README.md

metadata

title: GAIA Agent (LangGraph + Groq)
emoji: 🕵🏻‍♂️
colorFrom: indigo
colorTo: indigo
sdk: gradio
sdk_version: 5.25.2
app_file: app.py
pinned: false
hf_oauth: true
hf_oauth_expiration_minutes: 480

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

---

GAIA Agent (LangGraph + Groq)

This Space answers GAIA Level-1 questions with a LangGraph multi-node agent:

planner → [ingest_file] → research ⇄ tools → evidence → solver → judge ⇄ (loop) → formatter

• LLM: Groq (langchain-groq) — text/reasoning + Llama-4 vision + Whisper audio.
• Search: Tavily (langchain-tavily) with a Wikipedia fallback.
• Eval loop: an LLM-as-judge node loops wrong/ill-formatted answers back to research (up to MAX_JUDGE_RETRIES).
• Structured handoffs: every node-to-node transfer is a Pydantic model (gaia_agent/schemas.py), so context stays precise.

Secrets (required)

Set these as Space secrets (Settings → Variables and secrets) — locally use a .env (copy .env.example):

Name	Purpose
GROQ_API_KEY	Groq LLM access
TAVILY_API_KEY	Tavily web search

Optional overrides: GROQ_TEXT_MODEL, GROQ_VISION_MODEL, GROQ_WHISPER_MODEL, MAX_JUDGE_RETRIES, RECURSION_LIMIT. See .env.example.

Local development

uv venv --python 3.11
uv pip install -e ".[dev]"
cp .env.example .env          # then fill in your keys
uv run pytest -q              # unit + graph/judge-loop tests
uv run langgraph dev          # LangGraph Studio: visualise the graph
python scripts/dry_run.py 3   # run the agent on 3 questions (no submit)