Stella Framework empowers developers to build robust AI agents that can maintain context, perform tool-assisted actions, and deliver dynamic conversational experiences. By abstracting the complexities of LLM integrations, Stella offers provider-agnostic adapters for OpenAI, Hugging Face, and self-hosted models. Agents can leverage customizable memory stores to recall user data and conversation history, and plugins enable interactions with external APIs, databases, or services. The built-in orchestration engine manages decision loops, while a concise DSL allows defining actions, tool calls, and response handling. Whether creating customer support bots, research assistants, or workflow automators, Stella provides a scalable foundation for deploying production-grade AI agents.

Agentic is a powerful AI agent that specializes in automating the creation of conversations throughout various stages of project management. By utilizing AI-driven technology, Agentic enables production teams to foster better communication, improve collaboration, and keep track of project developments effortlessly. Users can expect features like task automation, conversation history, and AI-generated reminders to enhance their productivity and streamline workflows.

AIFoundry-AgentService-Streamlit is an open-source demo application built with Streamlit that lets users quickly spin up AI agents via AIFoundry’s AgentService API. The interface includes options to select agent profiles, adjust conversational parameters like temperature and max tokens, and display conversation history. It supports streaming responses, multiple agent environments, and logs requests and responses for debugging. Written in Python, it simplifies testing and validating different agent configurations, accelerating the prototyping cycle and reducing integration overhead before production deployment.

ChatGBT is a powerful AI chatbot based on GPT architecture, offering free access to various top-tier models like GPT-4, Claude 3, and Meta Llama 3. The platform blends the latest NLP and advanced machine learning algorithms to deliver comprehensive answers and streamline productivity. With features like encrypted conversation history and multilingual support, it ensures a versatile and engaging interaction.

ChatGPT Spotlight is a Chrome extension designed to improve the accessibility of your ChatGPT conversations. Users can instantly search through their chats and GPTs without the need for a mouse, achieving this through keyboard shortcuts. The tool mimics the efficiency of MacOS Spotlight, making it quick and convenient for users looking for specific chat records or ideas. Its straightforward interface ensures that anyone can utilize it effectively, making it an essential tool for regular ChatGPT users.

Claude Helper enhances your Claude AI experience by allowing seamless folder uploads to Claude projects, equipped with advanced file handling options such as file exclusion by extension or pattern and version control. It also introduces a chat minimap for easy navigation of long conversations, quick project file removal, and customizable settings. This tool ensures that managing files, starting new projects, and navigating through long chat histories are simpler and quicker processes.

Claudify is an all-in-one productivity toolbox for Claude.ai users, designed to simplify and enhance chat experiences. Users can easily download chats in PDF, Markdown, or Text formats, copy entire conversations, disable the Enter key for sending messages, search messages quickly, and manage chat histories. Claudify helps you save time, boost productivity, and stay organized with efficient chat management tools.

Embabel Agent provides a structured approach for building AI agents in Node.js and browser environments. Developers define tools—such as HTTP fetchers, database connectors, or custom functions—and configure agent behaviors through simple JSON or JavaScript classes. The framework maintains conversation history, routes queries to the appropriate tool, and supports plugin extensions. Embabel Agent is ideal for creating chatbots with dynamic capabilities, automated assistants that interact with multiple APIs, and research prototypes that require on-the-fly orchestration of AI calls.

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.

PersonalAI offers a comprehensive agent framework that combines advanced LLM integrations with persistent semantic memory and an extensible plugin system. Developers can configure memory backends like Redis, SQLite, PostgreSQL, or vector stores to manage embeddings and recall past conversations. Built-in plugins support tasks such as web search, file reading/writing, and Python code execution, while a robust plugin API allows custom tool development. The agent orchestrates LLM prompts and tool invocations in a directed workflow, enabling context-aware responses and automated actions. Use local LLMs via Hugging Face or cloud services via OpenAI and Azure OpenAI. PersonalAI’s modular design facilitates rapid prototyping of domain-specific assistants, automated research bots, or knowledge management agents that learn and adapt over time.

LLMChat.me is an online service that aggregates dozens of open-source large language models into a unified chat interface. Users can select from models such as Vicuna, Alpaca, ChatGLM, and MOSS to generate text, code, or creative content. The platform stores conversation history, supports custom system prompts, and allows seamless switching between different model backends. Ideal for experimentation, prototyping, and productivity, LLMChat.me runs entirely in the browser without downloads, offering fast, secure, and free access to leading community-driven AI models.

OpenAI Agents JS enables developers to construct AI agents by combining OpenAI models with custom toolsets. Agents can process user input, call external APIs, manage stateful conversations with memory modules, and perform tasks like web scraping, code generation, or data lookup. The framework offers a plugin system for registering tools, a standardized Agent class for orchestration, built-in memory abstractions, and support for both chat-based and completion-based models. Features include error recovery, multi-tool orchestration, and customizable middleware. By defining tools and feeding them into the agent instance, you can deploy sophisticated AI-driven workflows in Node.js or browser contexts with minimal boilerplate. Additionally, it simplifies API key management and supports asynchronous operations, allowing agents to execute long-running tasks or integrate with databases and messaging queues effortlessly.

Python AI Agent provides a developer-friendly toolkit to orchestrate autonomous agents driven by large language models. It offers built-in mechanisms for defining custom tools and actions, maintaining conversation history with memory modules, and streaming responses for interactive experiences. Users can extend its plugin architecture to integrate APIs, databases, and external services, enabling agents to fetch data, perform computations, and automate workflows. The library supports configurable pipelines, error handling, and logging for robust deployments. With minimal boilerplate, developers can build chatbots, virtual assistants, data analyzers, or task automators that leverage LLM reasoning and multi-step decision making. The open-source nature encourages community contributions and adapts to any Python environment.

The AWS Sample Model Context Protocol Demos is an open-source repository showcasing standardized patterns for Large Language Model (LLM) context management and tool invocation. It features two complete demos—one in JavaScript/TypeScript and one in Python—that implement the Model Context Protocol, enabling developers to build AI agents that call AWS Lambda functions, preserve conversation history, and stream responses. Sample code demonstrates message formatting, function argument serialization, error handling, and customizable tool integrations, accelerating prototyping of generative AI applications.

StackMind.AI is an intelligent organizer and search tool for your ChatGPT history. It leverages advanced AI to analyze patterns, automatically creating and organizing folders for your conversations. This Chrome extension allows you to search ChatGPT conversations instantly using a sidebar button or hotkey. Customizable folder structures enable you to manage your chat data locally, keeping it private. Pinning important conversations and efficient AI-search capabilities transform your history into a valuable resource, enhancing productivity and workflow.

Superpower ChatGPT is a cutting-edge extension that elevates your ChatGPT experience by introducing functionalities designed for efficiency and ease of use. With this tool, users can organize their chats in folders, sync and search their chat history, access thousands of community prompts, export conversations, and utilize custom prompts tailored to individual needs. Additionally, features like an image gallery, voice GPT, and prompt chains allow for both creativity and utility. Overall, this extension makes navigating and optimizing conversations with ChatGPT more intuitive and individualized.

The AI Webpage Summarizer - ChatGPT Chrome extension transforms the way you interact with webpage content. Powered by OpenAI's GPT-4, it allows you to access summaries and ask questions directly about the webpage content you are viewing. This tool eliminates the hassle of switching tabs and manually copying text, making it a massive time-saver. You can simplify complex articles, extract key details from LinkedIn profiles, and get quick answers to specific questions regarding the content. It’s easy to use, responsive, and saves conversation history for future reference.

The ChatGPT Exporter extension is designed to enhance your experience with ChatGPT by allowing you to easily capture and preserve your conversations. With support for multiple file formats such as markdown, text, JSON, and CSV, you can store your insights from ChatGPT in a way that best suits your needs. It's ideal for users who want to keep a record of important chat discussions, share insights for research, or simply organize their interactions with the AI. This tool not only makes exporting conversations simple but also ensures that you can access your data anytime, anywhere.

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.