Metadata-Version: 2.4
Name: schema_gen_ai
Version: 0.1.0
Summary: A Python tool to generate Pydantic response schemas using various LLM APIs
Home-page: https://github.com/Gokul-A/schema_gen_ai
Author: Gokulakrishnan Anand
Author-email: Gokulakrishnan Anand <gokula04@gmail.com>
License: MIT
Project-URL: Homepage, https://github.com/Gokul-A/schema_gen_ai
Project-URL: Repository, https://github.com/Gokul-A/schema_gen_ai
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Libraries
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pydantic>=2.11.7
Requires-Dist: openai>=2.6.1
Requires-Dist: anthropic>=0.71.0
Requires-Dist: google-genai>=1.46.0
Dynamic: author
Dynamic: home-page
Dynamic: license-file
Dynamic: requires-python

# LLM Schema Generator

A Python library that generates Pydantic response schemas based on user descriptions using various LLM providers (OpenAI, Anthropic Claude, Google Gemini).

## Installation

Install from PyPI:

pip install schema_gen_ai

# Example: Using OpenAI

from schema_gen_ai import generate_schema

schema_code = generate_schema(
    description="Extract name, age, and occupation from a person's bio",
    provider="openai",
    api_key="your_openai_api_key",  # Or set OPENAI_API_KEY env var
    model="gpt-4o-mini"  # Optional
)

print(schema_code)


# Example: Using gemini

from schema_gen_ai import generate_schema

schema_code = generate_schema(
    description="Extract name, age, and occupation from a person's bio",
    provider="gemini",
    api_key="your_gemini_api_key",  # Or set GOOGLE_API_KEY env var
    model="gemini-2.5-flash"  # Optional
)

print(schema_code)


# Example: Using OpenAI

from schema_gen_ai import generate_schema

schema_code = generate_schema(
    description="Extract name, age, and occupation from a person's bio",
    provider="claude",
    api_key="your_claude_api_key",  # Or set ANTHROPIC_API_KEY env var
    model="claude-sonnet-4-5-20250929"  # Optional
)

print(schema_code)
