diwushennian4955/velocirag-nexaapi-tutorial
VelociRAG + NexaAPI: Lightning-Fast RAG Pipeline for AI Agents (No PyTorch!) — Python & JavaScript tutorial
Platform-specific configuration:
{
"mcpServers": {
"velocirag-nexaapi-tutorial": {
"command": "npx",
"args": [
"-y",
"velocirag-nexaapi-tutorial"
]
}
}
}Add the config above to .claude/settings.json under the mcpServers key.
[](https://colab.research.google.com/drive/1velocirag-nexaapi-tutorial) [](https://pypi.org/project/velocirag/) [](https://pypi.org/project/nexaapi/)
> VelociRAG just dropped on PyPI — an ONNX-powered RAG framework that runs without PyTorch. Pair it with NexaAPI ($0.003/image, 56+ models) and you have the fastest, cheapest AI agent stack available today.
| Metric | VelociRAG + NexaAPI | PyTorch RAG + DALL-E | |--------|--------------------|-----------------------| | Install time | ~30 seconds | 5-10 minutes | | Memory footprint | ~200MB | 2-4GB | | Retrieval speed | ~5ms (ONNX) | ~20ms (PyTorch) | | Image generation cost | $0.003 | $0.040 | | Models available | 56+ | 1 | | Serverless-friendly | ✅ Yes | ❌ No |
pip install velocirag nexaapiimport velocirag
from nexaai import NexaAPI # pip install nexaapi
client = NexaAPI(api_key='YOUR_NEXAAPI_KEY')
rag = velocirag.VelociRAG()
# Add documents
documents = [
'NexaAPI provides 56+ AI models at the cheapest prices.',
'Image generation costs only $0.003 per image.',
'Supports Flux, Stable Diffusion, SDXLoading reviews...