GPT Search is an intuitive browser extension designed to enhance your ChatGPT experience by allowing users to search their conversation history. This tool drains away the hassle of scrolling through long chats for specific information. Users can leverage advanced search operators to refine their searches, ensuring a fast and efficient way to revisit past interactions. After the initial caching, results are delivered blazingly fast, which is particularly useful for frequent users wanting to streamline their workflow.

DreamGPT is a versatile open-source platform designed to simplify the development, configuration, and deployment of AI agents powered by GPT models. It provides an intuitive Python SDK and command-line interface for scaffolding new agents, managing conversation history with pluggable memory backends, and integrating external tools via a standardized plugin system. Developers can define custom prompt flows, link to APIs or databases for retrieval-enhanced generation, and monitor agent performance through built-in logging and telemetry. DreamGPT’s modular architecture supports horizontal scaling in cloud environments and ensures secure handling of user data. With prebuilt templates for assistants, chatbots, and digital workers, teams can rapidly prototype specialized AI agents for customer service, data analysis, automation, and more.

Duet GPT is a Python-based open source framework for orchestrating multi-agent conversations between two GPT models. You define distinct agent roles, customized with system prompts, and the framework manages turn-taking, message passing, and conversation history automatically. This cooperative structure accelerates complex task resolution, enabling comparative reasoning, critique cycles, and iterative refinement through back-and-forth exchanges. Its seamless OpenAI API integration, simple configuration, and built-in logging make it ideal for research, prototyping, and production workflows in coding assistance, decision support, and creative ideation. Developers can extend the core classes to integrate new LLM services, adjust the iterator logic, and export transcripts in JSON or Markdown formats for post-analysis.