gata 1.19.0

Automated multi-agent pipeline that transforms news into satirical cartoons starring Gata

Gata Newsroom

An automated multi-agent pipeline that transforms daily topics into a recurring satirical cartoon series starring Gata, a serious investigative calico cat who views all geopolitics through the lens of feline priorities.

Install

pipx install gata

If pipx is not installed: sudo apt install pipx && pipx ensurepath

Required API keys

Three LLM provider accounts are required before you can run Gata:

Provider	Sign up	Environment variable
Anthropic	console.anthropic.com	ANTHROPIC_API_KEY
Google AI Studio	aistudio.google.com	GEMINI_API_KEY
xAI	console.x.ai	XAI_API_KEY

Auto-topic mode (pipeline.py without --topic) also requires a NewsAPI.org key in NEWSAPI_ORG_KEY. The gata command always requires a topic — Trend Scout is never used by it.

Export the keys in your shell, or place them in a .env file in the project root (it is gitignored and never committed):

# Option A — shell environment
export ANTHROPIC_API_KEY=...
export GEMINI_API_KEY=...
export XAI_API_KEY=...
export NEWSAPI_ORG_KEY=...   # only needed for auto-topic mode

# Option B — .env file (loaded automatically on startup)
ANTHROPIC_API_KEY=your_key_here
GEMINI_API_KEY=your_key_here
XAI_API_KEY=your_key_here
NEWSAPI_ORG_KEY=your_key_here

Quick start

gata "World Cup final: Argentina vs France"

This infers the most culturally relevant audience, negotiates a cultural angle, generates three independent cartoon concepts, picks the strongest one, and saves two PNGs to your working directory — one for the inferred audience and one for the UK public.

How it works

1. Trend Scout fetches today's top headlines for the community and ranks them by satirical potential; only used by pipeline.py when --topic is not supplied — the gata command always requires a topic and never invokes Trend Scout
2. Cultural Strategist — three Framers (Claude, Grok-mini, Gemini) independently propose a cultural angle; Grok-3 (Resonator) aggregates and picks the sharpest one
3. Satirist — three Panelists (Claude, Grok-mini, Gemini) independently generate a cartoon concept; Grok-3 (Aggregator) picks the strongest concept
4. Image Generator renders the approved concept into a PNG via a fallback chain of Gemini image models; overlays the Satirist-authored title as a dark banner at the top (suppressed with --no-title)
5. Explainer (opt-in via --html) — three Writers (Claude, Grok-mini, Gemini) independently draft an HTML explanation page; Grok-3 (Editor) picks the best one; runs twice — once in the target language, once in English
6. Bundle Writer saves the full output package: image, conversation logs, prompt card, telemetry, and summary

Agents

Agent	Sub-agents	LLMs	What it does
Trend Scout	—	Gemini	Fetches today's headlines from NewsAPI.org and picks the top 3 ranked by satirical potential for the community
Cultural Strategist	Framer ×3, Resonator	Claude · Grok-mini · Gemini (Framers) · Grok-3 (Resonator/aggregator)	Three Framers independently propose a cultural angle and audience references; Resonator picks the sharpest one
Satirist	Panelist ×3, Aggregator	Claude · Grok-mini · Gemini (panelists) · Grok-3 (aggregator)	Three panelists independently generate a cartoon concept; Aggregator picks the strongest
Image Generator	—	Gemini image models	Renders the approved image prompt into a PNG; tries up to 5 models in order before failing
Image Evaluator	—	Gemini vision models	Checks for LLM rendering artifacts and rates comedy; triggers regeneration up to 2 times on rejection
Explainer	Writer ×3, Editor	Claude · Grok-mini · Gemini (writers) · Grok-3 (editor/aggregator)	Three Writers independently draft HTML explanation pages (in-language + English); Editor picks the best per run

gata command

The simplest way to run the pipeline. Give it any topic and it generates two satirical cartoons: one for the most culturally relevant audience (inferred automatically) and one for the UK public.

# Generate cartoons for a news topic
gata "Interest rates stay high despite falling inflation"

# Any topic works — Gata will find the angle
gata "World Cup final: Argentina vs France"
gata "Tech layoffs hit Silicon Valley again"
gata "Portugal wins Eurovision"

# Also generate HTML explanation pages
gata "NATO summit in Brussels" --html

Output folder: {cwd}/{topic_slug}/ — one PNG per audience, plus a bundle folder per image. Run gata --help to see all options.

pipeline.py — advanced usage

# Named community (exact match in communities.yaml; topic selected by Trend Scout)
python pipeline.py --community uk-politics

# Free-text community (no entry required in communities.yaml)
python pipeline.py --community "US community that dislikes Trump"
python pipeline.py --community "Communauté française qui critique Macron"

# Community + topic mode (topic supplied directly — no Trend Scout)
python pipeline.py --community uk-politics --topic "Number 10 is becoming available for rent, again."
python pipeline.py --community "Adeptos portugueses de futebol" --topic "O Ronaldo vai levar Portugal ao mundial"

# Random community and topic
python pipeline.py

# Manual mode (bypasses communities.yaml entirely)
python pipeline.py --topic "AI hype" --audience "developers" --language "English" --tone "dry wit"

# Multi-panel cartoon
python pipeline.py --community uk-politics --panels 3 --layout horizontal
python pipeline.py --community portuguese-adults --panels 2 --layout vertical

# HTML explanation pages + suppress title banner
python pipeline.py --community uk-politics --html --no-title

Multi-panel flags

Flag	Values	Default	Description
--panels	1–4	1	Number of panels in the cartoon strip
--layout	horizontal, vertical	horizontal	Panel arrangement direction
--no-title	—	off	Suppress the title banner overlaid at the top of the image

Output bundle

Each run writes a bundle folder containing:

File	Description
cartoon.png	The generated image
agent0_log.txt	Cultural Strategist negotiation history
bc_log.txt	Satirist panel exchange log
prompt_card.txt	Verbatim image prompt for standalone reuse
telemetry.json	Per-agent timing, token counts, and cost (machine-readable)
summary.txt	Per-agent time, iterations, and cost (human-readable)
explanation.html	In-language explanation of the joke (--html only)
deep_dive_en.html	English operator deep-dive (--html only)

Communities

Communities are defined in communities.yaml. Each community specifies a target audience, output language, tone, seed topics, and optionally a default panel count.

Community	Language	Tone
uk-politics	English	Dry British wit
uk-tech-engineers	English	Dry British wit
portuguese-adults	Portuguese	Sátira política afiada
portuguese-politics	Portuguese	Sátira política afiada
us-startup-crowd	English	Sarcastic Silicon Valley cynicism

To add a new community, add an entry to communities.yaml — no code changes required.

Comedy configuration (humor.yaml)

humor.yaml controls comedy style and agent personality. All fields default to off.

Section	Field	Type	What it does
framer	wordplay_scan	bool	Framer actively looks for pun/wordplay opportunities
framer	joke_types	list	Menu of joke types the Framer chooses from
framer	language_register	string	Register for wordplay (vernacular, formal, …)
framer	inconvenience	0–100	How aggressively Framer surfaces uncomfortable truths
satirist	preferred_style	string	Tone commitment (deadpan, absurdist, …)
satirist	avoid	list	Joke types/styles to avoid
satirist	subversion	string	Subversion intensity (high, medium, low)
satirist	joke_explanation	bool	Add a <joke_explanation> block after each concept
satirist	inconvenience	0–100	How aggressively Satirist forces uncomfortable truths

Inconvenience levels: 0 = off; 1–33 = mild nudge; 34–66 = medium push; 67–100 = maximum.

Install from source (development)

python -m venv .venv && source .venv/bin/activate
pip install -e .

Architecture

See docs/architecture.md for agent diagrams and the communication protocol framework.

Status

Stage	Name	Status
1	Core pipeline — Satirist/Co-Satirist creative loop + image generation	✅
2	Community config + model fallback chains	✅
3	Cultural Strategist (Framer + Resonator)	✅
4	Text Output Bundle (logs, HTML explanations, prompt card)	✅
5	Trend Scout — automated topic discovery via NewsAPI.org + Gemini	✅
6	Free-text community mode	✅
7	Multi-panel cartoon format — --panels and --layout	✅
8	Multi-audience CLI	✅
9	Run telemetry — per-agent timing, token counts, cost	✅
10	Dynamic audiences	✅
11	Mood layer	✅
12	Run summary	✅
13	Optional HTML output	✅
14	Image cost pricing	✅
15	Single main audience	✅
16	Clean logging	✅
19	Inference model fallback	✅
20	Auto layout	✅
21	Gemini Satirist	✅
22	Image Evaluator	✅
23	Evaluator fidelity	✅
24	LLM provider abstraction	✅
25	Grok integration	✅
26	Protocol framework + Parallel Panel	✅
27	Cartoon title banner + --no-title flag	✅
29	Grok as primary decider — Grok-3 aggregator across all ParallelPanel agents	✅
30	Documentation overhaul — README + architecture doc	✅