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Official Python SDK for TokenBee LLM inference gateway and observability.

Project description

TokenBee Python SDK

Official Python SDK for TokenBee - The Intelligent LLM Inference Gateway with Observability, Compression, and Privacy.

Features

  • Unified API: Access multiple LLM providers (OpenAI, Anthropic, Google, Mistral, etc.) through a single interface.
  • Intelligent Compression: Reduce token usage and latency with context-aware compression.
  • Privacy Guard: Automatic PII masking and privacy-preserving inference.
  • Built-in Observability: Automatic tracking of latency, costs, and token usage.

Installation

pip install tokenbee-sdk

Quick Start

from tokenbee import TokenBee, TokenBeeModel, CompressionRate

# Initialize the client
client = TokenBee(
    api_key="your_api_key_here",
    compression="auto",
    rate=CompressionRate.MEDIUM
)

# Send a request
response = client.send(
    model=TokenBeeModel.OPENAI_GPT_4O,
    input={
        "messages": [
            {"role": "user", "content": "Explain quantum entanglement in simple terms."}
        ]
    }
)

print(response["choices"][0]["message"]["content"])

Advanced Usage

Compression Control

You can specify the compression rate and method per request:

response = client.send(
    model=TokenBeeModel.ANTHROPIC_CLAUDE_3_5_SONNET,
    input={
        "messages": [...],
        "compression": "on",
        "rate": CompressionRate.HIGH,
        "privacy": True
    }
)

Supported Models

The SDK provides a TokenBeeModel enum with popular models:

  • TokenBeeModel.OPENAI_GPT_4O
  • TokenBeeModel.ANTHROPIC_CLAUDE_3_5_SONNET
  • TokenBeeModel.GEMINI_2_0_FLASH
  • ... and many others.

License

MIT

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