Add interval-aware polling and a 'cycle' command for scheduling

- poll_due_sources(): polls only sources whose last successful poll is older
  than their poll_interval_minutes (or never polled), finally giving that
  config field meaning.
- classify gains only_unclassified to spend the LLM solely on new (heuristic)
  articles, so a frequent scheduled run stays cheap.
- 'cycle' command runs poll-due -> classify-new -> rebuild-today's-brief, with
  each step non-fatal so a down model endpoint or empty day never aborts it.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

goodnews/cli.py

@@ -3,11 +3,12 @@ from __future__ import annotations
 import argparse
 import os
 import sqlite3
+from datetime import date
 from pathlib import Path
 
 from .briefs import build_daily_brief, show_brief
 from .db import connect, init_db
-from .feeds import poll_all_sources, poll_source
+from .feeds import poll_all_sources, poll_due_sources, poll_source
 from .llm import LocalModelClient, classify_articles
 from .scoring import score_article
 from .sources import load_sources, upsert_sources
@@ -59,6 +60,16 @@ def main() -> None:
     classify_parser.add_argument("--base-url", help="OpenAI-compatible base URL, e.g. http://127.0.0.1:1234/v1")
     classify_parser.add_argument("--model", help="Local model name")
 
+    cycle_parser = subparsers.add_parser(
+        "cycle", help="Poll due sources, classify new articles, rebuild today's brief (for scheduling)"
+    )
+    cycle_parser.add_argument("--classify-limit", type=int, default=40)
+    cycle_parser.add_argument("--no-classify", action="store_true", help="Skip the LLM classify step")
+    cycle_parser.add_argument("--no-brief", action="store_true", help="Skip rebuilding today's brief")
+    cycle_parser.add_argument("--force", action="store_true", help="Poll all active sources, ignoring intervals")
+    cycle_parser.add_argument("--base-url", help="OpenAI-compatible base URL for classify")
+    cycle_parser.add_argument("--model", help="Local model name for classify")
+
     check_llm_parser = subparsers.add_parser("check-llm", help="Check local OpenAI-compatible model endpoint")
     check_llm_parser.add_argument("--base-url", help="OpenAI-compatible base URL, e.g. http://127.0.0.1:1234/v1")
     check_llm_parser.add_argument("--model", help="Expected local model name")
@@ -135,6 +146,8 @@ def main() -> None:
             print(f"  {scores['reason_text']}")
         if args.dry_run:
             print("Dry run only; database was not updated.")
+    elif args.command == "cycle":
+        run_cycle(conn, args)
     elif args.command == "check-llm":
         client = llm_client_from_args(args)
         try:
@@ -201,6 +214,38 @@ def list_recent(conn: sqlite3.Connection, limit: int, accepted_only: bool) -> No
         print(f"  {row['canonical_url']}")
 
 
+def run_cycle(conn: sqlite3.Connection, args: argparse.Namespace) -> None:
+    """One end-to-end pass for a scheduler: poll due sources, classify the new
+    arrivals, rebuild today's brief. Each step is independent and non-fatal so a
+    down model endpoint or empty day never aborts the whole cycle.
+    """
+    init_db(conn)
+
+    if args.force:
+        poll_result = poll_all_sources(conn)
+    else:
+        poll_result = poll_due_sources(conn)
+    print(f"poll: {_format_result(poll_result)}")
+
+    if not args.no_classify:
+        client = llm_client_from_args(args)
+        try:
+            results = classify_articles(
+                conn, client, limit=args.classify_limit, include_rejected=True, only_unclassified=True
+            )
+            print(f"classify: {len(results)} new article(s) scored by {client.model}")
+        except Exception as exc:  # endpoint down, timeout, etc. — keep going
+            print(f"classify: skipped ({exc})")
+
+    if not args.no_brief:
+        today = date.today().isoformat()
+        try:
+            brief_id = build_daily_brief(conn, brief_date=today, limit=5, replace=True)
+            print(f"brief: rebuilt {today} (id {brief_id})")
+        except Exception as exc:
+            print(f"brief: skipped ({exc})")
+
+
 def serve(args: argparse.Namespace) -> None:
     try:
         import uvicorn

goodnews/feeds.py

@@ -28,13 +28,40 @@ class FeedItem:
 
 
 def poll_all_sources(conn: sqlite3.Connection, limit: int | None = None) -> dict:
-    query = """
-        SELECT *
-        FROM sources
-        WHERE active = 1
-        ORDER BY id
+    return _poll_rows(conn, conn.execute(
+        "SELECT * FROM sources WHERE active = 1 ORDER BY id"
+    ).fetchall(), limit)
+
+
+def poll_due_sources(conn: sqlite3.Connection, limit: int | None = None) -> dict:
+    """Poll only active sources whose last successful poll is older than their
+    poll_interval_minutes (or that have never been polled successfully).
+
+    This is what makes poll_interval_minutes meaningful and lets a scheduler run
+    frequently without re-hitting feeds that are not yet due.
     """
-    rows = conn.execute(query).fetchall()
+    rows = conn.execute(
+        """
+        SELECT s.*
+        FROM sources s
+        WHERE s.active = 1
+          AND (
+            NOT EXISTS (
+                SELECT 1 FROM ingest_runs r
+                WHERE r.source_id = s.id AND r.status = 'ok'
+            )
+            OR (
+                SELECT MAX(r.finished_at) FROM ingest_runs r
+                WHERE r.source_id = s.id AND r.status = 'ok'
+            ) <= datetime('now', '-' || s.poll_interval_minutes || ' minutes')
+          )
+        ORDER BY s.id
+        """
+    ).fetchall()
+    return _poll_rows(conn, rows, limit)
+
+
+def _poll_rows(conn: sqlite3.Connection, rows: list[sqlite3.Row], limit: int | None) -> dict:
     if limit is not None:
         rows = rows[:limit]
 

goodnews/llm.py

@@ -200,8 +200,11 @@ def classify_articles(
     limit: int,
     include_rejected: bool = False,
     dry_run: bool = False,
+    only_unclassified: bool = False,
 ) -> list[tuple[int, dict]]:
-    rows = _classification_candidates(conn, limit=limit, include_rejected=include_rejected)
+    rows = _classification_candidates(
+        conn, limit=limit, include_rejected=include_rejected, only_unclassified=only_unclassified
+    )
     results = []
     for row in rows:
         try:
@@ -297,8 +300,16 @@ def _classification_candidates(
     conn: sqlite3.Connection,
     limit: int,
     include_rejected: bool,
+    only_unclassified: bool = False,
 ) -> list[sqlite3.Row]:
-    where = "" if include_rejected else "WHERE s.accepted = 1 OR s.constructive_score >= 4"
+    filters = []
+    if not include_rejected:
+        filters.append("(s.accepted = 1 OR s.constructive_score >= 4)")
+    if only_unclassified:
+        # Articles still carrying the fast heuristic score, i.e. not yet judged
+        # by the model. Lets a scheduled cycle only spend the LLM on new items.
+        filters.append("s.model_name LIKE 'heuristic-%'")
+    where = ("WHERE " + " AND ".join(filters)) if filters else ""
     return conn.execute(
         f"""
         SELECT