agentmemory-python / ROADMAP.md
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Roadmap

This is agentmemory-python's public roadmap. Items shift as priorities change.

  • Shipped β€” in main
  • Active β€” has an open PR
  • Planned β€” accepted, not started
  • Candidate β€” under consideration

Phase 1 β€” Foundation (done)

  • Python + Flask server replacing Node.js / iii-engine
  • SQLite WAL backend replacing Dolt SQL
  • Audit log replacing Dolt git versioning
  • BM25 search with Porter stemmer
  • Gemini 768-dim vector search + hybrid RRF fusion
  • 16-tool MCP endpoint
  • WebSocket live stream
  • Built-in HTML viewer (Dashboard, Sessions, Memories, Graph, Timeline, Lessons, Slots, Replay)
  • Knowledge graph visualization β€” folder nodes with unique colors, force-directed layout
  • 4-tier memory consolidation (Working β†’ Episodic β†’ Semantic β†’ Procedural)
  • Lessons system with confidence decay
  • HuggingFace Space deployment with sync fingerprinting
  • Dolt β†’ SQLite one-time migration (7502 rows, 19.6MB)

Phase 2 β€” Reliability

Active

  • Pytest test coverage for src/functions.py core operations (observe, remember, search, context)
  • Graph edge label bug β€” labels overlap at default zoom on dense graphs

Planned

  • Additional embedding providers β€” OpenAI text-embedding-3-small, local sentence-transformers
  • Hook scripts β€” prebuilt bash/PowerShell hook scripts for Claude Code, Cursor, Codex CLI pointing at http://localhost:3111
  • Memory export/import β€” JSON round-trip so users can migrate between instances
  • Health endpoint (/agentmemory/health) β€” richer than /livez, includes index sizes, sync status, last backup time
  • Graceful shutdown β€” flush BM25/vector index to DB before exit on SIGTERM

Phase 3 β€” Breadth

Candidate

  • Additional LLM providers β€” OpenRouter, Ollama (local), Cohere for compression and consolidation
  • MCP tool parity β€” expand from 16 to 30+ tools to match the most-used subset of the Node.js 53-tool surface
  • GitHub Actions hook β€” observe CI runs as memory events
  • Slack / Discord connector β€” ingest messages as observations
  • Multi-agent shared memory β€” namespace isolation for team use; agents share a pool with per-agent write attribution
  • RBAC β€” role-based access control for shared deployments
  • Benchmark harness β€” reproduce the LongMemEval-S R@5 metric on the Python stack
  • pip package β€” pip install agentmemory with a agentmemory CLI entrypoint

Non-goals

  • Full parity with the 128-endpoint / 53-tool Node.js surface β€” the Python version targets simplicity and HF deployment, not feature count
  • iii-engine worker model β€” the Python version intentionally avoids the iii runtime
  • Dolt git-versioned history β€” the audit log satisfies the write-tracking requirement without the complexity