litellm_team Resource

Manages a team configuration in LiteLLM. Teams allow you to group users and manage their access to models and usage limits.

Example Usage

Basic Team Configuration

hcl

resource "litellm_team" "engineering" {
  team_alias = "engineering-team"
  models     = ["gpt-4-proxy", "claude-2"]
  max_budget = 1000.0
}

Team with Comprehensive Configuration

hcl

resource "litellm_team" "advanced_team" {
  team_alias      = "ai-research-team"
  organization_id = "org_123456"
  models          = ["gpt-4-proxy", "claude-2", "gpt-3.5-turbo"]

  # Budget and rate limiting
  max_budget      = 1000.0
  soft_budget     = 800.0
  budget_duration = "1mo"
  tpm_limit       = 500000
  rpm_limit       = 5000
  blocked         = false

  # Who gets paged when spend crosses soft_budget
  soft_budget_alerting_emails = ["[email protected]"]

  # Tags for spend tracking and tag-based routing
  tags = ["team:ai-research", "environment:production"]

  # Team member permissions
  team_member_permissions = [
    "create_key",
    "delete_key",
    "view_spend",
    "edit_team"
  ]

  # Metadata for organization
  metadata = {
    department = "Engineering"
    project    = "AI Research"
    cost_center = "R&D-001"
  }
}

Team with Model Dependencies

hcl

# First create models
resource "litellm_model" "gpt4" {
  model_name          = "gpt-4-proxy"
  custom_llm_provider = "openai"
  base_model          = "gpt-4"
  model_api_key       = var.openai_api_key
}

resource "litellm_model" "claude" {
  model_name          = "claude-proxy"
  custom_llm_provider = "anthropic"
  base_model          = "claude-3-sonnet-20240229"
  model_api_key       = var.anthropic_api_key
}

# Then create team with access to these models
resource "litellm_team" "model_dependent_team" {
  team_alias = "model-users"
  models = [
    litellm_model.gpt4.model_name,
    litellm_model.claude.model_name
  ]
  
  max_budget      = 500.0
  budget_duration = "1mo"
  
  team_member_permissions = [
    "view_spend"
  ]
}

Argument Reference

The following arguments are supported:

team_alias - (Required) A human-readable identifier for the team.
organization_id - (Optional) The ID of the organization this team belongs to.
models - (Optional) List of model names that this team can access.
metadata - (Optional) A map of string metadata key-value pairs associated with the team. tags and soft_budget_alerting_emails are stored by the proxy under metadata but are managed through their own attributes below, not this map.
tags - (Optional) List of tags applied to the team, used for spend tracking and tag-based routing.
blocked - (Optional) Whether the team is blocked from making requests. Default is false.
tpm_limit - (Optional) Team-wide tokens per minute limit.
rpm_limit - (Optional) Team-wide requests per minute limit.
max_budget - (Optional) Maximum budget allocated to the team.
soft_budget - (Optional) Spend threshold at which the proxy sends a soft budget alert without blocking requests.
soft_budget_alerting_emails - (Optional) List of email addresses notified when the team's spend crosses soft_budget.
budget_duration - (Optional) Duration for the budget cycle. Valid values are:
- daily
- weekly
- monthly
- yearly
team_member_permissions - (Optional) List of permissions granted to team members. This controls what actions team members can perform within the team context.

Attribute Reference

In addition to the arguments above, the following attributes are exported:

id - The unique identifier for the team.

Import

Teams can be imported using the team ID:

shell

terraform import litellm_team.engineering <team-id>

Note: The team ID is generated when the team is created and is different from the team_alias.

Note on Team Members

Team members are managed through the separate litellm_team_member resource. This allows for more granular control over team membership and permissions. See the litellm_team_member resource documentation for details on managing team members.