What databases does HiveChat require?
HiveChat requires a PostgreSQL database. For local deployment, you must install PostgreSQL or connect to a remote one; Vercel deployment can use Neon (Serverless Postgres) provided by the Vercel platform.
@HiveNexus
An AI chat bot for small and medium-sized teams, supporting models such as Deepseek, Open AI, Claude, and Gemini. 专为中小团队设计的 AI 聊天应用,支持 Deepseek、Open AI、Claude、Gemini 等模型。
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HiveChat is an AI chat application designed for small and medium teams. It supports multiple large language models such as Deepseek, OpenAI, Claude, and Gemini, and allows configuring MCP servers via SSE mode. The application provides both an end-user chat interface and an admin panel for team management.
End users simply log in and start chatting. For administrators, the application requires installing dependencies (npm install), configuring a .env file with a PostgreSQL database URL and authentication secrets, initializing the database (npm run initdb), and then building and starting the server. Alternatively, it can be deployed via Docker or on Vercel with a one-click button. After deployment, the admin sets up the first admin account by visiting /setup.
HiveChat requires a PostgreSQL database. For local deployment, you must install PostgreSQL or connect to a remote one; Vercel deployment can use Neon (Serverless Postgres) provided by the Vercel platform.
For npm-based installations, run `npm run initdb` to apply any schema changes—it is safe to run even if no updates exist. For Docker upgrades, manual SQL may be required (see the release notes for specific versions).
Yes, the admin can enable or disable account registration in the admin panel, making it suitable for closed teams like companies or schools.
Data is stored in a PostgreSQL database. The application supports cloud data storage (via the configured database) but does not rely on any external cloud service except the database.
MCP servers can be configured using SSE (Server-Sent Events) mode only, as stated in the feature list.
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