knowledge-graph
Inside retain(): What Actually Happens When Your Agent Remembers
Calling retain() is one line of code. Underneath, a sentence becomes extracted facts, resolved entities, a knowledge graph, and consolidated observations. Here is the whole write path.
Entity Resolution in Agent Memory: One Person, Many Names
How agent memory decides that Sarah, Sarah Chen, and she are one person, and why Hindsight resolves entities with a co-occurrence graph, not embeddings.
Pipecat Voice AI Persistent Memory: Add Memory to Your Voice Pipeline
Add persistent long-term memory to Pipecat voice AI pipelines. Recall relevant past conversations and retain new exchanges with a single FrameProcessor between your user aggregator and LLM service.
Pydantic AI Persistent Memory: Add It in 5 Lines of Code
If you have built an AI agent with Pydantic AI, you already know it handles typed outputs, dependency injection, and async workflows well. But there is one thing it does not do: remember anything between runs. Every call to agent.run() starts with a blank slate. Your agent has no idea what the user said yesterday, what preferences they shared, or what it already researched.
How to Add Persistent Memory to OpenClaw with Hindsight
OpenClaw's built-in memory depends on the agent deciding what to save — and models don't do this consistently. Hindsight replaces it with automated extraction and auto-recall: every conversation is captured, facts and entities are extracted in the background, and relevant context is injected before every response automatically. One plugin install, one setup wizard, no Docker.