feat: add support for AWS Bedrock and Google Vertex AI in Claude Code module
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@ -124,51 +124,26 @@ AWS account with Bedrock access, Claude models enabled in Bedrock console, appro
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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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resource "coder_env" "aws_access_key" {
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agent_id = coder_agent.example.id
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name = "AWS_ACCESS_KEY_ID"
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value = "your-access-key-id"
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}
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resource "coder_env" "aws_secret_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 = "your-secret-access-key"
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sensitive = true
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}
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# Option 2: Using Bedrock API key (simpler)
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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 = "your-bedrock-api-key"
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sensitive = 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 = "3.0.1"
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agent_id = coder_agent.example.id
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workdir = "/home/coder/project"
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model = "us.anthropic.claude-3-7-sonnet-20250219-v1:0"
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source = "registry.coder.com/coder/claude-code/coder"
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version = "3.0.1"
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agent_id = coder_agent.example.id
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workdir = "/home/coder/project"
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model = "anthropic.claude-3-5-sonnet-20241022-v2:0" # Bedrock model ID
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use_bedrock = true
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aws_region = "us-west-2"
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# Option 1: Using AWS credentials
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aws_access_key_id = "AKIA..."
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aws_secret_access_key = "your-secret-key"
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# Option 2: Using Bedrock API key (alternative to AWS credentials)
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# aws_bearer_token_bedrock = "your-bedrock-api-key"
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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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> For model IDs and available models in your region, refer to the [AWS Bedrock documentation](https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html). 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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@ -179,33 +154,28 @@ GCP project with Vertex AI API enabled, Claude models enabled through Model Gard
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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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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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module "claude-code" {
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source = "registry.coder.com/coder/claude-code/coder"
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version = "3.0.1"
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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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source = "registry.coder.com/coder/claude-code/coder"
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version = "3.0.1"
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agent_id = coder_agent.example.id
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workdir = "/home/coder/project"
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model = "claude-3-5-sonnet@20241022" # Vertex AI model name
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use_vertex = true
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vertex_project_id = "your-gcp-project-id"
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vertex_region = "us-central1" # or "global"
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}
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```
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**Authentication**
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Vertex AI uses Google Cloud authentication. Ensure your workspace has access to Google Cloud credentials through one of these methods:
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1. **Application Default Credentials (ADC)**: Set up through `gcloud auth application-default login`
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2. **Service Account**: Configure `GOOGLE_APPLICATION_CREDENTIALS` environment variable
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3. **Workload Identity**: For GKE deployments
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Refer to the [Google Cloud authentication documentation](https://cloud.google.com/docs/authentication/application-default-credentials) for detailed setup instructions.
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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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@ -192,6 +192,57 @@ variable "claude_md_path" {
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default = "$HOME/.claude/CLAUDE.md"
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}
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variable "use_bedrock" {
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type = bool
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description = "Whether to use AWS Bedrock for Claude Code."
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default = false
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}
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variable "aws_region" {
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type = string
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description = "AWS region for Bedrock."
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default = ""
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}
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variable "aws_access_key_id" {
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type = string
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description = "AWS access key ID for Bedrock authentication."
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default = ""
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sensitive = true
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}
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variable "aws_secret_access_key" {
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type = string
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description = "AWS secret access key for Bedrock authentication."
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default = ""
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sensitive = true
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}
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variable "aws_bearer_token_bedrock" {
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type = string
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description = "AWS Bedrock API key for simplified authentication."
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default = ""
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sensitive = true
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}
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variable "use_vertex" {
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type = bool
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description = "Whether to use Google Vertex AI for Claude Code."
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default = false
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}
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variable "vertex_project_id" {
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type = string
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description = "Google Cloud project ID for Vertex AI."
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default = ""
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}
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variable "vertex_region" {
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type = string
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description = "Google Cloud region for Vertex AI."
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default = "global"
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}
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resource "coder_env" "claude_code_md_path" {
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count = var.claude_md_path == "" ? 0 : 1
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@ -221,6 +272,61 @@ resource "coder_env" "claude_api_key" {
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name = "CLAUDE_API_KEY"
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value = var.claude_api_key
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}
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resource "coder_env" "use_bedrock" {
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count = var.use_bedrock ? 1 : 0
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agent_id = var.agent_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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count = var.use_bedrock && var.aws_region != "" ? 1 : 0
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agent_id = var.agent_id
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name = "AWS_REGION"
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value = var.aws_region
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}
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resource "coder_env" "aws_access_key_id" {
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count = var.use_bedrock && var.aws_access_key_id != "" ? 1 : 0
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agent_id = var.agent_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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count = var.use_bedrock && var.aws_secret_access_key != "" ? 1 : 0
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agent_id = var.agent_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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resource "coder_env" "aws_bearer_token_bedrock" {
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count = var.use_bedrock && var.aws_bearer_token_bedrock != "" ? 1 : 0
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agent_id = var.agent_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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resource "coder_env" "use_vertex" {
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count = var.use_vertex ? 1 : 0
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agent_id = var.agent_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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count = var.use_vertex && var.vertex_project_id != "" ? 1 : 0
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agent_id = var.agent_id
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name = "ANTHROPIC_VERTEX_PROJECT_ID"
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value = var.vertex_project_id
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}
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resource "coder_env" "vertex_region" {
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count = var.use_vertex ? 1 : 0
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agent_id = var.agent_id
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name = "CLOUD_ML_REGION"
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value = var.vertex_region
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}
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locals {
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# we have to trim the slash because otherwise coder exp mcp will
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