Helio Playground is a sophisticated platform that provides a comprehensive environment for exploring and developing Large Language Model (LLM) applications. It offers a rich toolkit of components, enabling users to construct and evaluate LLM solutions tailored to their specific requirements.

Core Features and Capabilities: • Building Blocks: The platform provides a wide range of building blocks, including: o LLM Choices: Access to a variety of popular LLMs, such as Titan, Claude, Jurassic, Cohere, Mistral, etc. o Embedding Methods: Options for representing text as numerical vectors (embeddings from AWS Titan, Cohere, huggingface, etc.) o Solution Influencers: Frameworks (e.g., LangChain, Semantic), kernel, temperature, Top p, Top K, chunk size, chunk overlap, and more. o Data Processing: Tools for extracting text from PDFs using libraries like PyPDF and AWS Textract. o Vector Databases: Support for storing and retrieving embeddings using Faiss and AWS OpenSearch. o Retrieval Methods: Similarity search, MMR, and score thresholding. o Agent Tools: Components for building and managing LLM agents. o Chain Types: Different ways to combine LLM components into workflows. o Evaluation Types: Metrics for assessing LLM performance, including faithfulness, answer relevance, harmfulness, and cost efficiency. • Evaluation Framework: Helio Playground incorporates a rigorous evaluation framework based on the RAGAS evaluation chain. This enables users to assess the quality of their LLM solutions across various dimensions. • Consulting Services: The platform offers expert consulting and advisory services to help users prioritize use cases and select the most appropriate LLMs for their applications.