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Jon Saad-FalconandClaude Opus 4.6
f75afefcfb
Sets up a complete documentation website with 7 navigable sections (Home, Getting Started, User Guide, Architecture, API Reference, Deployment, Development), light/dark mode, search, code copy, and Mermaid diagram support. API reference pages use mkdocstrings to auto-generate docs from source docstrings. GitHub Actions workflow deploys to GitHub Pages on push to main. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
26 lines
1.5 KiB
Markdown
26 lines
1.5 KiB
Markdown
# API Reference
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This section contains the auto-generated API reference for the OpenJarvis Python
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package. Documentation is extracted directly from the source code docstrings
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using [mkdocstrings](https://mkdocstrings.github.io/).
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Each page documents a major module of the framework, including abstract base
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classes, concrete implementations, and utility functions.
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## Modules
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| Module | Description |
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|--------|-------------|
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| [SDK](sdk.md) | High-level `Jarvis` class and `MemoryHandle` proxy |
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| [Core](core.md) | Registries, types, configuration, and event bus |
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| [Engine](engine.md) | Inference engine ABC and backends (Ollama, vLLM, llama.cpp, SGLang, Cloud) |
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| [Agents](agents.md) | Agent ABC and implementations (Simple, Orchestrator, OpenClaw, Custom) |
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| [Memory](memory.md) | Memory backend ABC and implementations (SQLite, FAISS, ColBERT, BM25, Hybrid) |
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| [Tools](tools.md) | Tool ABC, executor, and built-in tools (Calculator, Think, Retrieval, LLM, FileRead) |
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| [Intelligence](intelligence.md) | Heuristic router and model catalog |
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| [Learning](learning.md) | Router policies, reward functions, and trace-driven learning |
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| [Traces](traces.md) | Trace storage, collection, and analysis |
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| [Telemetry](telemetry.md) | Telemetry storage, aggregation, and instrumented wrappers |
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| [Benchmarks](bench.md) | Benchmark ABC, suite runner, latency and throughput benchmarks |
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| [Server](server.md) | FastAPI application, OpenAI-compatible routes, and Pydantic models |
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