LLM Clients are a critical component of FlashLearn. They are responsible for executing the API calls to external language model providers. In essence, clients act as the communication layer between your workflow and the LLM service, handling the necessary authentication, request formatting, and response parsing.
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Calling the API:
Each client takes care of sending your structured JSON requests (defined by your tasks and skills) to the appropriate API endpoint. The client handles connection details, rate limiting, and error management so you can focus on designing robust workflows. -
OPENAI-Compatible Clients:
FlashLearn supports all clients that are compatible with the OpenAI API. This means you can integrate with various providers or custom implementations that adhere to the OpenAI specification. Whether you’re using the official OpenAI client or another compatible service, FlashLearn’s architecture ensures a seamless integration. -
Extensibility:
While the built-in support covers popular providers, you can also develop custom client wrappers as needed. This flexibility allows you to leverage different LLM services under a uniform interface, making it easier to switch providers or combine multiple sources in your workflows.
In summary, LLM Clients in FlashLearn abstract away the complexity of API interactions, enabling you to harness the power of large language models with minimal configuration.