Summarize 👉 Point at any URL or file. Get the gist.

Fast CLI for summarizing anything you can point at:

• Web pages (article extraction; Firecrawl fallback if sites block agents)
• YouTube links (best-effort transcripts, optional Apify fallback)
• Remote files (PDFs/images/audio/video via URL — downloaded and forwarded to the model)
• Local files (PDFs/images/audio/video/text — forwarded or inlined; support depends on provider/model)

It streams output by default on TTY and renders Markdown to ANSI (via markdansi). At the end it prints a single “Finished in …” line with timing, token usage, and a best-effort cost estimate (when pricing is available).

Install

Requires Node 22+.

• npx (no install):

npx -y @steipete/summarize "https://example.com" --model google/gemini-3-flash-preview

• npm (global install):

npm i -g @steipete/summarize

• Homebrew (custom tap):

brew install steipete/tap/summarize

Apple Silicon only (arm64).

Quickstart

summarize "https://example.com" --model google/gemini-3-flash-preview

Input can be a URL or a local file path:

npx -y @steipete/summarize "/path/to/file.pdf" --model google/gemini-3-flash-preview
npx -y @steipete/summarize "/path/to/image.jpeg" --model google/gemini-3-flash-preview

Remote file URLs work the same (best-effort; the file is downloaded and passed to the model):

npx -y @steipete/summarize "https://example.com/report.pdf" --model google/gemini-3-flash-preview

YouTube (supports youtube.com and youtu.be):

npx -y @steipete/summarize "https://youtu.be/dQw4w9WgXcQ" --youtube auto

What file types work?

This is “best effort” and depends on what your selected model/provider accepts. In practice these usually work well:

• text/* and common structured text (.txt, .md, .json, .yaml, .xml, …)
  • text-like files are inlined into the prompt (instead of attached as a file part) for better provider compatibility
• PDFs: application/pdf (provider support varies; Google is the most reliable in this CLI right now)
• Images: image/jpeg, image/png, image/webp, image/gif
• Audio/Video: audio/*, video/* (when supported by the model)

Notes:

• If a provider rejects a media type, the CLI fails fast with a friendly message (no “mystery stack traces”).
• xAI models currently don’t support attaching generic files (like PDFs) via the AI SDK; use a Google/OpenAI/Anthropic model for those.

Model ids

Use “gateway-style” ids: <provider>/<model>.

Examples:

• openai/gpt-5.2
• anthropic/claude-opus-4-5
• xai/grok-4-fast-non-reasoning
• google/gemini-3-flash-preview
• openrouter/openai/gpt-5-nano (force OpenRouter)

Note: some models/providers don’t support streaming or certain file media types. When that happens, the CLI prints a friendly error (or auto-disables streaming for that model when supported by the provider).

Output length

--length controls how much output we ask for (guideline), not a hard truncation.

npx -y @steipete/summarize "https://example.com" --length long
npx -y @steipete/summarize "https://example.com" --length 20k

• Presets: short|medium|long|xl|xxl
• Character targets: 1500, 20k, 20000
• Optional hard cap: --max-output-tokens <count> (e.g. 2000, 2k)
  • Provider/model APIs still enforce their own maximum output limits.
• Minimums: --length numeric values must be ≥ 50 chars; --max-output-tokens must be ≥ 16.

Limits

• Text inputs over 10 MB are rejected before tokenization.
• Text prompts are preflighted against the model’s input limit (LiteLLM catalog), using a GPT tokenizer.

Common flags

npx -y @steipete/summarize <input> [flags]

• --model <provider/model>: which model to use (defaults to google/gemini-3-flash-preview)
• --timeout <duration>: 30s, 2m, 5000ms (default 2m)
• --retries <count>: LLM retry attempts on timeout (default 1)
• --length short|medium|long|xl|xxl|<chars>
• --max-output-tokens <count>: hard cap for LLM output tokens (optional)
• --stream auto|on|off: stream LLM output (auto = TTY only; disabled in --json mode)
• --render auto|md-live|md|plain: Markdown rendering (auto = best default for TTY)
• --format md|text: website/file content format (default text)
• --preprocess off|auto|always: controls uvx markitdown usage (default auto; always forces file preprocessing)
  • Install uvx: brew install uv (or https://astral.sh/uv/)
• --extract: print extracted content and exit (no summary) — only for URLs
  • Deprecated alias: --extract-only
• --json: machine-readable output with diagnostics, prompt, metrics, and optional summary
• --verbose: debug/diagnostics on stderr
• --metrics off|on|detailed: metrics output (default on; detailed prints a breakdown to stderr)

Website extraction (Firecrawl + Markdown)

Non-YouTube URLs go through a “fetch → extract” pipeline. When the direct fetch/extraction is blocked or too thin, --firecrawl auto can fall back to Firecrawl (if configured).

• --firecrawl off|auto|always (default auto)
• --extract --format md|text (default text)
• --markdown-mode off|auto|llm (default auto; only affects --format md for non-YouTube URLs)
  • auto: use an LLM converter when configured; may fall back to uvx markitdown
  • llm: force LLM conversion (requires a configured model key)
  • off: disable LLM conversion (still may return Firecrawl Markdown when configured)
• Plain-text mode: use --format text.

YouTube transcripts

--youtube auto tries best-effort web transcript endpoints first. When captions aren't available, it falls back to:

1. Apify (if APIFY_API_TOKEN is set): Uses a scraping actor (faVsWy9VTSNVIhWpR)
2. yt-dlp + Whisper (if YT_DLP_PATH is set): Downloads audio via yt-dlp, transcribes with OpenAI Whisper if OPENAI_API_KEY is set, otherwise falls back to FAL (FAL_KEY)

Environment variables for yt-dlp mode:

• YT_DLP_PATH - path to yt-dlp binary
• OPENAI_API_KEY - OpenAI Whisper transcription (preferred)
• FAL_KEY - FAL AI Whisper fallback

Apify costs money but tends to be more reliable when captions exist.

Configuration

Single config location:

• ~/.summarize/config.json

Supported keys today:

{
  "model": "openai/gpt-5.2"
}

Also supported:

• model: "auto" (automatic model selection + fallback)
• auto.rules (customize candidates / ordering)
• media.videoMode: "auto"|"transcript"|"understand"

Note: the config is parsed leniently (JSON5), but comments are not allowed.

Precedence:

1. --model
2. SUMMARIZE_MODEL
3. ~/.summarize/config.json
4. default

Environment variables

Set the key matching your chosen --model:

• OPENAI_API_KEY (for openai/...)
• ANTHROPIC_API_KEY (for anthropic/...)
• XAI_API_KEY (for xai/...)
• GEMINI_API_KEY (for google/...)
  • also accepts GOOGLE_GENERATIVE_AI_API_KEY and GOOGLE_API_KEY as aliases

OpenRouter (OpenAI-compatible):

• Set OPENROUTER_API_KEY=...
• Prefer forcing OpenRouter per model id: --model openrouter/<provider>/<model> (e.g. openrouter/openai/gpt-5-nano)
• Optional: OPENROUTER_PROVIDERS=... to specify provider fallback order (e.g. groq,google-vertex)

Example:

OPENROUTER_API_KEY=sk-or-... summarize "https://example.com" --model openrouter/openai/gpt-5-nano

With provider ordering (falls back through providers in order):

OPENROUTER_API_KEY=sk-or-... OPENROUTER_PROVIDERS="groq,google-vertex" summarize "https://example.com"

Legacy: OPENAI_BASE_URL=https://openrouter.ai/api/v1 (and either OPENAI_API_KEY or OPENROUTER_API_KEY) also works.

Optional services:

• FIRECRAWL_API_KEY (website extraction fallback)
• YT_DLP_PATH (path to yt-dlp binary for audio extraction)
• FAL_KEY (FAL AI API key for audio transcription via Whisper)
• APIFY_API_TOKEN (YouTube transcript fallback)

Model limits

The CLI uses the LiteLLM model catalog for model limits (like max output tokens):

• Downloaded from: https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json
• Cached at: ~/.summarize/cache/

Library usage (optional)

This package also exports a small library:

• @steipete/summarize/content
• @steipete/summarize/prompts

Development

pnpm install
pnpm check