ThinkGPT is a Python library designed to enhance Large Language Models (LLMs) by implementing advanced reasoning techniques like Chain of Thoughts and generative agents. It addresses limitations in LLM context windows by providing long-term memory, knowledge compression, and higher-order reasoning primitives, enabling more intelligent decision-making within codebases.

How It Works

ThinkGPT leverages a modular approach with "thinking building blocks" including memory management for storing and retrieving past experiences, self-refinement for iterative improvement of model outputs based on criticism, and knowledge compression techniques like summarization and abstraction to fit information within LLM context limits. This allows LLMs to perform more complex reasoning and maintain coherence over extended interactions.

Quick Start & Requirements

• Install via pip: pip install git+https://github.com/alaeddine-13/thinkgpt.git
• Requires Python and an OpenAI API key.
• Official documentation: https://github.com/jina-ai/thinkgpt

Highlighted Details

• Implements memory, self-refinement, knowledge compression, inference, and natural language conditions.
• Offers one-shot and chunked summarization for large content.
• Supports abstracting rules from observations for knowledge compression.
• Enables natural language conditions and selections for LLM-driven decisions.

Maintenance & Community

• The project is hosted on GitHub by jina-ai.
• Community links are not explicitly mentioned in the README.

Licensing & Compatibility

• The README does not specify a license.

Limitations & Caveats

The library relies on OpenAI's models, meaning API costs and rate limits apply. The effectiveness of memory and refinement techniques is dependent on the underlying LLM's capabilities.