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Update landing page to five-pillar architecture and Phase 10 status

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Rewrites the main docs/index.md to reflect the current five-pillar
structure (Intelligence, Agents, Tools, Engine, Learning) with
accurate descriptions of each. Updates project status to v1.5
Phase 10 complete, seven agent types, 1800+ tests.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Jon Saad-Falcon
2026-02-24 05:15:30 +00:00
co-authored by Claude Opus 4.6
parent 8f641020ed
commit 160995c4c0
1 changed files with 17 additions and 11 deletions
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docs/index.md
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@@ -9,7 +9,13 @@ hide:
**Programming abstractions for on-device AI.**
OpenJarvis is a modular framework for building, running, and learning from local AI systems. It provides composable abstractions across four core pillars — Intelligence, Engine, Agentic Logic, and Memory — with a cross-cutting trace-driven learning system that improves routing decisions over time.
OpenJarvis is a modular framework for building, running, and learning from local AI systems. It provides composable abstractions across **five pillars** with a cross-cutting trace-driven learning system:
1. **Intelligence** -- The LM itself: Llama, Qwen, Claude, GPT, etc. Model catalog, generation defaults, quantization, and preferred engine configuration.
2. **Agents** -- The agentic harness for running it: system prompt (including objective, available tools, available models), context from past turns, retry logic, looping logic, exit logic. Seven agent types from simple single-turn to recursive decomposition.
3. **Tools** -- In an MCP interface, the available tools and LMs that can be called: web search, calculator, file read, code interpreter, retrieval systems, SQLite, sub-model calls, and any external MCP server.
4. **Engine** -- The inference runtime: Ollama, SGLang, vLLM, llama.cpp, cloud APIs (OpenAI, Anthropic, Google). All implement the same `InferenceEngine` ABC.
5. **Learning** -- Methodologies for improving Intelligence (weight updates via SFT) or Agents (changes to system prompt, tools available, models available, retry/looping/exit logic via agent advisor and ICL updater). Trace-driven feedback loop.
Everything runs on your hardware. Cloud APIs are optional.
@@ -19,11 +25,11 @@ Everything runs on your hardware. Cloud APIs are optional.
<div class="grid cards" markdown>
- **Four Core Pillars**
- **Five Composable Pillars**
---
Intelligence (model routing), Engine (inference runtime), Agentic Logic (tool-calling agents), and Memory (persistent searchable storage) — each with a clear ABC interface and decorator-based registry.
Intelligence (the model), Agents (agentic harness), Tools (MCP-based tool system with storage), Engine (inference runtime), and Learning (trace-driven improvement) — each with a clear ABC interface and decorator-based registry.
- **5 Engine Backends**
@@ -59,7 +65,7 @@ Everything runs on your hardware. Cloud APIs are optional.
---
Every agent interaction is recorded as a trace. The learning system uses accumulated traces to improve model routing decisions. Pluggable router policies: heuristic, trace-driven, and GRPO.
Every agent interaction is recorded as a trace. The learning system improves Intelligence (SFT weight updates) and Agents (system prompt, tool selection, retry logic). Pluggable policies: heuristic, trace-driven, SFT, agent advisor, ICL updater, GRPO.
- **Python SDK**
@@ -126,19 +132,19 @@ jarvis bench run --json
## Project Status
OpenJarvis v1.0 is complete. The framework includes the full four-pillar architecture, Python SDK, CLI, OpenAI-compatible API server, OpenClaw agent infrastructure, benchmarking framework, and Docker deployment. The test suite contains over 1,000 tests. Phase 6 (trace system and trace-driven learning) is in active development.
OpenJarvis v1.5 (Phase 10) is complete. The framework includes the full five-pillar architecture, seven agent types, Python SDK, CLI, OpenAI-compatible API server, benchmarking framework, and Docker deployment. The test suite contains over 1,800 tests.
| Component | Status |
|-----------|--------|
| Intelligence (model routing) | Stable |
| Intelligence (model catalog + config) | Stable |
| Agents (7 types: Simple, Orchestrator, NativeReAct, NativeOpenHands, RLM, OpenHands SDK, OpenClaw) | Stable |
| Tools (MCP interface + 5 storage backends) | Stable |
| Engine (5 backends) | Stable |
| Agentic Logic (agents + tools) | Stable |
| Memory (5 backends) | Stable |
| Learning (routing, SFT, agent advisor, ICL updater) | Stable |
| Python SDK | Stable |
| CLI | Stable |
| API Server | Stable |
| Trace System | Active Development |
| Trace-Driven Learning | Active Development |
| Trace System | Stable |
| Docker Deployment | Stable |
---
@@ -163,7 +169,7 @@ OpenJarvis v1.0 is complete. The framework includes the full four-pillar archite
---
Deep dive into the four-pillar design, registry pattern, query flow, and cross-cutting learning system.
Deep dive into the five-pillar design, registry pattern, query flow, and cross-cutting learning system.
- **[API Reference](api/index.md)**