elizaos-plugin-openai 2.0.0a4

elizaOS OpenAI Plugin - OpenAI API integration for text, image, audio, and embeddings

elizaOS OpenAI Plugin (Python)

A type-safe async Python client for OpenAI APIs, designed for use with elizaOS.

Features

• 🔒 Strong typing with Pydantic validation
• ⚡ Async-first using httpx
• 🎯 Fail-fast error handling - no silent failures
• 📝 Full API coverage:
  • Text generation (GPT-4, GPT-4o, etc.)
  • Embeddings (text-embedding-3-small, etc.)
  • Image generation (DALL-E)
  • Image description (GPT-4 Vision)
  • Audio transcription (Whisper)
  • Text-to-speech
  • Tokenization (tiktoken)

Installation

pip install elizaos-plugin-openai

Quick Start

import asyncio
from elizaos_plugin_openai import OpenAIPlugin

async def main():
    # Create plugin (uses OPENAI_API_KEY env var by default)
    async with OpenAIPlugin() as plugin:
        # Generate text
        response = await plugin.generate_text_large(
            "Explain quantum computing in 2 sentences."
        )
        print(response)

        # Create embedding
        embedding = await plugin.create_embedding("Hello, world!")
        print(f"Embedding dimensions: {len(embedding)}")

        # Describe an image
        description = await plugin.describe_image(
            "https://example.com/image.jpg"
        )
        print(f"Title: {description.title}")
        print(f"Description: {description.description}")

asyncio.run(main())

Configuration

from elizaos_plugin_openai import OpenAIPlugin

plugin = OpenAIPlugin(
    api_key="sk-...",  # Or use OPENAI_API_KEY env var
    base_url="https://api.openai.com/v1",
    small_model="gpt-5-mini",
    large_model="gpt-5",
    embedding_model="text-embedding-3-small",
    embedding_dimensions=1536,
)

Streaming

async with OpenAIPlugin() as plugin:
    async for chunk in plugin.stream_text("Tell me a story..."):
        print(chunk, end="", flush=True)

Tokenization

from elizaos_plugin_openai import tokenize, detokenize, count_tokens

# Count tokens
count = count_tokens("Hello, world!", model="gpt-5")
print(f"Token count: {count}")

# Tokenize and detokenize
tokens = tokenize("Hello, world!", model="gpt-5")
text = detokenize(tokens, model="gpt-5")

Error Handling

All API errors are raised as OpenAIClientError:

from elizaos_plugin_openai import OpenAIPlugin, OpenAIClientError

async with OpenAIPlugin() as plugin:
    try:
        result = await plugin.generate_text_large("...")
    except OpenAIClientError as e:
        print(f"API error ({e.status_code}): {e}")

License

MIT