8 Best botpress Alternatives in 2026 (Open Source)

botpress — The open-source hub to build & deploy GPT/LLM Agents ⚡️.

These 8 open-source tools do the same job. They are ordered by how closely they match botpress, with live GitHub data so you can see which projects are actively maintained.

ToolGitHub starsStars / 30dLast commit
botpress(original)14.9k+492026-09-29
Hexabot1.3k+552026-08-20
Chaindesk3.0k+42024-06-17
Dialoqbase1.8k+12026-06-29
LLMStack2.3k+22024-12-11
Langflow155.4k+1,4572026-09-29
Dify157.6k+3,6682026-09-30
iX1.0k+02024-03-03
AutoGen61.2k+7942026-04-06
  1. 1. Hexabot

    Hexabot is an open-source AI chatbot / agent builder. It allows you to create and manage multi-channel and multilingual chatbots / agents with ease.

    What sets it apart: vs Botpress/Rasa: open-source visual chatbot builder with built-in multi-LLM support, multi-channel deployment, and knowledge base — complete platform not just a framework

    Best for: Teams building multi-channel AI chatbots with visual flow editor; Organizations needing self-hosted chatbot with human handover

  2. 2. Chaindesk

    The no-code platform for building custom LLM Agents

    What sets it apart: vs Botpress/Voiceflow: no-code LLM agent builder with semantic search — evolved into Chaindesk managed platform for production chatbot deployment

    Best for: Non-technical users wanting to build LLM-powered chatbots; Quick customer support bot prototyping; Teams evaluating no-code LLM agent platforms

  3. 3. Dialoqbase

    Create chatbots with ease

    What sets it apart: vs Botpress/Rasa: open-source no-code chatbot builder with multi-LLM provider flexibility + multi-platform deployment (web, Telegram, Discord, WhatsApp) + PostgreSQL vector search — all self-hosted

    Best for: Quickly building custom chatbots from proprietary knowledge bases; Teams wanting multi-platform chatbot deployment (Telegram, Discord, web); Experimenting with different LLM providers for chatbot use cases

  4. 4. LLMStack

    No-code multi-agent framework to build LLM Agents, workflows and applications with your data

    What sets it apart: vs Flowise / Dify: no-code AI platform with multi-tenant support, built-in vector DB, and Slack/Discord integration — deploy AI agents from Google Drive/Notion data without writing code

    Best for: Non-developers wanting to build AI agents and chatbots without coding; Teams needing multi-LLM chain workflows with data integration; Organizations wanting self-hosted AI platforms with multi-tenant support

  5. 5. Langflow

    Langflow is a powerful tool for building and deploying AI-powered agents and workflows.

    What sets it apart: Best visual builder for LLM workflows with direct MCP server deployment — more production-ready than Flowise with API-first architecture

    Best for: Rapid prototyping of AI agent workflows with visual builder; Non-developers building LLM applications without coding

  6. 6. Dify

    Production-ready platform for agentic workflow development.

    What sets it apart: Unlike LangGraph (code-first orchestration), Dify offers a complete visual IDE combining workflow builder, RAG pipeline, prompt engineering, and production monitoring in one platform — the Vercel of LLM apps

    Best for: Teams building RAG-powered chatbots and AI apps with visual workflow and no backend coding; Product teams who need LLMOps monitoring alongside app development in one platform

  7. 7. iX

    Autonomous GPT-4 agent platform

    What sets it apart: vs LangChain/AutoGen: visual no-code drag-and-drop editor with native multi-agent orchestration and horizontal worker scaling — design complex agent workflows visually instead of writing code

    Best for: Building custom multi-agent teams with visual no-code editor; Rapid prototyping of AI workflows without coding; Organizations needing self-hosted parallel agent execution at scale

  8. 8. AutoGen

    A programming framework for agentic AI

    What sets it apart: Microsoft's layered multi-agent framework (Core/AgentChat/Extensions) with no-code Studio, .NET support, and MCP integration — most enterprise-backed open-source agent framework

    Best for: Building multi-agent AI systems with complex orchestration; Teams prototyping agent workflows with no-code Studio; Cross-language (Python/.NET) agent applications