KI-Agenten
hindsight
Agent memory that learns — so your agents get smarter over time.
★ 47,0 Tsd. SterneMIT
Anleitung ansehen →letta ist ein Open-Source-Projekt aus der Kategorie KI-Agenten von letta-ai (letta-ai/letta auf GitHub). Es hat 25.073 Sterne auf GitHub und 2.643 Forks, wird unter der Lizenz Apache-2.0 veröffentlicht und wurde zuletzt am 10. September 2026 auf GitHub aktualisiert.
Stateful AI agents with memory that learns and improves.
Choose one real workload to test the project against.
Clone it locally and read through the getting-started guide.
Install the stack it needs and set any environment variables.
Execute the starter example and check results before going further.
Agents that persist state across sessions.
Memory systems designed for long-term learning.
Agents that refine behavior over time.
More than a library — a full agent platform.
Permissive licensing.
25k+ stars and an active community.
Install Letta from PyPI.
pip install lettaAdd your model provider keys per the docs.
# see docs for server vs. local setupFollow the quickstart to launch your first stateful agent.
# see README for the exact CLI commandsIt is maintained by the letta-ai organization at letta-ai/letta, with 2,643 forks. The docs site tracks current development.
Yes. It is released under the Apache-2.0 license, which permits commercial use, modification, and redistribution. Read the LICENSE file for the exact terms.
You need model API access; check the docs for managed versus self-hosted options.
Compare memory models and statefulness — persistent, learning memory is Letta's core pitch.
Read the docs, install the package, and follow the quickstart to run your first agent.
Agent memory that learns — so your agents get smarter over time.
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Die anderen Projekte der Kategorie KI-Agenten mit den meisten Sternen im LibreAI-Katalog — die realistische Auswahl, falls letta nicht das Richtige ist.
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Verwandte Projekte der Kategorie KI-Agenten im Katalog, die letta bei den Sternen am nächsten stehen — zum Weiterstöbern auf beiden Seiten.
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Kostenlos und offen — hol dir den Quellcode, gib dem Repository einen Stern und leg los.