NeMo Retriever

SkillSearch

Lets your agent search and query a collection of documents like PDFs, Office files, audio, and video.

Then ask your AI: use the NeMo Retriever skill

Details

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Account requirements not reviewed. Check the skill instructions before use; Ahel provides instructions and does not run this skill.

No other account needed.

Add it as a step in a pipeline you build on Ahel, or connect Ahel to Claude, ChatGPT, Cursor, Claude Code or Codex and ask your AI to use it.

About this skill

Use when searching, extracting, ingesting, or querying a document collection with the NeMo Retriever 26.8.1 CLI, including local LanceDB indexes and deployed Retriever services. Use for PDFs, images, Office files, HTML, text, audio, and video; not for editing documents or web search.

What this skill tells your AI

The instructions your AI receives, as published by nvidia/skills in skills/nemo-retriever/SKILL.md and read by Ahel’s review.

Use the retriever CLI. Prefer it over hand-built retrieval code.

Install only when missing

Create a project-local Python environment:

uv venv .venv --python 3.12
export PATH="$PWD/.venv/bin:$PATH"

Install the package variant required by the workflow:

# Remote NIM or service client
uv pip install --python .venv/bin/python "nemo-retriever==26.8.1"

# Local GPU ingestion
uv pip install --python .venv/bin/python "nemo-retriever[local]==26.8.1"

# Local service using Hugging Face models
uv pip install --python .venv/bin/python \
  "nemo-retriever[service,local]==26.8.1"

# Local audio or video ingestion
uv pip install --python .venv/bin/python \
  "nemo-retriever[local,multimedia]==26.8.1"

Do not clone NeMo Retriever or install from a Git URL. If retriever is already on PATH, use that installation.

Local workflow

Build a local index:

retriever ingest <file-or-directory> \
  --lancedb-uri lancedb --table-name nemo-retriever

Query it:

retriever query "<question>" \
  --lancedb-uri lancedb --table-name nemo-retriever \
  --top-k 5 --format evidence

Use retriever ingest batch only for an explicitly requested Ray batch run.

Service workflow

Use these forms for an already deployed Retriever service:

retriever ingest service <file-or-directory> \
  --service-url "$RETRIEVER_SERVICE_URL"

retriever query service "<question>" \
  --service-url "$RETRIEVER_SERVICE_URL" \
  --top-k 5 --format evidence

Set NEMO_RETRIEVER_API_TOKEN when the service requires Bearer authentication. Do not pass local LanceDB flags to the service commands.

Rules

Use the existing index or service when one is provided; do not rebuild it.
Use retriever ingest --help, retriever query --help, or the relevant batch / service help for options not shown here.
Answer only from retrieved evidence; preserve source and page metadata when the task requests citations.

Signals

GitHub stars: 4k
Forks: 434
Last commit: Oct 2026

Ahel review

K1binfo
installs-packages

Automated review, not a security audit. Ruleset v1+k2.

Advanced

Item type: skill
Key: nemo-retriever
Source: github.com/nvidia/skills

github.com/nvidia/skills