Update README.md

README.md

@@ -297,89 +297,3 @@ mypy pydantic_prompt
 ## License
 
 MIT
-```
-
-# Updated PR Description
-
-```
-# Initial Implementation of PydanticPrompt Library
-
-This PR introduces PydanticPrompt, a lightweight Python library for documenting Pydantic models for LLM interactions using standard Python docstrings.
-
-## Overview
-
-PydanticPrompt allows developers to document their Pydantic models with standard Python docstrings and then easily format that documentation for inclusion in LLM prompts, providing a clean, consistent way to describe expected outputs for large language models.
-
-## Key Features
-
-- **Simple decorator interface** (`@prompt_schema`)
-- **Uses standard Python docstrings** for field documentation
-- **Automatic type inference** including generics and nested models
-- **Optional validation rule display**
-- **Warnings for undocumented fields**
-- **Seamless integration** with existing Pydantic models
-
-## Implementation Details
-
-- Core functionality built around field inspection and docstring extraction
-- Uses Pydantic's JSON schema for validation rule discovery
-- Modern type annotations with mypy validation
-- Automated CI setup with GitHub Actions
-- Comprehensive linting with Ruff
-
-## Example Usage
-
-```python
-from pydantic import BaseModel, Field
-from pydantic_prompt import prompt_schema
-
-@prompt_schema
-class UserProfile(BaseModel):
-    name: str
-    """The full name of the user"""
-
-    age: int = Field(ge=0)
-    """User's age in years - must be a positive integer"""
-
-    email: str = Field(pattern=r"[^@]+@[^@]+\.[^@]+")
-    """Valid email address that will be used for communication"""
-
-# In an LLM prompt
-prompt = f"""
-Extract a UserProfile from this text according to this schema:
-
-{UserProfile.format_for_llm(include_validation=True)}
-
-Text: John Doe is 32 years old, contact him at john.doe@example.com
-"""
-```
-
-## Test Results
-
-All tests are passing:
-
-```
-====================================================================== test session starts ======================================================================
-platform linux -- Python 3.12.1, pytest-8.3.5, pluggy-1.5.0 -- /workspaces/PydanticPrompt/.venv/bin/python
-cachedir: .pytest_cache
-rootdir: /workspaces/PydanticPrompt
-configfile: pyproject.toml
-testpaths: tests
-collected 4 items                                                                                                                                               
-
-tests/test_pydantic_prompt.py::test_basic_docstring_extraction PASSED                                                                                     [ 25%]
-tests/test_pydantic_prompt.py::test_optional_fields PASSED                                                                                                [ 50%]
-tests/test_pydantic_prompt.py::test_validation_rules PASSED                                                                                               [ 75%]
-tests/test_pydantic_prompt.py::test_nested_models PASSED                                                                                                  [100%]
-
-======================================================================= 4 passed in 0.13s =======================================================================
-```
-
-## Changes Made
-
-- Created core implementation with docstring extraction
-- Added comprehensive type hints with mypy validation
-- Set up CI with GitHub Actions for automated testing
-- Added linting script for consistent code style
-- Implemented warnings for undocumented fields
-- Created detailed documentation and examples