4 reactions
Rq- Voltagent.js We built an open source AI Agent framework with observability first.
We saw most AI Agent frameworks built for Python and felt the JS/TS ecosystem needs powerful, developer friendly tools too.
So, we built VoltAgent, an open-source framework specifically for building AI agents in TypeScript.
https://github.com/voltagent/voltagent
Our goal is to give JS devs a framework that avoids excessive boilerplate but is still flexible and powerful:
\- Modularity: Core building blocks (tools, memory, MCP) + add features as needed.
\- LLM-Agnostic: Use OpenAI, Anthropic, Gemini, etc. no vendor lock-in.
\- Observability First (like n8n style canvas): Debugging AI agents is tough. Our local-first Dev Console provides visual tracing & inspection, making life easier (seriously, check the demo, it's cool: https://console.voltagent.dev/demo).
Using VoltAgent something like:
import { VoltAgent, Agent } from "@voltagent/core";
import { VercelAIProvider } from "@voltagent/vercel-ai";
import { openai } from "@ai-sdk/openai";
const agent = new Agent({
name: "my-voltagent-app",
description: "A helpful assistant that answers questions",
llm: new VercelAIProvider(),
model: openai("gpt-4o-mini"),
});
const response = await agent.generateText("Explain uantum computing like I'm five.");
console.log("Complete esponse:", response.text);
Let us know what you think. Would love to get your feedback, contributions, or bug reports!
#js #dev #technology #programming
source
We saw most AI Agent frameworks built for Python and felt the JS/TS ecosystem needs powerful, developer friendly tools too.
So, we built VoltAgent, an open-source framework specifically for building AI agents in TypeScript.
https://github.com/voltagent/voltagent
Our goal is to give JS devs a framework that avoids excessive boilerplate but is still flexible and powerful:
\- Modularity: Core building blocks (tools, memory, MCP) + add features as needed.
\- LLM-Agnostic: Use OpenAI, Anthropic, Gemini, etc. no vendor lock-in.
\- Observability First (like n8n style canvas): Debugging AI agents is tough. Our local-first Dev Console provides visual tracing & inspection, making life easier (seriously, check the demo, it's cool: https://console.voltagent.dev/demo).
Using VoltAgent something like:
import { VoltAgent, Agent } from "@voltagent/core";
import { VercelAIProvider } from "@voltagent/vercel-ai";
import { openai } from "@ai-sdk/openai";
const agent = new Agent({
name: "my-voltagent-app",
description: "A helpful assistant that answers questions",
llm: new VercelAIProvider(),
model: openai("gpt-4o-mini"),
});
const response = await agent.generateText("Explain uantum computing like I'm five.");
console.log("Complete esponse:", response.text);
Let us know what you think. Would love to get your feedback, contributions, or bug reports!
#js #dev #technology #programming
source
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