AI Resource Radar is a local-first tracker for free AI tiers, GPU compute, grants, and prices. It keeps the source and verification time beside each result, so the answer is practical: what is free, how much you get, when it resets, what the restrictions are, and how to claim it.

The default collection pipeline is deterministic: no AI, API key, cookie, or account data is required. Optional reviewable features remain isolated from collection and cannot change its verified evidence.

Start with uvx

Try the keyless collector without creating a checkout or virtual environment:

uvx ai-resource-radar start --open

For the hosted snapshot, use Live Radar or fetch the documented public data manifest. The public site is an aggregate view; always follow an official source before relying on an offer. Its v0.7.1 snapshot adds crawlable Chinese and English provider pages, conservative copyable integration examples, and on-demand catalogue loading while remaining static and read-only. Pages binds each build to a fresh 23-source refresh and Git commit.

What you get

Free tiers and AI prices change frequently, while ordinary link lists quickly become stale. This project turns public source material into a small, explainable local database:

Quick start

Requires Python 3.11 or newer. Install from PyPI in an isolated environment:

python3 -m venv .venv
source .venv/bin/activate
python -m pip install ai-resource-radar

ai-radar refresh
ai-radar dashboard --open

The dashboard is available only on 127.0.0.1:18766.

On macOS, install the dashboard, menu bar helper, and 08:00 daily job:

ai-radar service install
ai-radar service status

To uninstall the services without deleting the database:

ai-radar service uninstall

Platform support

Windows is not tested yet. Linux CI verifies the deterministic core and dashboard; macOS CI also compiles and tests the Vision OCR and menu bar helpers.

What it tracks

The built-in adapters currently cover 23 sources:

Community sources can discover candidates but cannot upgrade an offer to “officially verified”. Each HTTPS source is allow-listed, limited to 16 MB, isolated on failure, and supports ETag/Last-Modified caching.

Explainable ranking

The radar deliberately avoids an opaque score:

Within a tier, results are ordered by mainland availability, estimated value, and recent changes. The dashboard shows the reasons instead of hiding them inside a number.

Optional extensions

AI efficiency tips

Official guidance and manually imported articles remain candidates until a human approves them. Approval is limited to the marked managed block in an AGENTS.md, creates a private backup, and is auditable and reversible. See docs/TIPS.md for the safety model and ai-radar tips --help for the CLI.

How it works

flowchart LR
    A[Allow-listed public sources] --> B[Source-specific deterministic parsers]
    B --> C[Normalized SQLite schema]
    C --> D[Explainable ranking and change detection]
    D --> E[Dashboard, CLI, and local notifications]

One failed source never clears data from other sources. A missing offer is removed only after two successful parses both confirm its absence. Parser drift keeps the last trusted value and marks the source for verification.

Useful commands

# Refresh all due sources, or bypass cadence
ai-radar refresh
ai-radar refresh --force

# Browse verified, no-card resources
ai-radar list --verified-only --no-card
ai-radar list --kind gpu --no-card

# Review recent changes
ai-radar changes --days 30

# Run the complete daily workflow
ai-radar daily

# Diagnose the database, source freshness, helpers, and services
ai-radar doctor
ai-radar doctor --json

Run ai-radar <command> --help for every filter and option.

Data, privacy, and storage

• SQLite schema v7 uses file mode 0600; no secrets, cookies, or account data are stored.
• Tips retain only bounded summaries and evidence. Approval updates only the marked AGENTS.md managed block and creates a private backup under ~/.codex/backups/ai-tips/.
• Full fetched pages are parsed in memory and are not archived.
• Fetch logs are retained for 90 days; ordinary changes and delivered notifications for 365 days.
• Important free-tier changes and unread notifications are retained.
• Periodic cleanup and threshold-based VACUUM prevent unbounded growth.
• The dashboard accepts only loopback Host/Origin requests and serves no remote assets.

See Architecture and Security for details. Existing users should also read the v0.2 migration guide; complete removal is documented in Uninstall.

Development

git clone https://github.com/xxy12341/ai-resource-radar.git
cd ai-resource-radar
python3 -m venv .venv
source .venv/bin/activate
python -m pip install -e .

python -m unittest discover -s tests -p 'test_*.py'
node --check src/ai_resource_radar/web/ai-resources.js

Contributions are welcome. Start with CONTRIBUTING.md, or open an issue with the official source URL and the policy or price that needs attention.

License

MIT