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.

Full Evecomparison →

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.

Full Rasacomparison →

What both add

Whichever you pick, you're inheriting a dependency tree and a vocabulary your team has to learn before they ship anything. Eve has its own class hierarchy and tool registration conventions; Rasa has its. Either way, when something misbehaves you'll be reading framework source before you reach the actual HTTP call.

If the real workload is one model and a handful of tools, both can feel like a workbench for driving a nail. The lesson below builds the same pattern in plain Python — useful as a comparison point even if you ultimately keep the framework.

By the numbers

By the numbers

Eve

GitHub Stars

3.5k

Forks

180

Language

TypeScript

License

Apache-2.0

Created

2026-06-17

Created by

Vercel

Backed by

Vercel (public)

Cloud/SaaS

Runs on Vercel Sandbox + AI Gateway; deploys anywhere Node runs

Production ready

Yes

github.com/vercel/eve

Rasa

GitHub Stars

21.1k

Forks

4.9k

Language

Python

License

Apache-2.0

Created

2016-10-14

Created by

Rasa Technologies

Cloud/SaaS

Rasa Pro / Rasa Cloud

Production ready

Yes

github.com/RasaHQ/rasa

GitHub stats as of April 2026. Stars indicate community interest, not necessarily quality or fit for your use case.

ConceptEveRasa
AgentA directory with `agent.ts` + `instructions.md` + subfolders — the framework wires them togetherRasa agent with NLU pipeline, dialogue policies, and action server
ToolsEach file in `tools/` exports one tool; schema comes from a Zod exportCustom actions running on a separate action server via HTTP
DurabilityVercel Workflow SDK checkpoints every step so a crashed agent resumes where it left off
Sub-agentsEach `subagents/*.ts` becomes a callable sub-agent the parent can hand off to
Sandboxed execVercel Sandbox runs untrusted code in isolated micro-VMs, one API call away
Schedules`schedules/*.ts` exports a cron expression + handler; Vercel runs it
NLUNLU pipeline: tokenizer, featurizer, intent classifier, entity extractor
DialogueStories/Rules YAML + dialogue policies for conversation flow
SlotsTyped slots for tracking entities and state across turns
CALMLLM 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 →