Providers

nagents supports multiple LLM providers with a unified interface, making it easy to switch between providers without changing your application logic.

Provider Types

Provider	Type	Description
OpenAI	ProviderType.OPENAI_COMPATIBLE	OpenAI API and compatible services
Anthropic	ProviderType.ANTHROPIC	Anthropic Claude API
Google	ProviderType.GEMINI_NATIVE	Google Gemini API

---

OpenAI Compatible

Works with OpenAI API and any compatible service (Azure, local models, etc.):

OpenAIAzure OpenAILocal Models

from nagents import Provider, ProviderType

provider = Provider(
    provider_type=ProviderType.OPENAI_COMPATIBLE,
    api_key="sk-...",
    model="gpt-4o-mini",
)

Available models:

• gpt-4o - Most capable
• gpt-4o-mini - Fast and affordable
• gpt-4-turbo - Previous generation
• gpt-3.5-turbo - Legacy, fastest

provider = Provider(
    provider_type=ProviderType.OPENAI_COMPATIBLE,
    api_key="your-azure-key",
    model="gpt-4",
    base_url="https://your-resource.openai.azure.com/openai/deployments/gpt-4",
)

Azure Configuration

Set base_url to your Azure OpenAI deployment endpoint.

# Ollama
provider = Provider(
    provider_type=ProviderType.OPENAI_COMPATIBLE,
    api_key="not-needed",  # (1)!
    model="llama2",
    base_url="http://localhost:11434/v1",
)

# vLLM
provider = Provider(
    provider_type=ProviderType.OPENAI_COMPATIBLE,
    api_key="not-needed",
    model="meta-llama/Llama-2-7b-chat-hf",
    base_url="http://localhost:8000/v1",
)

1. Local servers typically don't require an API key, but the parameter is still required.

---

Anthropic Claude

Native Anthropic API support with all Claude models:

from nagents import Provider, ProviderType

provider = Provider(
    provider_type=ProviderType.ANTHROPIC,
    api_key="sk-ant-...",
    model="claude-3-5-sonnet-20241022",
)

Available models:

Model	Description
claude-3-5-sonnet-20241022	Best balance of intelligence and speed
claude-3-opus-20240229	Most capable, best for complex tasks
claude-3-sonnet-20240229	Balanced performance
claude-3-haiku-20240307	Fastest, best for simple tasks

Model Selection

Start with claude-3-5-sonnet for most use cases. Use opus for complex reasoning and haiku for high-throughput, simple tasks.

---

Google Gemini

Native Gemini API support:

from nagents import Provider, ProviderType

provider = Provider(
    provider_type=ProviderType.GEMINI_NATIVE,
    api_key="...",
    model="gemini-2.0-flash",
)

Available models:

Model	Description
gemini-2.0-flash	Latest, fastest multimodal model
gemini-1.5-pro	Most capable, large context window
gemini-1.5-flash	Fast and efficient

---

Switching Providers

The unified interface makes it easy to switch providers dynamically:

multi_provider.py

import os
from pathlib import Path
from nagents import Agent, Provider, ProviderType, SessionManager

def get_provider(provider_name: str) -> Provider:
    """Create a provider based on name."""
    match provider_name:
        case "openai":
            return Provider(
                provider_type=ProviderType.OPENAI_COMPATIBLE,
                api_key=os.getenv("OPENAI_API_KEY"),
                model="gpt-4o-mini",
            )
        case "anthropic":
            return Provider(
                provider_type=ProviderType.ANTHROPIC,
                api_key=os.getenv("ANTHROPIC_API_KEY"),
                model="claude-3-5-sonnet-20241022",
            )
        case "gemini":
            return Provider(
                provider_type=ProviderType.GEMINI_NATIVE,
                api_key=os.getenv("GOOGLE_API_KEY"),
                model="gemini-2.0-flash",
            )
        case _:
            raise ValueError(f"Unknown provider: {provider_name}")


async def main():
    # Select provider from environment or config
    provider_name = os.getenv("LLM_PROVIDER", "openai")
    provider = get_provider(provider_name)

    session_manager = SessionManager(Path("sessions.db"))

    # Same agent code works with any provider!
    agent = Agent(
        provider=provider,
        session_manager=session_manager,
    )

    async for event in agent.run("Hello!"):
        if hasattr(event, 'chunk'):
            print(event.chunk, end="")

    await agent.close()

Provider Agnostic

Your application logic remains the same regardless of which provider you use. This makes it easy to:

• Switch providers for cost optimization
• Use different providers for different tasks
• Fail over to backup providers
• Test with local models, deploy with cloud providers

---

Provider Comparison

Feature Comparison

Feature	OpenAI	Anthropic	Gemini
Streaming
Tool Calling
Vision
Max Context	128K	200K	2M
Custom Base URL

---

Best Practices

Recommendations

1. Use environment variables for API keys
2. Start with smaller models (gpt-4o-mini, claude-3-haiku, gemini-flash) for development
3. Implement fallback logic for production systems
4. Monitor token usage via the usage field in events