You can develop agents however you want — either using a framework such as LangChain, Google ADK or AI SDK; or using just custom code — and deploy the agents to Blaxel with our developer tools (Blaxel CLI, GitHub app, GitHub action, etc.). Blaxel SDK provides methods to programmatically access and integrate various resources hosted on Blaxel into your agent’s code, such as: model APIs, tool servers, sandboxes, batch jobs, or other agents. The SDK handles authentication, secure connection management and telemetry automatically. This packaging makes Blaxel fully agnostic of the framework used to develop your agent and doesn’t prevent you from deploying your software on another platform.

​
Overview of the development/deployment process

Blaxel’s development paradigm is designed to have a minimal footprint on your usual development process. Your custom code remains platform-agnostic: you can deploy it on Blaxel or through traditional methods like Docker containers on VMs or Kubernetes clusters. When you deploy on Blaxel (CLI command bl deploy), Blaxel runs a specialized build process that integrates your code with its Global Agentics Network features.
At this time, Blaxel only supports custom agents developed in TypeScript or Python.
Here is a high-level overview of how agents can be built and deployed using Blaxel:
  1. Initialize a new project by creating a local git repository. This will contain your agent’s logic and connections, as well as all required dependencies. For quick setup, use Blaxel CLI command bl create-agent-app, which creates a pre-scaffolded local repository ready for development that you can deploy to Blaxel in one command.
  2. Develop and test your agent iteratively in a local environment.
    1. Develop your agent logic however you want (using an agentic framework or any custom TypeScript/Python code). Write your own functions as needed. Use Blaxel SDK commands to connect to resources from Blaxel such as model APIs and tool servers.
    2. Use Blaxel CLI command bl serve to serve your agent on your local machine. The execution workflow—including agent logic, functions, and model API calls—is broken down and sandboxed exactly as it would be when served on Blaxel.
  3. Deploy your agent. Use Blaxel CLI command bl deploy to build and deploy your agent on Blaxel. You can manage a development & production life-cycle by deploying multiple agents, with the according prefix or label.

​
Develop an agent on Blaxel

Check out the following guide to learn how to develop and deploy an agent using your preferred programming language on Blaxel.

TypeScript

Develop your AI agents in TypeScript using the Blaxel SDK.

Python

Develop your AI agents in Python using the Blaxel SDK.

Deploy an agent

Learn how to deploy your custom AI agents on Blaxel as a serverless endpoint.