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‎CHANGELOG.md‎

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## v0.0.92 (2025-12-25)
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### Feat
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- add cloud configuration examples and enhance path handling
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- support subdirectory basenames in output path generation
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- implement environment variable checks for cloud execution in code generator
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- enhance error handling for cloud execution in code generator
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- add centralized cloud configuration module for PDD CLI
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- enhance cloud URL configuration and authentication handling
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- enhance backup organization and schema validation
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### Fix
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- resolve path resolution mismatch in sync_orchestration
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- mock isatty in test fixture for headless mode compatibility
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- extend --force to skip API key prompts in CI/headless environments
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- add headless mode detection for CI/non-TTY environments
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- add timeout and non-TTY mode for pdd sync in CI
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- rename code.py to buggy.py in agentic test fixtures
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- correct typo in prompt tag from <proompt_content> to <prompt_content>
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- package docs and add fallback path resolution for includes
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### Refactor
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- remove local _safe_basename function and update tests for subdirectory handling
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- centralize cloud configuration and authentication handling
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## v0.0.91 (2025-12-24)
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### Feat
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- **Backup Directory Organization (Issue #174):** Moved all fix loop backup files from polluting source/test directories to `.pdd/backups/{module}/{timestamp}/` directory. Previously, backups like `module_1.py`, `module_2.py` would clutter the source directory; now they're stored as `.pdd/backups/module/20251224_143052/code_1.py` etc. Affects `fix_code_loop`, `fix_error_loop`, and `fix_verification_errors_loop`.
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- **Schema Validation Fallback (Issue #168):** Added `SchemaValidationError` exception to `llm_invoke.py`. When Pydantic/JSON schema validation fails, the error now triggers model fallback to try the next candidate model instead of just logging and skipping to the next batch item. This fixes cases where a model consistently returns malformed structured output.
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### Docs
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- **PDD Doctrine - The Mold Paradigm:** Expanded `docs/prompt-driven-development-doctrine.md` with ~300 lines covering the manufacturing analogy (wood carving → injection molding), the three capitals (test, prompt, grounding), tests as specification vs verification, compound returns of mold refinement, skill evolution for developers, and the complete analogy mapping table.
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### Data
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- **LLM Model Catalog Update:** Updated `data/llm_model.csv`:
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- Updated GLM model from 4p6 to 4p7 with revised pricing ($0.60/$2.20)
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- Enabled structured output (`True`) for DeepSeek v3.2-maas on Vertex AI
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### Deps
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- Updated `litellm[caching]` to version 1.80
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### Tests
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- Added ~700 lines of tests across `test_llm_invoke.py` and new `test_llm_invoke_integration.py` covering schema validation fallback behavior and model fallback on validation errors.
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- Added backup location verification tests in `test_fix_code_loop.py`, `test_fix_error_loop.py`, and `test_fix_verification_errors_loop.py` ensuring backups are created in `.pdd/backups/` directory.
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## v0.0.90 (2025-12-23)
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### Feat

‎README.md‎

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# PDD (Prompt-Driven Development) Command Line Interface
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![PDD-CLI Version](https://img.shields.io/badge/pdd--cli-v0.0.91-blue) [![Discord](https://img.shields.io/badge/Discord-join%20chat-7289DA.svg?logo=discord&logoColor=white)](https://discord.gg/Yp4RTh8bG7)
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![PDD-CLI Version](https://img.shields.io/badge/pdd--cli-v0.0.92-blue) [![Discord](https://img.shields.io/badge/Discord-join%20chat-7289DA.svg?logo=discord&logoColor=white)](https://discord.gg/Yp4RTh8bG7)
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## Introduction
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## Version
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Current version: 0.0.91
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Current version: 0.0.92
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To check your installed version, run:
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```
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These options can be used with any command:
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- `--force`: Overwrite existing files without asking for confirmation (commonly used with `sync`).
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- `--force`: Skip all interactive prompts (file overwrites, API key requests). Useful for CI/automation.
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- `--strength FLOAT`: Set the strength of the AI model (0.0 to 1.0, default is 0.5).
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- 0.0: Cheapest available model
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- 0.5: Default base model

‎context/core/cloud_example.py‎

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#!/usr/bin/env python3
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"""
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Example usage of the pdd.core.cloud module.
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This module provides centralized cloud configuration and authentication handling
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for PDD CLI commands. It manages:
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- Cloud function URLs (base URLs and specific endpoints)
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- JWT token retrieval (via environment variables or device flow)
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- Cloud feature availability checks
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File structure (relative to project root):
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pdd/
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core/
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cloud.py # The module being demonstrated
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context/
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core/
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cloud_example.py # This example file
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"""
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import os
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import sys
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from pathlib import Path
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# Ensure output directory exists
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script_dir = os.path.dirname(os.path.abspath(__file__))
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output_dir = os.path.join(script_dir, "output")
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os.makedirs(output_dir, exist_ok=True)
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# Add project root to sys.path to allow importing pdd module
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# Assuming script is in context/core/, project root is ../../
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project_root = os.path.abspath(os.path.join(script_dir, "../../"))
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if project_root not in sys.path:
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sys.path.insert(0, project_root)
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# Import the CloudConfig class and constants from the module
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from pdd.core.cloud import (
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CloudConfig,
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CLOUD_ENDPOINTS,
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PDD_CLOUD_URL_ENV,
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PDD_JWT_TOKEN_ENV,
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FIREBASE_API_KEY_ENV,
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GITHUB_CLIENT_ID_ENV,
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)
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# Import rich console for output
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from rich.console import Console
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console = Console()
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def example_cloud_urls():
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"""
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Demonstrate how to retrieve cloud URLs using CloudConfig.
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This shows:
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1. Getting the default base URL
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2. Getting specific endpoint URLs
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3. Overriding the base URL via environment variables (e.g., for local testing)
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"""
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console.print("[bold cyan]=== Cloud URL Configuration ===[/bold cyan]")
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# 1. Default Configuration
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base_url = CloudConfig.get_base_url()
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console.print(f"Default Base URL: [green]{base_url}[/green]")
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# 2. Specific Endpoints
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# CloudConfig.get_endpoint_url handles path construction automatically
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console.print("\n[bold]Endpoint URLs:[/bold]")
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for name in CLOUD_ENDPOINTS:
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url = CloudConfig.get_endpoint_url(name)
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console.print(f" - {name}: [blue]{url}[/blue]")
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# 3. Environment Override (Simulating a local emulator)
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console.print("\n[bold]Simulating Local Emulator Override:[/bold]")
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# Save original env var if it exists
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original_url = os.environ.get(PDD_CLOUD_URL_ENV)
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try:
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# Set a local emulator URL
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local_url = "http://127.0.0.1:5001/pdd-project/us-central1"
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os.environ[PDD_CLOUD_URL_ENV] = local_url
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console.print(f" Set {PDD_CLOUD_URL_ENV} = {local_url}")
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# Verify the override works
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new_base = CloudConfig.get_base_url()
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new_endpoint = CloudConfig.get_endpoint_url("generateCode")
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console.print(f" Overridden Base URL: [green]{new_base}[/green]")
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console.print(f" Overridden Endpoint: [blue]{new_endpoint}[/blue]")
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finally:
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# Restore environment
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if original_url:
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os.environ[PDD_CLOUD_URL_ENV] = original_url
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else:
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if PDD_CLOUD_URL_ENV in os.environ:
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del os.environ[PDD_CLOUD_URL_ENV]
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console.print()
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def example_cloud_availability():
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"""
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Demonstrate checking if cloud features are enabled.
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Cloud features require specific API keys to be present in the environment.
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"""
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console.print("[bold cyan]=== Cloud Availability Check ===[/bold cyan]")
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# Check current status
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is_enabled = CloudConfig.is_cloud_enabled()
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console.print(f"Cloud Enabled: [yellow]{is_enabled}[/yellow]")
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if not is_enabled:
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console.print("[dim]Cloud features are disabled because API keys are missing.[/dim]")
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console.print(f"[dim]Required: {FIREBASE_API_KEY_ENV}, {GITHUB_CLIENT_ID_ENV}[/dim]")
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else:
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console.print("[green]Cloud features are ready to use.[/green]")
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console.print()
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def example_authentication_flow():
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"""
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Demonstrate the authentication flow logic.
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Note: This example mocks the actual network calls to avoid interactive prompts
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or actual authentication requests during the demo run. It focuses on how
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the CloudConfig.get_jwt_token method prioritizes environment variables.
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"""
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console.print("[bold cyan]=== Authentication Flow ===[/bold cyan]")
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# 1. Testing/CI Flow (Token Injection)
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# This is the preferred method for CI/CD pipelines or automated tests
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console.print("[bold]Scenario 1: Token Injection (CI/Testing)[/bold]")
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fake_token = "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.fake.token"
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os.environ[PDD_JWT_TOKEN_ENV] = fake_token
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try:
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# When PDD_JWT_TOKEN is set, it returns immediately without network calls
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token = CloudConfig.get_jwt_token(verbose=True)
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console.print(f" Retrieved Token: [green]{token[:15]}...[/green]")
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if token == fake_token:
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console.print(" [success]Successfully retrieved injected token[/success]")
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finally:
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# Clean up
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if PDD_JWT_TOKEN_ENV in os.environ:
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del os.environ[PDD_JWT_TOKEN_ENV]
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# 2. Interactive Flow (Explanation)
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console.print("\n[bold]Scenario 2: Interactive Device Flow[/bold]")
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console.print(" If PDD_JWT_TOKEN is not set, CloudConfig.get_jwt_token() will:")
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console.print(" 1. Check for Firebase/GitHub credentials")
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console.print(" 2. Initiate the Device Flow (async)")
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console.print(" 3. Prompt the user to authorize via browser")
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console.print(" 4. Return the JWT token or None on failure")
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console.print("\n [dim]Skipping actual interactive auth for this non-interactive example.[/dim]")
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console.print()
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def main():
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"""
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Run all examples demonstrating the pdd.core.cloud module.
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"""
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console.print("\n[bold white on blue] PDD Cloud Config Module Examples [/bold white on blue]\n")
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example_cloud_urls()
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example_cloud_availability()
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example_authentication_flow()
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console.print("[bold green]Examples completed successfully![/bold green]")
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if __name__ == "__main__":
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main()

‎examples/hello/repo_root‎

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Subproject commit efe65d5056a7a737c50adbef5a3b01c29c32f44b

‎pdd/__init__.py‎

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"""PDD - Prompt Driven Development"""
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__version__ = "0.0.91"
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__version__ = "0.0.92"
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# Strength parameter used for LLM extraction across the codebase
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# Used in postprocessing, XML tagging, code generation, and other extraction

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