daidocs
Active·★ 53·Apache-2.0·Updated 2026-10-07
DaiDocs introduces an open, plain-text file format (.dai) for AI assistant memory, allowing memory to reside as files on your local disk that are readable by any tool or model. It boasts high performance on the LongMemEval-S benchmark, significantly outperforming models without a dedicated memory system while reading substantially fewer tokens.
#AI Memory#Plain-Text Format#LLM Context Management#Retrieval Augmented Generation#Agent Memory#Local-First#Benchmarked#Cross-Model Compatibility
01
Features
01Open, plain-text `.dai` file format for AI memory, ensuring data persistence and inspectability.
02Language and model agnostic, readable by any tool (grep, git) and multiple LLMs (Claude, GPT, Gemini).
03Automatic and keyless session saving to local disk, converting conversations into memory files.
04Benchmarked as second on LongMemEval-S, significantly reducing token usage for retrieval (10x fewer tokens).
02
Compatibility
Node.js
Runtime
Verified via docs
Python
Runtime
Verified via docs
Claude Code
IDE Integration
Verified via docs
LLM Frameworks (MCP)
Integration
Verified via docs
Cross-Platform
OS Compatibility
Verified via docs
03
Quick start
1
$ npx daidocs setup
04
Use cases
↳Storing AI assistant conversations as persistent, local files for long-term memory and easy inspection.
↳Integrating with various LLM agents and frameworks (e.g., LangChain, CrewAI) for enhanced memory recall.
↳Converting existing conversation histories from multiple sources into a unified, searchable memory store.
↳Enabling project-specific context and memory for development workflows within IDEs and CLI tools.
05
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