mirror of
https://github.com/ruvnet/RuView
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rUv
f49c722764
The Rust port lived two directories deep (rust-port/wifi-densepose-rs/) without any sibling under rust-port/ that warranted the extra level. Move the whole workspace up to v2/ to match v1/ (Python) at the same depth and shorten every cd / build command across the repo. git mv preserves history for all tracked files. 60 files updated for path references (CI workflows, ADRs, docs, scripts, READMEs, internal .claude-flow state). Two manual fixes for relative-cd paths in CLAUDE.md and ADR-043 that became wrong after the depth change (cd ../.. → cd ..). Validated: - cargo check --workspace --no-default-features → clean (after target/ nuke; the gitignored target/ was carried by the OS rename and had hard-coded old paths in build scripts) - cargo test --workspace --no-default-features → 1,539 passed, 0 failed, 8 ignored (same totals as pre-rename) - ESP32-S3 on COM7 → still streaming live CSI (cb #40300, RSSI -64 dBm) After-merge follow-up: contributors should `rm -rf v2/target` once and let cargo regenerate from the new path.
113 lines
3.6 KiB
Markdown
113 lines
3.6 KiB
Markdown
# ruv-neural-cli
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CLI tool for brain topology analysis, simulation, and visualization.
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## Overview
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`ruv-neural-cli` is the command-line binary (`ruv-neural`) that ties together
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the entire rUv Neural crate ecosystem. It provides subcommands for simulating
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neural sensor data, analyzing brain connectivity graphs, computing minimum cuts,
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running the full processing pipeline with an optional ASCII dashboard, and
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exporting to multiple visualization formats.
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## Installation
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```bash
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# Build from source
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cargo install --path .
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# Or run directly
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cargo run -p ruv-neural-cli -- <command>
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```
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## Commands
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### `simulate` -- Generate synthetic neural data
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```bash
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ruv-neural simulate --channels 64 --duration 10 --sample-rate 1000 --output data.json
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```
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| Flag | Default | Description |
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|------------------|---------|------------------------------|
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| `-c, --channels` | 64 | Number of sensor channels |
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| `-d, --duration` | 10.0 | Duration in seconds |
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| `-s, --sample-rate` | 1000.0 | Sample rate in Hz |
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| `-o, --output` | (none) | Output file path (JSON) |
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### `analyze` -- Analyze a brain connectivity graph
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```bash
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ruv-neural analyze --input graph.json --ascii --csv metrics.csv
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```
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| Flag | Default | Description |
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|----------------|---------|--------------------------------|
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| `-i, --input` | (required) | Input graph file (JSON) |
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| `--ascii` | false | Show ASCII visualization |
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| `--csv` | (none) | Export metrics to CSV file |
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### `mincut` -- Compute minimum cut
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```bash
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ruv-neural mincut --input graph.json --k 4
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```
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| Flag | Default | Description |
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|----------------|---------|--------------------------------|
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| `-i, --input` | (required) | Input graph file (JSON) |
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| `-k` | (none) | Multi-way cut with k partitions|
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### `pipeline` -- Full end-to-end pipeline
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```bash
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ruv-neural pipeline --channels 32 --duration 5 --dashboard
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```
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Runs: simulate -> preprocess -> build graph -> mincut -> embed -> decode.
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| Flag | Default | Description |
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|------------------|---------|--------------------------------|
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| `-c, --channels` | 32 | Number of sensor channels |
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| `-d, --duration` | 5.0 | Duration in seconds |
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| `--dashboard` | false | Show real-time ASCII dashboard |
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### `export` -- Export to visualization format
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```bash
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ruv-neural export --input graph.json --format dot --output graph.dot
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```
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| Flag | Default | Description |
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|------------------|---------|---------------------------------------|
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| `-i, --input` | (required) | Input graph file (JSON) |
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| `-f, --format` | d3 | Output format: d3, dot, gexf, csv, rvf |
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| `-o, --output` | (required) | Output file path |
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### `info` -- Show system information
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```bash
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ruv-neural info
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```
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Displays crate versions, available features, and system capabilities.
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## Global Options
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| Flag | Description |
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|------------------|------------------------------------|
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| `-v` | Increase verbosity (up to `-vvv`) |
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| `--version` | Print version |
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| `--help` | Print help |
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## Integration
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Depends on all workspace crates: `ruv-neural-core`, `ruv-neural-sensor`,
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`ruv-neural-signal`, `ruv-neural-graph`, `ruv-neural-mincut`, `ruv-neural-embed`,
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`ruv-neural-memory`, `ruv-neural-decoder`, and `ruv-neural-viz`. Uses `clap`
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for argument parsing and `tokio` for async runtime.
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## License
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MIT OR Apache-2.0
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