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Big tech companies are fighting for the agent space. Everyone's building the same stuff. Easy to get stuck with one vendor. |
**VoltAgent and VoltOps** stay open. VoltAgent is MIT licensed. Totally free. VoltOps runs in the cloud or on your servers. Your data stays yours. Big companies love this. |
Open source keeps you flexible. VoltAgent works with many providers, so switching models is easy. Ready for whatever comes next. |
## Conclusion |
AI agents will change everything. But you need more than just powerful models. Pick a framework that fits. Build solid infrastructure. Watch what's happening. Voice and text agents are different, but both need to work every time. |
Models will improve and agents might get simpler. But right now, you need solid engineering to succeed. |
## Practical Example: Your First Agent with VoltAgent |
Let's create a simple customer support agent: |
```typescript |
import { Agent } from "@voltagent/core"; |
import { VercelAIProvider } from "@voltagent/vercel-ai"; |
import { openai } from "@ai-sdk/openai"; |
// Define a customer support agent |
const supportAgent = new Agent({ |
name: "Customer Support", |
instructions: "You are a helpful customer support agent.", |
llm: new VercelAIProvider(), |
model: openai("gpt-4o-mini"), |
}); |
// Run the agent |
const response = await supportAgent.generateText( |
"What is the status of my order? Order number: 12345" |
); |
console.log(response.text); |
// "I'm checking your order. Order number 12345..." |
``` |
That's it. Add VoltOps and you'll see token usage, response times, and costs right away. |
Want to build agents that work? Move fast but stay flexible. VoltAgent and VoltOps do both. |
<|endoftext|> |
# source: VoltAgent__voltagent/website/blog/2025-05-15-top-ai-agent-frameworks/index.md type: docs |
--- |
title: Top 5 AI Agent Frameworks in 2025 |
description: We'll check out the top 5 frameworks to help you choose the best tools for your smart apps. |
tags: [frameworks] |
slug: ai-agent-frameworks |
image: https://cdn.voltagent.dev/2025-05-15-top-ai-agent-frameworks/social.png |
authors: necatiozmen |
--- |
## So, You Want to Build an AI Agent? |
Building AI that doesn't make you wanna pull your hair out? That actually _feels_ smart instead of just, y'know, parroting stuff back at you? Harder than those YouTube tutorials make it seem. Trust me on this one. |
You've probably seen all the Twitter threads and Discord chats hyping AI agents and thought "damn, I gotta get in on this!" Then reality hits: where the heck do you even START? |
I remember when I first tried building an agent. Opened up VS Code(Cursor:D) all confident and... promptly fell into a threeday rabbit hole just figuring out which framework wouldn't immediately make me regret my life choices. The options are OVERWHELMING, folks. |
The AI framework landscape? Total chaos. Everyone's got their favorite. Everyone's got opinions. New GitHub repos popping up faster than I can doom-scroll through my Twitter feed. How's a normal dev supposed to figure out what's worth their precious time? |
That's exactly why I wrote this post. |
I'm gonna walk you through five frameworks we've personally wrestled with. We'll look at what they're genuinely good at (not just what their marketing says), what kind of projects they shine for, and crucially who should use them... and who should run screaming in the other direction. |
By the end, you'll have a much clearer picture of which one deserves your next weekend project time. Or at least, you'll know which documentation you'll be cursing at for the next few days. 😅 |
Grab your coffee (you'll need it), and let's cut through the hype to find you a framework that'll actually help ship something cool! |
## The Top 5 AI Agent Frameworks |
### 1. VoltAgent: Why We Built It (And Where It Shines) |
 |
Let's start with [**VoltAgent**](https://github.com/VoltAgent/voltagent/). Full disclosure: I'm the maintainer, so yeah. But I'm also going to be brutally honest about where it works and where it doesn't. We built VoltAgent after a particularly frustrating sometime trying to piece together AI agents from various half-b... |
Every time we'd start a new agent project, we'd face the same problems: |
- Either wrestle with bare-metal LLM APIs and reinvent the wheel |
- Or get stuck with simplistic no-code tools that break the moment you need something custom |
So we created VoltAgent with a specific philosophy: give JavaScript/TypeScript developers a framework that feels like modern web development, not some academic research project. |
**The Key Design Decisions Behind VoltAgent** |
When I first sketched out VoltAgent, I had a few non-negotiables: |
- **First-Class TypeScript Support**: I'm a TypeScript dev at heart, and I was tired of Python-first libraries with JS/TS as an afterthought. VoltAgent is TypeScript-native from the ground up. |
- **Modular Architecture**: The `@voltagent/core` module establishes the foundation, but everything is pluggable. Need voice? Add `@voltagent/voice`. Need persistent memory? There's a package for that. I wanted zero bloat. |
- **Real Tool Integration**: This was my biggest frustration with other frameworks. "Tool use" usually meant calling a calculator or maybe a web search. But real agents need to integrate with your actual business systems. I built VoltAgent's tool system to handle messy, real-world integrations. |
- **State Management That Makes Sense**: Coming from React, I wanted state management that would feel intuitive. The memory system in VoltAgent borrows concepts from modern frontend development. |
- **Model Flexibility**: I've been burned too many times by being locked into one LLM provider. VoltAgent supports OpenAI, Anthropic, Google Vertex, and others with a unified interface. Switching providers is changing a config value, not rewriting your app. |
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