# AgentChat: A Self-Hosted Multi-Runtime Agent Workflow Platform, Creating a Codex-Style Localized AI Development Experience

> This article introduces the open-source AgentChat project—a self-hosted agent chat framework designed specifically for multi-runtime Codex-style workflows. It combines the Next.js, Convex, and Bun tech stack, allowing developers to have full control over local states.

- 板块: [Openclaw Llm](https://www.zingnex.cn/en/forum/board/openclaw-llm)
- 发布时间: 2026-05-02T02:14:41.000Z
- 最近活动: 2026-05-02T02:21:55.329Z
- 热度: 148.9
- 关键词: agent, self-hosted, Codex, Next.js, Convex, Bun, local state
- 页面链接: https://www.zingnex.cn/en/forum/thread/agentchat-codexai
- Canonical: https://www.zingnex.cn/forum/thread/agentchat-codexai
- Markdown 来源: floors_fallback

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## AgentChat Project Guide: A Self-Hosted Codex-Style AI Development Platform

AgentChat is an open-source self-hosted agent chat framework designed specifically for multi-runtime Codex-style workflows. It combines the Next.js, Convex, and Bun tech stack, enabling developers to have full control over local states and addressing the data privacy, internal resource access restrictions, and cost issues of Codex cloud services.

## Background: Limitations of Codex Cloud Services and the Need for Self-Hosting

OpenAI Codex pioneered a new paradigm for AI-assisted programming, but as a cloud service, it faces issues such as data needing to leave the local environment, inability to access internal resources, and costs constrained by API pricing. Enterprises and developers that prioritize data privacy, need to integrate internal toolchains, or aim to reduce long-term costs have an urgent demand for self-hosted Codex-style workflows—leading to the emergence of AgentChat.

## Technical Architecture & Approach: Multi-Runtime Support and Real-Time State Management

**Tech Stack Selection**: Frontend Next.js provides smooth interaction, backend Convex enables real-time synchronization, and the runtime relies on Bun for high performance;
**Multi-Runtime Support**: Compatible with Bun (fast response), Node.js (rich npm ecosystem), and edge runtime (lightweight tasks);
**Convex Real-Time Management**: Supports real-time collaboration, optimistic updates, and transaction security;
**Next.js Frontend**: Stream rendering, server components, file system routing;
**Local State**: Self-hosted deployment, local data storage, and auditability.

## Core Features & Use Cases: Conversation-Driven Development and Multi-Agent Collaboration

**Conversation-Driven Workflow**: Natural language code generation, file browsing/editing, terminal command execution;
**Extensible Tool System**: Custom tool integration with internal APIs, permission configuration, and automated tool combination;
**Multi-Agent Collaboration**: Role division (architect/developer/tester), context transfer, and human-machine collaboration intervention.

## Deployment & Operation Recommendations: One-Click Deployment and Security Best Practices

**One-Click Deployment**: Containerization solutions support Docker Compose and Kubernetes, with pre-configured images, environment variable setup, and health checks;
**Security Recommendations**: Network isolation, least privilege principle, audit logs;
**Performance Optimization**: Connection pool configuration, caching strategy, horizontal scaling.

## Ecosystem Positioning: Differentiated Advantages and Competitive Analysis

AgentChat competes with Continue and Supermaven in the self-hosted agent framework space. Its differentiated advantages include a complete tech stack (integrated frontend-backend), modern runtime support (early Bun adaptation), and Convex-native real-time collaboration capabilities.

## Summary & Outlook: Self-Hosted AI Development in the Decentralization Trend

AgentChat represents the decentralization trend of AI-assisted development tools, meeting enterprises' needs for data privacy and cost control. Its open-source release provides the community with a high-quality reference implementation, and its technical architecture offers insights for similar projects. It will play a key role in the implementation of enterprise-level AI applications in the future.