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pocketpaw/docs/memory/index.mdx
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Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-08 17:41:36 +05:30

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---
title: "Memory Overview: How PocketPaw Remembers"
description: "PocketPaw uses a two-tier memory system: file-based session storage for conversation history and optional Mem0 semantic memory for auto-learned long-term knowledge with vector search."
section: Memory
ogType: article
keywords: ["memory system", "session storage", "semantic memory", "mem0", "vector search"]
tags: ["memory", "overview"]
---
# Memory Overview: How PocketPaw Remembers
PocketPaw uses a two-tier memory system: file-based sessions for conversation history and optional Mem0 for semantic long-term memory.
<CardGroup>
<Card title="File Store" icon="lucide:database" href="/memory/file-store">
JSON-based session storage with indexing and search.
</Card>
<Card title="Mem0 Integration" icon="lucide:sparkles" href="/memory/mem0">
Semantic memory with auto-learning and vector search.
</Card>
<Card title="Sessions" icon="lucide:history" href="/memory/sessions">
Session management, grouping, and search.
</Card>
<Card title="Context Building" icon="lucide:layers" href="/memory/context-building">
How memory is assembled into the agent's context window.
</Card>
<Card title="Memory Isolation" icon="lucide:shield" href="/memory/memory-isolation">
Per-user memory scoping for multi-channel deployments.
</Card>
</CardGroup>
## Memory Architecture
```
┌─────────────────────────────────────┐
│ Context Builder │
│ (Assembles context for the agent) │
├──────────┬──────────────────────────┤
│ │ │
│ File │ Mem0 Semantic │
│ Store │ Memory (optional) │
│ │ │
│ Sessions │ Auto-learn │
│ Facts │ Semantic search │
│ Index │ Vector store │
└──────────┴──────────────────────────┘
```
## Quick Setup
### File Store (Default)
No configuration needed. Sessions are automatically saved to `~/.pocketpaw/memory/`.
### Mem0 (Optional)
For semantic memory with auto-learning:
```bash
curl -fsSL https://pocketpaw.xyz/install.sh | sh
# Or add the memory extra manually
pip install pocketpaw[memory]
export POCKETPAW_MEM0_AUTO_LEARN=true
export POCKETPAW_MEM0_LLM_PROVIDER="ollama"
export POCKETPAW_MEM0_LLM_MODEL="llama3.2"
export POCKETPAW_MEM0_EMBEDDER_PROVIDER="ollama"
export POCKETPAW_MEM0_EMBEDDER_MODEL="nomic-embed-text"
```