Understanding LLM providers and how they integrate with Agenite
Providers in Agenite are implementations of the LLMProvider
interface that connect your agents to specific large language model services. They translate the standardized Agenite messaging format into specific API calls and handle the response processing back into the Agenite format.
This provider abstraction allows your agents to:
Agenite includes official support for several popular LLM providers:
The OpenAI provider connects to OpenAI’s GPT models, including GPT-3.5 Turbo and GPT-4.
The Anthropic provider connects to Anthropic’s Claude models.
The AWS Bedrock provider connects to various models available on the AWS Bedrock service, including Claude, Llama, and more.
The Ollama provider connects to locally-hosted open-source models using Ollama.
Each provider has its own configuration options, but they typically include:
Here’s an example of the configuration options for the OpenAI provider:
Providers are passed to agents during initialization:
The agent uses the provider to handle all LLM communication, making it easy to switch providers:
You can create custom providers by implementing the LLMProvider
interface. This allows you to:
Here’s a simplified example of implementing a custom provider:
By extending BaseLLMProvider
, you only need to implement the generate
and stream
methods - the iterate
method will be handled for you.
When working with providers, follow these best practices:
Store API keys securely: Never hardcode API keys or credentials. Use environment variables or secure secret management.
Handle rate limits: Implement appropriate retry logic and respects rate limits of the LLM service.
Implement timeouts: Set reasonable timeouts to handle slow or non-responsive API calls.
Configure for your use case: Adjust provider configuration options to match your specific use case:
Implement error handling: Always handle errors from the LLM service gracefully.
Providers are a key component of Agenite’s flexibility. By implementing a common interface for different LLM services, providers enable your agents to use the best model for the job without being locked into a single vendor or technology.
In the next section, we’ll explore the concept of tools in Agenite and how they extend the capabilities of your agents.
Understanding LLM providers and how they integrate with Agenite
Providers in Agenite are implementations of the LLMProvider
interface that connect your agents to specific large language model services. They translate the standardized Agenite messaging format into specific API calls and handle the response processing back into the Agenite format.
This provider abstraction allows your agents to:
Agenite includes official support for several popular LLM providers:
The OpenAI provider connects to OpenAI’s GPT models, including GPT-3.5 Turbo and GPT-4.
The Anthropic provider connects to Anthropic’s Claude models.
The AWS Bedrock provider connects to various models available on the AWS Bedrock service, including Claude, Llama, and more.
The Ollama provider connects to locally-hosted open-source models using Ollama.
Each provider has its own configuration options, but they typically include:
Here’s an example of the configuration options for the OpenAI provider:
Providers are passed to agents during initialization:
The agent uses the provider to handle all LLM communication, making it easy to switch providers:
You can create custom providers by implementing the LLMProvider
interface. This allows you to:
Here’s a simplified example of implementing a custom provider:
By extending BaseLLMProvider
, you only need to implement the generate
and stream
methods - the iterate
method will be handled for you.
When working with providers, follow these best practices:
Store API keys securely: Never hardcode API keys or credentials. Use environment variables or secure secret management.
Handle rate limits: Implement appropriate retry logic and respects rate limits of the LLM service.
Implement timeouts: Set reasonable timeouts to handle slow or non-responsive API calls.
Configure for your use case: Adjust provider configuration options to match your specific use case:
Implement error handling: Always handle errors from the LLM service gracefully.
Providers are a key component of Agenite’s flexibility. By implementing a common interface for different LLM services, providers enable your agents to use the best model for the job without being locked into a single vendor or technology.
In the next section, we’ll explore the concept of tools in Agenite and how they extend the capabilities of your agents.