aydie-genai 1.1.0

A simple and unified Python library to interact with various Large Language Models (LLMs) like Gemini, GPT, Claude, and more by abstracting provider-specific code and authentication.

aydie_genai

A simple, unified, and powerful Python library for generative AI.

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aydie_genai is a Python library designed to eliminate the complexity of working with multiple Generative AI models. Instead of writing different code for Gemini, OpenAI, Claude, Groq, and others, you can use one simple, unified function to access them all.

Key Features

• Unified Interface: A single generate() function for all supported models.
• Simple & Intuitive: Get started in minutes. No need to learn multiple SDKs.
• Provider Agnostic: Switch between models like gpt-4o and gemini-1.5-pro by changing a single string.
• Built-in Documentation: Rich docstrings provide in-console help via help(genai.generate).
• Robust Error Handling: Custom exceptions for common issues like missing API keys.

Supported Models

Provider	Supported Models	Environment Variable
Google	gemini-1.5-pro, gemini-1.5-flash, gemini-1.0-pro, gemini-2.5-pro, gemini-2.5-flash	GOOGLE_API_KEY
OpenAI	gpt-4o, gpt-4-turbo, gpt-3.5-turbo, gpt-4.1, gpt-4.1-mini	OPENAI_API_KEY
Anthropic	claude-3-opus-20240229, claude-3-sonnet-20240229, claude-3-haiku-20240307, claude-3.5-sonnet	ANTHROPIC_API_KEY
Groq	llama3-70b-8192, llama3-8b-8192, mixtral-8x7b-32768, llama3-70b-131k	GROQ_API_KEY
DeepSeek	deepseek-chat, deepseek-coder, deepseek-v2-chat	DEEPSEEK_API_KEY

Installation

Install aydie_genai directly from PyPI:

pip install aydie-genai

⚡ Quick Start

1. Set Up Your API Keys

The library loads API keys from environment variables. The easiest way to manage these is to create a .env file in your project's root directory:

# .env file
GOOGLE_API_KEY="your_google_api_key"
OPENAI_API_KEY="your_openai_api_key"
ANTHROPIC_API_KEY="your_anthropic_api_key"
GROQ_API_KEY="your_groq_api_key"
DEEPSEEK_API_KEY="your_deepseek_api_key"

2. Generate a Response

Using the library is incredibly simple. Just import genai and call the generate function.

from aydie_genai import genai

# Example 1: Using Google Gemini
response_gemini = genai.generate(
    model='gemini-1.5-pro',
    prompt='Explain the theory of relativity in simple terms for a five-year-old.',
    system_instruction='You are a friendly and patient teacher.'
)
print("Gemini says:", response_gemini)

# Example 2: Switching to OpenAI's GPT-4o is as easy as changing the model name
response_openai = genai.generate(
    model='gpt-4o',
    prompt='Write a short story about a robot who discovers music.'
)
print("\nOpenAI says:", response_openai)

Function Parameters

The genai.generate() function accepts the following parameters:

Parameter	Type	Description
model	str	Required. The identifier for the model you want to use (e.g., 'gpt-4o').
prompt	str	Required. The main user input or question for the model.
system_instruction	str	A directive to guide the model's behavior or personality.
temperature	float	Controls randomness (0.0 for deterministic, 2.0 for random). Defaults to 1.0.
max_tokens	int	The maximum number of tokens to generate in the response. Defaults to 2048.
top_p	float	Nucleus sampling parameter. Defaults to 1.0.
api_key	str	Directly pass an API key, overriding the environment variable. Defaults to None.

Contributing

Contributions are welcome! Whether it's adding new models, improving documentation, or fixing bugs, your help is appreciated. Please feel free to open an issue or submit a pull request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

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