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3653e5893f
* feat(terraform): close key/team schema gaps, fix team read envelope, add import support * feat(terraform): add fallback resource/data source and key/team block resources * feat(terraform): add access group and unified access group resources and data sources * feat(terraform): add guardrail and prompt resources and data sources * feat(terraform): add agent and search tool resources and data sources * feat(terraform): add user and budget resources and data sources * feat(terraform): add tag and project resources and data sources * docs(terraform): changelog and readme for parity additions * feat(terraform): add data sources for keys, teams, models, organizations, and mcp servers * fix(terraform): key update 400 on empty budget_duration, key info envelope, config-supplied key * fix(terraform): hash raw keys to SHA-256 tokens in key lookup URLs and block resource IDs
169 lines
5.6 KiB
Markdown
169 lines
5.6 KiB
Markdown
# litellm_team Resource
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Manages a team configuration in LiteLLM. Teams allow you to group users and manage their access to models and usage limits.
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## Example Usage
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### Basic Team Configuration
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```hcl
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resource "litellm_team" "engineering" {
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team_alias = "engineering-team"
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models = ["gpt-4-proxy", "claude-2"]
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max_budget = 1000.0
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}
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```
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### Team with Comprehensive Configuration
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```hcl
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resource "litellm_team" "advanced_team" {
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team_alias = "ai-research-team"
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organization_id = "org_123456"
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models = ["gpt-4-proxy", "claude-2", "gpt-3.5-turbo"]
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# Budget and rate limiting
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max_budget = 1000.0
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soft_budget = 800.0
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budget_duration = "1mo"
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tpm_limit = 500000
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rpm_limit = 5000
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blocked = false
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# Who gets paged when spend crosses soft_budget
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soft_budget_alerting_emails = ["finops@example.com"]
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# Tags for spend tracking and tag-based routing
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tags = ["team:ai-research", "environment:production"]
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# Team member permissions
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team_member_permissions = [
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"create_key",
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"delete_key",
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"view_spend",
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"edit_team"
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]
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# Metadata for organization
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metadata = {
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department = "Engineering"
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project = "AI Research"
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cost_center = "R&D-001"
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}
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}
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```
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### Team with Model Dependencies
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```hcl
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# First create models
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resource "litellm_model" "gpt4" {
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model_name = "gpt-4-proxy"
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custom_llm_provider = "openai"
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base_model = "gpt-4"
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model_api_key = var.openai_api_key
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}
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resource "litellm_model" "claude" {
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model_name = "claude-proxy"
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custom_llm_provider = "anthropic"
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base_model = "claude-3-sonnet-20240229"
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model_api_key = var.anthropic_api_key
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}
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# Then create team with access to these models
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resource "litellm_team" "model_dependent_team" {
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team_alias = "model-users"
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models = [
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litellm_model.gpt4.model_name,
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litellm_model.claude.model_name
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]
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max_budget = 500.0
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budget_duration = "1mo"
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team_member_permissions = [
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"view_spend"
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]
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}
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```
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## Argument Reference
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The following arguments are supported:
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* `team_alias` - (Required) A human-readable identifier for the team.
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* `organization_id` - (Optional) The ID of the organization this team belongs to.
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* `models` - (Optional) List of model names that this team can access.
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* `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.
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* `tags` - (Optional) List of tags applied to the team, used for [spend tracking](https://docs.litellm.ai/docs/proxy/enterprise#tracking-spend-for-custom-tags) and [tag-based routing](https://docs.litellm.ai/docs/proxy/tag_routing).
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* `blocked` - (Optional) Whether the team is blocked from making requests. Default is `false`.
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* `tpm_limit` - (Optional) Team-wide tokens per minute limit.
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* `rpm_limit` - (Optional) Team-wide requests per minute limit.
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* `max_budget` - (Optional) Maximum budget allocated to the team.
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* `soft_budget` - (Optional) Spend threshold at which the proxy sends a soft budget alert without blocking requests.
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* `soft_budget_alerting_emails` - (Optional) List of email addresses notified when the team's spend crosses `soft_budget`.
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* `budget_duration` - (Optional) Duration for the budget cycle. Valid values are:
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* `daily`
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* `weekly`
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* `monthly`
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* `yearly`
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* `team_member_permissions` - (Optional) List of permissions granted to team members. This controls what actions team members can perform within the team context.
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* `model_aliases` - (Optional) Map of alias names to model names, letting the team call models under stable alias names.
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* `guardrails` - (Optional) List of guardrails applied to every request made by this team.
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* `prompts` - (Optional) List of prompt IDs the team is allowed to use.
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* `team_member_budget` - (Optional) Budget (in USD) applied to each individual team member.
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* `team_member_budget_duration` - (Optional) Reset cycle for the per-member budget (e.g. `30d`, `1mo`).
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* `team_member_rpm_limit` - (Optional) Requests per minute limit applied to each individual team member.
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* `team_member_tpm_limit` - (Optional) Tokens per minute limit applied to each individual team member.
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* `team_member_key_duration` - (Optional) Lifetime for keys created by team members (e.g. `1d`, `1w`).
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* `model_rpm_limit` - (Optional) Map of model name to requests per minute limit for that model.
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* `model_tpm_limit` - (Optional) Map of model name to tokens per minute limit for that model.
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* `allowed_passthrough_routes` - (Optional) List of pass-through routes this team is allowed to call.
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* `rpm_limit_type` - (Optional) How the RPM limit is enforced: `guaranteed_throughput` or `best_effort_throughput`. Changing this forces a new team to be created.
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* `tpm_limit_type` - (Optional) How the TPM limit is enforced: `guaranteed_throughput` or `best_effort_throughput`. Changing this forces a new team to be created.
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## Attribute Reference
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In addition to the arguments above, the following attributes are exported:
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* `id` - The unique identifier for the team.
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## Import
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Teams can be imported using the team ID:
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```shell
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terraform import litellm_team.engineering <team-id>
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```
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Note: The team ID is generated when the team is created and is different from the `team_alias`.
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## Note on Team Members
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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.
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