nvidia-deep-researcher

NVIDIA Deep Researcher — GitAgent PoC

This is a working proof of concept that defines NVIDIA's AIQ Deep Researcher agent in the gitagent standard. It demonstrates how GitAgent enhances a production multi-agent system with portability, versioning, compliance, and git-native lifecycle management.

What This Is

NVIDIA's Deep Researcher is a 3-agent hierarchy that produces comprehensive research reports:

• Orchestrator — coordinates workflow, writes final 3000-5000 word report
• Planner — builds TOC, generates search queries, writes structured plan
• Researcher — executes searches (max 8 calls), writes cited findings

This gitagent definition faithfully translates the NVIDIA Jinja2 prompts (orchestrator.j2, planner.j2, researcher.j2) into the gitagent standard format (SOUL.md, RULES.md, DUTIES.md, agent.yaml).

What GitAgent Adds

Capability	Without GitAgent	With GitAgent
Portability	Locked to LangChain runtime	Export to Claude Code, OpenAI, CrewAI, system-prompt
Prompt versioning	Prompts in Jinja2 templates	Every SOUL.md change is a git commit; bisect regressions
SOD enforcement	Implicit in code	Explicit roles, conflicts, and handoffs validated in CI
Fork & customize	Modify Python code	Fork for legal/medical/finance variants without touching code
Memory	No persistence across sessions	Version-controlled research session history
CI/CD	Manual testing	gitagent validate --compliance on every push
Audit trail	None	Every prompt, skill, and rule change traced via git

Quick Start

Validate

cd examples/nvidia-deep-researcher
gitagent validate --compliance

Export

# System prompt (for any LLM)
gitagent export --format system-prompt

# Claude Code (generates CLAUDE.md)
gitagent export --format claude-code

Info

gitagent info

Structure

nvidia-deep-researcher/
├── agent.yaml              # Agent manifest (models, skills, tools, SOD)
├── SOUL.md                 # Orchestrator identity and 8-step workflow
├── RULES.md                # Hard constraints (citations, report format, limits)
├── AGENTS.md               # Multi-agent architecture overview
├── DUTIES.md               # Segregation of duties policy
├── agents/
│   ├── planner/            # Plan generation sub-agent
│   └── researcher/         # Search execution sub-agent
├── skills/
│   ├── web-search/         # Tavily web search skill
│   ├── paper-search/       # Google Scholar skill
│   └── knowledge-retrieval/# RAG knowledge base skill
├── tools/
│   ├── tavily-web-search.yaml
│   ├── paper-search.yaml
│   └── knowledge-retrieval.yaml
├── knowledge/              # Document ingestion index
├── memory/                 # Research session persistence
├── hooks/                  # Bootstrap and teardown hooks
└── config/                 # Environment configurations

Fork & Customize

To create a domain-specific variant (e.g., legal research):

cp -r examples/nvidia-deep-researcher my-legal-researcher
cd my-legal-researcher

# Edit SOUL.md to add legal domain expertise
# Edit RULES.md to add legal citation requirements
# Add legal knowledge docs to knowledge/
# Update agent.yaml with domain-specific metadata

gitagent validate --compliance

No Python code changes needed — just edit the markdown and YAML files.

Upstream

This PoC is based on the NVIDIA AIQ Deep Researcher Blueprint:

• Repository: https://github.com/NVIDIA-AI-Blueprints/aiq
• Source path: src/aiq_agent/agents/deep_researcher
• Prompts: prompts/orchestrator.j2, prompts/planner.j2, prompts/researcher.j2