Research intake that reaches the hard places: gated APIs, paywalls, JS-walled pages, scanned PDFs.

gather pulls research out of the places most tools break on: arXiv papers, authenticated JSON APIs, JavaScript-rendered pages via a real headless browser, scanned images through OCR, and audio through transcription, alongside video, web, feeds, and local docs. The core runs with zero third-party runtime dependencies, and the same engine is reachable from the CLI, MCP tools, and plain Python. Every run writes a receipt you can re-check.

Project Telos | gather | crucible | index | forum | telos | learn | emet | buildlang

Features

• Extract any page to LLM-ready Markdown. gather extract turns a URL or local HTML file into structured Markdown plus a per-block record binding every block to its source node path and content hash. gather markdown prints the Markdown alone.
• Crawl whole sites. A concurrent, resumable crawler with robots.txt, sitemap discovery, URL dedup, and per-host throttling. gather crawl <url> --depth 2 --max-pages 50 emits an append-only, hash-chained ledger of the crawl as JSON.
• Track elements across redesigns. Fingerprint a scraped element once, then relocate it in any later version of the page and get a typed MATCH, RELOCATED, DRIFT, or GONE verdict (gather.track, Python API).
• Structured extraction with a hallucination check. gather.schema_extract binds schema fields to source nodes, and verify_record rejects any LLM-proposed field value not grounded in the fetched content.
• Streaming extraction. gather.stream parses an HTML stream chunk by chunk and emits partial-update commits as blocks complete, each folded into a hash chain, so a streamed extraction is replayable.
• Hard-source adapters behind one shape. Video with captions and comments (yt-dlp), static web, RSS/Atom feeds, local docs, arXiv, PDFs (pdftotext), authenticated JSON APIs (token from env, never logged), JS-rendered pages (headless Chromium), scanned images (tesseract), and audio (whisper). Each external tool is optional and only needed for its own adapter.
• Scholarly-graph federation. gather scholar queries OpenAlex, Semantic Scholar, and Crossref in one call, dedupes results by normalized DOI (never a fuzzy title match), and can capture citation edges as first-class records with --edges.
• A durable local corpus. Any fetch command takes --store DIR: bodies are content-addressed and deduped by hash, and gather corpus list|verify|digest|runs|search|stats|prune|availability inspects, re-checks, and queries what you stored.
• Multi-source runs. gather run config.json orchestrates many sources, a scope filter, and optional synthesis into one recorded session kept in the corpus history.
• Three surfaces, one engine. The full CLI, an MCP stdio server (gather mcp, tools gather.status, gather.doctor, gather.docs, gather.arxiv, gather.federation, gather.run), and a plain Python API.
• Zero-dependency core, opt-in speed. The core is pure standard library. gather-engine[fast] adds lxml parsing (about 2x on large documents), [browser] adds Playwright JS rendering, [stealth] adds curl_cffi TLS impersonation. gather caps reports what your install can actually do; a missing capability is reported as such, never faked.

Install

pip install gather-engine

The distribution is gather-engine; it installs the gather command and the gather package (import gather). Python 3.11+. From a source checkout, python -m gather runs the same CLI.

Quickstart

Extract a page to Markdown with a per-block receipt:

gather extract https://example.com/article

{
  "blocks": [
    {"path": "html[1]/body[1]/h1[1]", "sha256": "7e8cd2056da7...", "tag": "h1"},
    {"path": "html[1]/body[1]/p[1]",  "sha256": "64ec88ca00b2...", "tag": "p"}
  ],
  "content_sha256": "ef4430f5f70f...",
  "markdown_sha256": "752cce8836dd...",
  "method": "html-extract",
  "url": "https://example.com/article"
}

Then try the rest of the surface:

gather caps                                    # what this install can do (fast / browser / stealth)
gather crawl https://example.com --depth 2     # a hash-chained crawl ledger as JSON
gather arxiv "aperiodic monotile" --store ./corpus
gather scholar "10.1234/monotile" --edges --json
gather docs ./research-notes --scope "rubik,group theory"
gather corpus verify ./corpus                  # re-hash every stored body; non-zero exit on corruption

Offline demo, no install of extra tools, nothing downloaded:

python examples/demo.py        # one video parsed, scoped, digested, then a tampered receipt caught
python examples/pipeline.py    # the whole pipeline: run -> store -> verify -> recall, offline

demo.py prints each item with its hash and verify=True, then flips one receipt and shows the digest verification fail. The hash prefixes vary; the verify results are pinned by the test suite. For a browser-viewable version of the same proof, open examples/gather-demo.html.

Worked example: a mixed-source corpus

Gather from three different source types into one corpus, then re-check it:

gather web  "https://example.com/article" --store ./corpus
gather arxiv "2301.12345" --store ./corpus
gather docs ./notes --scope "monotile,tiling" --store ./corpus
gather corpus list ./corpus                 # every item with source, method, and hash
gather corpus search ./corpus --terms tiling --method http-get --json
gather corpus verify ./corpus               # MATCH per body, non-zero exit if anything is corrupt
gather corpus availability ./corpus         # per-record availability with typed outcomes

Every item carries its source, ref, method, timestamp, and a sha256 of the content, so verify can prove later that nothing in the corpus was altered, and search filters by scope terms, source, kind, or method.

Source federation, offline

Plan a fleet of sources before probing any of them:

gather federation validate registry.json --json   # check rows against a closed contract
gather federation plan registry.json --json       # one deterministic capture plan per source
gather federation policy policy.json --json       # audit retry/backoff rules as typed verdicts
gather federation entity entities.json --json     # audit entity-resolution matches

All four run offline; no probe fires. A registry row is a catalog fact and is never reported as coverage, availability, or content.

Optional capability backends

pip install 'gather-engine[fast]'      # lxml, about 2x parse speed on large docs
pip install 'gather-engine[browser]'   # Playwright JS render (then: playwright install chromium)
pip install 'gather-engine[stealth]'   # curl_cffi TLS/browser impersonation

The core never grows a hard dependency. Install a backend and it registers; skip it and the stdlib path or an explicit UNVERIFIABLE result stands in.

Python API

from gather.web import WebSource
from gather.digest import digest, verify_digest

items = WebSource().fetch("https://example.com/article")
d = digest(items)          # a sealed digest over every item's receipt
assert verify_digest(d)    # re-derive the seal; False if anything was altered

The same seams the CLI uses are importable: gather.extract, gather.crawl, gather.track, gather.schema_extract, gather.stream, gather.search, gather.store, gather.run, and the source adapters. ARCHITECTURE.md maps the modules and seams.

Security notes

The web adapter reads static HTML and does not run JavaScript; a client-rendered page yields its shell, and the method says so. The browser adapter runs a real headless browser and is the most exposed edge: its host guard covers only the first navigation, so do not point it at untrusted URLs where internal services are reachable. The threat model is in ARCHITECTURE.md. Credentials enter only through gather.credentials, read from the environment by name, never logged, never written into a receipt or URL.

Documentation

• docs/INTRODUCTION.md: what gather is, core concepts, and a first-ten-minutes walkthrough.
• USAGE.md: the operator surface, command by command.
• ARCHITECTURE.md: the design map, seams, and threat model.
• docs/WEB-ENGINE-UPLIFT.md: the web-data engine roadmap and benchmarks.
• docs/ENTERPRISE-READINESS.md: context envelopes, action receipts, and host-neutral operation for unattended agents.
• CHANGELOG.md: version history. Current release: 1.6.1.

Peer projects: crucible (judgment), index (code maps), forum (orchestration), telos (the engine).

Why it matters

Research breaks when sources become a blur. One rule sits underneath all of it: every item records how it was obtained. A quote fetched over HTTP, a page rendered in a browser, text recognized from a scan, and a statement synthesized from fragments are all valid items, but they are not equally direct, and the method field plus the digest seal keep that difference on the record and re-checkable. If that discipline matters to your workflow, gather was built for it; if you just need the intake, it never gets in your way.

License

Gather is fair-source: open to read, run, and build on, with commercial use reserved so the project can fund its own development. See LICENSE.

Work with it

Bring papers, transcripts, local docs, or awkward public materials that need provenance before synthesis; source-adapter testing and research-lab feedback are the most useful pressure right now. To develop against a checkout:

python -m pip install -e ".[dev]"
python -m pytest        # 417 tests
python -m ruff check src tests examples
python -m mypy

Keep the README, package metadata, and examples aligned with current behavior before opening a PR.