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Deepbot

DeepBot is an open-source, system-level AI assistant presented as an Electron desktop application for personal productivity and enterprise workflows. It describes multi-agent collaboration, parallel and scheduled tasks, memory, reusable skill extensions, and native Feishu integration.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Deepbot — OpenViST project profile in Workflow Agents.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Consider DeepBot when you want an AI assistant with a desktop interface and workflow-oriented features such as parallel tasks, scheduled work, skills and Feishu integration, rather than a chat-only interface.

Who it is for

  • People seeking a desktop assistant for personal productivity tasks.
  • Teams exploring AI-assisted enterprise workflows, including document processing, data analysis, monitoring and cross-department coordination.
  • Developers interested in building or extending an open-source TypeScript desktop assistant.

Documented uses

  • Handle work tasks involving documents, data analysis or system monitoring.
  • Coordinate multi-step work through multi-agent collaboration and parallel task processing.
  • Schedule recurring tasks and compose tools into reusable skills.
  • Connect assistant workflows with Feishu, including messaging and document operations.
Before you choose

Requirements & limits

  • The project is identified as MIT-licensed and its public repository is written primarily in TypeScript.
  • The README lists Python 3.11 or later; Node.js 20 and pnpm 10.23 are noted as optional for running JavaScript scripts.
  • The repository documents Windows and macOS desktop build commands, plus Linux/Docker support; its Docker instructions direct users to contact the author.
  • For macOS, the documented signed build requires Apple Developer credentials; the local unsigned build can trigger security warnings.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Start DeepBot in development mode

Install the repository dependencies and launch the development version.

Before you start

  • Python 3.11 or later
  • Node.js 20 or later and pnpm 10.23 or later for running JavaScript scripts
  • A supported environment listed in the README: macOS, Windows desktop, or Linux/Docker

Steps

  1. Clone the DeepBot repository.

  2. Change into the repository directory.

  3. Run pnpm install to install dependencies.

  4. Run pnpm run dev to start development mode.

Expected outcome

The development version is started from the repository.

Guide limitations

  • These instructions cover development startup, not configuration of a specific model or workflow.
Documentation 1 ↗
Source-based practical guide

Build a desktop app for Windows or macOS

Use the repository’s documented commands to create a desktop build.

Before you start

  • The DeepBot repository and its dependencies
  • For a signed macOS build, an Apple Developer account and signing credentials configured in .env

Steps

  1. Run pnpm run dist:win for a Windows build, or pnpm run dist:mac for a signed and notarized macOS build.

  2. For a macOS development build without signing, use pnpm run dist:mac:local instead.

Expected outcome

The selected platform’s desktop build command is invoked.

Guide limitations

  • The unsigned local macOS build may produce security warnings on first launch.
  • The README documents Docker deployment for Linux servers separately and directs users to contact the author for that version.
Documentation 1 ↗
COMPARE OPTIONS

Compare options for Agent orchestration

These projects document a common task and share a project role. This is a source-based comparison, not an execution benchmark or a guarantee of interchangeability.

ProjectDocumented purposePlatformAccess and requirements
DeepbotHandle work tasks involving documents, data analysis or system monitoring.Desktop, Linux, macOS, Windows
Agentic AI Helpdesk PlatformClassify tickets by issue domain and category, and estimate urgency and complexity.Cloud, Docker, Web
TgoConfigure multiple AI agents for different customer-service scenarios and connect supported LLM providers.Docker, Self-hosted, ServerThe repository describes Tgo as open source and provides self-hosting instructions. Its README lists minimum server requirements of four CPU cores and 8 GiB of RAM; local development setup lists macOS, Linux, and WSL2.
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
10 October 2026
Original website title
kevinluosl/deepbot · Official homepage title · retained in its source language
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