chore(main): release 0.2.16

[w7-mgfcode]

🤖 I have created a release beep boop

0.2.16 (2026-05-19)

Features

• backtest: wire feature-aware models into the backtesting fold loop (#244) (5a65e35)
• backtest: wire feature-aware models into the backtesting fold loop (#244) (12f6cdf)
• forecast: add LightGBM feature-aware forecasting model (#242) (2b44491)
• forecast: add LightGBM feature-aware forecasting model (#242) (2f1b8a5)
• forecast: add Prophet-like additive forecasting model (#248) (7531eac)
• forecast: add Prophet-like additive forecasting model (#248) (0d219bc)
• forecast: add XGBoost feature-aware forecasting model (#247) (2091f2f)
• forecast: add XGBoost feature-aware forecasting model (#247) (53d3d57)
• forecast: feature-aware forecasting foundation — shared feature-frame contract (a37abfe)
• forecast: feature-aware forecasting foundation — shared feature-frame contract (#238) (b116489)
• release: ship the MLZOO advanced ML model zoo (A–C2) to main (#252) (689ac94)

Bug Fixes

• api: allow Tailscale CGNAT origins in dev CORS allow-list (#246) (82c457e)
• api: allow Tailscale CGNAT origins in dev CORS allow-list (#246) (d7527a5)
• jobs,ui: reach model_exogenous + block empty assumption dates in the planner (f09dec0)
• jobs,ui: reach model_exogenous from the what-if planner (#229) (4a2e5dc)
• ui: block planner runs with empty assumption dates (#228) (34104c9)

Documentation

• docs: add MLZOO planning briefs and feature-contract notes (#238) (22e39aa)
• docs: add PRP-MLZOO-C1 xgboost model and split the MLZOO-C roadmap (#247) (7adc045)
• docs: add PRP-MLZOO-C2 prophet-like additive model (#248) (0a25a75)
• docs: document the Prophet-like additive model (#248) (079e0b7)
• land MLZOO planning briefs and sync uv.lock (97d8057)

---

This PR was generated with Release Please. See documentation.

Summary by Sourcery

Add changelog entry and version bump for the 0.2.16 release.

New Features:

• Introduce feature-aware forecasting foundation with a shared feature-frame contract and wire feature-aware models into the backtesting fold loop.
• Add LightGBM, XGBoost, and Prophet-like additive feature-aware forecasting models and ship the MLZOO advanced ML model zoo (A–C2) to main.

Bug Fixes:

• Allow Tailscale CGNAT origins in the dev API CORS allow-list.
• Ensure the what-if planner reaches model_exogenous configuration and prevent planner runs with empty assumption dates.

Documentation:

• Document the MLZOO planning briefs, feature-contract notes, and advanced ML models including XGBoost and the Prophet-like additive model.

Summary by CodeRabbit

Version 0.2.16

• New Features

  • Feature-aware forecasting models
  • Backtest wiring functionality
  • Advanced model zoo release

• Bug Fixes

  • API CORS allow-list updates
  • Planner fixes for model assumption date handling

• Documentation

  • Planning briefs and model documentation updates

[coderabbitai]

No actionable comments were generated in the recent review. 🎉

ℹ️ Recent review info

⚙️ Run configuration

Configuration used: defaults

Review profile: CHILL

Plan: Pro

Run ID: 993b1b4a-0832-4708-b9b1-8d5ad553ce21

📥 Commits

Reviewing files that changed from the base of the PR and between 689ac94 and e54b44a.

📒 Files selected for processing (3)

• .release-please-manifest.json
• CHANGELOG.md
• pyproject.toml

---

📝 Walkthrough

Walkthrough

Release version 0.2.16 is recorded across .release-please-manifest.json, pyproject.toml, and CHANGELOG.md. The changelog documents feature-aware forecasting models, backtest wiring, MLZOO advanced model zoo, API CORS updates, planner fixes for exogenous and empty assumption dates, and new model documentation.

Changes

Version 0.2.16 Release

Layer / File(s)	Summary
Release manifest and package version update .release-please-manifest.json, pyproject.toml	Version bumped from 0.2.15 to 0.2.16 in both the release manifest and package metadata.
Release changelog entry CHANGELOG.md	New v0.2.16 release section dated 2026-05-19 documents feature-aware forecasting models, backtest wiring, MLZOO advanced model zoo release, API CORS allow-list updates, planner fixes for model exogenous and empty assumption dates, and MLZOO planning briefs and model documentation.

Estimated code review effort

🎯 1 (Trivial) | ⏱️ ~2 minutes

Possibly related issues

• release: ship the MLZOO advanced ML model zoo (A–C2) to main #252: Main issue tracking v0.2.16 release and MLZOO advanced model zoo shipment.

Possibly related PRs

• w7-mgfcode/ForecastLabAI#234: Previous patch release (0.2.14 → 0.2.15) with same version-bump and changelog automation pattern.
• w7-mgfcode/ForecastLabAI#69: Earlier release automation PR updating .release-please-manifest.json, pyproject.toml, and CHANGELOG.md together.
• w7-mgfcode/ForecastLabAI#26: Early version-bump PR with same pattern of updating manifest and package version files.

Suggested labels

autorelease: tagged

Suggested reviewers

• w7-l7ab
• w7-learn

Poem

🐰 A little bump from fifteen to sixteen,
The finest release we've ever seen!
With forecasts aware and backtests that gleam,
MLZOO joins the feature dream!
Hop along, v0.2.16 flies!

🚥 Pre-merge checks | ✅ 5

✅ Passed checks (5 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title accurately summarizes the main change—a version bump release from 0.2.15 to 0.2.16, which is clearly reflected in all three modified files and the PR objectives.
Docstring Coverage	✅ Passed	No functions found in the changed files to evaluate docstring coverage. Skipping docstring coverage check.
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.

_{✏️ Tip: You can configure your own custom pre-merge checks in the settings.}

✨ Finishing Touches

🧪 Generate unit tests (beta)

• Create PR with unit tests
• Commit unit tests in branch release-please--branches--main--components--forecastlabai

---

Thanks for using CodeRabbit! It's free for OSS, and your support helps us grow. If you like it, consider giving us a shout-out.

❤️ Share

• X
• Mastodon
• Reddit
• LinkedIn

_{Comment @coderabbitai help to get the list of available commands and usage tips.}

[sourcery-ai]

Reviewer's Guide

Automated release bump to 0.2.16, updating the package version and changelog to include the latest feature, bugfix, and documentation entries for the MLZOO and feature‑aware forecasting work.

File-Level Changes

Change	Details	Files
Add 0.2.16 release entry to the changelog capturing new features, bug fixes, and documentation updates.	Insert a new 0.2.16 section with links to comparison tag and commit hashes. Document feature-aware forecasting foundation, LightGBM/XGBoost/Prophet-like models, and MLZOO model zoo release. Record API CORS, planner model_exogenous wiring, and planner validation bug fixes. Add documentation updates for MLZOO planning briefs and model docs including sync of uv.lock.	CHANGELOG.md
Bump library version metadata from 0.2.15 to 0.2.16 for the Python package and release tooling.	Update the project version field from 0.2.15 to 0.2.16 in the Python package configuration. Ensure release-please manifest is consistent with the new 0.2.16 version tag.	pyproject.toml .release-please-manifest.json

---

Tips and commands

Interacting with Sourcery

• Trigger a new review: Comment @sourcery-ai review on the pull request.
• Continue discussions: Reply directly to Sourcery's review comments.
• Generate a GitHub issue from a review comment: Ask Sourcery to create an
  issue from a review comment by replying to it. You can also reply to a
  review comment with @sourcery-ai issue to create an issue from it.
• Generate a pull request title: Write @sourcery-ai anywhere in the pull
  request title to generate a title at any time. You can also comment
  @sourcery-ai title on the pull request to (re-)generate the title at any time.
• Generate a pull request summary: Write @sourcery-ai summary anywhere in
  the pull request body to generate a PR summary at any time exactly where you
  want it. You can also comment @sourcery-ai summary on the pull request to
  (re-)generate the summary at any time.
• Generate reviewer's guide: Comment @sourcery-ai guide on the pull
  request to (re-)generate the reviewer's guide at any time.
• Resolve all Sourcery comments: Comment @sourcery-ai resolve on the
  pull request to resolve all Sourcery comments. Useful if you've already
  addressed all the comments and don't want to see them anymore.
• Dismiss all Sourcery reviews: Comment @sourcery-ai dismiss on the pull
  request to dismiss all existing Sourcery reviews. Especially useful if you
  want to start fresh with a new review - don't forget to comment
  @sourcery-ai review to trigger a new review!

Customizing Your Experience

Access your dashboard to:

• Enable or disable review features such as the Sourcery-generated pull request
  summary, the reviewer's guide, and others.
• Change the review language.
• Add, remove or edit custom review instructions.
• Adjust other review settings.

Getting Help

• Contact our support team for questions or feedback.
• Visit our documentation for detailed guides and information.
• Keep in touch with the Sourcery team by following us on X/Twitter, LinkedIn or GitHub.

[sourcery-ai]

Hey - I've found 1 issue

Prompt for AI Agents

Please address the comments from this code review:

## Individual Comments

### Comment 1
<location path="CHANGELOG.md" line_range="33" />
<code_context>
+### Documentation
+
+* **docs:** add MLZOO planning briefs and feature-contract notes ([#238](https://github.com/w7-mgfcode/ForecastLabAI/issues/238)) ([22e39aa](https://github.com/w7-mgfcode/ForecastLabAI/commit/22e39aa538d4aea0ddd188fb570faf9ab8537643))
+* **docs:** add PRP-MLZOO-C1 xgboost model and split the MLZOO-C roadmap ([#247](https://github.com/w7-mgfcode/ForecastLabAI/issues/247)) ([7adc045](https://github.com/w7-mgfcode/ForecastLabAI/commit/7adc045737f847c2e9ebf6034488bf36e8b64e6d))
+* **docs:** add PRP-MLZOO-C2 prophet-like additive model ([#248](https://github.com/w7-mgfcode/ForecastLabAI/issues/248)) ([0a25a75](https://github.com/w7-mgfcode/ForecastLabAI/commit/0a25a75307aaf37765fd9a67eba7cfbb19208eb1))
+* **docs:** document the Prophet-like additive model ([#248](https://github.com/w7-mgfcode/ForecastLabAI/issues/248)) ([079e0b7](https://github.com/w7-mgfcode/ForecastLabAI/commit/079e0b7965ad98b0635f93f66142ab7545487b97))
</code_context>
<issue_to_address>
**suggestion (typo):** Consider capitalizing “XGBoost” for consistency with the rest of the changelog and the library name.

Please change “xgboost” in this bullet to “XGBoost” to match the rest of this section and the library’s official name.

```suggestion
* **docs:** add PRP-MLZOO-C1 XGBoost model and split the MLZOO-C roadmap ([#247](https://github.com/w7-mgfcode/ForecastLabAI/issues/247)) ([7adc045](https://github.com/w7-mgfcode/ForecastLabAI/commit/7adc045737f847c2e9ebf6034488bf36e8b64e6d))
```
</issue_to_address>

---

Sourcery is free for open source - if you like our reviews please consider sharing them ✨

• X
• Mastodon
• LinkedIn
• Facebook

_{Help me be more useful! Please click 👍 or 👎 on each comment and I'll use the feedback to improve your reviews.}

[w7-mgfcode]

🤖 Created releases:

• v0.2.16

🌻