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Terraform Provider

Manage your AI infrastructure as code - version-control bots, datasets, skillsets, and secrets with standard Terraform workflows for reproducible, reviewable deployments.

ChatBotKit's Terraform provider brings infrastructure-as-code to your conversational AI stack. Define bots, datasets, skillsets, secrets, and integrations in declarative HCL, and manage everything through standard Terraform workflows. Every change is version-controlled, reviewable, and reproducible.

Whether you need consistent multi-environment deployments, pull-request-based reviews for agent changes, or instant rollback when something goes wrong, the Terraform provider treats your AI agent fleet as first-class infrastructure.

Key Features

  • Declarative Resource Management: Define bots, datasets, skillsets, secrets, and integrations as HCL resources.
  • Plan and Apply: Preview every change before it goes live with terraform plan.
  • Multi-Environment Support: Use workspaces and variable overrides to manage dev, staging, and production consistently.
  • Import Existing Resources: Bring manually created bots and datasets under Terraform management.
  • Drift Detection: Detect and correct manual changes that bypass your Terraform workflow.
  • Full Lifecycle Control: Create, update, destroy, and recreate your entire agent stack with a single command.

Getting Started

Add the provider to your configuration and run terraform init:

terraform {
  required_providers {
    chatbotkit = {
      source  = "chatbotkit/chatbotkit"
      version = "~> 1.0"
    }
  }
}

provider "chatbotkit" {
  api_secret = var.chatbotkit_api_secret
}

resource "chatbotkit_bot" "support_agent" {
  name      = "Customer Support Agent"
  model     = "claude-4.6-sonnet"
  backstory = "You are a helpful customer support agent for Acme Corp."
}

Then preview and apply your changes:

terraform plan
terraform apply

Browse the Terraform Provider documentation for the full resource reference and explore Tutorials for step-by-step guides.

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