thejayman77
38057d0354
- New taxonomy module: single source of truth for 6 topics x 5 flavors, shared by the LLM response schema (enum-constrained) and validation. - Classifier now assigns one topic + one flavor per article; json_schema enums force valid values, with coercion as a safety net. - article_scores gains topic/flavor columns via an idempotent migration. - New 'list-category' command to browse by topic and/or flavor, ranked by composite score. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
goodNews
Local-first constructive news ingestion prototype.
The first milestone is intentionally small: collect public RSS/Atom metadata, dedupe it, store short source-provided snippets, and attach early reason-coded heuristic scores. It does not store full article bodies.
Commands
From this directory:
python3 -m goodnews init-db
python3 -m goodnews import-sources
python3 -m goodnews poll --limit 3
python3 -m goodnews rescore
python3 -m goodnews check-llm --base-url http://127.0.0.1:1234/v1 --model gpt-oss
python3 -m goodnews classify --limit 10 --base-url http://127.0.0.1:1234/v1 --model gpt-oss
python3 -m goodnews build-brief --date 2026-05-27 --replace
python3 -m goodnews show-brief
python3 -m goodnews list-recent --limit 10
python3 -m goodnews list-recent --accepted-only --limit 10
python3 -m goodnews source-report
python3 -m goodnews list-runs
The SQLite database lives at:
data/goodnews.sqlite3
Sources live at:
config/sources.toml
Stored Article Data
For each article, the database stores:
- source
- canonical URL
- title
- short RSS/Atom description or summary
- author, if present
- published timestamp, if present
- image URL, if present
- language, if present
- hashes used for dedupe
- heuristic scores and reason codes
Next Steps
- Run the poller for a few days and inspect which sources produce useful candidates.
- Add source-level quality notes and deactivate noisy feeds.
- Replace or supplement
heuristic-v0with a local model classifier. - Add a daily brief builder that selects 5 items using scores and source diversity.
- Add a small web/API layer once the ingest data looks trustworthy.
Local Model Configuration
The classify command expects an OpenAI-compatible local chat-completions server.
You can pass settings directly:
python3 -m goodnews classify --base-url http://127.0.0.1:1234/v1 --model gpt-oss --limit 10
Or use environment variables:
export GOODNEWS_LLM_BASE_URL=http://127.0.0.1:1234/v1
export GOODNEWS_LLM_MODEL=gpt-oss
python3 -m goodnews classify --limit 10
classify rewrites the current score/reason row for selected candidates. rescore can restore the fast heuristic scores.