gata 1.14.0

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.

Status

Stage	Name	Status
1	Core pipeline (Satirist/Co-Satirist creative loop + image generation)	✅ Complete
2	Community config + model fallback chains	✅ Complete
3	Cultural Strategist (Framer + Resonator)	✅ Complete
4	Text Output Bundle (logs, HTML explanations, prompt card)	✅ Complete
5	Housekeeping + rules redefinition	✅ Complete
6	Trend Scout — automated topic discovery via NewsAPI.org + Gemini	✅ Complete
7	Comedy style configuration via humor.yaml	✅ Complete
8	Free-text community mode — --community accepts any description	✅ Complete
9	Multi-panel cartoon format — --panels and --layout flags	✅ Complete
10	Agent personality — inconvenience level (0–100) + dual satirist mode	✅ Complete
11	Dynamic news search — infers country + category from free-text; --community + --topic mode	✅ Complete
12	Run summary — per-agent time, iterations, and cost + grand total	✅ Complete
13	Optional HTML output — --html flag, off by default	✅ Complete
14	Image generation cost tracking — accurate $/image in telemetry and summary	✅ Complete
15	Single main audience default — one inferred audience + UK per run	✅ Complete
27	Cartoon title — Satirist-authored headline overlaid as dark banner at top of image	✅ Complete
29	Grok as primary decider — Grok-3 becomes the aggregator across all ParallelPanel agents; Cultural Strategist and Explainer converted from DualPersonaLoop	✅ Complete

How it works

1. Trend Scout fetches today's top headlines for the community and ranks them by satirical potential. For free-text communities, it infers the appropriate country and news category in a single Gemini call (infer_community_profile). In --community + --topic mode, Trend Scout is bypassed entirely.
2. Cultural Strategist — Claude, Grok-mini, and Gemini each independently propose a cultural angle (Framer role); Grok-3 evaluates all proposals and picks the sharpest one (Resonator role)
3. Parallel Panel — Claude, Grok-mini, and Gemini each independently generate a cartoon concept; Grok-3 (Aggregator) picks the strongest one
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) — Claude, Grok-mini, and Gemini each independently write two HTML explanation pages; Grok-3 (Editor) picks the best for each
6. Bundle writer saves the full output package: image, conversation logs, prompt card, telemetry, and summary — plus the HTML files when --html is set

All agents use prioritised model fallback chains. Grok-3 is the aggregator/decider across all ParallelPanel agents (Cultural Strategist, Satirist, Explainer). Grok-3-mini participates as a panelist alongside Claude and Gemini.

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 references; Grok-3 evaluates all proposals and picks/synthesises the sharpest one
Creative Loop	Panelist (Claude), Panelist (Grok-mini), Panelist (Gemini), Aggregator	Claude · Grok-mini · Gemini (parallel) · Grok-3 (Aggregator)	Claude, Grok-mini, and Gemini each independently generate a cartoon concept; Grok-3 picks the strongest one
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	After image generation, checks for LLM rendering artifacts (duplicate text, garbled text, character failures) and rates whether the cartoon is genuinely funny for the target audience; 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 two HTML pages each (in-language and English); Grok-3 picks the best page per run

Quick start

pipx install gata
export ANTHROPIC_API_KEY=...
export GEMINI_API_KEY=...
gata "World Cup Qatar vs Swiss"

This generates two satirical cartoons from a single topic — one for the most culturally relevant audience (inferred by the pipeline) and one for the UK public — saved to a subdirectory of your working directory.

Setup

Install from PyPI (recommended — installs the gata command globally):

pipx install gata

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

Install into a virtual environment (for use as a library or in scripts):

pip install gata

Install from source (for development):

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

Required secrets

Three API keys are required:

Variable	Where to get it	Used by
ANTHROPIC_API_KEY	console.anthropic.com	Cultural Strategist, Satirist, Explainer
GEMINI_API_KEY	aistudio.google.com	Trend Scout, Image Generator, Resonator, Co-Satirist fallback
XAI_API_KEY	console.x.ai	Panelist (Grok)
NEWSAPI_ORG_KEY	newsapi.org	Trend Scout (headline fetching)

Option A — .env file (recommended for local development)

Create a .env file in the project root. It is git-ignored and never committed.

ANTHROPIC_API_KEY=your_anthropic_key_here
GEMINI_API_KEY=your_gemini_key_here
XAI_API_KEY=your_xai_key_here
NEWSAPI_ORG_KEY=your_newsapi_key_here

The pipeline loads this file automatically on startup and logs credentials loaded from .env file to confirm.

Option B — environment variables (recommended for CI/CD and servers)

Export the variables in your shell before running the pipeline. The pipeline detects that no .env file is present and logs reading credentials from environment variables.

export ANTHROPIC_API_KEY=your_anthropic_key_here
export GEMINI_API_KEY=your_gemini_key_here
export XAI_API_KEY=your_xai_key_here
export NEWSAPI_ORG_KEY=your_newsapi_key_here
python pipeline.py --community uk-politics

In GitHub Actions, add the three values as repository secrets (Settings → Secrets and variables → Actions) and reference them in your workflow:

env:
  ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
  GEMINI_API_KEY: ${{ secrets.GEMINI_API_KEY }}
  XAI_API_KEY: ${{ secrets.XAI_API_KEY }}
  NEWSAPI_ORG_KEY: ${{ secrets.NEWSAPI_ORG_KEY }}

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"
# → infers audience (e.g. "german"), adds UK
# → saves german.png + uk.png to ./interest_rates_stay_high.../

# 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 (off by default — adds an extra Claude + Gemini call)
gata "NATO summit in Brussels" --html

Output folder: {cwd}/{topic_slug}/ — one PNG per audience, plus a bundle folder per image containing logs, prompt card, telemetry, and a cost/time summary. 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; language and tone inferred)
python pipeline.py --community "US community that dislikes Trump"
python pipeline.py --community "Communauté française qui critique Macron"

# Community + topic mode (brief from community, 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 (add --panels N and --layout direction to any mode above)
python pipeline.py --community uk-politics --panels 3 --layout horizontal
python pipeline.py --community portuguese-adults --panels 2 --layout vertical
python pipeline.py --topic "World Cup result" --audience "football fans" --language "English" --tone "excited" --panels 4 --layout horizontal

# Also generate the HTML explanation pages (off by default; add --html to any mode above)
python pipeline.py --community uk-politics --html

# Suppress title banner (shown by default; add --no-title to any mode above)
python pipeline.py --community uk-politics --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

CLI flags take precedence over communities.yaml panel config, which takes precedence over the defaults. Output filename prefix: {N}{d}_ for multi-panel (e.g. 3h_english_topic.png); no prefix for single-panel.

Output is saved to a bundle folder:

• Community mode: output/{community}/{topic}/
• Manual mode: output/manual/{topic}/

Each bundle contains:

• cartoon.png — the generated image
• agent0_log.txt — Agent 0 negotiation history (cultural strategy)
• bc_log.txt — B/C creative loop history (satirist + co-satirist exchange)
• 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, plus a run total (human-readable)

With --html (off by default), the bundle also contains:

• explanation.html — in-language explanation of the joke for end users
• deep_dive_en.html — English operator deep-dive (news context, cultural references, satirical logic)

Running gata <topic> also writes a top-level {output_dir}/summary.txt aggregating time and cost across every audience generated for that topic.

Communities

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

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 the comedy style and agent personality for every run. All fields default to off so the file is optional.

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 ("look beneath the obvious"); 34–66 = medium push ("don't let the target off the hook"); 67–100 = maximum ("if the audience doesn't squirm, it isn't ready").

Tech Stack

• Python 3.x
• Framer — Anthropic Claude (claude-sonnet-4-6 → claude-opus-4-7 → claude-haiku-4-5-20251001)
• Resonator — Google Gemini (gemini-2.5-pro → gemini-2.5-flash → gemini-2.0-flash)
• Panelist (Claude) — Anthropic Claude (claude-sonnet-4-6) — independent concept generator
• Panelist (Grok) — xAI Grok (grok-3) — independent concept generator
• Panelist (Gemini) — Google Gemini (gemini-2.5-flash) — independent concept generator
• Aggregator — Anthropic Claude (same fallback chain as Framer) — picks the strongest concept from the panel
• Image Generator — Google Gemini image models (gemini-3.1-flash-image-preview → gemini-3.1-flash-image → gemini-3-pro-image-preview → gemini-3-pro-image → gemini-2.5-flash-image)
• Explainer Writer — Anthropic Claude (claude-sonnet-4-6, max 8192 tokens)
• Explainer Editor — Google Gemini (gemini-2.5-flash → gemini-2.5-pro → gemini-2.0-flash)
• Trend Scout — fetches today's headlines from NewsAPI.org and uses Gemini gemini-2.5-flash to rank them by satirical potential for the community

Upcoming Work

See TODO.md for the full backlog. Key items:

• Post-generation image review — vision model checks for rendering artifacts (duplicate labels, garbled text, Gata integrity failures) and retries before writing the bundle
• Voting system — funny / not funny ratings per cartoon feeding back into the pipeline to improve future output
• Self-documenting CLI — pipeline.py with no arguments prints all calling modes with ready-to-copy examples
• Gemini fact-check gate — Gemini verifies every factual claim in the concept before the image prompt is finalised; returns with a FACT: tag if anything is wrong
• Batch image generation — use the Gemini Batch API to cut image generation cost by ~50%