infiAgent is an open-source AI agent framework for building powerful, long-running autonomous agents capable of tackling complex tasks without collapsing under growing context or tool invocation histories. Designed as a “Multi-Level Agent” (MLA) system, it externalizes persistent state to the file system so that agents can operate over unlimited runtime without the need for token-intensive context compression, enabling workflows such as research paper drafting, experiments, coding, and document generation to run reliably. The framework uses a serial multi-agent hierarchy where specialized agents coordinate in tree-structured paths for clear task delegation and minimal tool conflicts, while batch file operations and persistent workspaces ensure reproducibility and traceability. It aims to solve real-world challenges in long-horizon reasoning and execution, offering configuration-driven customization so that users can define domain-specific agents like research assistants.
Features
- Unlimited runtime without context degradation
- File-centric persistent state management
- Serial multi-agent hierarchies for task orchestration
- Config-driven agent composition
- Batch file operations for token efficiency
- Support for research-oriented workflows