BaseAI

Getting Started

Documentation (recommended)

1. Initialize a new BaseAI project

npx baseai@latest init

ROOT (of your app)├── baseai|  ├── baseai.config.ts|  ├── memory|  ├── pipes|  └── tools├── .env (your env file)└── package.json

2. Add API keys

# !! SERVER SIDE ONLY !!# Keep all your API keys secret — use only on the server side.# TODO: ADD: Both in your production and local env files.# Langbase API key for your User or Org account.# How to get this API key https://langbase.com/docs/api-reference/api-keysLANGBASE_API_KEY=# TODO: ADD: LOCAL ONLY. Add only to local env files.# Following keys are needed for local pipe runs. For providers you are using.# For Langbase, please add the key to your LLM keysets.# Read more: Langbase LLM Keysets https://langbase.com/docs/features/keysetsOPENAI_API_KEY=ANTHROPIC_API_KEY=COHERE_API_KEY=FIREWORKS_API_KEY=GOOGLE_API_KEY=GROQ_API_KEY=MISTRAL_API_KEY=PERPLEXITY_API_KEY=TOGETHER_API_KEY=XAI_API_KEY=

3. Create a new AI agent

npx baseai@latest pipe

import{PipeI}from'@baseai/core';constpipeSummary=():PipeI=>({// Replace with your API key https://langbase.com/docs/api-reference/api-keysapiKey:process.env.LANGBASE_API_KEY!,name:'summary',description:'AI Summary agent',status:'public',model:'openai:gpt-4o-mini',stream:true,json:false,store:true,moderate:true,top_p:1,max_tokens:1000,temperature:0.7,presence_penalty:1,frequency_penalty:1,stop:[],tool_choice:'auto',parallel_tool_calls:true,messages:[{role:'system',content:`You are a helpful AI agent. Make everything Less wordy.`}],variables:[],memory:[],tools:[]});exportdefaultpipeSummary;

4. Integrate pipe in your app

import{Pipe,getRunner}from'@baseai/core';importpipeSummarizerfrom'./baseai/pipes/summary';constpipe=newPipe(pipeSummarizer());constuserMsg=`Langbase studio is your playground to build, collaborate, and deploy AI. It allows you to experiment with your pipes in real-time, with real data, store messages, version your prompts, and truly helps you take your idea from building prototypes to deployed in production with LLMOps on usage, cost, and quality.A complete AI developers platform.- Collaborate: Invite all team members to collaborate on the pipe. Build AI together.- Developers & Stakeholders: All your R&D team, engineering, product, GTM (marketing and sales), literally invlove every stakeholder can collaborate on the same pipe. It's like a powerful version of GitHub x Google Docs for AI. A complete AI developers platform.`;asyncfunctionmain(){const{ stream}=awaitpipe.run({messages:[{role:'user',content:userMsg}],stream:true,});construnner=getRunner(stream);// Method 1: Using event listenersrunner.on('connect',()=>{console.log('Stream started.\n');});runner.on('content',content=>{process.stdout.write(content);});runner.on('end',()=>{console.log('\nStream ended.');});runner.on('error',error=>{console.error('Error:',error);});}main();

import'dotenv/config';

5. Run the AI agent

npx baseai@latest dev

npx tsx index.ts

Stream started.Langbase Studio is your AI development playground. Experiment in real-time with real data, store messages, and version prompts to move from prototype to production seamlessly.Key Features:-**Collaborate**: Invite team members to build AI together.-**Inclusive Teams**: Engage all stakeholders—R&D, engineering, product, and marketing—in a shared space. It’s like GitHub combined with Google Docs for AI development.Stream ended.

Tip

You can also run RAG locally with BaseAI. Check out the memory agent quickstartguide for more details.

Contributing

Authors

Security