Python Middleware Tool Claims 100% JSON Recovery for Broken LLM Data Streams

Engineering team Kylik Daniels Labs has developed a Python middleware framework designed to intercept and repair malformed JSON payloads produced by large language model streaming outputs. The tool targets a common problem in production AI pipelines where truncated network streams cause JSON parsing errors that break downstream data layers. According to the team's internal benchmarks run on an i7-14700F machine with 32GB RAM, the framework processed 10,000 simultaneous streaming anomalies in 0.1215 seconds, averaging 0.0122 milliseconds per operation with a reported 100% recovery rate. The solution operates entirely in local memory without external API calls or cloud dependencies, dynamically closing broken brackets and stripping markdown artifacts in real time. The project's source code, performance logs, and a FastAPI server wrapper have been made publicly available on GitHub for peer review.