Introducing Teel – Turbo-Efficient Execution Library for Agents (but not only)

Teel is an open-source Python runtime designed to accelerate agentic and other IO-bound workflows by automatically overlapping independent calls written in ordinary sequential code, avoiding explicit async syntax, futures, or manually managed task graphs. Developers mark expensive, side-effect-free functions with `@cacheable`, orchestration functions with `@jit`, and execute them within a Teel context, where a shadow interpreter examines upcoming bytecode, identifies calls whose inputs are ready, and launches them on background threads before the main program reaches them. Reported tests include an 83% average runtime reduction on Princeton’s unmodified Tree of Thoughts implementation, an 8.07x improvement on its longest run, and faster average performance than LLM-generated asynchronous JavaScript in a LangChain Deep Agents experiment. Teel can speculatively evaluate branches and memoize calls based on JSON-serialized arguments, but users must ensure cacheable functions are pure and safe to run early or unnecessarily, since side effects such as writes, payments, or time-dependent behavior can produce incorrect outcomes. The project provides trace output compatible with Perfetto for visualizing concurrency, but remains a proof of concept restricted to Python 3.12.13 and is primarily suited to IO-bound or GIL-free work rather than CPU-bound Python workloads.

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