Parallel Function Calling — Execute Multiple Tools

I will implement parallel function calling for your LLM application — enabling the model to call multiple functions simultaneously when they are independent, executing them in parallel, and returning all results to the model before the next reasoning step. Parallel function calling reduces latency for tasks requiring multiple independent data retrievals — a query requiring weather data, flight prices, and hotel availability can be resolved in the time of one API call rather than three sequential ones, making the difference between a 2-second and 6-second response time for the user.

The implementation covers parallel function call detection in the model's response, async parallel execution of all requested functions, result collection and error handling per function, consolidated result return to the model, and latency comparison demonstrating the parallel execution benefit.