Search Results for "next.js"

LLMChat is an open-source AI chat platform designed to provide a unified interface for interacting with multiple large language model providers while emphasizing privacy and advanced research capabilities. The system is built as a modern monorepo using technologies such as Next.js and TypeScript, enabling developers to deploy a full-featured web-based chatbot environment. One of its primary goals is to support sophisticated research workflows that combine conversational AI with information retrieval and reasoning tools. The platform includes specialized interaction modes such as deep research analysis and enhanced search capabilities that help users explore complex topics more effectively. ...

Agent Chat UI is an open-source web application that provides a graphical interface for interacting with AI agents built using LangGraph and related frameworks. The project is implemented as a modern Next.js application and allows users to chat with agent workflows running on remote or local LangGraph servers. Through a simple configuration process, developers can connect the interface to a deployed agent by specifying the server URL, assistant identifier, and authentication credentials. Once connected, the interface enables real-time conversations where messages are sent to the agent and responses are streamed back to the chat interface. ...

...It can run either with local language models or with cloud-based providers, allowing developers to deploy it privately or integrate with hosted AI services. The architecture separates the frontend and backend, using modern web technologies such as Next.js and FastAPI to deliver an interactive interface and scalable server logic. Farfalle also includes an agent-based search workflow that plans queries and executes multiple search steps to produce more accurate results than traditional keyword searches. The system supports multiple external search providers and integrates caching and rate-limiting mechanisms to maintain reliability during heavy usage.

AgentDock is an open-source framework designed to simplify the development, orchestration, and deployment of AI agents capable of executing complex automated workflows. The platform provides a backend-first architecture that allows developers to create sophisticated agent systems while maintaining flexibility in model providers and infrastructure choices. It consists of two main components: a core framework that handles agent logic and orchestration, and a reference client application that...

...The project presents itself as a starting point that already includes authentication, model access, streaming, and tool support so teams can focus on their own product-specific features. Its stack is centered on modern TypeScript web development, using technologies such as Next.js, AI SDK tooling, PostgreSQL, Redis, and type-safe configuration patterns. The repository highlights access to more than 120 models through a unified interface, covering providers such as Claude, GPT, Gemini, and Grok. It also supports practical product features like attachments, resumable streams, branching conversations, sharing, web search, image generation, code execution, and MCP support.

Fulling is an open-source AI-powered development environment designed to function as an autonomous full-stack engineering assistant. The platform provides a sandboxed workspace where developers can build complete applications with the help of an integrated AI coding agent. Instead of manually configuring development environments, the system automatically provisions the required infrastructure including a Linux environment, database services, and development tools. It integrates an AI pair...

...Developers can connect these nodes to create complex pipelines that orchestrate multiple language models and external services. Built on technologies such as LangChain, LangGraph, FastAPI, and Next.js, Flock combines a modern web interface with a flexible backend capable of supporting advanced AI workflows. The platform supports multi-agent collaboration, allowing developers to design workflows where different agents handle specialized tasks within the same system. Flock also includes features such as intent recognition, code execution nodes, and human-in-the-loop approval processes that make it suitable for production AI applications.