Karpathy 的 HackerTube 怎么做？用 Claude Code / Codex 爬 Hacker News 评论，做自己的去算法视频站（实测）

export ANTHROPIC_BASE_URL="https://api.aicodewith.ai"
export ANTHROPIC_AUTH_TOKEN="你的 API Key"
mkdir -p ~/hackertube-mini && cd ~/hackertube-mini
claude --model claude-opus-5-5

# ~/.codex/config.toml
model = "gpt-6.1-sol"
model_reasoning_effort = "medium"
model_provider = "aicodewith"

[model_providers.aicodewith]
name = "aicodewith"
base_url = "https://api.aicodewith.ai/chatgpt/v1"
wire_api = "responses"
experimental_bearer_token = "你的 API Key"

# comments posted on 2026-09-01 (UTC) that contain "youtu"
curl "https://hn.algolia.com/api/v1/search_by_date?query=youtu&tags=comment&hitsPerPage=1000&numericFilters=created_at_i>=1788220800,created_at_i<1788307200"

Build a mini "HackerTube" in this folder: a static site of the YouTube videos that Hacker News commenters keep recommending to each other.
1. Fetch data only from the official HN Algolia API (https://hn.algolia.com/api/v1/search_by_date, tags=comment). Take every comment created from 2026-09-01 00:00 UTC to 2026-10-31 23:59 UTC that contains a YouTube link (youtube.com/watch, youtu.be/, /embed/, /shorts/, m.youtube.com, music.youtube.com). Note the API returns at most 1000 hits per query, so split the time range into small enough windows. Be polite: at most 2 requests per second. Save raw hits to data/comments.jsonl.
2. Extract and normalize the 11-character video ids (HTML-unescape the comment text first), and drop the commenter's own repeated links within the same comment.
3. For each video count: mentions, distinct commenters, distinct months, first and last mention, and keep up to 3 short quotes with links to the HN comment (https://news.ycombinator.com/item?id=...). Keep a video only if at least 2 different people linked it. Rank by distinct commenters, then mentions.
4. Get titles for the kept videos from YouTube oEmbed (https://www.youtube.com/oembed?url=...&format=json, no API key); if oEmbed fails keep the id and mark it unavailable. Save data/videos.json.
5. Generate site/index.html: a single static page, no login and no tracking, with a grid of cards (thumbnail from https://i.ytimg.com/vi/<id>/hqdefault.jpg, title, channel, "N people / M mentions", one quote) and a client-side text filter.
6. Write the whole pipeline as a reusable script build.py (stdlib only, with a --since/--until option) and run it. Finally reply with: total comments fetched, unique videos found, videos kept, the top 10 videos (id, title, people, mentions), and any problems you hit.

# Claude Code, non-interactive: only allow the commands this job needs
cat prompt.txt | claude -p --model claude-opus-5-5 \
  --permission-mode acceptEdits \
  --allowedTools "Bash(python3:*)" "Bash(curl:*)" "Bash(ls:*)" "Bash(mkdir:*)" "Bash(head:*)" "Bash(wc:*)"

# Codex, non-interactive (reads the prompt from stdin)
codex exec --skip-git-repo-check --sandbox danger-full-access - < prompt.txt

{
  "id": "6IFVTcM28KA",
  "title": "216,000,000 Spy TVs | The LG Smart TV Problem",
  "people": 15, "mentions": 18, "months": 2,
  "first_mention": "2026-09-07T10:52:26Z",
  "last_mention": "2026-10-13T16:41:11Z",
  "quotes": [
    {"author": "wavesplash", "date": "2026-09-07",
     "url": "https://news.ycombinator.com/item?id=49597752",
     "text": "... Worth a watch to see how bad this is"}
  ]
}

python3 build.py --since 2026-09-01 --until 2026-10-31   # full run
python3 build.py --skip-fetch --min-people 3              # rebuild from saved comments with a stricter rule
python3 build.py --full-scan                              # scan every comment instead of the "youtu" prefilter (slow)

https://www.youtube.com/watch?v=sCr_gb8rdEI?t=11m     <- "?" instead of "&"
https://youtu.be/69o-8Mtd3Kc&t=330                    <- "&" instead of "?"
https://www.youtube.com/watch?v=909o_kbCdFgll         <- 13 characters, not 11

For each comment in data/comments.jsonl, read the comment text and the HN story title,
and label what the commenter does with the video: strong_rec, rec, reference, joke or critical.
Write the labels to data/stance.jsonl. Then only count strong_rec and rec,
keep a video if at least 3 different people recommended it in at least 3 different months,
and rank by the number of distinct months. Rebuild site/index.html.