Category guide
Open Source AI Chatbot
An open source AI chatbot is a conversational assistant whose source code is publicly licensed, so you can read it, change it, and run it on your own servers instead of a vendor's. As of July 2026 the four projects worth evaluating are LibreChat (41,381 GitHub stars) for a private ChatGPT-style interface, Chatwoot (34,824) for a self-hosted support inbox, Rasa (21,272) for building your own NLU, and ChatterMate (79) for an AI support agent grounded in your own documentation. They solve different problems, so choose by category first and popularity second.
Being direct about it: ChatterMate is the smallest project on this page by an enormous margin — 79 stars against Chatwoot's 34,824. If community size is your deciding factor, pick one of the others. Where we do compare well is maintenance recency and category fit, and both are in the table below.
Updated July 2026
How these tools actually differ
Most comparison lists rank these projects against each other as if they were interchangeable. They aren't. There are three distinct categories, and picking the wrong one wastes months.
Support platforms with no built-in AI. Chatwoot gives you inboxes, routing, SLAs and reporting for human agents. The AI is something you bolt on.
Frameworks where you build the AI yourself. Rasa and Botpress v12 are toolkits: you design intents, dialogue and training data. Powerful, and they assume engineering time you may not have.
General-purpose chat UIs. LibreChat is a front end for language models — excellent for internal staff use, not built for customer conversations.
AI-first support agents. ChatterMate sits here: the agent answers from your documents out of the box and hands off to a person when it should. Less mature, narrower scope, far less to configure.
The numbers, unedited
Latest release is the column most lists leave out. Botpress last tagged a release in June 2023 and Rasa in January 2025; Chatwoot and ChatterMate both shipped this week.
| Tool | Stars | Forks | Licence | Language | Latest release |
|---|---|---|---|---|---|
| ChatterMate | 79 | 33 | Apache-2.0 | Python | v1.0.17 — 2026-07-28 today |
| LibreChat | 41,381 | 8,526 | MIT | TypeScript | no tagged releases ships from main |
| Chatwoot | 34,824 | 8,369 | MIT (community edition) | Ruby | v4.16.2 — 2026-07-27 yesterday |
| Rasa | 21,272 | 4,921 | Apache-2.0 | Python | 3.6.21 — 2025-01-14 18 months ago |
| Botpress (v12 OSS) | 14,832 | 2,287 | MIT | TypeScript | v12.30.9 — 2023-06-22 3 years ago |
When to choose it
When ChatterMate is the right fit
Most open-source options were built for human agents, with AI added on top. ChatterMate is AI-first — built from the ground up for the AI era. If you want an agent that actually resolves instead of just deflecting, it’s the right fit.
Built for the AI era
Most open-source tools were built for human agents, with AI bolted on later. ChatterMate is AI-first — designed from the ground up for how support actually works now.
Trains itself in minutes
Point it at your docs, website and uploads and it's ready — no intent trees or dialogue flows to hand-build.
Every channel, one inbox
Web chat, WhatsApp, email, SMS, Messenger, Instagram, Telegram, LINE and Slack — all answered from a single shared inbox.
Captures & syncs leads
Qualifies leads inside the conversation and pushes them straight to HubSpot or Pipedrive — no forms, no copy-paste.
Tickets that investigate themselves
Creates and triages tickets, then investigates and resolves them using integrations like Elasticsearch / Kibana and CloudWatch.
Native Shopify app
One-click install — order status, catalogue and support stay in sync with your store.
Intelligent human handover
Hands off to a person at exactly the right moment, with the full conversation and context attached.
Rating & emotion analysis
Every conversation is scored for satisfaction and sentiment, so you see how customers actually feel.
Bring your own model
Run OpenAI, Anthropic, Google, Mistral and more on your own keys — flexibility with no lock-in.
A modern, fast UI
A clean, quick dashboard your team actually likes using — not a 2010-era admin panel.
Mobile PWA, out of the box
An installable mobile app for agents — answer on the go, no app store required.
A modern AI help center
A self-serve help centre with AI-written summaries and built-in chat, not just static articles.
Auto-built from your knowledge
Generates the help centre for you from your existing knowledge base, with AI.
When ChatterMate is the wrong choice
Four situations where one of the other projects is the better answer. If you're in one of them, we'd rather you knew now.
You need an omnichannel inbox
Email, WhatsApp and Instagram in one agent workspace, with routing and reporting your team already trusts — Chatwoot is years more mature at this. Use it, and add AI on top.
You have ML engineers and a regulator
Custom NLU, deterministic dialogue policies and auditable training data in a regulated industry — that's Rasa's job, not ours. It expects the engineering time; it rewards it.
You want a private ChatGPT for staff
An internal chat UI across multiple models, for your own team rather than your customers — LibreChat is built for exactly that, and ChatterMate is not.
You want a big community
We're at 79 stars. There are few tutorials, few Stack Overflow answers, and you will sometimes be the first person to hit a bug. You'll get a fast reply from us, but you'll be talking to us, not a forum.
What ChatterMate does well
Answers grounded in your docs
It reads your help centre, site and uploads, then answers with a citation to the source it used.
Human handoff built in
Low confidence, a refund, an angry customer — the conversation moves to a person with full history attached.
Runs fully local via Ollama
Point it at a local model and no conversation text leaves your network. No third-party API keys required.
Actively maintained
v1.0.17 shipped 28 July 2026 — today. See the releases page for the full history.
Self-hosting quickstart
Apache-2.0. A one-command self-host CLI brings up the full stack — Postgres, Redis, backend, frontend and worker — on Docker. Requires Node 18+ and Docker 24+, plus about 4 GB of free RAM before you add a local model.
npm install -g chattermate-deploy # self-host / deployment CLI chattermate-deploy init my-chattermate # scaffold the stack cd my-chattermate chattermate-deploy start # Postgres, Redis, backend, frontend, worker → http://localhost/
Honestly: fifteen minutes to a running instance, an afternoon to something you'd put in front of customers. You own TLS, backups, Postgres upgrades and the vector index, and you'll re-do parts of that on major versions. Our hosted plan exists because that work is real, not because the code is crippled.
Questions people actually ask
What is an open source AI chatbot?+
It's a conversational assistant whose source code is published under a licence that lets anyone read, modify and self-host it. In practice that means you can inspect how answers are generated, run it on your own servers, and swap the underlying language model. Most projects pair a chat interface with a retrieval layer that grounds answers in documents you supply.
Is open source really free?+
The licence is free; running it is not. You pay for a server, a database, storage for the vector index, and either GPU capacity for a local model or per-token fees to a model provider. Add engineering time for upgrades, backups and TLS. Once staff time is counted, a small self-hosted deployment usually costs more than the cheap VPS it runs on.
Can I self-host without sending data to OpenAI?+
Yes. ChatterMate, LibreChat and Rasa can all run against a local model served by Ollama or vLLM, so no conversation text leaves your infrastructure. You give up some answer quality compared with the largest hosted models, and you need enough VRAM to serve your concurrency. No third-party API key is required in that configuration.
Which is best for customer support?+
Chatwoot if you mainly need a mature omnichannel agent inbox and will add the AI yourself. ChatterMate if you want the AI answering first from your own documentation, with human handoff behind it. Rasa if you have ML engineers and strict control requirements. LibreChat isn't a support tool — it's a chat interface for your own staff.
How is this different from Chatwoot?+
Chatwoot is a support platform with no built-in AI agent: it gives you inboxes, routing and reporting, and you connect a model yourself. ChatterMate starts from the agent — it ingests your docs, answers with citations, and escalates when confidence drops. Chatwoot is far more mature, with 34,824 stars against our 79, and broader channel coverage.
What licence is ChatterMate?+
Apache-2.0. You can use, modify, self-host and redistribute it commercially, including inside closed-source products, as long as you keep the licence and attribution notices. Apache-2.0 also grants an explicit patent licence, which is why many companies prefer it to MIT for infrastructure. The full text sits in the repository.