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Jon Saad-FalconandClaude Opus 4.6
29beeed32d
- Add root CONTRIBUTING.md with incentives (paper acknowledgment, Mac Mini giveaway), contribution tiers, PR process, and maintainership path - Add CODE_OF_CONDUCT.md (Contributor Covenant v2.1) - Add .pre-commit-config.yaml with ruff lint + format hooks - Add GitHub issue templates (bug report, feature request, new eval dataset) - Add PR template with test/lint/format checklist - Rewrite docs roadmap with GitHub Projects structure, current focus areas, and collapsible version history - Remove Development section from MkDocs nav; replace with top-level Roadmap tab - Delete changelog, extending docs (consolidated into CONTRIBUTING.md) - Delete root ROADMAP.md (content now lives in docs site) - Add pre-commit to dev extras in pyproject.toml - Add Roadmap link to README Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
4.6 KiB
4.6 KiB
Roadmap
OpenJarvis uses GitHub Projects boards organized by domain to plan and track work. Each board has quarterly columns so contributors can see what's coming and where help is needed.
How We Plan
- Work is organized into domain-specific project boards (see below)
- Each board uses quarterly columns: Backlog → Q2 2026 → Q3 2026 → Q4 2026 → Future
- Issues are labeled by difficulty (
good-first-issue,help-wanted) and type (type:bug,type:feature,type:perf,type:docs,type:eval) - Domain labels (
domain:agents,domain:engine,domain:tools, etc.) connect issues to the right board
Want to contribute? Check the boards below, pick an issue labeled good-first-issue or help-wanted, and comment "take" to claim it.
Active Project Boards
| Board | Scope | Link |
|---|---|---|
| Agents & Tools | Agent types, tool implementations, MCP | TBD — boards will be linked once created on GitHub |
| Engine & Inference | Engine backends, streaming, performance | TBD |
| Learning & Routing | GRPO, trace-driven policies, rewards | TBD |
| Evals & Benchmarks | Datasets, scorers, benchmark infra | TBD |
| Frontend & Desktop | Tauri app, dashboard, leaderboard | TBD |
| Rust Port | PyO3 bindings, crate parity | TBD |
Current Focus Areas
These are the areas where active development is happening and contributions are most impactful:
- GRPO training from trace data — moving router policies beyond heuristics using reinforcement learning from execution traces
- Multi-model orchestration pipelines — coordinating multiple models within a single query (e.g., small model for classification, large model for generation)
- Energy-aware routing — using power consumption data from telemetry to optimize for energy efficiency alongside latency and quality
- Plugin ecosystem — community-contributed engines, tools, and agents distributed as Python packages
- Federated memory — memory backends that synchronize across devices
How to Get Involved
- Browse the project boards for issues that interest you
- Look for
good-first-issueandhelp-wantedlabels - Read the Contributing Guide for the full process
- Comment "take" on an issue to claim it
Version History
| Version | Phase | Status | Delivers |
|---|---|---|---|
| v0.1 | Phase 0 -- Scaffolding | :material-check-circle:{ .green } Complete | Project scaffolding, registry system (RegistryBase[T]), core types (Message, ModelSpec, Conversation, ToolResult), configuration loader with hardware detection, Click CLI skeleton |
| v0.2 | Phase 1 -- Intelligence + Inference | :material-check-circle:{ .green } Complete | Intelligence primitive (model catalog, heuristic router), inference engines (Ollama, vLLM, llama.cpp), engine discovery and health probing, jarvis ask command working end-to-end |
| v0.3 | Phase 2 -- Memory | :material-check-circle:{ .green } Complete | Memory backends (SQLite/FTS5, FAISS, ColBERTv2, BM25, Hybrid/RRF), document chunking and ingestion pipeline, context injection with source attribution, jarvis memory commands |
| v0.4 | Phase 3 -- Agents + Tools + Server | :material-check-circle:{ .green } Complete | Agent system (SimpleAgent, OrchestratorAgent), tool system (Calculator, Think, Retrieval, LLM, FileRead), ToolExecutor dispatch engine, OpenAI-compatible API server (jarvis serve) |
| v0.5 | Phase 4 -- Learning + Telemetry | :material-check-circle:{ .green } Complete | Learning system (HeuristicRouter policy, TraceDrivenPolicy, GRPO stub), reward functions, telemetry aggregation (per-model/engine stats, export), --router CLI flag, jarvis telemetry commands |
| v1.0 | Phase 5 -- SDK + Production | :material-check-circle:{ .green } Complete | Python SDK (Jarvis class, MemoryHandle), multi-platform channel system (Telegram, Discord, Slack, WhatsApp, etc.), benchmarking framework (latency, throughput), Docker deployment (CPU + GPU), MkDocs documentation site |
| v1.1 | Phase 6 -- Traces + Learning | :material-check-circle:{ .green } Complete | Trace system (TraceStore, TraceCollector, TraceAnalyzer), trace-driven learning, MCP integration layer |
| v1.5 | Phase 10 -- Agent Restructuring | :material-check-circle:{ .green } Complete | BaseAgent helpers, ToolUsingAgent intermediate base, NativeReActAgent, NativeOpenHandsAgent, RLMAgent, OpenHandsAgent (SDK), accepts_tools introspection, backward-compat shims, CustomAgent removed |