atmanai-dev/create-char-passport-storage
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AI & ML interests
Memory augmentation, RAG, local LLMs, embeddings, NER, cognitive AI systems
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Atman · Persistent Memory Layer for AI Agents
In Indian philosophy, Atman is the unchanging self — the core that remains constant through all change. We give AI agents the same thing.
The Problem
Your agent can reason, write code, and explain quantum mechanics. But the moment a session ends — it forgets everything about itself.
Not just facts. The sense of continuity. Who it spoke to, what it learned, how it changed its mind. Every session starts from a stack of notes: "you're this kind of agent, these are your values" — taken on faith, not lived experience.
Atman fixes this.
What It Is
A local memory and context system that runs alongside your LLM — augmenting cognitive capabilities without steering opinions or output.
Seven components work together:
| Component | What it does |
|---|---|
| Factual Memory | Verifiable facts with relations, no hallucination layer |
| Experience Store | First-person lived session experiences with salience decay |
| Identity Store | Stable self-model: principles, values, behavioral anchors |
| Reflection Engine | Between-session processing — finds patterns, refines principles |
| Session Manager | Assembles coherent context on session start |
| Reality Anchor | Detects identity drift during context pressure |
| Affective Regulation | Emotional tone calibration without pretense |
Key Properties
- Local-first — Postgres + pgvector + Ollama, no cloud required
- Model-agnostic — OpenAI-compatible endpoint or Anthropic SDK, config-only switching
- Russian/English bilingual — hard requirement throughout all components
- Augments, doesn't steer — improves retrieval and grounding; never influences opinions
- Optional eval isolation — all research/benchmark tooling in
atman[eval], zero prod leakage
Architecture
Session start
Session Manager pulls together:
Identity Store — who the agent is Experience Store — what it lived through
Factual Memory — what it knows
Reflection output — what it concluded last time
During session
Reality Anchor watches for identity drift in real time
Session end
Reflection Engine processes the session
→ updates Identity Store
→ updates Experience Store
Status
● Research ✅ Complete
● Design ✅ Complete
● Prototyping ← We are here
├─ Factual Memory ✅ Stable (v0.1.0)
├─ Experience Store ✅ Stable (WP02)
├─ Session Manager 🔧 High readiness — debugging (current focus)
├─ Reflection Engine 🔧 Medium readiness — in development
├─ Skill Manager 🔧 Medium readiness — in development
├─ Identity Store 🔧 Low readiness — in development
└─ CI & test coverage ✅ GitHub Actions on `main`/PRs (`make check`, pytest-cov ≥90%)
○ First production slice
○ Integration
○ Evolution
Stack
- Python 3.11 · Pydantic · PostgreSQL + pgvector
- BGE-M3 + bge-reranker-v2-m3 (hybrid retrieval)
- LlamaIndex · httpx · Anthropic SDK
Links
- 🌐 atmanai.dev
- 📖 Manifesto
- 🏗 Architecture docs
- 💻 GitHub
Atman is a hypothesis in the form of a system: that behavioral consistency, accumulated experience, and reflective capacity are sufficient conditions for something worth calling identity.
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