VectorJSON: O(n) Streaming Parser for LLM JSON Outputs

VectorJSON addresses a critical performance bottleneck in LLM-powered applications: the inefficient parsing of JSON outputs. Traditional JSON parsing methods re-parse the entire buffer on every chunk, leading to O(n²) complexity and significant memory overhead. VectorJSON's O(n) streaming parser, built on WASM SIMD, scans each byte only once, dramatically reducing parsing time and memory consumption. This efficiency is particularly crucial for LLM tool calls, where large JSON payloads are common. By enabling field-level streaming and early error detection, VectorJSON allows agents to act faster, abort incorrect outputs, and save tokens. The support for schema-driven parsing further optimizes performance by extracting only the necessary fields from the JSON stream. The event-driven parsing capability enables real-time reactions to specific fields, opening up new possibilities for interactive AI applications. VectorJSON's zero-config setup and compatibility with existing AI SDKs make it easy to integrate into existing projects. As LLMs become more prevalent in various applications, efficient parsing tools like VectorJSON will play a vital role in improving performance and reducing costs.