roampal-ai
roampal
Python

Memory that learns what works.

Last updated Aug 1, 2026
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README

Roampal

Status Python 3.10+ Built with Tauri Multi-Provider License

Memory that learns what works. So you can do more of it.

Say it worked. Say it didn't. The AI remembers.

Stop re-explaining yourself every conversation. Roampal remembers outcomes, learns from feedback, and gets smarter over timeโ€”all 100% private and local.

Roampal - AI Chat with Persistent Memory

85.8% non-adversarial on LoCoMo (1,986 questions). +23 pts over raw ingestion. Absorbs 1,135 poison memories losing only 4 pts. (Paper)

GitHub Stars


Benchmark Results

LoCoMo dataset (1,986 questions, 5 categories, corrected ground truths). Evaluated with roampal-labs. Dual-graded by local 20B + MiniMax M2.7.

| Metric | Result | |--------|--------| | Non-adversarial accuracy (MiniMax-regraded) | 85.8% | | Overall (all 5 categories) | 76.6% | | vs raw ingestion baseline | +23 pts (76.6% vs 53.0%, p<0.0001) | | Poison resilience | -4.2 pts after 1,135 adversarial memories | | No-memory baseline | 6.0% (model has zero LoCoMo knowledge) | | Architecture vs model | Architecture: +23 pts. Model swap (GPT-4o-mini): 1.5-2.5 pts |

  • System learns through natural conversation, not transcript ingestion
  • Absorbs 1,135 poison memories with spoofed trust signals, retaining 72.4% accuracy
  • Wilson scoring hurts retrieval at every stage (p<0.001) โ€” removed from ranking
Component-level retrieval ablation

| Config | Hit@1 Clean | Hit@1 Poison | p-value | |--------|-------------|--------------|---------| | TagCascade + cosine | 27.3% | 29.0% | baseline | | Overlap + cosine | 25.8% | 28.0% | p=0.0003 | | Pure CE | 25.4% | 28.4% | โ€” | | TagCascade + Wilson | 23.0% | 25.0% | p<0.0001 |

  • Cross-encoder: +17.8 Hit@1 over cosine (p<0.0001)
  • Tag routing (two-lane): +6.1 Hit@1 clean, +7.5 poison (p<0.0001)
  • Wilson: -4.3 Hit@1 in every configuration
  • Nursery slot: zero benefit (p=1.0)
Full methodology in roampal-labs


Quick Start

Your AI starts learning about you immediately.

Table of Contents


Key Features

Memory That Learns

  • Outcome tracking: Scores every result (+0.2 worked, -0.3 failed)
  • Smart promotion: Good advice becomes permanent, bad advice auto-deletes
  • Cross-conversation: Recalls from ALL past chats
Your Knowledge Base
  • Memory Bank: Permanent storage of preferences, identity, goals
  • Books: Upload .txt/.md docs as searchable reference
  • Pattern recognition: Detects what works across conversations
Privacy First
  • 100% local: All data on your machine
  • Works offline: No internet after model download
  • No telemetry: Your data never leaves your computer

MCP Integration

Connect Roampal to Claude Desktop, Cursor, and other MCP-compatible tools.

Settings โ†’ Integrations โ†’ Connect โ†’ Restart your tool

7 tools available: searchmemory, addtomemorybank, updatememory, archivememory, getcontextinsights, recordresponse, scorememories

Full MCP documentation โ†’


Architecture

โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚                    5-TIER MEMORY                        โ”‚
โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค
โ”‚   Books     โ”‚   Working   โ”‚   History   โ”‚   Patterns   โ”‚
โ”‚ (permanent) โ”‚   (24h)     โ”‚  (30 days)  โ”‚  (permanent) โ”‚
โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค
โ”‚                    Memory Bank                          โ”‚
โ”‚            (permanent user identity/prefs)              โ”‚
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜

Core Technology:

  • TagCascade Retrieval: Tag-routed search + cross-encoder reranking (ONNX)
  • Outcome-Based Learning: Memories adapt based on feedback
  • Sidecar LLM: Background model summarizes exchanges, extracts facts and tags
Architecture deep-dive โ†’


Supported Models

Works with any tool-calling model via Ollama or LM Studio:

| Model | Provider | Parameters | |-------|----------|------------| | Llama 3.x | Meta | 3B - 70B | | Qwen 2.5 | Alibaba | 3B - 72B | | Mistral/Mixtral | Mistral AI | 7B - 8x22B | | GPT-OSS | OpenAI (Apache 2.0) | 20B - 120B |


Documentation

| Document | Description | |----------|-------------| | Architecture | 5-tier memory, retrieval pipeline, technical deep-dive | | Benchmarks | LoCoMo evaluation, TagCascade results | | Release Notes | Latest (v0.3.3): multimodal image input, dynamic capability + context detection, ChromaDB phantom-handling closing issue #8, atomic config writes, Harmony token cleanup |


Important Notices

AI Safety: LLMs may generate incorrect information. Always verify critical information. Don't rely on AI for medical, legal, or financial advice.

Model Licenses: Downloaded models (Llama, Qwen, etc.) have their own licenses. Review before commercial use.


Support

  • Discord: https://discord.gg/F87za86R3v
  • Email: roampal@protonmail.com
  • GitHub: https://github.com/roampal-ai/roampal/issues
  • Author: Logan Teague

Pricing

Free & open-source (Apache 2.0 License)

  • Build from source โ†’ completely free
  • Pre-built executable: $19.99 one-time (saves hours of setup)
  • Zero telemetry, full data ownership

Made with love for people who want AI that actually remembers

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