Mar 13, 2026
- Your last push
- 27 days ago
- Upstream last push
- 7 days ago
- Tracked since
- Mar 17, 2026
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