ThinkGPT is a Python library from Jina AI that gives large language models abilities that go beyond raw text generation: reasoning, memory and self-improvement techniques implemented as composable building blocks. It packages agent-style methods – such as structured reasoning, reflection and long-term memory – into a small API that works on top of existing LLM calls. It is an open-source project on GitHub with around 1,600 stars.
Plain LLM calls are stateless and single-shot, which limits them on tasks that need planning, recall or checking their own work. ThinkGPT layers techniques on top: it can break problems into reasoning steps, store and retrieve memories across sessions, summarize and compress context, and let the model critique and refine its outputs. The library is model-agnostic and lightweight, designed for developers who want agent-like behavior in a few lines of Python rather than adopting a full agent framework.
ThinkGPT is free and open source under the Apache 2.0 license. You pay only for the underlying model API usage you plug into it.
Python developers who want memory and reasoning techniques in their LLM applications without committing to a heavyweight agent framework.
ThinkGPT grew out of Jina AI’s research into giving language models capabilities that resemble thinking: decomposing problems, remembering facts between calls and reflecting on intermediate answers. It deliberately stays a library rather than a platform – there is no server to run and no lock-in – so developers can adopt a single technique, such as its memory summarization, without restructuring an application around a full agent framework.