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feat: Implement builder pattern for model configuration with multi-pr… (#2)
* feat: Implement builder pattern for model configuration with multi-provider support - Add comprehensive builder pattern for creating model configurations - Introduce support for OpenAI and Anthropic API integrations - Enhance prompt template configuration with flexible builder methods - Update prompts.json with improved schema definitions - Add builder usage examples and test suite - Extend README with builder pattern documentation - Bump version to 0.1.4 * docs: Add PyPI downloads badge to README * ci: Refactor test dependencies and GitHub Actions workflow - Remove dev dependencies from main requirements.txt - Add separate requirements-test.txt for test dependencies - Update CI workflow to install test requirements separately - Add environment variables for API keys in test workflow * ci: Install package in editable mode for testing - Add `pip install -e .` to CI workflow - Ensures tests can import local package during GitHub Actions runs * - Update test_prepare_model_config_required_fields to use specific error message matching
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‎.github/workflows/ci.yml

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@@ -26,9 +26,14 @@ jobs:
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip
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pip install -e ".[dev]"
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pip install -r requirements.txt
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pip install -r requirements-test.txt
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pip install -e .
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- name: Run tests
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env:
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OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
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ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
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run: |
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pytest --cov=promptix --cov-report=xml
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‎CHANGELOG.md

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# Changelog
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## [0.1.4] - 2024-02-02
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### Added
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- Builder pattern support for creating model configurations
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- New builder classes for CustomerSupport and CodeReview templates
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- Integration with both OpenAI and Anthropic APIs through builders
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- Comprehensive test suite for builder pattern functionality
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- Example implementations showing builder pattern usage
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### Changed
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- Enhanced model configuration preparation with builder pattern
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- Improved documentation with builder pattern examples
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- Added type hints and validation for builder methods
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## [0.1.3] - 2024-01-26
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### Added

‎README.md

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[![PyPI version](https://badge.fury.io/py/promptix.svg)](https://badge.fury.io/py/promptix)
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[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
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[![Python Versions](https://img.shields.io/pypi/pyversions/promptix.svg)](https://pypi.org/project/promptix/)
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[![PyPI Downloads](https://static.pepy.tech/badge/promptix)](https://pepy.tech/projects/promptix)
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A Python library for managing and using prompts with Promptix Studio integration. Promptix makes it easy to manage, version, and use prompts in your applications with a built-in web interface.
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@@ -87,6 +88,61 @@ model_config = Promptix.prepare_model_config(
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response = client.chat.completions.create(**model_config)
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```
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## Builder Pattern
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Promptix provides a fluent builder pattern interface for creating model configurations:
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```python
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from promptix import Promptix
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import openai
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client = openai.OpenAI()
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# Using builder pattern for CustomerSupport
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model_config = (
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Promptix.builder("CustomerSupport")
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.with_user_name("John Doe")
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.with_issue_type("account_settings")
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.with_issue_description("User cannot access account settings page")
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.with_technical_level("intermediate")
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.with_priority("medium")
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.with_memory([
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{"role": "user", "content": "I'm having trouble with my account settings"}
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])
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.build()
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)
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response = client.chat.completions.create(**model_config)
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# Using builder pattern for Code Review
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code_config = (
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Promptix.builder("CodeReview")
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.with_code_snippet(code_snippet)
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.with_programming_language("Python")
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.with_review_focus("Security and SQL Injection")
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.with_severity("high")
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.build()
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)
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# Anthropic Integration
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anthropic_config = (
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Promptix.builder("CustomerSupport")
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.with_version("v5")
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.with_user_name("John Doe")
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.with_issue_type("account_settings")
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.with_memory(memory)
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.for_client("anthropic")
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.build()
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)
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```
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The builder pattern provides:
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- Type-safe configuration building
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- Fluent interface for better code readability
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- Automatic validation of required fields
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- Support for multiple LLM providers
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- Clear separation of configuration concerns
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## Advanced Usage
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### Version Control

‎examples/builder_usage.py

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from promptix import Promptix
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import openai
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import anthropic
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from dotenv import load_dotenv
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# Load environment variables
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load_dotenv()
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def basic_builder_example() -> None:
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"""Basic example of using the builder pattern with OpenAI.
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This example demonstrates how to use Promptix with OpenAI's API for a customer support scenario.
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Requires OPENAI_API_KEY to be set in environment variables.
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"""
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try:
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client = openai.OpenAI() # Will automatically use OPENAI_API_KEY from environment
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memory= [
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{"role": "user", "content": "I'm having trouble with my account settings"},
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]
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# Build configuration using the builder pattern with CustomerSupport
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model_config = (
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Promptix.builder("CustomerSupport")
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.with_user_name("John Doe")
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.with_issue_type("account_settings")
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.with_issue_description("User cannot access account settings page after recent update")
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.with_technical_level("intermediate")
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.with_priority("medium")
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.with_memory(memory)
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.build()
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)
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print("Model Config:", model_config)
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print("\n\n")
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response = client.chat.completions.create(**model_config)
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print("Basic Example Response:", response.choices[0].message.content)
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except Exception as e:
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print(f"Error in basic builder example: {str(e)}")
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def advanced_builder_example() -> None:
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"""Advanced example showing code review features with OpenAI.
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This example demonstrates how to use Promptix for code review scenarios.
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Requires OPENAI_API_KEY to be set in environment variables.
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"""
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try:
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client = openai.OpenAI()
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memory= [
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{"role": "user", "content": "Can you review this code for security issues?"},
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]
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code_snippet = '''
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def process_user_input(data):
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query = f"SELECT * FROM users WHERE id = {data['user_id']}"
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return execute_query(query)
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'''
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model_config = (
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Promptix.builder("CodeReview")
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.with_code_snippet(code_snippet)
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.with_programming_language("Python")
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.with_review_focus("Security and SQL Injection")
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.with_severity("high")
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.with_memory(memory)
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.build()
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)
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print("Model Config:", model_config)
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print("\n\n")
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response = client.chat.completions.create(**model_config)
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print("Advanced Example Response:", response.choices[0].message.content)
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except Exception as e:
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print(f"Error in advanced builder example: {str(e)}")
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def anthropic_builder_example() -> None:
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"""Example of using the builder with Anthropic.
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This example demonstrates how to use Promptix with Anthropic's API.
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Requires ANTHROPIC_API_KEY to be set in environment variables.
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"""
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try:
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client = anthropic.Anthropic() # Will automatically use ANTHROPIC_API_KEY from environment
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memory= [
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{"role": "user", "content": "I'm having trouble with my account settings"},
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]
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model_config = (
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Promptix.builder("CustomerSupport")
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.with_version("v5")
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.with_user_name("John Doe")
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.with_issue_type("account_settings")
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.with_issue_description("User cannot access account settings page after recent update")
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.with_technical_level("intermediate")
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.with_priority("medium")
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.with_memory(memory)
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.for_client("anthropic")
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.build()
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)
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print("Anthropic Model Config:", model_config)
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print("\n\n")
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message = client.messages.create(**model_config)
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print("Anthropic Response:", message.content)
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except Exception as e:
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print(f"Error in Anthropic builder example: {str(e)}")
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if __name__ == "__main__":
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print("\n=== Basic Builder Example (CustomerSupport) ===")
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basic_builder_example()
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print("\n=== Advanced Builder Example (CodeReview) ===")
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advanced_builder_example()
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print("\n=== Anthropic Builder Example ===")
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anthropic_builder_example()

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