KI-Agenten
agent-memory
Long-term memory runtime for AI agents — plain Markdown as truth, local ranked retrieval, no API key
★ 2,6 Tsd. SterneMIT
Anleitung ansehen →LongMemory ist ein Open-Source-Projekt aus der Kategorie KI-Agenten von CaviraOSS (CaviraOSS/LongMemory auf GitHub). Es hat 4.523 Sterne auf GitHub und 506 Forks, wird unter der Lizenz Apache-2.0 veröffentlicht und wurde zuletzt am 20. September 2026 auf GitHub aktualisiert.
LongMemory: local-first memory for AI agents with temporal truth, provenance, and hybrid recall
Use the npm library in-process, the global CLI, the Docker/HTTP server, or the MCP server for agent clients.
Install the package from npm (or the Python SDK from PyPI).
Create a memory instance or run the CLI init to create a local database.
Ingest a first fact or conversation, then recall it with the mode that fits your question.
Records keep both recorded time and valid time, so facts can change without rewriting history.
Source, author, confidence, and timestamps travel with memory items; nothing is silently lost.
Strict, historical, associative, and world-grounded recall over BM25, vector, and graph signals.
Tenant, user, project, session, and role scopes, with encryption at rest and a tamper-evident audit trail (per the README).
In-process library, CLI, HTTP server on port 7331, Docker image, MCP server, dashboard, and VS Code extension.
OpenAI-compatible endpoints, Google Gemini, Amazon Bedrock, Ollama, or a built-in local embedder.
Clone the project and enter its directory for the source/server path.
git clone https://github.com/CaviraOSS/LongMemory.git
cd LongMemoryAdd it to a Node project, or install the CLI globally.
npm install longmemory
# or: npm install --global longmemoryInitialize a database and run your first recall from the CLI.
longmemory init
longmemory recall "current project priorities" --mode associativeCaviraOSS publishes LongMemory (server images under ghcr.io/caviraoss); it is an open-source project.
Yes, Apache-2.0 licensed and local-first — your data stays in a local SQLite database unless you choose otherwise.
Not necessarily: local and Ollama embedding options avoid hosted APIs; choosing OpenAI, Gemini, or Bedrock embeddings uses your own keys.
A vector store returns similar chunks. LongMemory adds typed records, temporal validity, provenance, governance scopes, and recall modes that combine keyword, vector, and graph signals.
Run `npm install longmemory` and use `createMemory()`, or install the CLI globally and run `longmemory init` then `longmemory recall`.
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