wordtoken 0.1.2

A unified library for interacting with LLMs, managing tokens, and estimating costs.

WordToken

WordToken is a lightweight and flexible Python library for interacting with popular large language model (LLM) providers, such as OpenAI and Anthropic's Claude. It offers a unified interface for generating text, estimating token usage, and calculating costs, making it ideal for both experimentation and production use.

Features

• Unified Interface: Interact seamlessly with multiple LLM providers through a single API.
• Token Management: Estimate token usage for prompts and responses.
• Cost Estimation: Calculate costs based on provider-specific pricing.
• Extensible: Easily add support for additional LLM providers.
• Sandbox-Friendly: Designed for experimentation and real-world integration.

Installation

Install WordToken using pip:

pip install wordtoken

Supported LLM Providers

•	OpenAI
•	Anthropic Claude

Usage

Initialize the Library

from wordtoken import WordToken

# Initialize WordToken with your API key
token = WordToken(api_key="your-api-key")

Generate Text

# Generate text with OpenAI
response = wordtoken.send_prompt(
    prompt="Write a short story about a robot learning to love.",
    model="gpt-3.5-turbo",
    max_tokens=100,
    temperature=0.7
)
print(response["output"])

Estimate Tokens

# Estimate tokens for a prompt
tokens = wordtoken.estimate_tokens(prompt="Hello, world!", model="gpt-3.5-turbo")
print(f"Estimated tokens: {tokens}")

Estimate Costs

# Estimate cost for a given number of tokens
tokens = 100  # Example token count
cost = wordtoken.calculate_cost(tokens=tokens, model="gpt-3.5-turbo")
print(f"Estimated cost: ${cost:.4f}")

Configuration

Available Models and Defaults

• OpenAI:
• Models: gpt-3.5-turbo, gpt-4, gpt-4o
• Pricing: Automatically managed based on the latest OpenAI rates.
• Claude (Anthropic):
• Models: claude-v1, claude-v2, etc.
• Pricing: Configurable for Anthropic's usage tiers.

Adding New Providers

Extend the library by adding a new adapter in the adapters.py file and updating the unified interface in the init.py file.

Development

Clone the Repository

git clone https://github.com/your-username/wordtoken.git
cd wordtoken

Install Dependencies

pip install -r requirements.txt

Run Tests

pytest

License

WordToken is licensed under the Apache License 2.0.

Contributing

Contributions are welcome! Please feel free to submit a pull request.

Roadmap

•	Support for additional LLM providers (e.g., Google Gemini, Cohere).
•	Advanced token visualization and usage analytics.
•	Integration with sandbox tools for prompt experimentation.

Contact

For questions or feedback, please contact [e-mail].