Langbase Docs
Langbase is the most powerful serverless AI cloud for building and deploying AI agents.
Build, deploy, and scale serverless AI agents with tools and memory (RAG). Simple AI primitives no bloated frameworks, all with a world-class developer experience without using any frameworks.
CHAI.new — vibe code ai agents.can build agents for you, literally vibe code any ai agent| Products | Description |
|---|---|
| CHAI.new ✨ | Vibe code any AI agent. Chai turns prompts into prod-ready agents |
| Pipe Agents | Pipes are a standard way to build serverless AI agents with tools and memory |
| AI Memory | Auto RAG AI primitve for agents to give them human like long-term memory |
| Workflow | Build multi-step agents with built-in durable features like timeouts and retries |
| Threads | Store and manage AI agents context and conversation history without managing DBs |
| Agent | Agents is an AI primitive to build serverless agents with unified API over 600+ LLMs |
| Parser | AI primitive to extract text content from various document formats, for RAG |
| Chunker | AI primitive to split text into smaller, manageable chunks for context, for RAG |
| Embed | AI primitive to convert text into vector embeddings unified API multiple models, for RAG |
| Tools | Pre-built and hosted tools for AI agents like web crawler and web search with Exa |
| AI Studio | Langbase studio is your playground to build, collaborate, and deploy AI agents. Experiment on your agent changes and memory retrieval in real-time, with real data, store messages, version your prompts, optimize cost, see usage, and traces. Access Langbase Studio. A complete AI developers platform. - Collaborate: Invite all team members to collaborate on the pipe. Build AI together. - Developers & Stakeholders: Work with all your R&D team, engineering, product, GTM (marketing and sales). It's like a powerful version of GitHub x Google Docs for AI. |
Why Langbase?
Langbase is the best way to build and deploy AI agents.
Our mission: AI for all. Not just ML wizards. Every. Single. Developer.
Build AI agents without any bloated frameworks. You write the logic, we handle the logistics.
Compared to complex AI frameworks, Langbase is serverless and the first composable AI platform.
- Start by building simple AI agents (pipes)
- Then train serverless semantic Memory agents (RAG) to get accurate and trusted results
Get started for free:
- CHAI.new: Vibe code any AI agent. Chai turns prompts into prod-ready agents.
- AI Studio: Build, collaborate, and deploy AI Agents with tools and Memory (RAG).
- Langbase SDK: Easiest wasy to build AI Agents with TypeScript. (recommended)
- HTTP API: Build AI agents with any language (Python, Go, PHP, etc.).
Get started
Agent Architectures
Explore different agent architectures and how to build them.
Langbase SDK
Learn how to use the Langbase SDK to build AI agents with TypeScript.
AI Agents (Pipes)
Build and deploy serverless AI agents we call pipes with tools.
Memory Agents
Build AI agents with Memory for Retrieval-augmented generation (RAG).
Guides
Docs AI Agent: AI in docs
Build an AI agent with RAG that answers questions from your docs.
AI Email Agent: Handle your emails
Build a composable multi agent architecture using Langbase SDK.
Build your own v0, Lovable, or Bolt
Build a coding agent like v0, lovable, bolt with Langbase SDK.
Understand how RAG works
Understand how RAG works and how to use it in your app.
Langbase Agent Examples
Explore open-source Langbase agent examples on GitHub.
Internet Research Agent Tool
Build a tool for AI agents that can help you research on the internet.
Features
CHAI.new ✨
Vibe code any AI agent. Chai turns prompts into prod-ready agents
Pipe Agents
Pipes are a standard way to build serverless AI agents with memory
AI Memory
Auto RAG AI primitive for agents to give them human like long-term memory
Workflow
Build multi-step agents with built-in durable features like timeouts and retries
Threads
Store and manage AI agents context and conversation history
Agent
AI primitive to build serverless agents with unified API over 600+ LLMs
Parser
AI primitive to extract text content from various document formats, for RAG
Chunker
AI primitive to split text into smaller, manageable chunks for context, for RAG
Embed
Convert text into vector embeddings unified API multiple models, for RAG
Tools
Hosted tools for AI agents like web crawler and web search with Exa
AI Studio
AI playground to experiment, build, collaborate, and deploy AI agents
Memory
Use agentic RAG memory with 30-50x in-expensive vector storage
Threads
Store and retrieve messages in a Pipe for a conversation-like experience
Versions
Create and manage versions of agents to track changes and compare results
Fork
Fork to make a copy of any open agent in your account and ship faster
Variables
Add variables to a prompts in Pipes to make them dynamic
Logs
Detailed logs of each Pipe request with information like LLM request cost etc
Auto tool calling
Auto tool calling enables agents to call external tools and APIs
Few-shot
Few-shot messages enable LLMs to learn from simple system and AI prompt examples
Prompt
Context for the LLM and the user, shaping the conversation and responses
Rerank
Rerank to reorder a list of documents based on semantic relevance
Prompt Optimization
Optimizer models optimize a prompt for enhanced results
Safety
Define a safety prompt for any LLM
Stream
Stream agent responses to improve the user's agent experience
Moderation
Set custom moderation settings for OpenAI models in a Pipe
JSON mode
JSON mode of Pipe instructs the LLM to give output in JSON
Experiments
Run experiments to test the performance of different LLMs and prompts
Readme
Add a README to a Pipe to provide additional information
API & SDK
Managed API to deploy and scale serverless AI agents with Langbase
Keysets
Add all LLM API keys once to seamless switch between models in a Pipe
Usage
View insights of each Pipe request
Examples
Multiple ready to use examples to quickly setup the Pipe
Model Presets
Configure response parameters of LLMs in a Pipe using model presets
Organizations
Foster collaboration among users within a shared workspace via organizations
Open Pipes
Open Pipes on Langbase allows users to create and share pipes with the public