cmdop-llm 0.1.0

Python SDK for CMDOP LLM Service - OpenAI-compatible API for 200+ AI models

CMDOP LLM Python SDK

Python SDK for CMDOP LLM Service - OpenAI-compatible API for 200+ AI models.

Installation

pip install cmdop-llm

Quick Start

from cmdop_llm import CmdopLLM

client = CmdopLLM(api_key="your-api-key")

response = client.chat.completions.create(
    model="anthropic/claude-3.5-sonnet",
    messages=[{"role": "user", "content": "Hello!"}]
)
print(response.choices[0].message.content)

Features

• Drop-in OpenAI replacement - Same API, different models
• 200+ Models - GPT-4, Claude, Llama, Mistral, Gemini via single endpoint
• Streaming - Real-time token streaming
• Vision & OCR - Image analysis and text extraction
• Image Generation - FLUX, DALL-E and other models
• Async Support - Full async/await support

Environment Variables

export CMDOP_API_KEY="your-api-key"
export CMDOP_BASE_URL="https://llm.cmdop.com"  # Optional, default

Usage Examples

Chat Completion

from cmdop_llm import CmdopLLM

client = CmdopLLM()

response = client.chat.completions.create(
    model="openai/gpt-4o",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Explain quantum computing."}
    ],
    temperature=0.7,
    max_tokens=1000,
)
print(response.choices[0].message.content)

Streaming

stream = client.chat.completions.create(
    model="anthropic/claude-3.5-sonnet",
    messages=[{"role": "user", "content": "Write a poem."}],
    stream=True,
)

for chunk in stream:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="")

Vision Analysis

result = client.vision.analyze(
    image_url="https://example.com/image.jpg",
    prompt="Describe this image"
)
print(result.description)
print(result.extracted_text)

OCR Text Extraction

result = client.ocr.extract(
    image_url="https://example.com/document.png"
)
print(result.text)

Image Generation

response = client.images.generate(
    model="black-forest-labs/FLUX.1-schnell",
    prompt="A futuristic cityscape",
    size="1024x1024",
)
print(response.data[0].url)

Async Usage

import asyncio
from cmdop_llm import AsyncCmdopLLM

async def main():
    client = AsyncCmdopLLM()

    response = await client.chat.completions.create(
        model="openai/gpt-4o",
        messages=[{"role": "user", "content": "Hello!"}]
    )
    print(response.choices[0].message.content)

asyncio.run(main())

Available Models

Access 200+ models including:

• OpenAI: gpt-4o, gpt-4o-mini, gpt-4-turbo
• Anthropic: claude-3.5-sonnet, claude-3-opus, claude-3-haiku
• Google: gemini-pro, gemini-1.5-pro
• Meta: llama-3.1-405b, llama-3.1-70b
• Mistral: mistral-large, mixtral-8x22b
• Image: FLUX.1-schnell, FLUX.1-pro, stable-diffusion-xl

Use model format: provider/model-name (e.g., openai/gpt-4o)

API Reference

CmdopLLM

CmdopLLM(
    api_key: str = None,       # From CMDOP_API_KEY env if not set
    base_url: str = None,      # Default: https://llm.cmdop.com
    timeout: float = None,     # Request timeout
    max_retries: int = 2,      # Retry count
)

Resources

• client.chat.completions - Chat completions (OpenAI compatible)
• client.images - Image generation (OpenAI compatible)
• client.models - List available models
• client.vision - Vision analysis (CMDOP specific)
• client.ocr - OCR extraction (CMDOP specific)

License

MIT