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XControl

XControl is a modular multi-tenant management platform written in Go. The project integrates several optional components to provide a visual control plane for traffic statistics, configuration export and multi-node management.

This repository contains the API server, agent code and a Next.js-based UI.

Components

  • ui-homepage
  • ui-panel
  • xcontrol-cli
  • xcontrol-server

All UI components provide both Chinese and English interfaces.

Tech Stack

Category Technology Version
Framework Go 1.24
Framework Next.js 14.1.0
Gateway OpenResty 1.27.1.2
Database PostgreSQL + pgvector N/A
Cache Redis N/A
Model (Local) HuggingFace Hub + Ollama N/A
Model (Online) Chutes AskAI + CodePRobot N/A

LangChainGo 核心功能一览

XControl 通过 LangChainGo 统一接入多种大模型，并为 AskAI、CLI 与 Server 提供链式调用能力：

  • LLM 接口层（Model I/O）：统一调用 OpenAI、Hugging Face、Ollama、Google AI、Cohere 等模型接口。
  • Chains（链式流程）：将 prompt、检索结果、工具调用等组合成完整流程，支持 RAG、聊天、代码生成等场景。
  • 工具与 Agent 体系：定义 Web 搜索、Scraper、SQL 查询等工具，并集成到 LLM Agent，实现 ReAct 风格的工具调用。
  • 向量检索与数据接入：适配 PGVector、Weaviate、Qdrant、MongoDB Atlas Vector Search、Chroma、Pinecone、Redis Vector 等向量存储。
  • 文档加载与分块：提供 Document Loaders 与 Text Splitters，用于处理长文本与构建向量检索块。
  • Memory 与历史追踪：支持 Conversation Buffer 等对话记忆机制，增强交互体验。

Supported Platforms

Tested on Ubuntu 22.04 x64 and macOS 26 arm64.

Installation

make install
make init-db   # initialize database (optional)

Features

  • XCloudFlow Multi-cloud IaC engine built with Pulumi SDK and Go. GitHub →
  • KubeGuard Kubernetes cluster application and node-level backup system. GitHub →
  • XConfig Lightweight task execution & configuration orchestration engine. GitHub →
  • CodePRobot AI-driven GitHub Issue to Pull Request generator and code patching tool. GitHub →
  • OpsAgent AIOps-powered intelligent monitoring, anomaly detection and RCA. GitHub →
  • XStream Cross-border developer proxy accelerator for global accessibility. GitHub →

The docs directory contains a more detailed overview and design documents for each module.

Building

make build

This produces a binary under bin/xcontrol. Run make agent to build the node agent.

Testing

make test

Deployment

make start

This launches the server, homepage and panel. Use make stop to stop all components.

The API server also accepts a custom configuration file:

xcontrol-server --config path/to/server.yaml

Logging

Both xcontrol-cli and xcontrol-server accept a --log-level flag to control verbosity. The level may be one of debug, info, warn, or error:

xcontrol-cli --log-level debug
xcontrol-server --log-level warn

The server's log level can also be set in the configuration file:

log:
  level: info

The flag value takes precedence over the configuration file.

Changelog

See docs/changelog.md for a list of completed changes, including all work from Milestone 1.

Roadmap

The roadmap below is also available in docs/Roadmap.md.

Milestone 1: MVP (Completed)

  • Use default Redis port (#98) and establish PostgreSQL & Redis baseline.
  • Stream RAG sync progress for GitHub repository synchronization (#100).
  • Add client-side Markdown parsing to the CLI (#104).
  • Refactor RAG ingestion into the CLI with a server upsert endpoint (#103).
  • RAG API functional tests and per-file ingestion workflow (#115).
  • Allow RAG upsert to migrate embedding dimensions (#119) and document pgvector initialization (#120).
  • Ingest files automatically (#123).

Milestone 2: Hybrid Search

  • CLI and server dynamically support 1024-dimensional embeddings.
  • Update docs and configs to vector(1024) (#130).
  • Add embedding configuration fields (#131).
  • Add RAG API integration tests for vectors (#132).
  • Add allama support (#136).
  • Deploy homepage via rsync from CI and fix SSH directory creation (#18, #19).
  • Deploy XControl panel via GitHub Actions (#20).
  • Fix yarn lock context concatenation (#21).

Milestone 3: Production Monitoring & Optimization

  • Switch server and CLI to Cobra (#133).
  • Add repo sync proxy configuration (#135).
  • Allow custom AskAI timeout (#141).
  • Add log level support to CLI and server and log AskAI errors (#125, #140).
  • Continue performance optimization, error handling, multi-model support, permission control, hot reload, and improve RAG upsert docs (#129).

License

This project is licensed under the terms of the MIT License.