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https://github.com/mastra-ai/mastra

The TypeScript AI framework.
https://github.com/mastra-ai/mastra

agents ai chatbots javascript llm nextjs nodejs reactjs typescript workflows

Last synced: 16 days ago
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The TypeScript AI framework.

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README 

        
# Mastra



[![Mastra framework homepage](mastra-homepage.png)](https://mastra.ai)



Mastra is an opinionated Typescript framework that helps you build AI applications and features quickly. It gives you the set of primitives you need: workflows, agents, RAG, integrations, syncs and evals. You can run Mastra on your local machine, or deploy to a serverless cloud.



The main Mastra features are:



| Features                                                                           | Description                                                                                                                                                                                                                                                                              |

| ---------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |

| [LLM Models](https://mastra.ai/docs/guide/how-to/00-llm-models)                    | Mastra supports a variety of LLM providers, including OpenAI, Anthropic, Google Gemini. You can choose the specific model and provider, choose system and user prompts, and decide whether to stream the response.                                                                       |

| [Agents](https://mastra.ai/docs/guide/how-to/01-creating-agents)                   | Agents are systems where the language model chooses a sequence of actions. In Mastra, agents provide LLM models with tools, workflows, and synced data. Agents can call your own functions or APIs of third-party integrations and access knowledge bases you build.                     |

| [Tools](https://mastra.ai/docs/guide/how-to/02-adding-tools)                       | Tools are typed functions that can be executed by agents or workflows, with built-in integration access and parameter validation. Each tool has a schema that defines its inputs, an executor function that implements its logic, and access to configured integrations.                 |

| [Workflows](https://mastra.ai/docs/guide/how-to/03-building-workflows)             | Workflows are durable graph-based state machines. They have loops, branching, wait for human input, embed other workflows, do error handling, retries, parsing and so on. They can be built in code or with a visual editor. Each step in a workflow has built-in OpenTelemetry tracing. |

| [RAG](https://mastra.ai/docs/guide/how-to/04-knowledge-sources)                    | Retrieval-augemented generation (RAG) lets you construct a knowledge base for agents. RAG is an ETL pipeline with specific querying techniques, including chunking, embedding, and vector search.                                                                                        |

| [Integrations & Syncs](https://mastra.ai/docs/guide/how-to/06-adding-integrations) | In Mastra, syncs are async functions that can be deployed as background tasks across different execution environments. Integrations are auto-generated, type-safe API clients for third-party services that can be used as tools for agents or steps in workflows.                       |

| [Evals](https://mastra.ai/docs/guide/how-to/08-running-evals)                      | Evals are automated tests that evaluate LLM outputs using model-graded, rule-based, and statistical methods. Each eval returns a normalized score between 0-1 that can be logged and compared. Evals can be customized with your own prompts and scoring functions.                      |



## Quick Start



### Prerequisites



- Node.js (v20.0+)



## Get an LLM provider API key



If you don't have an API key for an LLM provider, you can get one from the following services:



- [OpenAI](https://platform.openai.com/)

- [Anthropic](https://console.anthropic.com/settings/keys)

- [Google Gemini](https://ai.google.dev/gemini-api/docs)



If you don't have an account with these providers, you can sign up and get an API key. OpenAI and Anthropic require a credit card to get an API key. Gemini does not and has a generous free tier for its API.



## Create a new project



As a first step, create a project directory and navigate into it:



```bash copy

mkdir hello-mastra

cd hello-mastra

```



Next, initialize a TypeScript project using npm:



```bash copy npm2yarn

npm init -y

npm install typescript tsx @types/node @mastra/core@alpha --save-dev

```



### Add an index.ts file



```bash

mkdir src

touch src/index.ts

```



Then, add this code to `src/index.ts`:



```typescript

import { Agent } from '@mastra/core';



async function main() {

  const agent = new Agent({

    name: 'story-writer',

    maxSteps: 3,

    model: {

      provider: 'OPEN_AI',

      name: 'gpt-4o',

      toolChoice: 'auto',

    },

    instructions: `You are a helpful assistant who writes creative stories.`,

    tools: {},

  });



  const result = await agent.text({

    messages: ['Write a short story about a robot learning to paint.'],

  });



  console.log('Agent response:', result.text);

}



main();

```



### Run the script



Finally, run the script:



```bash copy

OPENAI_API_KEY= npx tsx src/index.ts

```



If you're using Anthropic, set the `ANTHROPIC_API_KEY`. If you're using Gemini, set the `GOOGLE_GENERATIVE_AI_API_KEY`.



## Support



We have an [open community Discord](https://discord.gg/yPBW9aTX). Come and say hello and let us know if you have any questions or need any help getting things running.



It's also super helpful if you leave the project a star here at the [top of the page](https://github.com/mastra-ai/mastra)