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A lightweight Python library offering a unified interface for experimenting with popular large language models (LLMs) like OpenAI and Anthropic. WordToken simplifies prompt generation, token estimation, and cost calculation, making it an ideal tool for testing and research purposes.

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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 contact@wordtoken.com.

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A lightweight Python library offering a unified interface for experimenting with popular large language models (LLMs) like OpenAI and Anthropic. WordToken simplifies prompt generation, token estimation, and cost calculation, making it an ideal tool for testing and research purposes.

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