What is Contextwaise?
Contextwaise is a cutting-edge API and agent SDK tailored for teams focused on building retrieval-augmented generation (RAG) applications, AI agents, and various large language model (LLM) products. It assesses retrieved materials, including passages, web pages, chat logs, and tool outputs, in line with the specific requirements of the task at hand, delivering pertinent context while respecting a designated token limit prior to the model's engagement. Equipped with a flexible REST API, it supports requests in any programming language, while its TypeScript and Python SDKs enhance agent workflows and integrate effortlessly with Vercel AI SDK, Anthropic SDK, and OpenAI SDK. The output systematically preserves the sequence of submissions, generating reports that outline token modifications, potential cost savings, and rationales for excluded content. Contextwaise also includes features such as request logging, adjustable budgets, and quality assurance; its agent SDKs can disclose segments of excluded tool outputs for additional clarification. By employing this solution, engineering teams can significantly reduce unnecessary model inputs while maintaining their retrieval resources, prompts, and interactions with model providers, thus simplifying the development workflow. This optimization not only improves efficiency but also empowers teams to advance their AI-driven applications more effectively and creatively. Ultimately, Contextwaise serves as an essential tool for fostering innovation in the AI landscape.