66 lines
1.3 KiB
JSON
66 lines
1.3 KiB
JSON
{
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"name": "ruvllm-esp32",
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"version": "0.3.1",
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"description": "RuvLLM ESP32 - Tiny LLM inference for ESP32 microcontrollers with INT8 quantization, RAG, HNSW vector search, and multi-chip federation. Run AI on $4 hardware.",
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"keywords": [
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"esp32",
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"llm",
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"ai",
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"inference",
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"embedded",
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"microcontroller",
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"rag",
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"vector-search",
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"hnsw",
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"quantization",
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"edge-ai",
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"iot",
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"machine-learning",
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"neural-network",
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"esp32-s3",
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"xtensa",
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"riscv",
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"offline-ai",
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"tiny-ml",
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"semantic-memory"
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],
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"author": "RuVector Team",
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"license": "MIT",
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"repository": {
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"type": "git",
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"url": "https://github.com/ruvnet/ruvector.git",
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"directory": "examples/ruvLLM/esp32-flash"
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},
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"homepage": "https://github.com/ruvnet/ruvector/tree/main/examples/ruvLLM/esp32-flash",
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"bugs": {
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"url": "https://github.com/ruvnet/ruvector/issues"
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},
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"bin": {
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"ruvllm-esp32": "./bin/cli.js"
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},
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"files": [
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"bin/",
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"binaries/",
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"scripts/",
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"templates/",
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"web-flasher/",
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"README.md"
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],
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"scripts": {
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"postinstall": "node bin/postinstall.js"
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},
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"engines": {
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"node": ">=16.0.0"
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},
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"os": [
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"darwin",
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"linux",
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"win32"
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],
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"cpu": [
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"x64",
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"arm64"
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],
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"preferGlobal": true
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}
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