Comparisons / Eve vs Rasa
Eve vs Rasa: Which Agent Framework to Use?
Eve vs Rasa, head to head
Eve and Rasa both let you build an agent, but they sit in different parts of the stack and they assume different things about who's writing the code.
Eve is Vercel's open-source TypeScript agent framework, launched June 17 2026.
Rasa is an open-source framework for building conversational AI — chatbots and virtual assistants.
Underneath, both wrap the same thing: a model call, a tool dispatch, a loop. The decision is about which abstraction your team wants to think in day to day, and which ecosystem you're willing to inherit along with it. There's an honest, framework-free version of the same pattern in about 60 lines of Python in the lesson at the bottom of this page — useful as a baseline regardless of which framework wins.
Pick Eve if
Pick Eve if eve earns its keep when you want durable execution, sandboxed code exec, and multi-model routing without wiring three separate services. If you're already on Vercel, it composes; if not, the runtime pieces are the value and they don't travel. For a single-loop tool-using agent, plain TypeScript ships faster. The tradeoffs in its intro should match how your team already thinks about agents; Rasa will feel like translation if they don't.
Pick Rasa if
Pick Rasa if rasa is purpose-built for production conversational AI with enterprise requirements — on-premise deployment, regulatory compliance, deterministic business logic. For general-purpose agents or simple chatbots, an LLM with a system prompt and a few tools is faster to build and more flexible. The tradeoffs in its intro should match how your team already thinks about agents; Eve will feel like translation if they don't.
By the numbers
By the numbers
Eve
3.5k
180
TypeScript
Apache-2.0
2026-06-17
Vercel
Vercel (public)
Runs on Vercel Sandbox + AI Gateway; deploys anywhere Node runs
Yes
Rasa
21.1k
4.9k
Python
Apache-2.0
2016-10-14
Rasa Technologies
Rasa Pro / Rasa Cloud
Yes
GitHub stats as of April 2026. Stars indicate community interest, not necessarily quality or fit for your use case.
| Concept | Eve | Rasa |
|---|---|---|
| Agent | A directory with `agent.ts` + `instructions.md` + subfolders — the framework wires them together | Rasa agent with NLU pipeline, dialogue policies, and action server |
| Tools | Each file in `tools/` exports one tool; schema comes from a Zod export | Custom actions running on a separate action server via HTTP |
| Durability | Vercel Workflow SDK checkpoints every step so a crashed agent resumes where it left off | — |
| Sub-agents | Each `subagents/*.ts` becomes a callable sub-agent the parent can hand off to | — |
| Sandboxed exec | Vercel Sandbox runs untrusted code in isolated micro-VMs, one API call away | — |
| Schedules | `schedules/*.ts` exports a cron expression + handler; Vercel runs it | — |
| NLU | — | NLU pipeline: tokenizer, featurizer, intent classifier, entity extractor |
| Dialogue | — | Stories/Rules YAML + dialogue policies for conversation flow |
| Slots | — | Typed slots for tracking entities and state across turns |
| CALM | — | LLM for understanding + deterministic `Flows` for business logic |
Or build your own in 60 lines
Both Eve and Rasa implement the same 8 patterns. An agent is a function. Tools are a dict. The loop is a while loop. The whole thing composes in ~60 lines of Python.
No framework. No dependencies. No opinions. Just the code.
Build it from scratch →