LLMCompiler is an open-source framework designed to optimize how large language models orchestrate multiple external tool or function calls during complex reasoning tasks. Traditional LLM agent systems typically execute tool calls sequentially, which can create latency, higher costs, and reduced reliability when solving multi-step problems. LLMCompiler addresses this limitation by applying principles from classical compilers to analyze a task and construct an execution plan that allows multiple functions to run in parallel whenever possible. The framework builds a dependency graph of required operations, identifying which tasks must run sequentially and which can be executed simultaneously. Its architecture includes components such as a planning module that constructs the task graph, a task dispatcher that manages dependencies, and an executor that performs parallel calls.
Features
- Parallel orchestration of multiple LLM function calls
- Compiler-inspired planning system for tool execution graphs
- Task dependency analysis using directed acyclic graphs
- Integration with both open-source and proprietary LLM models
- Reduced latency and operational cost compared with sequential tool calling
- Framework for building efficient agent workflows