Which AI providers are supported for the memory system?

It supports a wide range of providers including OpenAI, Anthropic, Google AI, Azure, OpenRouter, and local models via Ollama.

Do I need Docker to use this memory system?

No, it uses an embedded LadybugDB, meaning no external containers or database services are required for local storage.

How does the memory system capture information?

The system automatically extracts insights and patterns during sessions and stores them as 'episodes' in a knowledge graph for future retrieval.

Can I use this for local-only development?

Yes, by configuring the Ollama provider for both LLM and embeddings, you can run the entire memory system offline.

Auto-Claude Memory System

Name: Auto-Claude Memory System
Author: adaptationio

byadaptationio

데이터 과학 및 ML

Implements a persistent knowledge graph memory system for Auto-Claude to retain context and learn patterns across development sessions.

소개

The Auto-Claude Memory System leverages Graphiti and LadybugDB to provide cross-session context retention for Claude Code. By building a persistent knowledge graph of entities, relationships, and session insights, it allows the AI to remember architecture patterns, previous solutions, and project-specific gotchas without needing external databases like Docker. It supports multiple providers including OpenAI, Anthropic, and local-first options like Ollama, ensuring seamless context recovery and improved decision-making in long-term projects.

주요 기능

Multi-provider support for OpenAI, Anthropic, Voyage, and local Ollama models
0 GitHub stars
Graphiti-based persistent knowledge graph for cross-session context retention
Automated insight extraction to capture patterns and solutions naturally
Semantic search capabilities to find relevant entities and relationships
Embedded LadybugDB storage requiring no Docker or external database setup

사용 사례

Maintaining long-term architectural patterns across multiple coding sessions
Recalling specific project gotchas and previously implemented solutions
Creating a searchable knowledge base of a complex codebase during development

소개

주요 기능

Multi-provider support for OpenAI, Anthropic, Voyage, and local Ollama models
0 GitHub stars
Graphiti-based persistent knowledge graph for cross-session context retention
Automated insight extraction to capture patterns and solutions naturally
Semantic search capabilities to find relevant entities and relationships
Embedded LadybugDB storage requiring no Docker or external database setup

사용 사례

Maintaining long-term architectural patterns across multiple coding sessions
Recalling specific project gotchas and previously implemented solutions
Creating a searchable knowledge base of a complex codebase during development