How to Build and Deploy AI Agents with Langbase

Langbase is a serverless platform for building, evaluating, and shipping AI agents at scale. It combines model routing, memory, and retrieval in one API. This guide walks you through creating your first agent and calling it from code.

What Is Langbase?

Langbase provides composable primitives: prompts, memory (RAG), and agents that can call tools. Because it is serverless, you get low-latency scaling without managing infrastructure, and you can switch models without rewriting your application.

How to Use Langbase: Step by Step

1. Create an account and API key

Sign up, then generate an API key from the dashboard. Store it as an environment variable in your project, never in source control.

2. Install the SDK

Add the Langbase SDK to your Node or Python project. The SDK wraps authentication and streaming so you can focus on prompts.

3. Build a prompt primitive

Define a system prompt plus variables. Prompts are versioned, so you can test changes and roll back if quality drops.

4. Add memory for retrieval

Upload documents to a memory store and let the agent retrieve relevant chunks at query time. This grounds answers in your own data and cuts hallucinations.

5. Create an agent

Combine a prompt, a model, and a set of tools into an agent. Tools can be HTTP endpoints, so your agent can query databases or trigger workflows.

6. Test and evaluate

Run a set of representative inputs and compare outputs across models. Evaluation data helps you pick the cheapest model that still meets quality goals.

7. Deploy and stream

Call your agent from production code with streaming enabled for responsive UX. Scale is handled for you, so you can focus on product features.

Tips for Getting the Most Out of Langbase

• Keep system prompts short and specific; put factual context in memory instead.
• Use evaluation runs before switching models to avoid silent quality regressions.
• Version prompts alongside your code so rollbacks are trivial.
• Add a fallback model for reliability during provider outages.

Final Thoughts

Langbase removes the friction between an idea and a working result, whether you are automating research, writing code, or orchestrating multi-step AI workflows. Start with a small, concrete task, review every step the agent takes, and expand from there. With the workflow above you can go from installation to a finished, verified result in a single session.