thejayman77
5601022cf7
- New frontend/ SvelteKit static SPA (Svelte 5), served by FastAPI from frontend/build (falls back to the legacy page if unbuilt). - Calm design system: cream/sage palette, serif headlines, generous space, no urgency colors, gentle motion (respects prefers-reduced-motion). - Home screen: mood-mode nav (Today/Wonder/People Helping/Solutions/Light Only/Grounded), the daily brief as a hero + remaining four, browsable mood lanes, an explicit calm end-state, inline Not today / Less like this / Hide affordances, and device-local Calm Filters mirroring goodnews/filters.py. - Backend: moods.py + GET /api/moods (single source of truth for the modes); FilterPrefs gains max_cortisol/max_ragebait ceilings (for Light Only). - Push categorical filters (include/mute topics+flavors, ceilings) into SQL in queries.feed so low-ranked-but-matching items (e.g. discovery for Wonder) are not truncated by ranking; only avoid-terms stay a Python pass. - PWA manifest + icon (installable; offline deferred per plan). - Multi-stage Dockerfile builds the site then serves it from the API. - Tests: queries.feed categorical filters (63 total). README updated. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
335 lines
11 KiB
Python
335 lines
11 KiB
Python
"""FastAPI service for goodNews.
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A read-only JSON API over the ingestion database, plus a small static site that
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consumes it. The same endpoints back both the website and any future companion
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app; the auto-generated OpenAPI docs at /docs are that shared contract.
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Run with the bundled CLI: goodnews serve
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Or directly: uvicorn goodnews.api:app --host 0.0.0.0 --port 8000
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The database path comes from GOODNEWS_DB (falling back to the repo's data dir),
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so the API and CLI always read the same file.
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"""
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from __future__ import annotations
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import json
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import os
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import re
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import sqlite3
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from collections import Counter
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from contextlib import contextmanager
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from datetime import datetime, timezone
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from pathlib import Path
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from fastapi import FastAPI, HTTPException, Query
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from fastapi.middleware.cors import CORSMiddleware
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from fastapi.staticfiles import StaticFiles
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from pydantic import BaseModel
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from . import feeds, queries
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from .db import connect, init_db
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from .filters import filter_articles, prefs_from_json
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from .llm import LocalModelClient
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from .moods import MOODS
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from .taxonomy import FLAVORS, TOPICS
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ROOT = Path(__file__).resolve().parents[1]
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DEFAULT_DB = ROOT / "data" / "goodnews.sqlite3"
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# Prefer the built SvelteKit site; fall back to the legacy single-page harness.
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FRONTEND_DIR = ROOT / "frontend" / "build"
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LEGACY_STATIC = Path(__file__).resolve().parent / "static"
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STATIC_DIR = FRONTEND_DIR if FRONTEND_DIR.is_dir() else LEGACY_STATIC
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def db_path() -> Path:
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return Path(os.environ.get("GOODNEWS_DB", str(DEFAULT_DB)))
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@contextmanager
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def get_conn():
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conn = connect(db_path())
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try:
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yield conn
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finally:
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conn.close()
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# --- Response models (the companion-app contract) ---------------------------
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class Category(BaseModel):
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key: str
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description: str
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class CategoriesResponse(BaseModel):
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topics: list[Category]
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flavors: list[Category]
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class CategoryCount(BaseModel):
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topic: str | None
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flavor: str | None
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count: int
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class Article(BaseModel):
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id: int
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title: str
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description: str | None = None
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url: str
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image_url: str | None = None
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published_at: str | None = None
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source: str
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topic: str | None = None
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flavor: str | None = None
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accepted: bool
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rank_score: int | None = None
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reason_code: str | None = None
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reason_text: str | None = None
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model_name: str | None = None
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rank: int | None = None # position within a brief, when applicable
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@classmethod
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def from_row(cls, row: dict) -> "Article":
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return cls(
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id=row["id"],
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title=row["title"],
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description=row.get("description"),
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url=row["canonical_url"],
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image_url=row.get("image_url"),
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published_at=row.get("published_at"),
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source=row["source_name"],
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topic=row.get("topic"),
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flavor=row.get("flavor"),
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accepted=bool(row.get("accepted")),
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rank_score=row.get("rank_score"),
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reason_code=row.get("reason_code"),
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reason_text=row.get("reason_text"),
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model_name=row.get("model_name"),
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rank=row.get("rank"),
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)
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class FeedResponse(BaseModel):
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topic: str | None
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flavor: str | None
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count: int
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items: list[Article]
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class BriefResponse(BaseModel):
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brief_date: str | None
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title: str | None
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items: list[Article]
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class RejectedExample(BaseModel):
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title: str
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reason: str
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class Candidate(BaseModel):
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id: int
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feed_url: str
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homepage_url: str | None = None
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name: str | None = None
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status: str
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preview: dict | None = None
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notes: str | None = None
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last_previewed_at: str | None = None
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created_at: str | None = None
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updated_at: str | None = None
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class SourcePreview(BaseModel):
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url: str
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sampled: int
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classified: bool
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accepted: int
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acceptance_rate: float
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avg_cortisol: float
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avg_ragebait: float
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avg_pr_risk: float
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newest_published: str | None
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recent_7d: int
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topic_mix: dict[str, int]
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flavor_mix: dict[str, int]
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examples_accepted: list[str]
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examples_rejected: list[RejectedExample]
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# --- App --------------------------------------------------------------------
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def create_app() -> FastAPI:
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app = FastAPI(
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title="goodNews API",
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version="0.1.0",
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description="Constructive, uplifting news — metadata and links only.",
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)
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# The website and companion app may live on other origins; allow them.
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_methods=["GET"],
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allow_headers=["*"],
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)
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@app.get("/healthz")
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def healthz() -> dict:
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with get_conn() as conn:
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init_db(conn)
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scored = conn.execute("SELECT COUNT(*) FROM article_scores").fetchone()[0]
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return {"status": "ok", "scored_articles": scored}
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@app.get("/api/categories", response_model=CategoriesResponse)
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def categories() -> CategoriesResponse:
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return CategoriesResponse(
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topics=[Category(key=k, description=v) for k, v in TOPICS.items()],
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flavors=[Category(key=k, description=v) for k, v in FLAVORS.items()],
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)
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@app.get("/api/moods")
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def moods() -> list[dict]:
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# The humane front door: each mood resolves to a filter preset the
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# client merges with the user's own Calm Filters.
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return MOODS
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@app.get("/api/category-counts", response_model=list[CategoryCount])
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def category_counts(accepted_only: bool = True, prefs: str | None = Query(None)) -> list[CategoryCount]:
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fp = prefs_from_json(prefs)
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with get_conn() as conn:
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if fp.is_empty():
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rows = queries.category_counts(conn, accepted_only=accepted_only)
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else:
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# Count over the SAME filtered set the feed would return, so the
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# browse numbers always match what the user actually sees.
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allrows = queries.feed(conn, accepted_only=accepted_only, limit=100000, offset=0)
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kept = filter_articles(allrows, fp, datetime.now(timezone.utc))
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counts = Counter((r["topic"], r["flavor"]) for r in kept)
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rows = [
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{"topic": t, "flavor": f, "count": n}
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for (t, f), n in sorted(counts.items(), key=lambda kv: (str(kv[0][0]), str(kv[0][1])))
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]
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return [CategoryCount(**row) for row in rows]
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@app.get("/api/feed", response_model=FeedResponse)
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def feed(
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topic: str | None = Query(None),
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flavor: str | None = Query(None),
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accepted_only: bool = True,
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limit: int = Query(30, ge=1, le=100),
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offset: int = Query(0, ge=0),
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prefs: str | None = Query(None),
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) -> FeedResponse:
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if topic and topic.lower() not in TOPICS:
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raise HTTPException(400, f"unknown topic: {topic}")
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if flavor and flavor.lower() not in FLAVORS:
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raise HTTPException(400, f"unknown flavor: {flavor}")
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fp = prefs_from_json(prefs)
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now = datetime.now(timezone.utc)
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with get_conn() as conn:
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if fp.is_empty():
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rows = queries.feed(
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conn, topic=topic, flavor=flavor, accepted_only=accepted_only, limit=limit, offset=offset
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)
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else:
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# Categorical filters (include/mute topics+flavors incl. active
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# pauses, cortisol ceiling) go to SQL so nothing is truncated by
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# ranking. Only word-boundary avoid-terms need a Python pass, so
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# over-fetch just enough to cover what they might remove.
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kw = dict(
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include_topics=fp.include_topics or None,
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include_flavors=fp.include_flavors or None,
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mute_topics=list(fp.muted_topics(now)) or None,
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mute_flavors=list(fp.muted_flavors(now)) or None,
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max_cortisol=fp.max_cortisol,
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max_ragebait=fp.max_ragebait,
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)
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if fp.avoid_terms:
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raw = queries.feed(
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conn, topic=topic, flavor=flavor, accepted_only=accepted_only,
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limit=min(2000, (offset + limit) * 4 + 50), offset=0, **kw,
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)
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kept = filter_articles(raw, fp, now) # drops avoid-term matches
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rows = kept[offset : offset + limit]
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else:
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rows = queries.feed(
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conn, topic=topic, flavor=flavor, accepted_only=accepted_only,
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limit=limit, offset=offset, **kw,
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)
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return FeedResponse(
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topic=topic,
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flavor=flavor,
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count=len(rows),
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items=[Article.from_row(r) for r in rows],
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)
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@app.get("/api/brief", response_model=BriefResponse)
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def brief(
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date: str | None = Query(None),
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limit: int = Query(10, ge=1, le=50),
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prefs: str | None = Query(None),
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) -> BriefResponse:
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fp = prefs_from_json(prefs)
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with get_conn() as conn:
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data = queries.brief(conn, brief_date=date, limit=limit)
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items = data["items"]
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if not fp.is_empty():
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# MVP: filter the stored brief DOWN; no refill from outside the brief.
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items = filter_articles(items, fp, datetime.now(timezone.utc))
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return BriefResponse(
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brief_date=data["brief_date"],
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title=data["title"],
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items=[Article.from_row(r) for r in items],
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)
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@app.get("/api/brief-dates", response_model=list[str])
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def brief_dates(limit: int = Query(30, ge=1, le=365)) -> list[str]:
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with get_conn() as conn:
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return queries.available_dates(conn, limit=limit)
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@app.get("/api/candidates", response_model=list[Candidate])
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def candidates(status: str | None = Query(None)) -> list[Candidate]:
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from .sources import list_candidates
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with get_conn() as conn:
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rows = list_candidates(conn, status=status)
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out = []
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for r in rows:
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d = dict(r)
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pj = d.pop("preview_json", None)
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d["preview"] = json.loads(pj) if pj else None
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out.append(Candidate(**d))
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return out
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@app.get("/api/source-preview", response_model=SourcePreview)
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def source_preview(
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url: str = Query(..., max_length=2048),
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sample: int = Query(25, ge=1, le=50),
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classify: bool = Query(False, description="Also classify with the local model (accurate but slower)"),
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) -> SourcePreview:
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# Read-only sample scoring; nothing is persisted. Only http(s) is allowed.
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# NOTE: fetching a user-supplied URL is an SSRF surface — before exposing
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# this publicly, also block private/loopback/link-local address ranges.
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if not re.match(r"^https?://", url, re.IGNORECASE):
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raise HTTPException(400, "url must start with http:// or https://")
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client = LocalModelClient.from_env() if classify else None
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try:
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data = feeds.preview_feed(url, sample=sample, client=client)
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except Exception as exc:
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raise HTTPException(502, f"could not preview feed: {exc}")
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return SourcePreview(**data)
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# Static site last, mounted at root, so /api/* and /healthz win.
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if STATIC_DIR.is_dir():
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app.mount("/", StaticFiles(directory=str(STATIC_DIR), html=True), name="site")
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return app
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app = create_app()
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