📄️ Installing JorEl
Installation
📄️ Initialization
Creating the JorEl instance
📄️ Generating responses
JorEl provides several methods for generating responses from LLMs. Let's explore each one.
📄️ Using Images
JorEl makes it easy to work with images when using vision-capable models. You can include images in your requests using the ImageContent class, which supports loading images from various sources.
📄️ Working with Documents
JorEl allows you to provide context documents to inform the LLM's responses. Documents are structured pieces of information that can be referenced by the LLM during generation.
📄️ Using Tools
Tools allow LLMs to perform actions or retrieve information during conversations. JorEl provides a flexible system for defining and using tools.
📄️ Token Tracking
JorEl automatically tracks token usage across all generations, including complex scenarios where multiple API calls are made due to tool usage. This helps you monitor costs and optimize your LLM usage.
📄️ Cancellation Support
JorEl supports cancelling ongoing LLM generations using the standard AbortSignal API. This is useful for implementing timeouts, user-initiated cancellations, or cleaning up when operations are no longer needed.
📄️ Advanced Configuration
JorEl provides advanced configuration options for fine-tuning LLM behavior, including model-specific parameters and defaults. This guide covers configuration options beyond the basics.