pictovap 0.7.9

Image workflow for content publishers who spend hours finding free images and placing them in articles.

Pictovap

Pictovap is for content publishers who spend hours finding free images and placing them in articles. It turns that manual loop into an inspectable workflow, from image search to a reviewable publishing plan. WordPress Gutenberg is the first-class integration today; the adapter-based core remains CMS-neutral.

Why This Exists

Pictovap began with a production pain at Yoldaolmak.com, an independent Turkish travel publisher. Long-form guides repeatedly reached the same last-mile bottleneck: an editor still had to find rights-appropriate images, decide which section each one belonged to, prepare metadata, upload assets to WordPress, and place Gutenberg blocks by hand. That work could take tens of minutes per article, and its cost grew directly with publishing volume.

This was not an abstract feature request. The project was extracted from that workflow so the hard-won parts could become reusable, reviewable open-source infrastructure for other publishers and CMS integrations. The original production case and its boundaries are documented in the Yoldaolmak case study.

The Problem

Every publisher runs the same manual routine before an article can go live: find images that actually fit the section they're going into, check whether the license permits the intended use, resize and convert them to the site's format, write alt text and a caption for each one, and place them at the right point in the CMS. None of this is hard, individually. It is, however, repetitive, easy to get wrong under deadline pressure, and it scales linearly with how much a publisher writes. Skipped alt text quietly erodes accessibility and SEO. Untracked image provenance is a license or attribution problem waiting to surface later, when it's expensive to fix. None of this shows up in a style guide — it shows up as an hour of an editor's afternoon, per article, forever.

Point solutions exist for pieces of this: stock photo plugins, DAM systems, generic AI image generators. What's largely missing is the connective layer — something that reads what the article actually needs, evaluates candidates against that need with a visible, auditable reason for every accept and reject, and hands a CMS a placement plan it can execute without a human re-deriving the same context from scratch.

The Solution

Pictovap is that connective layer, built as an open, adapter-based pipeline rather than a closed SaaS product:

Article Input → Visual Brief → Candidate Images → Fit Score
              → Provenance Pack → CMS Placement → Editor Report

• Visual Brief — a structured read of what imagery the article actually needs, derived from its heading structure and content, not from a generic "insert 3 images" rule.
• Fit Score — every candidate is scored against the brief with a transparent, deterministic reason attached (selected, rejected, or needs_review, plus why). No black-box relevance number.
• Provenance Pack — a persistent audit trail for every selected image: source, license status, attribution, a content hash, and the exact processing actions applied. This is what makes "where did this image come from and are we allowed to use it" answerable six months later.
• CMS Placement — a CMS-agnostic plan describing where and how each image should be placed, independent of whether the destination is WordPress, Ghost, Strapi, or something a contributor writes an adapter for tomorrow.
• Editor Report — a human-readable Markdown review surface, so an editor signs off on a report, not raw JSON, before anything reaches production.

What makes this radical isn't any single stage — it's that the whole pipeline is a public, inspectable contract instead of a hosted black box, and that it is honest about its own workings by default: the credential-free demo below runs the entire pipeline end-to-end, with zero API keys and zero network calls, so you can read exactly what it does before you ever hand it a real site.

Pictovap is not a stock photo search tool, a DAM, a generic AI image generator, or a WordPress-only plugin. It has no graphical interface yet — it is a CLI-first, adapter-based core, with the editor report as the intended human review surface and CMS adapters as the machine-facing execution layer.

Quickstart

Requires Python 3.10 or newer.

Install from PyPI and run the credential-free demo:

pip install pictovap
pictovap demo

  Brief:      4 slots from 3 sections
  Evaluated:  5 candidates
  Selected:   3 images
  Rejected:   4 candidates
  Placements: 3 instructions

No .env file, no API keys, no network calls — every candidate and score above comes from deterministic mock data, on purpose. This is the demo's guarantee, not just its default state.

Try Your Own Article

pictovap plan \
  --article path/to/your/article.md \
  --profile examples/profiles/sample-publisher.yaml \
  --output my-plan.json \
  --report my-report.md

my-plan.json is the canonical, machine-readable artifact for adapters and automation. my-report.md is the same plan, rendered for a human editor to review before anything gets published.

If you try Pictovap with a real non-sensitive article, please report whether the slots, scores, and report matched your editorial intent in issue #8. A Python version, operating system, command, and traceback are enough; do not include private article content.

External adapters should use only the documented public contracts. See the API Stability Policy for stable, experimental, and internal surfaces.

For the shortest implementation path, see the Framework Guide and the runnable external renderer package.

Adapters

Pictovap connects to the outside world only through adapters — the core pipeline has no hardcoded dependency on any specific image provider or CMS.

Image sources: Pictovap ships in-tree adapters for local folders, Unsplash, DepositPhotos, Openverse, and Pexels. Their protocol behavior and request/response handling are covered by unit tests; live availability depends on each provider and the credentials supplied by the publisher. Pixabay and Wikimedia Commons are open contribution opportunities — see Good First Issues. See Image Source Adapters.

CMS placement: WordPress is the most complete in-tree adapter. Ghost and Strapi are reference implementations with mocked API tests and documented limitations. See CMS Adapters.

Image-source adapters degrade gracefully when unconfigured — a missing API key produces an empty result, not a crash, so a partially configured profile still runs. CMS adapters fail clearly when publishing credentials are missing. Writing a new adapter means implementing one method (search_candidates or place) against a documented Protocol; see the Adapter Overview.

Third-party adapters can ship as independent Python packages. Generate a working package with pictovap scaffold provider <name> or pictovap scaffold cms <name>, validate it with pictovap.testing, and expose it through a standard Python entry point. See Building Adapter Plugins.

An installed plugin is a first-class runtime component, not only a discovered class. The same external package can be checked, planned, previewed, and run:

pictovap doctor --provider acme-images
pictovap plan --article article.md --provider acme-images --output plan.json
pictovap publish --plan plan.json --cms acme-cms --dry-run

Constructor settings are repeatable KEY=VALUE options. For credentials, use KEY=@ENV_VAR; Pictovap resolves the environment value without echoing it in diagnostics or output.

Language-Aware by Design

Pictovap's own code, comments, and documentation are English. The credential-free deterministic metadata path currently supports Turkish and English: article language is detected automatically (or set explicitly via the publisher profile), and alt text and captions follow that language. Other language codes can travel through the profile and visual-plan contracts, but their deterministic metadata templates are not yet implemented.

Current Status and Limitations

Pictovap is early open-source infrastructure. It has a genuinely credential-free local demo, documented core primitives, a real test suite, and a working adapter model — it does not yet claim broad ecosystem adoption or a large external contributor base.

Specifically:

• WordPress has the broadest in-tree placement behavior. Ghost and Strapi have mocked API tests and documented functional gaps; validate them against your own deployment before relying on them for publishing (see CMS Adapters).
• The credential-free demo always uses deterministic mock candidates by design, regardless of what's configured in .env — pictovap plan is where real, credentialed sources are used.
• Deterministic structural extraction and local metadata templates are tested for English and Turkish; other languages currently require a contributor language pack or an external metadata provider.

Compatibility Note

Product name: Pictovap. Since 0.3.0 the Python package, import name, and console-script entry point are all pictovap; pictova remains a deprecated alias — see Brand & Naming.

Contributing

Zero-install contribution: You don't need a local Python environment to contribute. Click Code -> Create codespace on main in GitHub to launch a configured, browser-based VS Code environment with the project dependencies ready to run.

The July 2026 Adapter Sprint has three claimable provider and CMS integrations with exact acceptance tests.

See the Documentation Portal for architecture, concepts, and adapter-writing guides, and DEVELOPER.md for the contribution workflow. Pull requests that add a new image source or CMS adapter, improve test coverage, or fix documentation are all welcome.

License

MIT — see LICENSE.