Open-source alternatives to MyGPTReader

ChatGPT-Next-Web is a web-based chat interface for interacting with large language models via API or self-hosted model runners. It functions as a prompt management tool and a cross-platform application available for web, mobile, and desktop environments. The project distinguishes itself through a plugin integration gateway that extends model capabilities with external tools like network search and calculators. It includes a self-hosted administrative dashboard for controlling model lists, member permissions, and access passwords on private infrastructure. The application covers prompt engine

Context-Engineering is a prompt engineering framework and cognitive architecture for large language models. It provides a set of patterns and methodologies for designing structured prompts and modular reasoning flows that decompose complex tasks into specialized, step-by-step problem solving templates. The project distinguishes itself through stateful prompt management and context window optimization. It maintains persistent memory across multiple interaction turns by compressing conversation history into compact internal state cells and employs techniques to maximize information density per

ChatGPT-Next-Web is a cross-platform web interface and frontend for interacting with large language models. It functions as a self-hosted client that allows users to connect to various AI model providers through a unified chat interface compatible with web browsers and desktop operating systems. The project includes a prompt template manager for creating and organizing reusable masks to standardize interactions. It supports self-hosting on private clouds to maintain data security and provides a centralized administrative panel for managing API resources and member access permissions. The app

LangChain4j is a framework and library for building applications powered by large language models on the JVM. It provides a unified API for developing AI agents, implementing retrieval augmented generation, and integrating generative AI capabilities into professional software built with frameworks like Spring Boot or Quarkus. The project enables the creation of autonomous agents that can reason through tasks, manage memory, and execute external tools to achieve specific goals. It differentiates itself through a unified model interface that allows developers to switch between multiple model pr

This project is a self-hosted, web-based interface designed for interacting with large language models. It provides a centralized dashboard that enables users to manage model communications, maintain persistent conversation histories, and organize prompt libraries within a private, containerized environment. The platform distinguishes itself through robust administrative and security controls, including support for enterprise identity providers, password-based access, and request rate limiting. It facilitates flexible connectivity by allowing users to configure custom network proxies, manage

This repository is a collection of frameworks and guides for Llama models, functioning as a fine-tuning framework, an inference pipeline, and an AI workflow orchestrator. It provides tools for adapting large language models to specific datasets and domains. The project includes a parameter-efficient fine-tuning toolkit that utilizes techniques like low-rank adaptation to reduce memory and compute requirements. It also serves as an implementation guide for retrieval-augmented generation, combining model inference with external data retrieval to improve response accuracy. The capability surfac

Higress is an AI API gateway and cloud-native traffic manager that functions as a Kubernetes ingress controller. It provides a centralized system for routing, securing, and optimizing traffic directed toward large language models, AI agents, and microservice architectures. The project distinguishes itself through deep AI orchestration, including the ability to host and manage Model Context Protocol servers that transform REST APIs into tools for AI agents. It features specialized AI infrastructure for model request proxying, protocol translation across multiple providers, and semantic-based c

OpenViking is a multi-tenant context server and knowledge base administration system designed to provide AI agents with persistent long-term memory. It enables the indexing of diverse documents and codebases to support retrieval-augmented generation, allowing agents to recall past interactions, user preferences, and learned experiences across sessions. The project is distinguished by its use of a URI-based virtual filesystem to organize memories, resources, and skills. It implements a tiered context loading system that balances retrieval precision with token budgets by structuring data into a

This project serves as an educational resource and guide for prompt engineering, providing a structured methodology for interacting with large language models. It focuses on teaching core strategies to improve the reliability, accuracy, and consistency of model outputs across a variety of natural language processing tasks. The framework emphasizes the use of standardized templates and logical decomposition to manage complex instructions. By implementing techniques such as few-shot context injection, iterative refinement, and delimiter-based segmentation, the project demonstrates how to guide

This project is an LLM translation plugin and extension for the Bob translation tool. It connects the application to external large language models via API to provide real-time text translation, automated grammar correction, and content polishing. The plugin functions as an AI prompt engineering tool, allowing for the definition of custom system instructions and templates to control the style, tone, and reasoning depth of the output. It operates as a streamed API client that processes incremental text responses to display translation results in real time. Its capabilities cover translation b

This project is a collection of specialized toolsets for AI research automation, local storage analysis, and prompt library management. It provides frameworks for retrieving curated news and research papers via keyword queries and generating comprehensive long-form reports through cross-sectional subject analysis. The system includes capabilities for AI content generation that enforce specific narrative rules, rhythmic constraints, and banned vocabulary to replicate authorial personas. It also features a prompt library with standardized instruction schemas to ensure consistent agent behavior

This is a software development kit and framework for implementing the Model Context Protocol in Go. It provides a standardized system for building servers and clients that exchange external resources, proprietary data, and executable tools to provide context for large language models. The SDK includes a JSON-RPC communication library and an integration framework to expose local data, prompt templates, and typed functions to AI models. It enables the development of both protocol servers that provide external context and clients that consume these remote tools and resources. The project covers

Chainlit is a Python framework designed for building and deploying interactive, stateful conversational AI interfaces. It provides a backend-driven platform that connects language models and agent frameworks to a web-based chat frontend, managing the complexities of session state, message history, and real-time communication. The framework distinguishes itself by offering a component-based UI builder that allows developers to inject interactive widgets, rich media, and data visualizations directly into the chat stream. It supports the visualization of complex agent workflows, enabling users t

This project is a Telegram bot bridge that connects the Telegram chat interface to large language models. It functions as a relay that routes user prompts to an artificial intelligence service and returns the generated text responses to the user. The application uses session token authentication to access language model services via browser-extracted cookies. Access to the bot is managed through a whitelist controller that restricts interactions to a predefined list of authorized user identifiers. The system is designed for containerized deployment to ensure consistent execution across diffe

QChatGPT is an LLM bot orchestration platform and multi-platform chatbot gateway. It serves as a bridge that routes messages between various instant messaging services and AI models using a unified codebase, functioning as an agentic workflow manager to handle complex multi-turn dialogues. The platform distinguishes itself through an extensible plugin framework that allows for the addition of custom logic and event-driven features via standardized protocols. It also includes a web-based bot controller, providing a browser interface to manage bot behavior and monitor real-time performance with

This is a software development kit for integrating the Model Context Protocol into Java applications. It serves as a framework for building AI servers and communication layers that exchange prompts, resources, and tool definitions between AI clients and servers. The SDK provides a transport-agnostic communication layer, allowing bidirectional data exchange over standard I/O, HTTP, or Server-Sent Events. It includes a generative AI resource manager for exposing structured data and prompt templates, and a standardized interface for implementing protocol clients and servers. The project covers

This project is a multi-purpose REST API utility collection and developer suite. It serves as a centralized service for real-time information aggregation, data transformation, and a wide array of programmatic tools. The service distinguishes itself by providing a broad range of specialized content delivery endpoints, from curated daily summaries and global trending rankings to randomized entertainment content like jokes and quotes. It also functions as a real-time aggregator for environmental and network data, including weather forecasts, currency exchange rates, and public IP lookups. The c

This project provides a Chinese large language model based on the LLaMA architecture. It is an instruction-tuned model optimized for natural language processing and multi-turn conversations in Chinese. The system includes a framework for parameter-efficient fine-tuning using low-rank adaptation and quantization to reduce memory requirements. It also implements retrieval augmented generation for local document question answering and supports long-context processing for sequences up to 64K tokens. The project covers a broad set of capabilities including supervised instruction tuning, reinforce

This project is a ChatGPT-powered bot integrated into the Feishu chat platform, enabling conversational AI, image generation, and voice interaction within both private and group chats. It connects large language models to the team messaging environment, allowing users to engage in multi-topic conversations, generate images from text prompts, and analyze uploaded images using vision models. The bot supports persona preset switching, allowing predefined role templates to modify the AI's behavior and tone with a single command. It maintains separate conversation histories per topic using session

Swarms is a multi-agent orchestration framework and autonomous agent toolkit designed to coordinate large language model agents. It serves as a workflow engine for managing agent relationships, providing the infrastructure to build autonomous agents with integrated memory, tool-calling capabilities, and reasoning loops. The framework is distinguished by its multi-agent consensus systems, which utilize voting, adversarial debates, and judge agents to synthesize high-quality responses. It supports a variety of collaboration patterns, including director-worker hierarchies, expert synthesis, and

The inspector is a diagnostic and validation tool for the Model Context Protocol. It provides an interactive interface and a transport proxy to discover, inspect, and execute the tools, prompts, and resources provided by an MCP server. The project serves as a debugger and compliance tester to verify that server implementations adhere to the protocol specification and JSON-RPC standards. It allows for real-time monitoring of message exchanges and logs between clients and servers across various transport layers, such as standard input/output and Server-Sent Events. The tool covers a broad rang

leek-fund is a financial market extension for VSCode that enables the monitoring of real-time pricing data for stocks, funds, and futures directly within the editor status bar. It functions as a market data dashboard and portfolio tracker, allowing users to manage investment portfolios and track global exchange price fluctuations without leaving their workspace. The project distinguishes itself by integrating an AI market analyst to process investment information and interpret market trends. It further incorporates a financial news aggregator that streams real-time market alerts and social up

The BeeAI Framework is an LLM agent framework and multi-agent orchestration engine used to build autonomous agents that coordinate reasoning, tool execution, and complex workflows. It functions as a structured AI output controller and RAG integration library, providing a unified interface to manage multiple language model providers. The framework is distinguished by its implementation of the Model Context Protocol, allowing agents, tools, and models to be shared between different AI platforms and hosted as agentic tooling servers. It enables the design of collaborative agent teams through dec

LiteRT-LM is a high-performance inference framework designed to execute large language models locally on mobile, desktop, and IoT hardware. It serves as an on-device model runtime that utilizes CPU, GPU, and NPU acceleration to provide low-latency processing. The framework is distinguished by its ability to process text, vision, and audio inputs through a single multi-modal inference engine. It features a local HTTP server that emulates OpenAI-compatible API endpoints and a WebGPU-based runtime for executing models directly within a web browser. To ensure output reliability, it includes a con

mcp-feedback-enhanced is a human-in-the-loop orchestrator and feedback tool for the Model Context Protocol. It provides a graphical interface for reviewing and approving AI-driven operations to prevent automated execution errors, using a socket-based system to synchronize state between backend AI processes and a user-facing interface. The project distinguishes itself by supporting a cross-platform deployment model available via native desktop wrappers and web browsers. It includes environment-aware context detection to identify if the system is running locally, via SSH, or within WSL, allowin