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fix(python): resolve ruff lint/format errors, add RELEASING.md
- Fix f-string and unused variable warnings in release script - Format all Python files to pass ruff format --check - Add RELEASING.md documenting release process for both runtimes Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
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‎RELEASING.md‎

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# Releasing Prompty
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This document describes how to publish new versions of the Prompty runtimes.
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## Overview
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Both runtimes use **tag-based releases**: you run a local script that bumps
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versions, commits, tags, and pushes. The tag triggers a CI workflow that
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builds, tests, and publishes to the package registry via OIDC (no secrets needed).
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| Runtime | Registry | Tag format | Script |
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|---------|----------|------------|--------|
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| Python | [PyPI](https://pypi.org/project/prompty/) | `python/{version}` | `python scripts/release.py` |
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| TypeScript | [npm](https://www.npmjs.com/package/@prompty/core) | `typescript/{version}` | `npm run release` |
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## Python
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### Prerequisites
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- Push access to `microsoft/prompty`
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- [PyPI trusted publisher](https://docs.pypi.org/trusted-publishers/) configured for `prompty`
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### Version format
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Python uses [PEP 440](https://peps.python.org/pep-0440/):
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`2.0.0a1` (alpha), `2.0.0b1` (beta), `2.0.0rc1` (release candidate), `2.0.0` (stable)
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### Publishing
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```bash
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cd runtime/python/prompty
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# Preview what will happen
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python scripts/release.py --dry-run
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# Bump prerelease: 2.0.0a1 → 2.0.0a2
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python scripts/release.py
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# Bump minor: 2.0.0a2 → 2.1.0a1
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python scripts/release.py --bump minor
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# Bump major: 2.1.0a1 → 3.0.0a1
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python scripts/release.py --bump major
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# Set explicit version (e.g., exit prerelease)
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python scripts/release.py --version 2.0.0
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```
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The script:
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1. Updates `prompty/_version.py`
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2. Commits: `chore(python): release v{version}`
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3. Tags: `python/{version}`
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4. Pushes commit + tag to origin
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CI (`prompty-python.yml`) then:
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1. Tests on Python 3.11/3.12/3.13 × ubuntu/macOS/windows (9 jobs)
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2. Builds wheel + sdist with flit
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3. Publishes to PyPI via OIDC trusted publisher
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### Verify
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```bash
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pip install prompty==2.0.0a2
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python -c "import prompty; print(prompty.__version__)"
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```
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## TypeScript
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### Prerequisites
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- Push access to `microsoft/prompty`
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- [npm trusted publishers](https://docs.npmjs.com/trusted-publishers) configured for
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`@prompty/core`, `@prompty/openai`, and `@prompty/foundry`
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### Version format
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TypeScript uses [semver](https://semver.org/) with prerelease:
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`2.0.0-alpha.1`, `2.0.0-beta.1`, `2.0.0-rc.1`, `2.0.0`
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### Publishing
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```bash
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cd runtime/typescript
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# Preview what will happen
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npm run release -- --dry-run
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# Bump prerelease: 2.0.0-alpha.1 → 2.0.0-alpha.2
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npm run release
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# Bump minor: 2.0.0-alpha.2 → 2.1.0-alpha.1
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npm run release -- --bump minor
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# Bump major: 2.1.0-alpha.1 → 3.0.0-alpha.1
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npm run release -- --bump major
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# Set explicit version (e.g., exit prerelease)
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npm run release -- --version 2.0.0
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```
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The script:
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1. Updates all 4 `packages/*/package.json` (linked versions)
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2. Updates cross-package `@prompty/*` dependency references
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3. Commits: `chore(typescript): release v{version}`
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4. Tags: `typescript/{version}`
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5. Pushes commit + tag to origin
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CI (`prompty-ts-release.yml`) then:
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1. Installs, builds, and tests
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2. Auto-detects npm dist-tag (`alpha` for prereleases, `latest` for stable)
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3. Publishes `@prompty/core`, `@prompty/openai`, `@prompty/foundry` via OIDC
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### Verify
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```bash
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npm info @prompty/core versions --json | tail -5
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```
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## Packages published
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### Python (single package with extras)
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| Install | What you get |
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|---------|-------------|
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| `pip install prompty` | Core only |
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| `pip install prompty[openai]` | + OpenAI provider |
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| `pip install prompty[foundry]` | + Microsoft Foundry provider |
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| `pip install prompty[jinja2]` | + Jinja2 renderer |
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| `pip install prompty[all]` | Everything |
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### TypeScript (separate packages)
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| Package | What it is |
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|---------|-----------|
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| `@prompty/core` | Loader, pipeline, types, tracing |
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| `@prompty/openai` | OpenAI provider |
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| `@prompty/foundry` | Microsoft Foundry provider |
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## Troubleshooting
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### OIDC publish fails with 403
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The trusted publisher config on the registry must match exactly:
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- **Owner**: `microsoft`
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- **Repository**: `prompty`
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- **Workflow filename**: `prompty-python.yml` (Python) or `prompty-ts-release.yml` (TypeScript)
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- **Environment**: *(leave blank)*
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### Tests pass locally but fail in CI
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The CI runs `ruff check .` and `ruff format --check .` before tests.
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Always run both locally before releasing:
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```bash
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# Python
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cd runtime/python/prompty
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ruff check . && ruff format --check . && python -m pytest tests/ -q
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# TypeScript
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cd runtime/typescript
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npm run build && npm run test
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```

‎runtime/python/prompty/prompty/model/_Connection.py‎

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@@ -82,11 +82,8 @@ def load_kind(data: dict, context: LoadContext | None) -> "Connection":
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return OAuthConnection.load(data, context)
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else:
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raise ValueError(
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f"Unknown Connection discriminator value: {discriminator_value}"
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)
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raise ValueError(f"Unknown Connection discriminator value: {discriminator_value}")
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else:
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raise ValueError("Missing Connection discriminator property: 'kind'")
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def save(self, context: SaveContext | None = None) -> dict[str, Any]:

‎runtime/python/prompty/prompty/model/_Prompty.py‎

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@@ -120,9 +120,7 @@ def load_inputs(data: dict | list, context: LoadContext | None) -> list[Property
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return [Property.load(item, context) for item in data]
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@staticmethod
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def save_inputs(
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items: list[Property], context: SaveContext | None
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) -> dict[str, Any] | list[dict[str, Any]]:
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def save_inputs(items: list[Property], context: SaveContext | None) -> dict[str, Any] | list[dict[str, Any]]:
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if context is None:
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context = SaveContext()
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# Check if we can use shorthand (only primary property set)
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if context.use_shorthand and hasattr(item, "_shorthand_property"):
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shorthand_prop = item._shorthand_property
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if (
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shorthand_prop
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and len(item_data) == 1
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and shorthand_prop in item_data
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):
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if shorthand_prop and len(item_data) == 1 and shorthand_prop in item_data:
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result[name] = item_data[shorthand_prop]
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continue
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result[name] = item_data
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return [Property.load(item, context) for item in data]
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@staticmethod
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def save_outputs(
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items: list[Property], context: SaveContext | None
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) -> dict[str, Any] | list[dict[str, Any]]:
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def save_outputs(items: list[Property], context: SaveContext | None) -> dict[str, Any] | list[dict[str, Any]]:
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if context is None:
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context = SaveContext()
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# Check if we can use shorthand (only primary property set)
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if context.use_shorthand and hasattr(item, "_shorthand_property"):
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shorthand_prop = item._shorthand_property
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if (
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shorthand_prop
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and len(item_data) == 1
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and shorthand_prop in item_data
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):
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if shorthand_prop and len(item_data) == 1 and shorthand_prop in item_data:
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result[name] = item_data[shorthand_prop]
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continue
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result[name] = item_data
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return [Tool.load(item, context) for item in data]
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@staticmethod
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def save_tools(
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items: list[Tool], context: SaveContext | None
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) -> dict[str, Any] | list[dict[str, Any]]:
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def save_tools(items: list[Tool], context: SaveContext | None) -> dict[str, Any] | list[dict[str, Any]]:
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if context is None:
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context = SaveContext()
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# Check if we can use shorthand (only primary property set)
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if context.use_shorthand and hasattr(item, "_shorthand_property"):
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shorthand_prop = item._shorthand_property
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if (
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shorthand_prop
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and len(item_data) == 1
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and shorthand_prop in item_data
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):
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if shorthand_prop and len(item_data) == 1 and shorthand_prop in item_data:
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result[name] = item_data[shorthand_prop]
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continue
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result[name] = item_data

‎runtime/python/prompty/prompty/model/_Property.py‎

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return ObjectProperty.load(data, context)
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else:
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# create new instance (stop recursion)
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return Property()
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else:
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# create new instance
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return Property()
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if data is not None and "kind" in data:
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instance.kind = data["kind"]
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if data is not None and "properties" in data:
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instance.properties = ObjectProperty.load_properties(
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data["properties"], context
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)
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instance.properties = ObjectProperty.load_properties(data["properties"], context)
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if context is not None:
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instance = context.process_output(instance)
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return instance
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@staticmethod
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def load_properties(
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data: dict | list, context: LoadContext | None
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) -> list[Property]:
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def load_properties(data: dict | list, context: LoadContext | None) -> list[Property]:
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if isinstance(data, dict):
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result: list[Property] = []
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for k, v in data.items():
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return [Property.load(item, context) for item in data]
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@staticmethod
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def save_properties(
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items: list[Property], context: SaveContext | None
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) -> dict[str, Any] | list[dict[str, Any]]:
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def save_properties(items: list[Property], context: SaveContext | None) -> dict[str, Any] | list[dict[str, Any]]:
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if context is None:
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context = SaveContext()
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# Check if we can use shorthand (only primary property set)
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if context.use_shorthand and hasattr(item, "_shorthand_property"):
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shorthand_prop = item._shorthand_property
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if (
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shorthand_prop
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and len(item_data) == 1
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and shorthand_prop in item_data
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):
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if shorthand_prop and len(item_data) == 1 and shorthand_prop in item_data:
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result[name] = item_data[shorthand_prop]
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continue
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result[name] = item_data
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if obj.kind is not None:
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result["kind"] = obj.kind
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if obj.properties is not None:
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result["properties"] = ObjectProperty.save_properties(
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obj.properties, context
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)
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result["properties"] = ObjectProperty.save_properties(obj.properties, context)
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return result
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‎runtime/python/prompty/prompty/model/_Tool.py‎

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return [Binding.load(item, context) for item in data]
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@staticmethod
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def save_bindings(
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items: list[Binding], context: SaveContext | None
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) -> dict[str, Any] | list[dict[str, Any]]:
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def save_bindings(items: list[Binding], context: SaveContext | None) -> dict[str, Any] | list[dict[str, Any]]:
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if context is None:
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context = SaveContext()
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104102
# Check if we can use shorthand (only primary property set)
105103
if context.use_shorthand and hasattr(item, "_shorthand_property"):
106104
shorthand_prop = item._shorthand_property
107-
if (
108-
shorthand_prop
109-
and len(item_data) == 1
110-
and shorthand_prop in item_data
111-
):
105+
if shorthand_prop and len(item_data) == 1 and shorthand_prop in item_data:
112106
result[name] = item_data[shorthand_prop]
113107
continue
114108
result[name] = item_data
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132126
return OpenApiTool.load(data, context)
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134128
else:
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136129
# load default instance
137130
return CustomTool.load(data, context)
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139132
else:
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141133
raise ValueError("Missing Tool discriminator property: 'kind'")
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143135
def save(self, context: SaveContext | None = None) -> dict[str, Any]:
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236228
if data is not None and "kind" in data:
237229
instance.kind = data["kind"]
238230
if data is not None and "parameters" in data:
239-
instance.parameters = FunctionTool.load_parameters(
240-
data["parameters"], context
241-
)
231+
instance.parameters = FunctionTool.load_parameters(data["parameters"], context)
242232
if data is not None and "strict" in data:
243233
instance.strict = data["strict"]
244234
if context is not None:
245235
instance = context.process_output(instance)
246236
return instance
247237

248238
@staticmethod
249-
def load_parameters(
250-
data: dict | list, context: LoadContext | None
251-
) -> list[Property]:
239+
def load_parameters(data: dict | list, context: LoadContext | None) -> list[Property]:
252240
if isinstance(data, dict):
253241
result: list[Property] = []
254242
for k, v in data.items():
@@ -263,9 +251,7 @@ def load_parameters(
263251
return [Property.load(item, context) for item in data]
264252

265253
@staticmethod
266-
def save_parameters(
267-
items: list[Property], context: SaveContext | None
268-
) -> dict[str, Any] | list[dict[str, Any]]:
254+
def save_parameters(items: list[Property], context: SaveContext | None) -> dict[str, Any] | list[dict[str, Any]]:
269255
if context is None:
270256
context = SaveContext()
271257

@@ -281,11 +267,7 @@ def save_parameters(
281267
# Check if we can use shorthand (only primary property set)
282268
if context.use_shorthand and hasattr(item, "_shorthand_property"):
283269
shorthand_prop = item._shorthand_property
284-
if (
285-
shorthand_prop
286-
and len(item_data) == 1
287-
and shorthand_prop in item_data
288-
):
270+
if shorthand_prop and len(item_data) == 1 and shorthand_prop in item_data:
289271
result[name] = item_data[shorthand_prop]
290272
continue
291273
result[name] = item_data

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