Pydantic AI Integration
no_llm provides seamless integration with Pydantic AI, allowing you to use any no_llm model through the Pydantic AI interface.
Installation
pip install "no_llm[pydantic-ai]"
Usage
The integration provides a NoLLMModel
class that wraps no_llm models for use with Pydantic AI:
from no_llm.integrations.pydantic_ai import NoLLMModel
from no_llm.registry import ModelRegistry
from pydantic_ai import Agent
from pydantic_ai.settings import ModelSettings
# Get models from registry
registry = ModelRegistry()
models = list(registry.list_models(provider="openai"))
# Create NoLLMModel with fallbacks
model = NoLLMModel(*models)
# Use with Pydantic AI
agent = Agent(model, model_settings=ModelSettings(temperature=0.7))
result = agent.run_sync("What is the capital of France?")
Features
- Model Fallbacks: Automatically tries alternative models if the primary model fails
- Parameter Validation: Validates and merges parameters from both no_llm and Pydantic AI settings
- Provider Support: Works with all no_llm supported providers including:
- OpenAI
- Anthropic
- Google Vertex AI
- Mistral
- Groq
- And more
Model Settings
The integration merges model settings from both no_llm and Pydantic AI:
# no/llm parameters are merged with Pydantic AI settings, and validated with no/llm
agent = Agent(
model,
model_settings=ModelSettings(
temperature=0.7,
top_p=0.9,
max_tokens=1000
)
)