unified-llm-api-abstraction
Provides a single, consistent API interface to interact with multiple LLM providers (OpenAI, Anthropic, Cohere, Google) without rewriting code for provider-specific implementations. Abstracts away provider-specific authentication, request formatting, and response parsing.
streaming-response-generation
Enables real-time streaming of LLM responses token-by-token instead of waiting for complete responses. Supports both server-side streaming and client-side consumption with native integration for React applications.
token-usage-tracking
Tracks and reports token consumption across LLM API calls. Provides visibility into usage patterns and costs for billing and optimization purposes.
multi-modal-input-handling
Supports processing of multiple input modalities including text, images, and other content types through unified interface. Routes different input types to appropriate LLM providers with capability detection.
conversation-context-optimization
Automatically optimizes conversation context by summarizing, truncating, or prioritizing messages to stay within token limits. Maintains semantic meaning while reducing context size.
react-hook-integration-for-chat
Provides pre-built React hooks (useChat, useCompletion) that handle state management, message history, and streaming updates automatically. Eliminates boilerplate for managing conversation state and UI synchronization.
function-calling-schema-generation
Automatically generates and validates function calling schemas with strong TypeScript type inference. Enables structured tool use and function invocation through LLMs with runtime type safety.
prompt-engineering-abstraction
Provides utilities and patterns for constructing, managing, and optimizing prompts without writing raw prompt strings. Abstracts common prompt engineering patterns into reusable components.
+5 more capabilities