Chimeric

Chimeric is a unified Python interface for multiple LLM providers with automatic provider detection and seamless switching.

Setup

Chimeric provides a unified interface for 7 major AI providers:

Each provider can be installed individually or together using extras:

# Individual providers
pip install "chimeric[openai]"
pip install "chimeric[anthropic]"
pip install "chimeric[google]"
pip install "chimeric[cohere]"
pip install "chimeric[groq]"
pip install "chimeric[cerebras]"
pip install "chimeric[grok]"

# Multiple providers
pip install "chimeric[openai,anthropic,google]"

# All providers
pip install "chimeric[all]"

Quickstart

from chimeric import Chimeric

client = Chimeric()  # Auto-detects API keys from environment

response = client.generate(
    model="gpt-4o",
    messages="Hello!"
)
print(response.content)

Use Cases

Multi-Provider Switching:

# Seamlessly switch between providers - string input
gpt_response = client.generate(model="gpt-4o", messages="Explain quantum computing")
claude_response = client.generate(model="claude-3-5-haiku-latest", messages="Write a poem about AI")
gemini_response = client.generate(model="gemini-2.5-flash", messages="Summarize climate change")

Flexibility:

# Mixed usage in same application
unified = client.generate(model="claude-3-5-haiku-latest", messages="Code review this function")
native = client.generate(model="claude-3-5-haiku-latest", messages="Debug this error", native=True)

# Use unified for consistent cross-provider code
print(unified.content)

# Use native for provider-specific features
if hasattr(native, 'stop_reason'):
    print(f"Claude stop reason: {native.stop_reason}")

Streaming:

stream = client.generate(
    model="gpt-4o",
    messages="Tell me a story about space exploration",
    stream=True
)

for chunk in stream:
    print(chunk.content, end="", flush=True)

Function Calling:

@client.tool()
def get_weather(city: str) -> str:
    """Get current weather for a city."""
    return f"Sunny, 72°F in {city}"


response = client.generate(
    model="gpt-4o",
    messages=[{"role": "user", "content": "What's the weather in NYC?"}]
)

Async Support:

import asyncio


async def main():
    response = await client.agenerate(
        model="claude-3-5-sonnet-latest",
        messages=[{"role": "user", "content": "Analyze this data"},
                  {"role": "assistant",
                   "content": "I'd be happy to help analyze data. What data would you like me to look at?"},
                  {"role": "user", "content": "Sales figures from Q4"}]
    )
    print(response.content)


asyncio.run(main())

Known Limitations

• Beta Status: API may change as we refine the interface
• Provider Dependencies: Each provider requires separate installation extra
• Rate Limits: Subject to individual provider rate limits and quotas
• Multimodal Support: Image and audio support is untested and may vary by provider
• Model Availability: Some models may not be available in all regions

Roadmap

• Embeddings Support: Unified interface for text embeddings across providers
• Mutli-Modal Support: Enhanced support for images and audio
• Cost Tracking: Built-in usage and cost monitoring
• Advanced Routing: Load balancing and failover between providers

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License: Chimeric is licensed under the MIT License.