319 lines
11 KiB
Markdown
319 lines
11 KiB
Markdown
---
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display_name: Claude Code
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description: Run the Claude Code agent in your workspace.
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icon: ../../../../.icons/claude.svg
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verified: true
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tags: [agent, claude-code, ai, tasks, anthropic]
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---
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# Claude Code
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Run the [Claude Code](https://docs.anthropic.com/en/docs/agents-and-tools/claude-code/overview) agent in your workspace to generate code and perform tasks. This module integrates with [AgentAPI](https://github.com/coder/agentapi) for task reporting in the Coder UI.
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```tf
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module "claude-code" {
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source = "registry.coder.com/coder/claude-code/coder"
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version = "4.2.2"
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agent_id = coder_agent.example.id
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workdir = "/home/coder/project"
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claude_api_key = "xxxx-xxxxx-xxxx"
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}
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```
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> [!WARNING]
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> **Security Notice**: This module uses the `--dangerously-skip-permissions` flag when running Claude Code tasks. This flag bypasses standard permission checks and allows Claude Code broader access to your system than normally permitted. While this enables more functionality, it also means Claude Code can potentially execute commands with the same privileges as the user running it. Use this module _only_ in trusted environments and be aware of the security implications.
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> [!NOTE]
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> By default, this module is configured to run the embedded chat interface as a path-based application. In production, we recommend that you configure a [wildcard access URL](https://coder.com/docs/admin/setup#wildcard-access-url) and set `subdomain = true`. See [here](https://coder.com/docs/tutorials/best-practices/security-best-practices#disable-path-based-apps) for more details.
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## Prerequisites
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- An **Anthropic API key** or a _Claude Session Token_ is required for tasks.
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- You can get the API key from the [Anthropic Console](https://console.anthropic.com/dashboard).
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- You can get the Session Token using the `claude setup-token` command. This is a long-lived authentication token (requires Claude subscription)
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### Session Resumption Behavior
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By default, Claude Code automatically resumes existing conversations when your workspace restarts. Sessions are tracked per workspace directory, so conversations continue where you left off. If no session exists (first start), your `ai_prompt` will run normally. To disable this behavior and always start fresh, set `continue = false`
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## Examples
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### Usage with Agent Boundaries
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This example shows how to configure the Claude Code module to run the agent behind a process-level boundary that restricts its network access.
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```tf
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module "claude-code" {
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source = "dev.registry.coder.com/coder/claude-code/coder"
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enable_boundary = true
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boundary_version = "4.2.2"
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boundary_log_dir = "/tmp/boundary_logs"
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boundary_log_level = "WARN"
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boundary_additional_allowed_urls = ["GET *google.com"]
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boundary_proxy_port = "8087"
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version = "4.2.2"
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}
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```
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### Usage with Tasks and Advanced Configuration
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This example shows how to configure the Claude Code module with an AI prompt, API key shared by all users of the template, and other custom settings.
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```tf
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data "coder_parameter" "ai_prompt" {
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type = "string"
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name = "AI Prompt"
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default = ""
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description = "Initial task prompt for Claude Code."
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mutable = true
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}
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module "claude-code" {
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source = "registry.coder.com/coder/claude-code/coder"
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version = "4.2.2"
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agent_id = coder_agent.example.id
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workdir = "/home/coder/project"
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claude_api_key = "xxxx-xxxxx-xxxx"
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# OR
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claude_code_oauth_token = "xxxxx-xxxx-xxxx"
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claude_code_version = "4.2.2" # Pin to a specific version
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agentapi_version = "4.2.2"
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ai_prompt = data.coder_parameter.ai_prompt.value
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model = "sonnet"
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permission_mode = "plan"
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mcp = <<-EOF
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{
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"mcpServers": {
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"my-custom-tool": {
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"command": "my-tool-server"
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"args": ["--port", "8080"]
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}
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}
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}
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EOF
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}
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```
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### Standalone Mode
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Run and configure Claude Code as a standalone CLI in your workspace.
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```tf
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module "claude-code" {
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source = "registry.coder.com/coder/claude-code/coder"
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version = "4.2.2"
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agent_id = coder_agent.example.id
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workdir = "/home/coder"
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install_claude_code = true
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claude_code_version = "4.2.2"
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report_tasks = false
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cli_app = true
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}
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```
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### Usage with Claude Code Subscription
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```tf
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variable "claude_code_oauth_token" {
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type = string
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description = "Generate one using `claude setup-token` command"
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sensitive = true
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value = "xxxx-xxx-xxxx"
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}
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module "claude-code" {
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source = "registry.coder.com/coder/claude-code/coder"
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version = "4.2.2"
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agent_id = coder_agent.example.id
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workdir = "/home/coder/project"
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claude_code_oauth_token = var.claude_code_oauth_token
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}
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```
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### Usage with AWS Bedrock
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#### Prerequisites
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AWS account with Bedrock access, Claude models enabled in Bedrock console, appropriate IAM permissions.
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Configure Claude Code to use AWS Bedrock for accessing Claude models through your AWS infrastructure.
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```tf
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resource "coder_env" "bedrock_use" {
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agent_id = coder_agent.example.id
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name = "CLAUDE_CODE_USE_BEDROCK"
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value = "1"
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}
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resource "coder_env" "aws_region" {
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agent_id = coder_agent.example.id
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name = "AWS_REGION"
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value = "us-east-1" # Choose your preferred region
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}
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# Option 1: Using AWS credentials
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variable "aws_access_key_id" {
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type = string
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description = "Your AWS access key ID. Create this in the AWS IAM console under 'Security credentials'."
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sensitive = true
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value = "xxxx-xxx-xxxx"
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}
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variable "aws_secret_access_key" {
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type = string
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description = "Your AWS secret access key. This is shown once when you create an access key in the AWS IAM console."
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sensitive = true
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value = "xxxx-xxx-xxxx"
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}
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resource "coder_env" "aws_access_key_id" {
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agent_id = coder_agent.example.id
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name = "AWS_ACCESS_KEY_ID"
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value = var.aws_access_key_id
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}
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resource "coder_env" "aws_secret_access_key" {
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agent_id = coder_agent.example.id
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name = "AWS_SECRET_ACCESS_KEY"
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value = var.aws_secret_access_key
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}
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# Option 2: Using Bedrock API key (simpler)
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variable "aws_bearer_token_bedrock" {
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type = string
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description = "Your AWS Bedrock bearer token. This provides access to Bedrock without needing separate access key and secret key."
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sensitive = true
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value = "xxxx-xxx-xxxx"
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}
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resource "coder_env" "bedrock_api_key" {
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agent_id = coder_agent.example.id
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name = "AWS_BEARER_TOKEN_BEDROCK"
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value = var.aws_bearer_token_bedrock
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}
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module "claude-code" {
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source = "registry.coder.com/coder/claude-code/coder"
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version = "4.2.2"
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agent_id = coder_agent.example.id
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workdir = "/home/coder/project"
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model = "global.anthropic.claude-sonnet-4-5-20250929-v1:0"
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}
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```
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> [!NOTE]
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> For additional Bedrock configuration options (model selection, token limits, region overrides, etc.), see the [Claude Code Bedrock documentation](https://docs.claude.com/en/docs/claude-code/amazon-bedrock).
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### Usage with Google Vertex AI
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#### Prerequisites
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GCP project with Vertex AI API enabled, Claude models enabled through Model Garden, service account with Vertex AI permissions, appropriate IAM permissions (Vertex AI User role).
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Configure Claude Code to use Google Vertex AI for accessing Claude models through Google Cloud Platform.
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```tf
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variable "vertex_sa_json" {
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type = string
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description = "The complete JSON content of your Google Cloud service account key file. Create a service account in the GCP Console under 'IAM & Admin > Service Accounts', then create and download a JSON key. Copy the entire JSON content into this variable."
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sensitive = true
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}
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resource "coder_env" "vertex_use" {
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agent_id = coder_agent.example.id
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name = "CLAUDE_CODE_USE_VERTEX"
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value = "1"
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}
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resource "coder_env" "vertex_project_id" {
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agent_id = coder_agent.example.id
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name = "ANTHROPIC_VERTEX_PROJECT_ID"
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value = "your-gcp-project-id"
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}
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resource "coder_env" "cloud_ml_region" {
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agent_id = coder_agent.example.id
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name = "CLOUD_ML_REGION"
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value = "global"
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}
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resource "coder_env" "vertex_sa_json" {
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agent_id = coder_agent.example.id
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name = "VERTEX_SA_JSON"
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value = var.vertex_sa_json
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}
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resource "coder_env" "google_application_credentials" {
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agent_id = coder_agent.example.id
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name = "GOOGLE_APPLICATION_CREDENTIALS"
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value = "/tmp/gcp-sa.json"
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}
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module "claude-code" {
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source = "registry.coder.com/coder/claude-code/coder"
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version = "4.2.2"
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agent_id = coder_agent.example.id
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workdir = "/home/coder/project"
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model = "claude-sonnet-4@20250514"
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pre_install_script = <<-EOT
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#!/bin/bash
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# Write the service account JSON to a file
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echo "$VERTEX_SA_JSON" > /tmp/gcp-sa.json
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# Install prerequisite packages
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sudo apt-get update
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sudo apt-get install -y apt-transport-https ca-certificates gnupg curl
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# Add Google Cloud public key
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curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | sudo gpg --dearmor -o /usr/share/keyrings/cloud.google.gpg
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# Add Google Cloud SDK repo to apt sources
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echo "deb [signed-by=/usr/share/keyrings/cloud.google.gpg] https://packages.cloud.google.com/apt cloud-sdk main" | sudo tee /etc/apt/sources.list.d/google-cloud-sdk.list
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# Update and install the Google Cloud SDK
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sudo apt-get update && sudo apt-get install -y google-cloud-cli
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# Authenticate gcloud with the service account
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gcloud auth activate-service-account --key-file=/tmp/gcp-sa.json
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EOT
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}
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```
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> [!NOTE]
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> For additional Vertex AI configuration options (model selection, token limits, region overrides, etc.), see the [Claude Code Vertex AI documentation](https://docs.claude.com/en/docs/claude-code/google-vertex-ai).
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## Troubleshooting
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If you encounter any issues, check the log files in the `~/.claude-module` directory within your workspace for detailed information.
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```bash
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# Installation logs
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cat ~/.claude-module/install.log
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# Startup logs
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cat ~/.claude-module/agentapi-start.log
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# Pre/post install script logs
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cat ~/.claude-module/pre_install.log
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cat ~/.claude-module/post_install.log
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```
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> [!NOTE]
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> To use tasks with Claude Code, you must provide an `anthropic_api_key` or `claude_code_oauth_token`.
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> The `workdir` variable is required and specifies the directory where Claude Code will run.
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## References
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- [Claude Code Documentation](https://docs.anthropic.com/en/docs/agents-and-tools/claude-code/overview)
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- [AgentAPI Documentation](https://github.com/coder/agentapi)
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- [Coder AI Agents Guide](https://coder.com/docs/tutorials/ai-agents)
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