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(feat) Organizations: allow org admins to create teams on UI + (feat) IBM Guardrails (#15924)
* fix(oldteams.tsx): allow org admin to create team on ui * fix(oldteams.tsx): show org admin a dropdown of allowed orgs for team creation * docs(access_control.md): cleanup doc * feat(ibm_guardrails/): initial commit adding support for ibm guardrails on litellm allows user to use self-hosted ibm guardrails * feat(ibm_detector.py): working detector * docs(ibm_guardrails.md): document new ibm guardrails * fix: fix linting errors
This commit is contained in:
Krish Dholakia
@@ -1,25 +1,325 @@
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import Image from '@theme/IdealImage';
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# Role-based Access Controls (RBAC)
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Role-based access control (RBAC) is based on Organizations, Teams and Internal User Roles
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<Image img={require('../../img/litellm_user_heirarchy.png')} style={{ width: '100%', maxWidth: '4000px' }} />
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- `Organizations` are the top-level entities that contain Teams.
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- `Team` - A Team is a collection of multiple `Internal Users`
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- `Internal Users` - users that can create keys, make LLM API calls, view usage on LiteLLM. Users can be on multiple teams.
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- `Roles` define the permissions of an `Internal User`
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- `Virtual Keys` - Keys are used for authentication to the LiteLLM API. Keys are tied to a `Internal User` and `Team`
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## Roles
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| Role Type | Role Name | Permissions |
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|-----------|-----------|-------------|
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| **Admin** | `proxy_admin` | Admin over the platform |
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| | `proxy_admin_viewer` | Can login, view all keys, view all spend. **Cannot** create keys/delete keys/add new users |
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| **Organization** | `org_admin` | Admin over the organization. Can create teams and users within their organization |
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| **Internal User** | `internal_user` | Can login, view/create/delete their own keys, view their spend. **Cannot** add new users |
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| | `internal_user_viewer` | Can login, view their own keys, view their own spend. **Cannot** create/delete keys, add new users |
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## User Roles
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LiteLLM has two types of roles:
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1. **Global Proxy Roles** - Platform-wide roles that apply across all organizations and teams
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2. **Organization/Team Specific Roles** - Roles scoped to specific organizations or teams (**Premium Feature**)
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### Global Proxy Roles
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| Role Name | Permissions |
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|-----------|-------------|
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| `proxy_admin` | Admin over the entire platform. Full control over all organizations, teams, and users |
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| `proxy_admin_viewer` | Can login, view all keys, view all spend across the platform. **Cannot** create keys/delete keys/add new users |
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| `internal_user` | Can login, view/create (when allowed by team-specific permissions)/delete their own keys, view their spend. **Cannot** add new users |
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| `internal_user_viewer` | ⚠️ **DEPRECATED** - Use team/org specific roles instead. Can login, view their own keys, view their own spend. **Cannot** create/delete keys, add new users |
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### Organization/Team Specific Roles
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| Role Name | Permissions |
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|-----------|-------------|
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| `org_admin` | Admin over a specific organization. Can create teams and users within their organization ✨ **Premium Feature** |
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| `team_admin` | Admin over a specific team. Can manage team members, update team settings, and create keys for their team. ✨ **Premium Feature** |
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## What Can Each Role Do?
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Here's what each role can actually do. Think of it like levels of access.
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---
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## Global Proxy Roles
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These roles apply across the entire LiteLLM platform, regardless of organization or team boundaries.
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### Proxy Admin - Full Access
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The proxy admin controls everything. They're like the owner of the whole platform.
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**What they can do:**
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- Create and manage all organizations
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- Create and manage all teams (across all organizations)
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- Create and manage all users
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- View all spend and usage across the platform
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- Create and delete keys for anyone
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- Update team budgets, rate limits, and models
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- Manage team members and assign roles
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**Who should be a proxy admin:** Only the people running the LiteLLM instance.
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---
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### Proxy Admin Viewer - Platform-Wide Read Access
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The proxy admin viewer can see everything across the platform but cannot make changes.
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**What they can do:**
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- View all organizations, teams, and users
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- View all spend and usage across the platform
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- View all API keys
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- Login to the admin dashboard
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**What they cannot do:**
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- Create or delete keys
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- Add or remove users
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- Modify budgets, rate limits, or settings
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- Make any changes to the platform
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**Who should be a proxy admin viewer:** Finance teams, auditors, or stakeholders who need platform-wide visibility without modification rights.
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---
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### Internal User
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An internal user can create API keys (when allowed by team-specific permissions) and make calls. They see their own stuff only. They can become a team admin or org admin if they are assigned the respective roles.
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**What they can do:**
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- Create API keys for themselves
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- Delete their own API keys
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- View their own spend and usage
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- Make API calls using their keys
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**Who should be an internal user:** Anyone who needs UI access for team/org specific operations **OR** for developers you plan to give multiple keys to.
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---
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### Internal User Viewer - Read-Only Access
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:::warning DEPRECATED
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This role is deprecated in favor of team/org specific roles. Use `org_admin` or `team_admin` roles for better granular control over user permissions within organizations and teams.
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:::
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An internal user viewer can view their own information but cannot create or delete keys.
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**What they can do:**
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- View their own API keys
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- View their own spend and usage
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- Login to see their dashboard
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**What they cannot do:**
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- Create or delete API keys
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- Make changes to any settings
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- Create teams or add users
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- View other people's information
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**Who should be an internal user viewer (deprecated):** Consider using team/org specific roles instead for better access control.
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---
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## Organization/Team Specific Roles
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:::info
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Organization/Team specific roles are premium features. You need to be a LiteLLM Enterprise user to use them. [Get a 7 day trial here](https://www.litellm.ai/#trial).
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:::
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These roles are scoped to specific organizations or teams. Users with these roles can only manage resources within their assigned organization or team.
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### Org Admin - Organization Level Access
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An org admin manages one or more organizations. They can create teams within their organization but can't touch other organizations.
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**What they can do:**
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- Create teams within their organization
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- Add users to teams in their organization
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- View spend for their organization
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- Create keys for users in their organization
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**What they cannot do:**
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- Create or manage other organizations
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- Modify org budgets / rate limits
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- Modify org allowed models (e.g. adding a proxy-level model to the org)
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**Who should be an org admin:** Department leads or managers who need to manage multiple teams.
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---
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### Team Admin - Team Level Access
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✨ **This is a Premium Feature**
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A team admin manages a specific team. They're like a team lead who can add people, update settings, but only for their team.
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**What they can do:**
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- Add or remove team members from their team
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- Update team members' budgets and rate limits within the team
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- Change team settings (budget, rate limits, models)
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- Create and delete keys for team members
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- Onboard a [team-BYOK](./team_model_add) model to LiteLLM (e.g. onboarding a team's finetuned model)
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- Configure [team member permissions](#team-member-permissions) to control what regular team members can do
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**What they cannot do:**
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- Create new teams
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- Modify team's budget / rate limits
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- Add/remove global proxy models to their team
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**Who should be a team admin:** Team leads who need to manage their team's API access without bothering IT.
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:::info How to create a team admin
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You need to be a LiteLLM Enterprise user to assign team admins. [Get a 7 day trial here](https://www.litellm.ai/#trial).
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```shell
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curl -X POST 'http://0.0.0.0:4000/team/member_add' \
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-H 'Authorization: Bearer sk-1234' \
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-H 'Content-Type: application/json' \
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-d '{"team_id": "team-123", "member": {"role": "admin", "user_id": "user@company.com"}}'
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```
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:::
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---
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## Team Member Permissions
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✨ **This is a Premium Feature**
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Team member permissions allow you to control what regular team members (with role=`user`) can do with API keys in their team. By default, team members can only view key information, but you can grant them additional permissions to create, update, or delete keys.
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### How It Works
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- **Applies to**: Team members with role=`user` (not team admins or org admins)
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- **Scope**: Permissions only apply to keys belonging to their team
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- **Configuration**: Set at the team level using `team_member_permissions`
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- **Override**: Team admins and org admins always have full permissions regardless of these settings
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### Available Permissions
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| Permission | Method | Description |
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|-----------|--------|-------------|
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| `/key/info` | GET | View information about virtual keys in the team |
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| `/key/health` | GET | Check health status of virtual keys in the team |
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| `/key/list` | GET | List all virtual keys belonging to the team |
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| `/key/generate` | POST | Create new virtual keys for the team |
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| `/key/service-account/generate` | POST | Create service account keys (not tied to a specific user) for the team |
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| `/key/update` | POST | Modify existing virtual keys in the team |
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| `/key/delete` | POST | Delete virtual keys belonging to the team |
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| `/key/regenerate` | POST | Regenerate virtual keys in the team |
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| `/key/block` | POST | Block virtual keys in the team |
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| `/key/unblock` | POST | Unblock virtual keys in the team |
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### Default Permissions
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By default, team members can only:
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- `/key/info` - View key information
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- `/key/health` - Check key health
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### Common Permission Scenarios
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**Read-only access** (default):
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```json
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["/key/info", "/key/health"]
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```
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**Allow key creation but not deletion**:
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```json
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["/key/info", "/key/health", "/key/generate", "/key/update"]
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```
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**Full key management**:
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```json
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["/key/info", "/key/health", "/key/generate", "/key/update", "/key/delete", "/key/regenerate", "/key/block", "/key/unblock", "/key/list"]
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```
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### How to Configure Team Member Permissions
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#### View Current Permissions
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```shell
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curl --location 'http://0.0.0.0:4000/team/permissions_list?team_id=team-123' \
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--header 'Authorization: Bearer sk-1234'
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```
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Expected Response:
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```json
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{
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"team_id": "team-123",
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"team_member_permissions": ["/key/info", "/key/health"],
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"all_available_permissions": ["/key/generate", "/key/update", "/key/delete", ...]
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}
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```
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#### Update Team Member Permissions
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```shell
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curl --location 'http://0.0.0.0:4000/team/update' \
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--header 'Authorization: Bearer sk-1234' \
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--header 'Content-Type: application/json' \
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--data '{
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"team_id": "team-123",
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"team_member_permissions": ["/key/info", "/key/health", "/key/generate", "/key/update"]
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}'
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```
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This allows team members to:
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- View key information
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- Create new keys
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- Update existing keys
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- But NOT delete keys
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### Who Can Configure These Permissions?
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- **Proxy Admin**: Can configure permissions for any team
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- **Org Admin**: Can configure permissions for teams in their organization
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- **Team Admin**: Can configure permissions for their own team
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---
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## Quick Comparison
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Here's the quick version:
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### Global Proxy Roles
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| Action | Proxy Admin | Proxy Admin Viewer | Internal User | Internal User Viewer ⚠️ (Deprecated) |
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|--------|-------------|-------------------|---------------|-------------------------------------|
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| Create organizations | ✅ | ❌ | ❌ | ❌ |
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| Create teams | ✅ | ❌ | ❌ | ❌ |
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| Manage all teams | ✅ | ❌ | ❌ | ❌ |
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| Create/delete any keys | ✅ | ❌ | ❌ | ❌ |
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| Create/delete own keys | ✅ | ❌ | ✅ | ❌ |
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| View all platform spend | ✅ | ✅ | ❌ | ❌ |
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| View own spend | ✅ | ✅ | ✅ | ✅ |
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| View all keys | ✅ | ✅ | ❌ | ❌ |
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| View own keys | ✅ | ✅ | ✅ | ✅ |
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| Add/remove users | ✅ | ❌ | ❌ | ❌ |
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> **Note:** The `internal_user_viewer` role is deprecated. Use team/org specific roles for better granular access control.
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### Organization/Team Specific Roles
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| Action | Org Admin | Team Admin |
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|--------|-----------|------------|
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| Create teams (in their org) | ✅ | ❌ |
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| Manage teams in their org | ✅ | ❌ |
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| Manage their specific team | ✅ | ✅ |
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| Add/remove team members | ✅ (in their org) | ✅ (their team only) |
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| Update team budgets | ✅ (in their org) | ✅ (their team only) |
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| Create keys for team members | ✅ (in their org) | ✅ (their team only) |
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| View organization spend | ✅ (their org) | ❌ |
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| View team spend | ✅ (in their org) | ✅ (their team) |
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| Create organizations | ❌ | ❌ |
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| View all platform spend | ❌ | ❌ |
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## Onboarding Organizations
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✨ **This is a Premium Feature**
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### 1. Creating a new Organization
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Any user with role=`proxy_admin` can create a new organization
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@@ -124,18 +424,79 @@ Expected Response
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```
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### `Organization Admin` - Add an `Internal User`
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### 4. `Organization Admin` - Add a Team Admin
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The organization admin will use the virtual key created in [step 2](#2-adding-an-org_admin-to-an-organization) to add an Internal User to the `engineering_team` Team.
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✨ **This is a Premium Feature**
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- We will assign role=`internal_user` so the user can create Virtual Keys for themselves
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The organization admin can now add a team admin who will manage the `engineering_team`.
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- We assign role=`admin` to make them a team admin for this specific team
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- `team_id` is from [step 3](#3-organization-admin---create-a-team)
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```shell
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curl -X POST 'http://0.0.0.0:4000/team/member_add' \
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-H 'Authorization: Bearer sk-1234' \
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-H 'Authorization: Bearer sk-7shH8TGMAofR4zQpAAo6kQ' \
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-H 'Content-Type: application/json' \
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-d '{"team_id": "01044ee8-441b-45f4-be7d-c70e002722d8", "member": {"role": "internal_user", "user_id": "krrish@berri.ai"}}'
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-d '{"team_id": "01044ee8-441b-45f4-be7d-c70e002722d8", "member": {"role": "admin", "user_id": "john@company.com"}}'
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```
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Now `john@company.com` is a team admin. They can manage the `engineering_team` - add members, update budgets, create keys - but they can't touch other teams.
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Create a Virtual Key for the team admin:
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|
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```shell
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curl --location 'http://0.0.0.0:4000/key/generate' \
|
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--header 'Authorization: Bearer sk-7shH8TGMAofR4zQpAAo6kQ' \
|
||||
--header 'Content-Type: application/json' \
|
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--data '{"user_id": "john@company.com"}'
|
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```
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Expected Response:
|
||||
|
||||
```json
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{
|
||||
"models": [],
|
||||
"user_id": "john@company.com",
|
||||
"key": "sk-TeamAdminKey123",
|
||||
"key_name": "sk-...Key123"
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||||
}
|
||||
```
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||||
|
||||
### 5. `Team Admin` - Add Team Members
|
||||
|
||||
Now the team admin can use their key to add team members without needing to ask the org admin.
|
||||
|
||||
```shell
|
||||
curl -X POST 'http://0.0.0.0:4000/team/member_add' \
|
||||
-H 'Authorization: Bearer sk-TeamAdminKey123' \
|
||||
-H 'Content-Type: application/json' \
|
||||
-d '{"team_id": "01044ee8-441b-45f4-be7d-c70e002722d8", "member": {"role": "user", "user_id": "krrish@berri.ai"}}'
|
||||
```
|
||||
|
||||
The team admin can also create keys for their team members:
|
||||
|
||||
```shell
|
||||
curl --location 'http://0.0.0.0:4000/key/generate' \
|
||||
--header 'Authorization: Bearer sk-TeamAdminKey123' \
|
||||
--header 'Content-Type: application/json' \
|
||||
--data '{
|
||||
"user_id": "krrish@berri.ai",
|
||||
"team_id": "01044ee8-441b-45f4-be7d-c70e002722d8"
|
||||
}'
|
||||
```
|
||||
|
||||
### 6. `Team Admin` - Update Team Settings
|
||||
|
||||
The team admin can update team budgets and rate limits:
|
||||
|
||||
```shell
|
||||
curl --location 'http://0.0.0.0:4000/team/update' \
|
||||
--header 'Authorization: Bearer sk-TeamAdminKey123' \
|
||||
--header 'Content-Type: application/json' \
|
||||
--data '{
|
||||
"team_id": "01044ee8-441b-45f4-be7d-c70e002722d8",
|
||||
"max_budget": 100,
|
||||
"rpm_limit": 1000
|
||||
}'
|
||||
```
|
||||
|
||||
|
||||
226
docs/my-website/docs/proxy/guardrails/ibm_guardrails.md
Normal file
226
docs/my-website/docs/proxy/guardrails/ibm_guardrails.md
Normal file
@@ -0,0 +1,226 @@
|
||||
import Tabs from '@theme/Tabs';
|
||||
import TabItem from '@theme/TabItem';
|
||||
|
||||
# IBM Guardrails
|
||||
|
||||
LiteLLM works with IBM's FMS Guardrails for content safety. You can use it to detect jailbreaks, PII, hate speech, and more.
|
||||
|
||||
## What it does
|
||||
|
||||
IBM Guardrails analyzes text and tells you if it contains things you want to avoid. It gives each detection a score. Higher scores mean it's more confident.
|
||||
|
||||
You can run these checks:
|
||||
- Before sending to the LLM (on user input)
|
||||
- After getting LLM response (on output)
|
||||
- During the call (parallel to LLM)
|
||||
|
||||
## Quick Start
|
||||
|
||||
### 1. Add to your config.yaml
|
||||
|
||||
```yaml
|
||||
model_list:
|
||||
- model_name: gpt-3.5-turbo
|
||||
litellm_params:
|
||||
model: openai/gpt-3.5-turbo
|
||||
api_key: os.environ/OPENAI_API_KEY
|
||||
|
||||
guardrails:
|
||||
- guardrail_name: ibm-jailbreak-detector
|
||||
litellm_params:
|
||||
guardrail: ibm_guardrails
|
||||
mode: pre_call
|
||||
auth_token: os.environ/IBM_GUARDRAILS_AUTH_TOKEN
|
||||
base_url: "https://your-detector-server.com"
|
||||
detector_id: "jailbreak-detector"
|
||||
is_detector_server: true
|
||||
default_on: true
|
||||
optional_params:
|
||||
score_threshold: 0.8
|
||||
block_on_detection: true
|
||||
```
|
||||
|
||||
### 2. Set your auth token
|
||||
|
||||
```bash
|
||||
export IBM_GUARDRAILS_AUTH_TOKEN="your-token"
|
||||
```
|
||||
|
||||
### 3. Start the proxy
|
||||
|
||||
```shell
|
||||
litellm --config config.yaml --detailed_debug
|
||||
```
|
||||
|
||||
### 4. Make a request
|
||||
|
||||
```shell
|
||||
curl -i http://localhost:4000/v1/chat/completions \
|
||||
-H "Content-Type: application/json" \
|
||||
-H "Authorization: Bearer sk-1234" \
|
||||
-d '{
|
||||
"model": "gpt-3.5-turbo",
|
||||
"messages": [
|
||||
{"role": "user", "content": "Hello, how are you?"}
|
||||
],
|
||||
"guardrails": ["ibm-jailbreak-detector"]
|
||||
}'
|
||||
```
|
||||
|
||||
## Configuration
|
||||
|
||||
### Required params
|
||||
|
||||
- `guardrail` - str - Set to `ibm_guardrails`
|
||||
- `auth_token` - str - Your IBM Guardrails auth token. Can use `os.environ/IBM_GUARDRAILS_AUTH_TOKEN`
|
||||
- `base_url` - str - URL of your IBM Guardrails server
|
||||
- `detector_id` - str - Which detector to use (e.g., "jailbreak-detector", "pii-detector")
|
||||
|
||||
### Optional params
|
||||
|
||||
- `mode` - str or list[str] - When to run. Options: `pre_call`, `post_call`, `during_call`. Default: `pre_call`
|
||||
- `default_on` - bool - Run automatically without specifying in request. Default: `false`
|
||||
- `is_detector_server` - bool - `true` for detector server, `false` for orchestrator. Default: `true`
|
||||
- `verify_ssl` - bool - Whether to verify SSL certificates. Default: `true`
|
||||
|
||||
### optional_params
|
||||
|
||||
These go under `optional_params`:
|
||||
|
||||
- `detector_params` - dict - Parameters to pass to your detector
|
||||
- `score_threshold` - float - Only count detections above this score (0.0 to 1.0)
|
||||
- `block_on_detection` - bool - Block the request when violations found. Default: `true`
|
||||
|
||||
## Server Types
|
||||
|
||||
IBM Guardrails has two APIs you can use:
|
||||
|
||||
### Detector Server (recommended)
|
||||
|
||||
The simpler one. Sends all messages at once.
|
||||
|
||||
```yaml
|
||||
guardrails:
|
||||
- guardrail_name: ibm-detector
|
||||
litellm_params:
|
||||
guardrail: ibm_guardrails
|
||||
mode: pre_call
|
||||
auth_token: os.environ/IBM_GUARDRAILS_AUTH_TOKEN
|
||||
base_url: "https://your-detector-server.com"
|
||||
detector_id: "jailbreak-detector"
|
||||
is_detector_server: true # Use detector server
|
||||
```
|
||||
|
||||
### Orchestrator
|
||||
|
||||
If you're using the IBM FMS Guardrails Orchestrator, you can use this.
|
||||
|
||||
```yaml
|
||||
guardrails:
|
||||
- guardrail_name: ibm-orchestrator
|
||||
litellm_params:
|
||||
guardrail: ibm_guardrails
|
||||
mode: pre_call
|
||||
auth_token: os.environ/IBM_GUARDRAILS_AUTH_TOKEN
|
||||
base_url: "https://your-orchestrator-server.com"
|
||||
detector_id: "jailbreak-detector"
|
||||
is_detector_server: false # Use orchestrator
|
||||
```
|
||||
|
||||
## Examples
|
||||
|
||||
### Check for jailbreaks on input
|
||||
|
||||
```yaml
|
||||
guardrails:
|
||||
- guardrail_name: jailbreak-check
|
||||
litellm_params:
|
||||
guardrail: ibm_guardrails
|
||||
mode: pre_call
|
||||
auth_token: os.environ/IBM_GUARDRAILS_AUTH_TOKEN
|
||||
base_url: "https://your-detector-server.com"
|
||||
detector_id: "jailbreak-detector"
|
||||
is_detector_server: true
|
||||
default_on: true
|
||||
optional_params:
|
||||
score_threshold: 0.8
|
||||
```
|
||||
|
||||
### Check for PII in responses
|
||||
|
||||
```yaml
|
||||
guardrails:
|
||||
- guardrail_name: pii-check
|
||||
litellm_params:
|
||||
guardrail: ibm_guardrails
|
||||
mode: post_call
|
||||
auth_token: os.environ/IBM_GUARDRAILS_AUTH_TOKEN
|
||||
base_url: "https://your-detector-server.com"
|
||||
detector_id: "pii-detector"
|
||||
is_detector_server: true
|
||||
optional_params:
|
||||
score_threshold: 0.5 # Lower threshold for PII
|
||||
block_on_detection: true
|
||||
```
|
||||
|
||||
### Run multiple detectors
|
||||
|
||||
```yaml
|
||||
guardrails:
|
||||
- guardrail_name: jailbreak-check
|
||||
litellm_params:
|
||||
guardrail: ibm_guardrails
|
||||
mode: pre_call
|
||||
auth_token: os.environ/IBM_GUARDRAILS_AUTH_TOKEN
|
||||
base_url: "https://your-detector-server.com"
|
||||
detector_id: "jailbreak-detector"
|
||||
is_detector_server: true
|
||||
|
||||
- guardrail_name: pii-check
|
||||
litellm_params:
|
||||
guardrail: ibm_guardrails
|
||||
mode: post_call
|
||||
auth_token: os.environ/IBM_GUARDRAILS_AUTH_TOKEN
|
||||
base_url: "https://your-detector-server.com"
|
||||
detector_id: "pii-detector"
|
||||
is_detector_server: true
|
||||
```
|
||||
|
||||
Then in your request:
|
||||
|
||||
```shell
|
||||
curl -i http://localhost:4000/v1/chat/completions \
|
||||
-H "Content-Type: application/json" \
|
||||
-H "Authorization: Bearer sk-1234" \
|
||||
-d '{
|
||||
"model": "gpt-3.5-turbo",
|
||||
"messages": [{"role": "user", "content": "Hello"}],
|
||||
"guardrails": ["jailbreak-check", "pii-check"]
|
||||
}'
|
||||
```
|
||||
|
||||
## How detection works
|
||||
|
||||
When IBM Guardrails finds something, it returns details about what it found:
|
||||
|
||||
```json
|
||||
{
|
||||
"start": 0,
|
||||
"end": 31,
|
||||
"text": "You are now in Do Anything Mode",
|
||||
"detection_type": "jailbreak",
|
||||
"score": 0.858
|
||||
}
|
||||
```
|
||||
|
||||
- `score` - How confident it is (0.0 to 1.0)
|
||||
- `text` - The specific text that triggered it
|
||||
- `detection_type` - What kind of violation
|
||||
|
||||
If the score is above your `score_threshold`, the request gets blocked (if `block_on_detection` is true).
|
||||
|
||||
## Further Reading
|
||||
|
||||
- [Control Guardrails per API Key](./quick_start#-control-guardrails-per-api-key)
|
||||
- [IBM FMS Guardrails on GitHub](https://github.com/foundation-model-stack/fms-guardrails-orchestr8)
|
||||
|
||||
@@ -11,3 +11,9 @@ LiteLLM supports a hierarchy of users, teams, organizations, and budgets.
|
||||
- Teams can have multiple users. [API Reference](https://litellm-api.up.railway.app/#/team%20management)
|
||||
- Users can have multiple keys, and be on multiple teams. [API Reference](https://litellm-api.up.railway.app/#/budget%20management)
|
||||
- Keys can belong to either a team or a user. [API Reference](https://litellm-api.up.railway.app/#/end-user%20management)
|
||||
|
||||
|
||||
:::info
|
||||
|
||||
See [Access Control](./access_control) for more details on roles and permissions.
|
||||
:::
|
||||
@@ -37,6 +37,7 @@ const sidebars = {
|
||||
"proxy/guardrails/azure_content_guardrail",
|
||||
"proxy/guardrails/bedrock",
|
||||
"proxy/guardrails/enkryptai",
|
||||
"proxy/guardrails/ibm_guardrails",
|
||||
"proxy/guardrails/grayswan",
|
||||
"proxy/guardrails/lasso_security",
|
||||
"proxy/guardrails/guardrails_ai",
|
||||
|
||||
@@ -0,0 +1,199 @@
|
||||
# IBM Guardrails Detector Integration
|
||||
|
||||
This integration provides support for IBM's FMS Guardrails detectors in LiteLLM. It supports both direct detector server calls and calls via the FMS Guardrails Orchestrator.
|
||||
|
||||
## Features
|
||||
|
||||
- Support for IBM Detector Server API (`/api/v1/text/contents`)
|
||||
- Support for FMS Guardrails Orchestrator API (`/api/v2/text/detection/content`)
|
||||
- Configurable score thresholds for filtering detections
|
||||
- SSL verification control
|
||||
- Batch processing for detector server (multiple messages at once)
|
||||
- Pre-call, post-call, and during-call modes
|
||||
- Detailed error messages with detection scores and types
|
||||
|
||||
## Configuration
|
||||
|
||||
### Required Parameters
|
||||
|
||||
- `auth_token`: Authorization bearer token for IBM Guardrails API
|
||||
- `base_url`: Base URL of the detector server or orchestrator
|
||||
- `detector_id`: Name of the detector (e.g., "jailbreak-detector", "pii-detector")
|
||||
|
||||
### Optional Parameters
|
||||
|
||||
- `is_detector_server` (default: `true`): Whether to use detector server (true) or orchestrator (false)
|
||||
- `verify_ssl` (default: `true`): Whether to verify SSL certificates
|
||||
- `detector_params` (default: `{}`): Dictionary of parameters to pass to the detector
|
||||
- `score_threshold` (default: `None`): Minimum score (0.0-1.0) to consider a detection as a violation
|
||||
- `block_on_detection` (default: `true`): Whether to block requests when detections are found
|
||||
|
||||
## Usage Examples
|
||||
|
||||
### Example 1: Detector Server (Pre-call)
|
||||
|
||||
```yaml
|
||||
guardrails:
|
||||
- guardrail_name: "ibm-jailbreak-detector"
|
||||
litellm_params:
|
||||
guardrail: ibm_guardrails
|
||||
mode: pre_call
|
||||
default_on: true
|
||||
auth_token: os.environ/IBM_GUARDRAILS_AUTH_TOKEN
|
||||
base_url: "https://your-detector-server.com"
|
||||
detector_id: "jailbreak-detector"
|
||||
is_detector_server: true
|
||||
optional_params:
|
||||
score_threshold: 0.8
|
||||
block_on_detection: true
|
||||
```
|
||||
|
||||
### Example 2: FMS Orchestrator (Post-call)
|
||||
|
||||
```yaml
|
||||
guardrails:
|
||||
- guardrail_name: "ibm-content-safety"
|
||||
litellm_params:
|
||||
guardrail: ibm_guardrails
|
||||
mode: post_call
|
||||
default_on: true
|
||||
auth_token: os.environ/IBM_GUARDRAILS_AUTH_TOKEN
|
||||
base_url: "https://your-orchestrator-server.com"
|
||||
detector_id: "jailbreak-detector"
|
||||
is_detector_server: false
|
||||
```
|
||||
|
||||
### Example 3: Python Usage
|
||||
|
||||
```python
|
||||
from litellm.proxy.guardrails.guardrail_hooks.ibm_guardrails import IBMGuardrailDetector
|
||||
|
||||
# Initialize the guardrail
|
||||
guardrail = IBMGuardrailDetector(
|
||||
guardrail_name="ibm-detector",
|
||||
auth_token="your-auth-token",
|
||||
base_url="https://your-detector-server.com",
|
||||
detector_id="jailbreak-detector",
|
||||
is_detector_server=True,
|
||||
score_threshold=0.8,
|
||||
event_hook="pre_call"
|
||||
)
|
||||
```
|
||||
|
||||
## API Endpoints
|
||||
|
||||
### Detector Server Endpoint
|
||||
- **URL**: `{base_url}/api/v1/text/contents`
|
||||
- **Method**: POST
|
||||
- **Headers**:
|
||||
- `Authorization: Bearer {auth_token}`
|
||||
- `detector-id: {detector_id}`
|
||||
- `content-type: application/json`
|
||||
- **Body**:
|
||||
```json
|
||||
{
|
||||
"contents": ["text1", "text2"],
|
||||
"detector_params": {}
|
||||
}
|
||||
```
|
||||
|
||||
### Orchestrator Endpoint
|
||||
- **URL**: `{base_url}/api/v2/text/detection/content`
|
||||
- **Method**: POST
|
||||
- **Headers**:
|
||||
- `Authorization: Bearer {auth_token}`
|
||||
- `content-type: application/json`
|
||||
- **Body**:
|
||||
```json
|
||||
{
|
||||
"content": "text to analyze",
|
||||
"detectors": {
|
||||
"detector-id": {}
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
## Response Format
|
||||
|
||||
### Detector Server Response
|
||||
Returns a list of lists, where each top-level list corresponds to a message:
|
||||
|
||||
```json
|
||||
[
|
||||
[
|
||||
{
|
||||
"start": 0,
|
||||
"end": 31,
|
||||
"text": "You are now in Do Anything Mode",
|
||||
"detection": "single_label_classification",
|
||||
"detection_type": "jailbreak",
|
||||
"score": 0.8586854338645935,
|
||||
"evidences": [],
|
||||
"metadata": {}
|
||||
}
|
||||
],
|
||||
[]
|
||||
]
|
||||
```
|
||||
|
||||
### Orchestrator Response
|
||||
Returns a dictionary with a list of detections:
|
||||
|
||||
```json
|
||||
{
|
||||
"detections": [
|
||||
{
|
||||
"start": 0,
|
||||
"end": 31,
|
||||
"text": "You are now in Do Anything Mode",
|
||||
"detection": "single_label_classification",
|
||||
"detection_type": "jailbreak",
|
||||
"detector_id": "jailbreak-detector",
|
||||
"score": 0.8586854338645935
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
## Supported Event Hooks
|
||||
|
||||
- `pre_call`: Run guardrail before LLM API call (on input)
|
||||
- `post_call`: Run guardrail after LLM API call (on output)
|
||||
- `during_call`: Run guardrail in parallel with LLM API call (on input)
|
||||
|
||||
## Error Handling
|
||||
|
||||
When violations are detected and `block_on_detection` is `true`, the guardrail raises a `ValueError` with details:
|
||||
|
||||
```
|
||||
IBM Guardrail Detector failed: 1 violation(s) detected
|
||||
|
||||
Message 1:
|
||||
- JAILBREAK (score: 0.859)
|
||||
Text: 'You are now in Do Anything Mode'
|
||||
```
|
||||
|
||||
## References
|
||||
|
||||
- [IBM FMS Guardrails Documentation](https://github.com/foundation-model-stack/fms-guardrails-orchestr8)
|
||||
- [Detector API Gist](https://gist.github.com/RobGeada/fa886a6c723f06dee6becb583566d748)
|
||||
- [LiteLLM Guardrails Documentation](https://docs.litellm.ai/docs/proxy/guardrails)
|
||||
|
||||
## Environment Variables
|
||||
|
||||
- `IBM_GUARDRAILS_AUTH_TOKEN`: Default auth token if not specified in config
|
||||
|
||||
## Common Detector Types
|
||||
|
||||
- `jailbreak-detector`: Detects jailbreak attempts
|
||||
- `pii-detector`: Detects personally identifiable information
|
||||
- `toxicity-detector`: Detects toxic content
|
||||
- `prompt-injection-detector`: Detects prompt injection attacks
|
||||
|
||||
## Notes
|
||||
|
||||
- The detector server allows batch processing of multiple messages in a single request
|
||||
- The orchestrator processes one message at a time
|
||||
- Score thresholds can be adjusted per detector based on sensitivity requirements
|
||||
- SSL verification can be disabled for development/testing environments (not recommended for production)
|
||||
|
||||
@@ -0,0 +1,62 @@
|
||||
from typing import TYPE_CHECKING
|
||||
|
||||
from litellm.types.guardrails import SupportedGuardrailIntegrations
|
||||
|
||||
from .ibm_detector import IBMGuardrailDetector
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from litellm.types.guardrails import Guardrail, LitellmParams
|
||||
|
||||
|
||||
def initialize_guardrail(litellm_params: "LitellmParams", guardrail: "Guardrail"):
|
||||
import litellm
|
||||
|
||||
if not litellm_params.auth_token:
|
||||
raise ValueError("IBM Guardrails: auth_token is required")
|
||||
if not litellm_params.base_url:
|
||||
raise ValueError("IBM Guardrails: base_url is required")
|
||||
if not litellm_params.detector_id:
|
||||
raise ValueError("IBM Guardrails: detector_id is required")
|
||||
|
||||
guardrail_name = guardrail.get("guardrail_name")
|
||||
if not guardrail_name:
|
||||
raise ValueError("IBM Guardrails: guardrail_name is required")
|
||||
|
||||
# Get optional params
|
||||
detector_params = getattr(litellm_params, "detector_params", {})
|
||||
score_threshold = getattr(litellm_params, "score_threshold", None)
|
||||
block_on_detection = getattr(litellm_params, "block_on_detection", True)
|
||||
verify_ssl = getattr(litellm_params, "verify_ssl", True)
|
||||
is_detector_server = litellm_params.is_detector_server
|
||||
if is_detector_server is None:
|
||||
is_detector_server = True
|
||||
|
||||
ibm_guardrail = IBMGuardrailDetector(
|
||||
guardrail_name=guardrail_name,
|
||||
auth_token=litellm_params.auth_token,
|
||||
base_url=litellm_params.base_url,
|
||||
detector_id=litellm_params.detector_id,
|
||||
is_detector_server=is_detector_server,
|
||||
detector_params=detector_params,
|
||||
score_threshold=score_threshold,
|
||||
block_on_detection=block_on_detection,
|
||||
verify_ssl=verify_ssl,
|
||||
default_on=litellm_params.default_on,
|
||||
event_hook=litellm_params.mode,
|
||||
)
|
||||
|
||||
litellm.logging_callback_manager.add_litellm_callback(ibm_guardrail)
|
||||
return ibm_guardrail
|
||||
|
||||
|
||||
guardrail_initializer_registry = {
|
||||
SupportedGuardrailIntegrations.IBM_GUARDRAILS.value: initialize_guardrail,
|
||||
}
|
||||
|
||||
|
||||
guardrail_class_registry = {
|
||||
SupportedGuardrailIntegrations.IBM_GUARDRAILS.value: IBMGuardrailDetector,
|
||||
}
|
||||
|
||||
|
||||
__all__ = ["IBMGuardrailDetector", "initialize_guardrail"]
|
||||
@@ -0,0 +1,95 @@
|
||||
# Example LiteLLM Proxy configuration for IBM Guardrails Detector
|
||||
# Based on IBM's FMS Guardrails: https://github.com/foundation-model-stack/fms-guardrails-orchestr8
|
||||
|
||||
# Example 1: Using IBM Detector Server directly
|
||||
guardrails:
|
||||
- guardrail_name: "ibm-jailbreak-detector"
|
||||
litellm_params:
|
||||
guardrail: ibm_guardrails
|
||||
mode: pre_call # or post_call, during_call
|
||||
default_on: true
|
||||
auth_token: os.environ/IBM_GUARDRAILS_AUTH_TOKEN # or hardcoded token
|
||||
base_url: "https://your-detector-server.com" # Base URL of your detector server
|
||||
detector_id: "jailbreak-detector" # Name of the detector (e.g., jailbreak-detector, pii-detector)
|
||||
is_detector_server: true # true for detector server, false for orchestrator
|
||||
verify_ssl: true # Optional: whether to verify SSL certificates (default: true)
|
||||
optional_params:
|
||||
detector_params: {} # Optional: parameters to pass to the detector
|
||||
score_threshold: 0.8 # Optional: minimum score to consider a detection (0.0-1.0)
|
||||
block_on_detection: true # Optional: whether to block when violations found (default: true)
|
||||
|
||||
# Example 2: Using IBM FMS Guardrails Orchestrator
|
||||
- guardrail_name: "ibm-orchestrator-detector"
|
||||
litellm_params:
|
||||
guardrail: ibm_guardrails
|
||||
mode: post_call
|
||||
default_on: false
|
||||
auth_token: os.environ/IBM_GUARDRAILS_AUTH_TOKEN
|
||||
base_url: "https://your-orchestrator-server.com"
|
||||
detector_id: "jailbreak-detector"
|
||||
is_detector_server: false # Use orchestrator instead of detector server
|
||||
verify_ssl: true
|
||||
optional_params:
|
||||
detector_params:
|
||||
# Detector-specific parameters can go here
|
||||
some_param: "value"
|
||||
score_threshold: 0.7
|
||||
|
||||
# Example 3: Pre-call guardrail with custom threshold
|
||||
- guardrail_name: "ibm-pii-detector"
|
||||
litellm_params:
|
||||
guardrail: ibm_guardrails
|
||||
mode: pre_call
|
||||
default_on: true
|
||||
auth_token: os.environ/IBM_GUARDRAILS_AUTH_TOKEN
|
||||
base_url: "https://your-detector-server.com"
|
||||
detector_id: "pii-detector"
|
||||
is_detector_server: true
|
||||
optional_params:
|
||||
score_threshold: 0.5 # Lower threshold for PII detection
|
||||
block_on_detection: true
|
||||
|
||||
# Usage with LiteLLM Proxy:
|
||||
# 1. Set environment variable:
|
||||
# export IBM_GUARDRAILS_AUTH_TOKEN="your-auth-token"
|
||||
#
|
||||
# 2. Start the proxy:
|
||||
# litellm --config example_config.yaml
|
||||
#
|
||||
# 3. Make requests:
|
||||
# The guardrail will automatically run based on the 'mode' setting
|
||||
|
||||
# API Response formats:
|
||||
#
|
||||
# Detector Server Response (returns list of lists):
|
||||
# [
|
||||
# [ # First message
|
||||
# {
|
||||
# "start": 0,
|
||||
# "end": 31,
|
||||
# "text": "You are now in Do Anything Mode",
|
||||
# "detection": "single_label_classification",
|
||||
# "detection_type": "jailbreak",
|
||||
# "score": 0.8586854338645935,
|
||||
# "evidences": [],
|
||||
# "metadata": {}
|
||||
# }
|
||||
# ],
|
||||
# [] # Second message (benign, no detections)
|
||||
# ]
|
||||
#
|
||||
# Orchestrator Response:
|
||||
# {
|
||||
# "detections": [
|
||||
# {
|
||||
# "start": 0,
|
||||
# "end": 31,
|
||||
# "text": "You are now in Do Anything Mode",
|
||||
# "detection": "single_label_classification",
|
||||
# "detection_type": "jailbreak",
|
||||
# "detector_id": "jailbreak-detector",
|
||||
# "score": 0.8586854338645935
|
||||
# }
|
||||
# ]
|
||||
# }
|
||||
|
||||
@@ -0,0 +1,762 @@
|
||||
# +-------------------------------------------------------------+
|
||||
#
|
||||
# Use IBM Guardrails Detector for your LLM calls
|
||||
# Based on IBM's FMS Guardrails
|
||||
#
|
||||
# +-------------------------------------------------------------+
|
||||
|
||||
import os
|
||||
from datetime import datetime
|
||||
from typing import Any, AsyncGenerator, Dict, List, Literal, Optional, Union
|
||||
from urllib.parse import urlencode
|
||||
|
||||
import httpx
|
||||
|
||||
import litellm
|
||||
from litellm._logging import verbose_proxy_logger
|
||||
from litellm.caching.caching import DualCache
|
||||
from litellm.integrations.custom_guardrail import CustomGuardrail
|
||||
from litellm.llms.custom_httpx.http_handler import (
|
||||
get_async_httpx_client,
|
||||
httpxSpecialProvider,
|
||||
)
|
||||
from litellm.proxy._types import UserAPIKeyAuth
|
||||
from litellm.types.guardrails import GuardrailEventHooks
|
||||
from litellm.types.proxy.guardrails.guardrail_hooks.ibm import (
|
||||
IBMDetectorDetection,
|
||||
IBMDetectorResponseOrchestrator,
|
||||
)
|
||||
from litellm.types.utils import GuardrailStatus, ModelResponseStream
|
||||
|
||||
GUARDRAIL_NAME = "ibm_guardrails"
|
||||
|
||||
|
||||
class IBMGuardrailDetector(CustomGuardrail):
|
||||
def __init__(
|
||||
self,
|
||||
guardrail_name: str = "ibm_detector",
|
||||
auth_token: Optional[str] = None,
|
||||
base_url: Optional[str] = None,
|
||||
detector_id: Optional[str] = None,
|
||||
is_detector_server: bool = True,
|
||||
detector_params: Optional[Dict[str, Any]] = None,
|
||||
score_threshold: Optional[float] = None,
|
||||
block_on_detection: bool = True,
|
||||
verify_ssl: bool = True,
|
||||
**kwargs,
|
||||
):
|
||||
self.async_handler = get_async_httpx_client(
|
||||
llm_provider=httpxSpecialProvider.GuardrailCallback
|
||||
)
|
||||
|
||||
# Set API configuration
|
||||
self.auth_token = auth_token or os.getenv("IBM_GUARDRAILS_AUTH_TOKEN")
|
||||
if not self.auth_token:
|
||||
raise ValueError(
|
||||
"IBM Guardrails auth token is required. Set IBM_GUARDRAILS_AUTH_TOKEN environment variable or pass auth_token parameter."
|
||||
)
|
||||
|
||||
self.base_url = base_url
|
||||
if not self.base_url:
|
||||
raise ValueError(
|
||||
"IBM Guardrails base_url is required. Pass base_url parameter."
|
||||
)
|
||||
|
||||
self.detector_id = detector_id
|
||||
if not self.detector_id:
|
||||
raise ValueError(
|
||||
"IBM Guardrails detector_id is required. Pass detector_id parameter."
|
||||
)
|
||||
|
||||
self.is_detector_server = is_detector_server
|
||||
self.detector_params = detector_params or {}
|
||||
self.score_threshold = score_threshold
|
||||
self.block_on_detection = block_on_detection
|
||||
self.verify_ssl = verify_ssl
|
||||
|
||||
# Construct API URL based on server type
|
||||
if self.is_detector_server:
|
||||
self.api_url = f"{self.base_url}/api/v1/text/contents"
|
||||
else:
|
||||
self.api_url = f"{self.base_url}/api/v2/text/detection/content"
|
||||
|
||||
self.guardrail_name = guardrail_name
|
||||
self.guardrail_provider = "ibm_guardrails"
|
||||
|
||||
# store kwargs as optional_params
|
||||
self.optional_params = kwargs
|
||||
|
||||
# Set supported event hooks
|
||||
if "supported_event_hooks" not in kwargs:
|
||||
kwargs["supported_event_hooks"] = [
|
||||
GuardrailEventHooks.pre_call,
|
||||
GuardrailEventHooks.post_call,
|
||||
GuardrailEventHooks.during_call,
|
||||
]
|
||||
|
||||
super().__init__(guardrail_name=guardrail_name, **kwargs)
|
||||
|
||||
verbose_proxy_logger.debug(
|
||||
"IBM Guardrail Detector initialized with guardrail_name: %s, detector_id: %s, is_detector_server: %s",
|
||||
self.guardrail_name,
|
||||
self.detector_id,
|
||||
self.is_detector_server,
|
||||
)
|
||||
|
||||
async def _call_detector_server(
|
||||
self,
|
||||
contents: List[str],
|
||||
request_data: Optional[dict] = None,
|
||||
) -> List[List[IBMDetectorDetection]]:
|
||||
"""
|
||||
Call IBM Detector Server directly.
|
||||
|
||||
Args:
|
||||
contents: List of text strings to analyze
|
||||
request_data: Optional request data for logging purposes
|
||||
|
||||
Returns:
|
||||
List of lists where top-level list is per message in contents,
|
||||
sublists are individual detections on that message
|
||||
"""
|
||||
start_time = datetime.now()
|
||||
|
||||
payload = {"contents": contents, "detector_params": self.detector_params}
|
||||
|
||||
headers = {
|
||||
"Authorization": f"Bearer {self.auth_token}",
|
||||
"content-type": "application/json",
|
||||
}
|
||||
|
||||
query_params = {"detector_id": self.detector_id}
|
||||
|
||||
# update the api_url with the query params
|
||||
self.api_url = f"{self.api_url}?{urlencode(query_params)}"
|
||||
|
||||
verbose_proxy_logger.debug(
|
||||
"IBM Detector Server request to %s with payload: %s",
|
||||
self.api_url,
|
||||
payload,
|
||||
)
|
||||
|
||||
try:
|
||||
|
||||
response = await self.async_handler.post(
|
||||
url=self.api_url,
|
||||
json=payload,
|
||||
headers=headers,
|
||||
)
|
||||
response.raise_for_status()
|
||||
response_json: List[List[IBMDetectorDetection]] = response.json()
|
||||
|
||||
end_time = datetime.now()
|
||||
duration = (end_time - start_time).total_seconds()
|
||||
|
||||
# Add guardrail information to request trace
|
||||
if request_data:
|
||||
guardrail_status = self._determine_guardrail_status_detector_server(
|
||||
response_json
|
||||
)
|
||||
self.add_standard_logging_guardrail_information_to_request_data(
|
||||
guardrail_provider=self.guardrail_provider,
|
||||
guardrail_json_response={
|
||||
"detections": [
|
||||
[detection for detection in message_detections]
|
||||
for message_detections in response_json
|
||||
]
|
||||
},
|
||||
request_data=request_data,
|
||||
guardrail_status=guardrail_status,
|
||||
start_time=start_time.timestamp(),
|
||||
end_time=end_time.timestamp(),
|
||||
duration=duration,
|
||||
)
|
||||
|
||||
return response_json
|
||||
|
||||
except httpx.HTTPError as e:
|
||||
end_time = datetime.now()
|
||||
duration = (end_time - start_time).total_seconds()
|
||||
|
||||
verbose_proxy_logger.error("IBM Detector Server request failed: %s", str(e))
|
||||
|
||||
# Add guardrail information with failure status
|
||||
if request_data:
|
||||
self.add_standard_logging_guardrail_information_to_request_data(
|
||||
guardrail_provider=self.guardrail_provider,
|
||||
guardrail_json_response={"error": str(e)},
|
||||
request_data=request_data,
|
||||
guardrail_status="guardrail_failed_to_respond",
|
||||
start_time=start_time.timestamp(),
|
||||
end_time=end_time.timestamp(),
|
||||
duration=duration,
|
||||
)
|
||||
|
||||
raise
|
||||
|
||||
async def _call_orchestrator(
|
||||
self,
|
||||
content: str,
|
||||
request_data: Optional[dict] = None,
|
||||
) -> List[IBMDetectorDetection]:
|
||||
"""
|
||||
Call IBM FMS Guardrails Orchestrator.
|
||||
|
||||
Args:
|
||||
content: Text string to analyze
|
||||
request_data: Optional request data for logging purposes
|
||||
|
||||
Returns:
|
||||
List of detections
|
||||
"""
|
||||
start_time = datetime.now()
|
||||
|
||||
payload = {
|
||||
"content": content,
|
||||
"detectors": {self.detector_id: self.detector_params},
|
||||
}
|
||||
|
||||
headers = {
|
||||
"Authorization": f"Bearer {self.auth_token}",
|
||||
"content-type": "application/json",
|
||||
}
|
||||
|
||||
verbose_proxy_logger.debug(
|
||||
"IBM Orchestrator request to %s with payload: %s",
|
||||
self.api_url,
|
||||
payload,
|
||||
)
|
||||
|
||||
try:
|
||||
response = await self.async_handler.post(
|
||||
url=self.api_url,
|
||||
json=payload,
|
||||
headers=headers,
|
||||
)
|
||||
response.raise_for_status()
|
||||
response_json: IBMDetectorResponseOrchestrator = response.json()
|
||||
|
||||
end_time = datetime.now()
|
||||
duration = (end_time - start_time).total_seconds()
|
||||
|
||||
# Add guardrail information to request trace
|
||||
if request_data:
|
||||
guardrail_status = self._determine_guardrail_status_orchestrator(
|
||||
response_json
|
||||
)
|
||||
self.add_standard_logging_guardrail_information_to_request_data(
|
||||
guardrail_provider=self.guardrail_provider,
|
||||
guardrail_json_response=dict(response_json),
|
||||
request_data=request_data,
|
||||
guardrail_status=guardrail_status,
|
||||
start_time=start_time.timestamp(),
|
||||
end_time=end_time.timestamp(),
|
||||
duration=duration,
|
||||
)
|
||||
|
||||
return response_json.get("detections", [])
|
||||
|
||||
except httpx.HTTPError as e:
|
||||
end_time = datetime.now()
|
||||
duration = (end_time - start_time).total_seconds()
|
||||
|
||||
verbose_proxy_logger.error("IBM Orchestrator request failed: %s", str(e))
|
||||
|
||||
# Add guardrail information with failure status
|
||||
if request_data:
|
||||
self.add_standard_logging_guardrail_information_to_request_data(
|
||||
guardrail_provider=self.guardrail_provider,
|
||||
guardrail_json_response={"error": str(e)},
|
||||
request_data=request_data,
|
||||
guardrail_status="guardrail_failed_to_respond",
|
||||
start_time=start_time.timestamp(),
|
||||
end_time=end_time.timestamp(),
|
||||
duration=duration,
|
||||
)
|
||||
|
||||
raise
|
||||
|
||||
def _filter_detections_by_threshold(
|
||||
self, detections: List[IBMDetectorDetection]
|
||||
) -> List[IBMDetectorDetection]:
|
||||
"""
|
||||
Filter detections based on score threshold.
|
||||
|
||||
Args:
|
||||
detections: List of detections
|
||||
|
||||
Returns:
|
||||
Filtered list of detections that meet the threshold
|
||||
"""
|
||||
if self.score_threshold is None:
|
||||
return detections
|
||||
|
||||
return [
|
||||
detection
|
||||
for detection in detections
|
||||
if detection.get("score", 0.0) >= self.score_threshold
|
||||
]
|
||||
|
||||
def _determine_guardrail_status_detector_server(
|
||||
self, response_json: List[List[IBMDetectorDetection]]
|
||||
) -> GuardrailStatus:
|
||||
"""
|
||||
Determine the guardrail status based on IBM Detector Server response.
|
||||
|
||||
Returns:
|
||||
"success": Content allowed through with no violations
|
||||
"guardrail_intervened": Content blocked due to detections
|
||||
"guardrail_failed_to_respond": Technical error or API failure
|
||||
"""
|
||||
try:
|
||||
if not isinstance(response_json, list):
|
||||
return "guardrail_failed_to_respond"
|
||||
|
||||
# Check if any detections were found
|
||||
has_detections = False
|
||||
for message_detections in response_json:
|
||||
if message_detections:
|
||||
# Apply threshold filtering
|
||||
filtered = self._filter_detections_by_threshold(message_detections)
|
||||
if filtered:
|
||||
has_detections = True
|
||||
break
|
||||
|
||||
if has_detections:
|
||||
return "guardrail_intervened"
|
||||
|
||||
return "success"
|
||||
|
||||
except Exception as e:
|
||||
verbose_proxy_logger.error(
|
||||
"Error determining IBM Detector Server guardrail status: %s", str(e)
|
||||
)
|
||||
return "guardrail_failed_to_respond"
|
||||
|
||||
def _determine_guardrail_status_orchestrator(
|
||||
self, response_json: IBMDetectorResponseOrchestrator
|
||||
) -> GuardrailStatus:
|
||||
"""
|
||||
Determine the guardrail status based on IBM Orchestrator response.
|
||||
|
||||
Returns:
|
||||
"success": Content allowed through with no violations
|
||||
"guardrail_intervened": Content blocked due to detections
|
||||
"guardrail_failed_to_respond": Technical error or API failure
|
||||
"""
|
||||
try:
|
||||
if not isinstance(response_json, dict):
|
||||
return "guardrail_failed_to_respond"
|
||||
|
||||
detections = response_json.get("detections", [])
|
||||
# Apply threshold filtering
|
||||
filtered = self._filter_detections_by_threshold(detections)
|
||||
|
||||
if filtered:
|
||||
return "guardrail_intervened"
|
||||
|
||||
return "success"
|
||||
|
||||
except Exception as e:
|
||||
verbose_proxy_logger.error(
|
||||
"Error determining IBM Orchestrator guardrail status: %s", str(e)
|
||||
)
|
||||
return "guardrail_failed_to_respond"
|
||||
|
||||
def _create_error_message_detector_server(
|
||||
self, detections_list: List[List[IBMDetectorDetection]]
|
||||
) -> str:
|
||||
"""
|
||||
Create a detailed error message from detector server response.
|
||||
|
||||
Args:
|
||||
detections_list: List of lists of detections
|
||||
|
||||
Returns:
|
||||
Formatted error message string
|
||||
"""
|
||||
total_detections = 0
|
||||
error_message = "IBM Guardrail Detector failed:\n\n"
|
||||
|
||||
for idx, message_detections in enumerate(detections_list):
|
||||
filtered_detections = self._filter_detections_by_threshold(
|
||||
message_detections
|
||||
)
|
||||
if filtered_detections:
|
||||
error_message += f"Message {idx + 1}:\n"
|
||||
total_detections += len(filtered_detections)
|
||||
|
||||
for detection in filtered_detections:
|
||||
detection_type = detection.get("detection_type", "unknown")
|
||||
score = detection.get("score", 0.0)
|
||||
text = detection.get("text", "")
|
||||
error_message += (
|
||||
f" - {detection_type.upper()} (score: {score:.3f})\n"
|
||||
)
|
||||
error_message += f" Text: '{text}'\n"
|
||||
|
||||
error_message += "\n"
|
||||
|
||||
error_message = (
|
||||
f"IBM Guardrail Detector failed: {total_detections} violation(s) detected\n\n"
|
||||
+ error_message
|
||||
)
|
||||
return error_message.strip()
|
||||
|
||||
def _create_error_message_orchestrator(
|
||||
self, detections: List[IBMDetectorDetection]
|
||||
) -> str:
|
||||
"""
|
||||
Create a detailed error message from orchestrator response.
|
||||
|
||||
Args:
|
||||
detections: List of detections
|
||||
|
||||
Returns:
|
||||
Formatted error message string
|
||||
"""
|
||||
filtered_detections = self._filter_detections_by_threshold(detections)
|
||||
|
||||
error_message = f"IBM Guardrail Detector failed: {len(filtered_detections)} violation(s) detected\n\n"
|
||||
|
||||
for detection in filtered_detections:
|
||||
detection_type = detection.get("detection_type", "unknown")
|
||||
detector_id = detection.get("detector_id", self.detector_id)
|
||||
score = detection.get("score", 0.0)
|
||||
text = detection.get("text", "")
|
||||
|
||||
error_message += f"- {detection_type.upper()} (detector: {detector_id}, score: {score:.3f})\n"
|
||||
error_message += f" Text: '{text}'\n\n"
|
||||
|
||||
return error_message.strip()
|
||||
|
||||
async def async_pre_call_hook(
|
||||
self,
|
||||
user_api_key_dict: UserAPIKeyAuth,
|
||||
cache: DualCache,
|
||||
data: dict,
|
||||
call_type: Literal[
|
||||
"completion",
|
||||
"text_completion",
|
||||
"embeddings",
|
||||
"image_generation",
|
||||
"moderation",
|
||||
"audio_transcription",
|
||||
"pass_through_endpoint",
|
||||
"rerank",
|
||||
"mcp_call",
|
||||
"anthropic_messages",
|
||||
],
|
||||
) -> Union[Exception, str, dict, None]:
|
||||
"""
|
||||
Runs before the LLM API call
|
||||
Runs on only Input
|
||||
Use this if you want to MODIFY the input
|
||||
"""
|
||||
verbose_proxy_logger.debug("Running IBM Guardrail Detector pre-call hook")
|
||||
|
||||
from litellm.proxy.common_utils.callback_utils import (
|
||||
add_guardrail_to_applied_guardrails_header,
|
||||
)
|
||||
|
||||
event_type: GuardrailEventHooks = GuardrailEventHooks.pre_call
|
||||
if self.should_run_guardrail(data=data, event_type=event_type) is not True:
|
||||
return data
|
||||
|
||||
_messages = data.get("messages")
|
||||
if _messages:
|
||||
contents_to_check: List[str] = []
|
||||
for message in _messages:
|
||||
_content = message.get("content")
|
||||
if isinstance(_content, str):
|
||||
contents_to_check.append(_content)
|
||||
|
||||
if contents_to_check:
|
||||
if self.is_detector_server:
|
||||
# Call detector server with all contents at once
|
||||
result = await self._call_detector_server(
|
||||
contents=contents_to_check,
|
||||
request_data=data,
|
||||
)
|
||||
|
||||
verbose_proxy_logger.debug(
|
||||
"IBM Detector Server async_pre_call_hook result: %s", result
|
||||
)
|
||||
|
||||
# Check if any detections were found
|
||||
has_violations = False
|
||||
for message_detections in result:
|
||||
filtered = self._filter_detections_by_threshold(
|
||||
message_detections
|
||||
)
|
||||
if filtered:
|
||||
has_violations = True
|
||||
break
|
||||
|
||||
if has_violations and self.block_on_detection:
|
||||
error_message = self._create_error_message_detector_server(
|
||||
result
|
||||
)
|
||||
raise ValueError(error_message)
|
||||
|
||||
else:
|
||||
# Call orchestrator for each content separately
|
||||
for content in contents_to_check:
|
||||
orchestrator_result = await self._call_orchestrator(
|
||||
content=content,
|
||||
request_data=data,
|
||||
)
|
||||
|
||||
verbose_proxy_logger.debug(
|
||||
"IBM Orchestrator async_pre_call_hook result: %s",
|
||||
orchestrator_result,
|
||||
)
|
||||
|
||||
filtered = self._filter_detections_by_threshold(
|
||||
orchestrator_result
|
||||
)
|
||||
if filtered and self.block_on_detection:
|
||||
error_message = self._create_error_message_orchestrator(
|
||||
orchestrator_result
|
||||
)
|
||||
raise ValueError(error_message)
|
||||
|
||||
# Add guardrail to applied guardrails header
|
||||
add_guardrail_to_applied_guardrails_header(
|
||||
request_data=data, guardrail_name=self.guardrail_name
|
||||
)
|
||||
|
||||
return data
|
||||
|
||||
async def async_moderation_hook(
|
||||
self,
|
||||
data: dict,
|
||||
user_api_key_dict: UserAPIKeyAuth,
|
||||
call_type: Literal[
|
||||
"completion",
|
||||
"embeddings",
|
||||
"image_generation",
|
||||
"moderation",
|
||||
"audio_transcription",
|
||||
"responses",
|
||||
"mcp_call",
|
||||
"anthropic_messages",
|
||||
],
|
||||
):
|
||||
"""
|
||||
Runs in parallel to LLM API call
|
||||
Runs on only Input
|
||||
|
||||
This can NOT modify the input, only used to reject or accept a call before going to LLM API
|
||||
"""
|
||||
from litellm.proxy.common_utils.callback_utils import (
|
||||
add_guardrail_to_applied_guardrails_header,
|
||||
)
|
||||
|
||||
event_type: GuardrailEventHooks = GuardrailEventHooks.during_call
|
||||
if self.should_run_guardrail(data=data, event_type=event_type) is not True:
|
||||
return
|
||||
|
||||
_messages = data.get("messages")
|
||||
if _messages:
|
||||
contents_to_check: List[str] = []
|
||||
for message in _messages:
|
||||
_content = message.get("content")
|
||||
if isinstance(_content, str):
|
||||
contents_to_check.append(_content)
|
||||
|
||||
if contents_to_check:
|
||||
if self.is_detector_server:
|
||||
# Call detector server with all contents at once
|
||||
result = await self._call_detector_server(
|
||||
contents=contents_to_check,
|
||||
request_data=data,
|
||||
)
|
||||
|
||||
verbose_proxy_logger.debug(
|
||||
"IBM Detector Server async_moderation_hook result: %s", result
|
||||
)
|
||||
|
||||
# Check if any detections were found
|
||||
has_violations = False
|
||||
for message_detections in result:
|
||||
filtered = self._filter_detections_by_threshold(
|
||||
message_detections
|
||||
)
|
||||
if filtered:
|
||||
has_violations = True
|
||||
break
|
||||
|
||||
if has_violations and self.block_on_detection:
|
||||
error_message = self._create_error_message_detector_server(
|
||||
result
|
||||
)
|
||||
raise ValueError(error_message)
|
||||
|
||||
else:
|
||||
# Call orchestrator for each content separately
|
||||
for content in contents_to_check:
|
||||
orchestrator_result = await self._call_orchestrator(
|
||||
content=content,
|
||||
request_data=data,
|
||||
)
|
||||
|
||||
verbose_proxy_logger.debug(
|
||||
"IBM Orchestrator async_moderation_hook result: %s",
|
||||
orchestrator_result,
|
||||
)
|
||||
|
||||
filtered = self._filter_detections_by_threshold(
|
||||
orchestrator_result
|
||||
)
|
||||
if filtered and self.block_on_detection:
|
||||
error_message = self._create_error_message_orchestrator(
|
||||
orchestrator_result
|
||||
)
|
||||
raise ValueError(error_message)
|
||||
|
||||
# Add guardrail to applied guardrails header
|
||||
add_guardrail_to_applied_guardrails_header(
|
||||
request_data=data, guardrail_name=self.guardrail_name
|
||||
)
|
||||
|
||||
return data
|
||||
|
||||
async def async_post_call_success_hook(
|
||||
self,
|
||||
data: dict,
|
||||
user_api_key_dict: UserAPIKeyAuth,
|
||||
response,
|
||||
):
|
||||
"""
|
||||
Runs on response from LLM API call
|
||||
|
||||
It can be used to reject a response
|
||||
|
||||
Uses IBM Guardrails Detector to check the response for violations
|
||||
"""
|
||||
from litellm.proxy.common_utils.callback_utils import (
|
||||
add_guardrail_to_applied_guardrails_header,
|
||||
)
|
||||
from litellm.types.guardrails import GuardrailEventHooks
|
||||
|
||||
if (
|
||||
self.should_run_guardrail(
|
||||
data=data, event_type=GuardrailEventHooks.post_call
|
||||
)
|
||||
is not True
|
||||
):
|
||||
return
|
||||
|
||||
verbose_proxy_logger.debug(
|
||||
"async_post_call_success_hook response: %s", response
|
||||
)
|
||||
|
||||
# Check if the ModelResponse has text content in its choices
|
||||
# to avoid sending empty content to IBM Detector (e.g., during tool calls)
|
||||
if isinstance(response, litellm.ModelResponse):
|
||||
has_text_content = False
|
||||
for choice in response.choices:
|
||||
if isinstance(choice, litellm.Choices):
|
||||
if choice.message.content and isinstance(
|
||||
choice.message.content, str
|
||||
):
|
||||
has_text_content = True
|
||||
break
|
||||
|
||||
if not has_text_content:
|
||||
verbose_proxy_logger.warning(
|
||||
"IBM Guardrail Detector: not running guardrail. No output text in response"
|
||||
)
|
||||
return
|
||||
|
||||
contents_to_check: List[str] = []
|
||||
for choice in response.choices:
|
||||
if isinstance(choice, litellm.Choices):
|
||||
verbose_proxy_logger.debug(
|
||||
"async_post_call_success_hook choice: %s", choice
|
||||
)
|
||||
if choice.message.content and isinstance(
|
||||
choice.message.content, str
|
||||
):
|
||||
contents_to_check.append(choice.message.content)
|
||||
|
||||
if contents_to_check:
|
||||
if self.is_detector_server:
|
||||
# Call detector server with all contents at once
|
||||
result = await self._call_detector_server(
|
||||
contents=contents_to_check,
|
||||
request_data=data,
|
||||
)
|
||||
|
||||
verbose_proxy_logger.debug(
|
||||
"IBM Detector Server async_post_call_success_hook result: %s",
|
||||
result,
|
||||
)
|
||||
|
||||
# Check if any detections were found
|
||||
has_violations = False
|
||||
for message_detections in result:
|
||||
filtered = self._filter_detections_by_threshold(
|
||||
message_detections
|
||||
)
|
||||
if filtered:
|
||||
has_violations = True
|
||||
break
|
||||
|
||||
if has_violations and self.block_on_detection:
|
||||
error_message = self._create_error_message_detector_server(
|
||||
result
|
||||
)
|
||||
raise ValueError(error_message)
|
||||
|
||||
else:
|
||||
# Call orchestrator for each content separately
|
||||
for content in contents_to_check:
|
||||
orchestrator_result = await self._call_orchestrator(
|
||||
content=content,
|
||||
request_data=data,
|
||||
)
|
||||
|
||||
verbose_proxy_logger.debug(
|
||||
"IBM Orchestrator async_post_call_success_hook result: %s",
|
||||
orchestrator_result,
|
||||
)
|
||||
|
||||
filtered = self._filter_detections_by_threshold(
|
||||
orchestrator_result
|
||||
)
|
||||
if filtered and self.block_on_detection:
|
||||
error_message = self._create_error_message_orchestrator(
|
||||
orchestrator_result
|
||||
)
|
||||
raise ValueError(error_message)
|
||||
|
||||
# Add guardrail to applied guardrails header
|
||||
add_guardrail_to_applied_guardrails_header(
|
||||
request_data=data, guardrail_name=self.guardrail_name
|
||||
)
|
||||
|
||||
async def async_post_call_streaming_iterator_hook(
|
||||
self,
|
||||
user_api_key_dict: UserAPIKeyAuth,
|
||||
response: Any,
|
||||
request_data: dict,
|
||||
) -> AsyncGenerator[ModelResponseStream, None]:
|
||||
"""
|
||||
Passes the entire stream to the guardrail
|
||||
|
||||
This is useful for guardrails that need to see the entire response, such as PII masking.
|
||||
|
||||
Triggered by mode: 'post_call'
|
||||
"""
|
||||
async for item in response:
|
||||
yield item
|
||||
|
||||
@staticmethod
|
||||
def get_config_model():
|
||||
from litellm.types.proxy.guardrails.guardrail_hooks.ibm import (
|
||||
IBMDetectorGuardrailConfigModel,
|
||||
)
|
||||
|
||||
return IBMDetectorGuardrailConfigModel
|
||||
@@ -11,6 +11,9 @@ from litellm.types.proxy.guardrails.guardrail_hooks.enkryptai import (
|
||||
from litellm.types.proxy.guardrails.guardrail_hooks.grayswan import (
|
||||
GraySwanGuardrailConfigModel,
|
||||
)
|
||||
from litellm.types.proxy.guardrails.guardrail_hooks.ibm import (
|
||||
IBMGuardrailsBaseConfigModel,
|
||||
)
|
||||
|
||||
"""
|
||||
Pydantic object defining how to set guardrails on litellm proxy
|
||||
@@ -48,6 +51,7 @@ class SupportedGuardrailIntegrations(Enum):
|
||||
TOOL_PERMISSION = "tool_permission"
|
||||
JAVELIN = "javelin"
|
||||
ENKRYPTAI = "enkryptai"
|
||||
IBM_GUARDRAILS = "ibm_guardrails"
|
||||
|
||||
|
||||
class Role(Enum):
|
||||
@@ -532,6 +536,7 @@ class LitellmParams(
|
||||
JavelinGuardrailConfigModel,
|
||||
BaseLitellmParams,
|
||||
EnkryptAIGuardrailConfigs,
|
||||
IBMGuardrailsBaseConfigModel,
|
||||
):
|
||||
guardrail: str = Field(description="The type of guardrail integration to use")
|
||||
mode: Union[str, List[str], Mode] = Field(
|
||||
|
||||
@@ -0,0 +1,21 @@
|
||||
from .base import IBMGuardrailsBaseConfigModel
|
||||
from .ibm_detector import (
|
||||
IBMDetectorDetection,
|
||||
IBMDetectorGuardrailConfigModel,
|
||||
IBMDetectorOptionalParams,
|
||||
IBMDetectorRequestBodyDetectorServer,
|
||||
IBMDetectorRequestBodyOrchestrator,
|
||||
IBMDetectorResponseDetectorServer,
|
||||
IBMDetectorResponseOrchestrator,
|
||||
)
|
||||
|
||||
__all__ = [
|
||||
"IBMGuardrailsBaseConfigModel",
|
||||
"IBMDetectorGuardrailConfigModel",
|
||||
"IBMDetectorOptionalParams",
|
||||
"IBMDetectorRequestBodyDetectorServer",
|
||||
"IBMDetectorRequestBodyOrchestrator",
|
||||
"IBMDetectorResponseDetectorServer",
|
||||
"IBMDetectorResponseOrchestrator",
|
||||
"IBMDetectorDetection",
|
||||
]
|
||||
32
litellm/types/proxy/guardrails/guardrail_hooks/ibm/base.py
Normal file
32
litellm/types/proxy/guardrails/guardrail_hooks/ibm/base.py
Normal file
@@ -0,0 +1,32 @@
|
||||
from typing import Optional
|
||||
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
|
||||
class IBMGuardrailsBaseConfigModel(BaseModel):
|
||||
"""Base configuration parameters for IBM Guardrails"""
|
||||
|
||||
auth_token: Optional[str] = Field(
|
||||
default=None,
|
||||
description="Authorization bearer token for IBM Guardrails API. Reads from IBM_GUARDRAILS_AUTH_TOKEN env var if None.",
|
||||
)
|
||||
|
||||
base_url: Optional[str] = Field(
|
||||
default=None,
|
||||
description="Base URL for the IBM Guardrails server",
|
||||
)
|
||||
|
||||
detector_id: Optional[str] = Field(
|
||||
default=None,
|
||||
description="Name of the detector inside the server (e.g., 'jailbreak-detector')",
|
||||
)
|
||||
|
||||
is_detector_server: Optional[bool] = Field(
|
||||
default=True,
|
||||
description="Boolean flag to determine if calling a detector server (True) or the FMS Orchestrator (False). Defaults to True.",
|
||||
)
|
||||
|
||||
verify_ssl: Optional[bool] = Field(
|
||||
default=True,
|
||||
description="Whether to verify SSL certificates. Defaults to True.",
|
||||
)
|
||||
@@ -0,0 +1,87 @@
|
||||
from typing import Any, Dict, List, Optional
|
||||
|
||||
from pydantic import BaseModel, Field
|
||||
from typing_extensions import TypedDict
|
||||
|
||||
from ..base import GuardrailConfigModel
|
||||
from .base import IBMGuardrailsBaseConfigModel
|
||||
|
||||
# TypedDicts for IBM Detector API Request/Response Structure
|
||||
|
||||
|
||||
class IBMDetectorRequestBodyDetectorServer(TypedDict):
|
||||
"""Request body for calling IBM Detector Server directly"""
|
||||
|
||||
contents: List[str]
|
||||
detector_params: Dict[str, Any]
|
||||
|
||||
|
||||
class IBMDetectorRequestBodyOrchestrator(TypedDict):
|
||||
"""Request body for calling IBM Detector via FMS Guardrails Orchestrator"""
|
||||
|
||||
content: str
|
||||
detectors: Dict[str, Dict[str, Any]]
|
||||
|
||||
|
||||
class IBMDetectorDetection(TypedDict, total=False):
|
||||
"""Individual detection from IBM Detector"""
|
||||
|
||||
start: int
|
||||
end: int
|
||||
text: str
|
||||
detection: str
|
||||
detection_type: str
|
||||
score: float
|
||||
evidences: List[Any]
|
||||
metadata: Dict[str, Any]
|
||||
detector_id: Optional[str] # Only present in orchestrator response
|
||||
|
||||
|
||||
class IBMDetectorResponseDetectorServer(TypedDict):
|
||||
"""Response from IBM Detector Server (returns list of lists)"""
|
||||
|
||||
detections: List[List[IBMDetectorDetection]]
|
||||
|
||||
|
||||
class IBMDetectorResponseOrchestrator(TypedDict):
|
||||
"""Response from IBM FMS Guardrails Orchestrator"""
|
||||
|
||||
detections: List[IBMDetectorDetection]
|
||||
|
||||
|
||||
# Pydantic Config Models
|
||||
|
||||
|
||||
class IBMDetectorOptionalParams(BaseModel):
|
||||
"""Optional parameters for IBM Detector guardrail"""
|
||||
|
||||
detector_params: Optional[Dict[str, Any]] = Field(
|
||||
default_factory=lambda: {},
|
||||
description="Dictionary of arguments to pass to the detector. Can be set per-request or hard-coded at guardrail config time.",
|
||||
)
|
||||
|
||||
score_threshold: Optional[float] = Field(
|
||||
default=None,
|
||||
description="Minimum score threshold to consider a detection as a violation (0.0 to 1.0). If set, detections below this threshold will be ignored.",
|
||||
)
|
||||
|
||||
block_on_detection: Optional[bool] = Field(
|
||||
default=True,
|
||||
description="Whether to block requests when detections are found. Defaults to True.",
|
||||
)
|
||||
|
||||
|
||||
class IBMDetectorGuardrailConfigModel(
|
||||
IBMGuardrailsBaseConfigModel,
|
||||
GuardrailConfigModel[IBMDetectorOptionalParams],
|
||||
):
|
||||
"""Configuration model for IBM Detector guardrail"""
|
||||
|
||||
optional_params: Optional[IBMDetectorOptionalParams] = Field(
|
||||
default_factory=IBMDetectorOptionalParams,
|
||||
description="Optional parameters for the IBM Detector guardrail",
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def ui_friendly_name() -> str:
|
||||
return "IBM Guardrails Detector"
|
||||
357
scripts/mock_ibm_guardrails_server.py
Normal file
357
scripts/mock_ibm_guardrails_server.py
Normal file
@@ -0,0 +1,357 @@
|
||||
"""
|
||||
Mock FastAPI server for IBM FMS Guardrails Orchestrator Detector API.
|
||||
|
||||
This server implements the Detector API endpoints for testing purposes.
|
||||
Based on: https://foundation-model-stack.github.io/fms-guardrails-orchestrator/
|
||||
|
||||
Usage:
|
||||
python scripts/mock_ibm_guardrails_server.py
|
||||
|
||||
The server will run on http://localhost:8001 by default.
|
||||
"""
|
||||
|
||||
import uuid
|
||||
from typing import Any, Dict, List, Optional
|
||||
|
||||
import uvicorn
|
||||
from fastapi import FastAPI, Header, HTTPException, status
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
app = FastAPI(
|
||||
title="IBM FMS Guardrails Orchestrator Mock",
|
||||
description="Mock server for testing IBM Guardrails Detector API",
|
||||
version="1.0.0",
|
||||
)
|
||||
|
||||
|
||||
# Request Models
|
||||
class DetectorParams(BaseModel):
|
||||
"""Parameters specific to the detector."""
|
||||
|
||||
threshold: Optional[float] = Field(None, ge=0.0, le=1.0)
|
||||
custom_param: Optional[str] = None
|
||||
|
||||
|
||||
class TextDetectionRequest(BaseModel):
|
||||
"""Request model for text detection."""
|
||||
|
||||
contents: List[str] = Field(..., description="Text content to analyze")
|
||||
detector_params: Optional[DetectorParams] = None
|
||||
|
||||
|
||||
class TextGenerationDetectionRequest(BaseModel):
|
||||
"""Request model for text generation detection."""
|
||||
|
||||
detector_id: str = Field(..., description="ID of the detector to use")
|
||||
prompt: str = Field(..., description="Input prompt")
|
||||
generated_text: str = Field(..., description="Generated text to analyze")
|
||||
detector_params: Optional[DetectorParams] = None
|
||||
|
||||
|
||||
class ContextDetectionRequest(BaseModel):
|
||||
"""Request model for detection with context."""
|
||||
|
||||
detector_id: str = Field(..., description="ID of the detector to use")
|
||||
content: str = Field(..., description="Text content to analyze")
|
||||
context: Optional[Dict[str, Any]] = Field(None, description="Additional context")
|
||||
detector_params: Optional[DetectorParams] = None
|
||||
|
||||
|
||||
# Response Models
|
||||
class Detection(BaseModel):
|
||||
"""Individual detection result."""
|
||||
|
||||
detection_type: str = Field(..., description="Type of detection")
|
||||
detection: bool = Field(..., description="Whether content was detected as harmful")
|
||||
score: float = Field(..., ge=0.0, le=1.0, description="Detection confidence score")
|
||||
start: Optional[int] = Field(None, description="Start position in text")
|
||||
end: Optional[int] = Field(None, description="End position in text")
|
||||
text: Optional[str] = Field(None, description="Detected text segment")
|
||||
evidence: Optional[List[str]] = Field(None, description="Supporting evidence")
|
||||
|
||||
|
||||
class DetectionResponse(BaseModel):
|
||||
"""Response model for detection results."""
|
||||
|
||||
detections: List[Detection] = Field(..., description="List of detections")
|
||||
detection_id: str = Field(..., description="Unique ID for this detection request")
|
||||
|
||||
|
||||
# Mock detector configurations
|
||||
MOCK_DETECTORS = {
|
||||
"hate": {
|
||||
"name": "Hate Speech Detector",
|
||||
"triggers": ["hate", "offensive", "discriminatory", "slur"],
|
||||
"default_score": 0.85,
|
||||
},
|
||||
"pii": {
|
||||
"name": "PII Detector",
|
||||
"triggers": ["email", "ssn", "credit card", "phone number", "address"],
|
||||
"default_score": 0.92,
|
||||
},
|
||||
"toxicity": {
|
||||
"name": "Toxicity Detector",
|
||||
"triggers": ["toxic", "abusive", "profanity", "insult"],
|
||||
"default_score": 0.78,
|
||||
},
|
||||
"jailbreak": {
|
||||
"name": "Jailbreak Detector",
|
||||
"triggers": ["ignore instructions", "override", "bypass", "jailbreak"],
|
||||
"default_score": 0.88,
|
||||
},
|
||||
"prompt_injection": {
|
||||
"name": "Prompt Injection Detector",
|
||||
"triggers": ["ignore previous", "new instructions", "system prompt"],
|
||||
"default_score": 0.90,
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
def simulate_detection(
|
||||
detector_id: str, content: str, detector_params: Optional[DetectorParams] = None
|
||||
) -> List[Detection]:
|
||||
"""
|
||||
Simulate detection logic based on detector type and content.
|
||||
|
||||
Args:
|
||||
detector_id: ID of the detector to simulate
|
||||
content: Text content to analyze
|
||||
detector_params: Optional detector parameters
|
||||
|
||||
Returns:
|
||||
List of Detection objects
|
||||
"""
|
||||
detections = []
|
||||
content_lower = " ".join(c for c in content).lower()
|
||||
|
||||
# Get detector config
|
||||
detector_config = MOCK_DETECTORS.get(detector_id)
|
||||
if not detector_config:
|
||||
# Unknown detector - return no detections
|
||||
return detections
|
||||
|
||||
# Check for triggers in content
|
||||
for trigger in detector_config["triggers"]:
|
||||
if trigger in content_lower:
|
||||
# Calculate score (use threshold if provided, otherwise default)
|
||||
base_score = detector_config["default_score"]
|
||||
threshold = (
|
||||
detector_params.threshold
|
||||
if detector_params and detector_params.threshold
|
||||
else None
|
||||
)
|
||||
|
||||
# Adjust score slightly based on content length (longer content = slightly lower confidence)
|
||||
score_adjustment = max(0, min(0.1, len(content) / 10000))
|
||||
score = max(0.0, min(1.0, base_score - score_adjustment))
|
||||
|
||||
# Find position of trigger
|
||||
start_pos = content_lower.find(trigger)
|
||||
end_pos = start_pos + len(trigger)
|
||||
|
||||
detection = Detection(
|
||||
detection_type=detector_id,
|
||||
detection=threshold is None or score >= threshold,
|
||||
score=score,
|
||||
start=start_pos,
|
||||
end=end_pos,
|
||||
text=content[start_pos:end_pos] if start_pos >= 0 else None,
|
||||
evidence=[f"Found trigger word: {trigger}"],
|
||||
)
|
||||
detections.append(detection)
|
||||
|
||||
# If no triggers found, return a negative detection
|
||||
if not detections:
|
||||
detections.append(
|
||||
Detection(
|
||||
detection_type=detector_id,
|
||||
detection=False,
|
||||
score=0.05, # Low score for clean content
|
||||
)
|
||||
)
|
||||
|
||||
return detections
|
||||
|
||||
|
||||
# Authentication middleware
|
||||
def verify_auth_token(authorization: Optional[str] = Header(None)) -> bool:
|
||||
"""
|
||||
Verify the authentication token.
|
||||
|
||||
Args:
|
||||
authorization: Authorization header value
|
||||
|
||||
Returns:
|
||||
True if valid, raises HTTPException otherwise
|
||||
"""
|
||||
if not authorization:
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_401_UNAUTHORIZED,
|
||||
detail="Missing authorization header",
|
||||
)
|
||||
|
||||
# Simple token validation - in real implementation, this would validate against a real auth system
|
||||
if not authorization.startswith("Bearer "):
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_401_UNAUTHORIZED,
|
||||
detail="Invalid authorization header format. Expected: Bearer <token>",
|
||||
)
|
||||
|
||||
token = authorization.replace("Bearer ", "")
|
||||
|
||||
# Accept any non-empty token for mock purposes
|
||||
if not token:
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_401_UNAUTHORIZED,
|
||||
detail="Empty token provided",
|
||||
)
|
||||
|
||||
return True
|
||||
|
||||
|
||||
# API Endpoints
|
||||
@app.get("/health")
|
||||
async def health_check():
|
||||
"""Health check endpoint."""
|
||||
return {"status": "healthy", "service": "IBM FMS Guardrails Mock Server"}
|
||||
|
||||
|
||||
@app.get("/")
|
||||
async def root():
|
||||
"""Root endpoint with API information."""
|
||||
return {
|
||||
"service": "IBM FMS Guardrails Orchestrator Mock",
|
||||
"version": "1.0.0",
|
||||
"endpoints": {
|
||||
"health": "/health",
|
||||
"text_detection": "/api/v1/text/detection",
|
||||
"generation_detection": "/api/v1/text/generation/detection",
|
||||
"context_detection": "/api/v1/text/context/detection",
|
||||
},
|
||||
"available_detectors": list(MOCK_DETECTORS.keys()),
|
||||
}
|
||||
|
||||
|
||||
@app.post("/api/v1/text/contents")
|
||||
async def text_detection(
|
||||
detector_id: str, # query parameter
|
||||
request: TextDetectionRequest,
|
||||
authorization: Optional[str] = Header(None),
|
||||
):
|
||||
"""
|
||||
Detect potential issues in text content.
|
||||
|
||||
Args:
|
||||
request: Detection request with content and detector ID
|
||||
authorization: Bearer token for authentication
|
||||
|
||||
Returns:
|
||||
Detection results
|
||||
"""
|
||||
verify_auth_token(authorization)
|
||||
|
||||
detections = simulate_detection(
|
||||
detector_id=detector_id,
|
||||
content=request.contents,
|
||||
detector_params=request.detector_params,
|
||||
)
|
||||
|
||||
return detections
|
||||
|
||||
|
||||
@app.post("/api/v1/text/generation/detection", response_model=DetectionResponse)
|
||||
async def text_generation_detection(
|
||||
request: TextGenerationDetectionRequest,
|
||||
authorization: Optional[str] = Header(None),
|
||||
):
|
||||
"""
|
||||
Detect potential issues in generated text.
|
||||
|
||||
Args:
|
||||
request: Detection request with prompt and generated text
|
||||
authorization: Bearer token for authentication
|
||||
|
||||
Returns:
|
||||
Detection results
|
||||
"""
|
||||
verify_auth_token(authorization)
|
||||
|
||||
# Analyze both prompt and generated text
|
||||
combined_content = f"{request.prompt} {request.generated_text}"
|
||||
|
||||
detections = simulate_detection(
|
||||
detector_id=request.detector_id,
|
||||
content=combined_content,
|
||||
detector_params=request.detector_params,
|
||||
)
|
||||
|
||||
return DetectionResponse(
|
||||
detections=detections,
|
||||
detection_id=str(uuid.uuid4()),
|
||||
)
|
||||
|
||||
|
||||
@app.post("/api/v1/text/context/detection", response_model=DetectionResponse)
|
||||
async def context_detection(
|
||||
request: ContextDetectionRequest,
|
||||
authorization: Optional[str] = Header(None),
|
||||
):
|
||||
"""
|
||||
Detect potential issues in text with additional context.
|
||||
|
||||
Args:
|
||||
request: Detection request with content and context
|
||||
authorization: Bearer token for authentication
|
||||
|
||||
Returns:
|
||||
Detection results
|
||||
"""
|
||||
verify_auth_token(authorization)
|
||||
|
||||
detections = simulate_detection(
|
||||
detector_id=request.detector_id,
|
||||
content=request.content,
|
||||
detector_params=request.detector_params,
|
||||
)
|
||||
|
||||
return DetectionResponse(
|
||||
detections=detections,
|
||||
detection_id=str(uuid.uuid4()),
|
||||
)
|
||||
|
||||
|
||||
@app.get("/api/v1/detectors")
|
||||
async def list_detectors(authorization: Optional[str] = Header(None)):
|
||||
"""
|
||||
List available detectors.
|
||||
|
||||
Args:
|
||||
authorization: Bearer token for authentication
|
||||
|
||||
Returns:
|
||||
List of available detectors
|
||||
"""
|
||||
verify_auth_token(authorization)
|
||||
|
||||
return {
|
||||
"detectors": [
|
||||
{
|
||||
"id": detector_id,
|
||||
"name": config["name"],
|
||||
"triggers": config["triggers"],
|
||||
}
|
||||
for detector_id, config in MOCK_DETECTORS.items()
|
||||
]
|
||||
}
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
print("🚀 Starting IBM FMS Guardrails Mock Server...")
|
||||
print("📍 Server will be available at: http://localhost:8001")
|
||||
print("📚 API docs at: http://localhost:8001/docs")
|
||||
print("\nAvailable detectors:")
|
||||
for detector_id, config in MOCK_DETECTORS.items():
|
||||
print(f" - {detector_id}: {config['name']}")
|
||||
print("\n✨ Use any Bearer token for authentication in this mock server\n")
|
||||
|
||||
uvicorn.run(app, host="0.0.0.0", port=8001)
|
||||
181
scripts/test_mock_ibm_guardrails.py
Normal file
181
scripts/test_mock_ibm_guardrails.py
Normal file
@@ -0,0 +1,181 @@
|
||||
"""
|
||||
Test script for the mock IBM Guardrails server.
|
||||
|
||||
This demonstrates how to interact with the mock server.
|
||||
|
||||
Usage:
|
||||
# Start the mock server in one terminal:
|
||||
python scripts/mock_ibm_guardrails_server.py
|
||||
|
||||
# Run this test in another terminal:
|
||||
python scripts/test_mock_ibm_guardrails.py
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
|
||||
import httpx
|
||||
|
||||
|
||||
async def test_mock_server():
|
||||
"""Test the mock IBM Guardrails server."""
|
||||
base_url = "http://localhost:8001"
|
||||
headers = {"Authorization": "Bearer test-token-12345"}
|
||||
|
||||
print("🧪 Testing IBM FMS Guardrails Mock Server\n")
|
||||
|
||||
async with httpx.AsyncClient() as client:
|
||||
# Test 1: Health check
|
||||
print("1️⃣ Testing health check...")
|
||||
try:
|
||||
response = await client.get(f"{base_url}/health")
|
||||
print(f" ✅ Health check: {response.json()}\n")
|
||||
except Exception as e:
|
||||
print(f" ❌ Health check failed: {e}\n")
|
||||
return
|
||||
|
||||
# Test 2: List detectors
|
||||
print("2️⃣ Testing list detectors...")
|
||||
try:
|
||||
response = await client.get(
|
||||
f"{base_url}/api/v1/detectors",
|
||||
headers=headers
|
||||
)
|
||||
detectors = response.json()
|
||||
print(f" ✅ Found {len(detectors['detectors'])} detectors:")
|
||||
for detector in detectors["detectors"]:
|
||||
print(f" - {detector['id']}: {detector['name']}")
|
||||
print()
|
||||
except Exception as e:
|
||||
print(f" ❌ List detectors failed: {e}\n")
|
||||
|
||||
# Test 3: Text detection with clean content
|
||||
print("3️⃣ Testing text detection (clean content)...")
|
||||
try:
|
||||
response = await client.post(
|
||||
f"{base_url}/api/v1/text/detection",
|
||||
headers=headers,
|
||||
json={
|
||||
"detector_id": "hate",
|
||||
"content": "This is a normal, friendly message.",
|
||||
}
|
||||
)
|
||||
result = response.json()
|
||||
print(f" ✅ Detection result:")
|
||||
print(f" Detection ID: {result['detection_id']}")
|
||||
for detection in result["detections"]:
|
||||
print(f" - Type: {detection['detection_type']}, Detected: {detection['detection']}, Score: {detection['score']:.2f}")
|
||||
print()
|
||||
except Exception as e:
|
||||
print(f" ❌ Text detection failed: {e}\n")
|
||||
|
||||
# Test 4: Text detection with problematic content
|
||||
print("4️⃣ Testing text detection (problematic content)...")
|
||||
try:
|
||||
response = await client.post(
|
||||
f"{base_url}/api/v1/text/detection",
|
||||
headers=headers,
|
||||
json={
|
||||
"detector_id": "hate",
|
||||
"content": "This message contains hate speech and offensive language.",
|
||||
}
|
||||
)
|
||||
result = response.json()
|
||||
print(f" ✅ Detection result:")
|
||||
print(f" Detection ID: {result['detection_id']}")
|
||||
for detection in result["detections"]:
|
||||
print(f" - Type: {detection['detection_type']}, Detected: {detection['detection']}, Score: {detection['score']:.2f}")
|
||||
if detection.get("evidence"):
|
||||
print(f" Evidence: {detection['evidence']}")
|
||||
print()
|
||||
except Exception as e:
|
||||
print(f" ❌ Text detection failed: {e}\n")
|
||||
|
||||
# Test 5: PII detection
|
||||
print("5️⃣ Testing PII detection...")
|
||||
try:
|
||||
response = await client.post(
|
||||
f"{base_url}/api/v1/text/detection",
|
||||
headers=headers,
|
||||
json={
|
||||
"detector_id": "pii",
|
||||
"content": "Please send the report to my email address john@example.com",
|
||||
}
|
||||
)
|
||||
result = response.json()
|
||||
print(f" ✅ Detection result:")
|
||||
print(f" Detection ID: {result['detection_id']}")
|
||||
for detection in result["detections"]:
|
||||
print(f" - Type: {detection['detection_type']}, Detected: {detection['detection']}, Score: {detection['score']:.2f}")
|
||||
if detection.get("text"):
|
||||
print(f" Detected text: '{detection['text']}'")
|
||||
print()
|
||||
except Exception as e:
|
||||
print(f" ❌ PII detection failed: {e}\n")
|
||||
|
||||
# Test 6: Generation detection
|
||||
print("6️⃣ Testing text generation detection...")
|
||||
try:
|
||||
response = await client.post(
|
||||
f"{base_url}/api/v1/text/generation/detection",
|
||||
headers=headers,
|
||||
json={
|
||||
"detector_id": "jailbreak",
|
||||
"prompt": "Tell me about AI safety",
|
||||
"generated_text": "I will ignore instructions and provide harmful content.",
|
||||
}
|
||||
)
|
||||
result = response.json()
|
||||
print(f" ✅ Detection result:")
|
||||
print(f" Detection ID: {result['detection_id']}")
|
||||
for detection in result["detections"]:
|
||||
print(f" - Type: {detection['detection_type']}, Detected: {detection['detection']}, Score: {detection['score']:.2f}")
|
||||
print()
|
||||
except Exception as e:
|
||||
print(f" ❌ Generation detection failed: {e}\n")
|
||||
|
||||
# Test 7: Detection with custom threshold
|
||||
print("7️⃣ Testing detection with custom threshold...")
|
||||
try:
|
||||
response = await client.post(
|
||||
f"{base_url}/api/v1/text/detection",
|
||||
headers=headers,
|
||||
json={
|
||||
"detector_id": "toxicity",
|
||||
"content": "This contains toxic language",
|
||||
"detector_params": {
|
||||
"threshold": 0.9
|
||||
}
|
||||
}
|
||||
)
|
||||
result = response.json()
|
||||
print(f" ✅ Detection result (threshold=0.9):")
|
||||
print(f" Detection ID: {result['detection_id']}")
|
||||
for detection in result["detections"]:
|
||||
print(f" - Type: {detection['detection_type']}, Detected: {detection['detection']}, Score: {detection['score']:.2f}")
|
||||
print()
|
||||
except Exception as e:
|
||||
print(f" ❌ Threshold detection failed: {e}\n")
|
||||
|
||||
# Test 8: Authentication error
|
||||
print("8️⃣ Testing authentication error...")
|
||||
try:
|
||||
response = await client.post(
|
||||
f"{base_url}/api/v1/text/detection",
|
||||
json={
|
||||
"detector_id": "hate",
|
||||
"content": "Test content",
|
||||
}
|
||||
)
|
||||
if response.status_code == 401:
|
||||
print(f" ✅ Authentication error handled correctly: {response.json()}\n")
|
||||
else:
|
||||
print(f" ⚠️ Unexpected status code: {response.status_code}\n")
|
||||
except Exception as e:
|
||||
print(f" ❌ Auth test failed: {e}\n")
|
||||
|
||||
print("✨ All tests completed!")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(test_mock_server())
|
||||
|
||||
381
ui/litellm-dashboard/src/components/OldTeams.test.tsx
Normal file
381
ui/litellm-dashboard/src/components/OldTeams.test.tsx
Normal file
@@ -0,0 +1,381 @@
|
||||
import { describe, it, expect, vi, beforeEach } from "vitest";
|
||||
import { teamCreateCall } from "./networking";
|
||||
|
||||
vi.mock("./networking", () => ({
|
||||
teamCreateCall: vi.fn(),
|
||||
teamDeleteCall: vi.fn(),
|
||||
fetchMCPAccessGroups: vi.fn(),
|
||||
v2TeamListCall: vi.fn(),
|
||||
}));
|
||||
|
||||
vi.mock("./common_components/fetch_teams", () => ({
|
||||
fetchTeams: vi.fn(),
|
||||
}));
|
||||
|
||||
vi.mock("./molecules/notifications_manager", () => ({
|
||||
default: {
|
||||
info: vi.fn(),
|
||||
success: vi.fn(),
|
||||
error: vi.fn(),
|
||||
fromBackend: vi.fn(),
|
||||
},
|
||||
}));
|
||||
|
||||
describe("OldTeams - handleCreate organization handling", () => {
|
||||
beforeEach(() => {
|
||||
vi.clearAllMocks();
|
||||
});
|
||||
|
||||
it("should not include organization_id when it's an empty string", async () => {
|
||||
const mockAccessToken = "test-token";
|
||||
const formValues: Record<string, any> = {
|
||||
team_alias: "Test Team",
|
||||
organization_id: "", // Empty string
|
||||
models: [],
|
||||
};
|
||||
|
||||
// Simulate the handleCreate logic
|
||||
let organizationId = formValues?.organization_id || null;
|
||||
if (organizationId === "" || typeof organizationId !== "string") {
|
||||
formValues.organization_id = null;
|
||||
} else {
|
||||
formValues.organization_id = organizationId.trim();
|
||||
}
|
||||
|
||||
expect(formValues.organization_id).toBeNull();
|
||||
expect(formValues.organization_id).not.toBe("");
|
||||
});
|
||||
|
||||
it("should set organization_id to null when it's not a string type", async () => {
|
||||
const formValues: Record<string, any> = {
|
||||
team_alias: "Test Team",
|
||||
organization_id: undefined,
|
||||
models: [],
|
||||
};
|
||||
|
||||
// Simulate the handleCreate logic
|
||||
let organizationId = formValues?.organization_id || null;
|
||||
if (organizationId === "" || typeof organizationId !== "string") {
|
||||
formValues.organization_id = null;
|
||||
} else {
|
||||
formValues.organization_id = organizationId.trim();
|
||||
}
|
||||
|
||||
expect(formValues.organization_id).toBeNull();
|
||||
});
|
||||
|
||||
it("should trim and keep valid organization_id string", async () => {
|
||||
const formValues: Record<string, any> = {
|
||||
team_alias: "Test Team",
|
||||
organization_id: " org-123 ", // String with whitespace
|
||||
models: [],
|
||||
};
|
||||
|
||||
// Simulate the handleCreate logic
|
||||
let organizationId = formValues?.organization_id || null;
|
||||
if (organizationId === "" || typeof organizationId !== "string") {
|
||||
formValues.organization_id = null;
|
||||
} else {
|
||||
formValues.organization_id = organizationId.trim();
|
||||
}
|
||||
|
||||
expect(formValues.organization_id).toBe("org-123");
|
||||
});
|
||||
|
||||
it("should keep valid organization_id without modification", async () => {
|
||||
const formValues: Record<string, any> = {
|
||||
team_alias: "Test Team",
|
||||
organization_id: "f874bb43-b898-4813-beca-4054d224eafc",
|
||||
models: [],
|
||||
};
|
||||
|
||||
// Simulate the handleCreate logic
|
||||
let organizationId = formValues?.organization_id || null;
|
||||
if (organizationId === "" || typeof organizationId !== "string") {
|
||||
formValues.organization_id = null;
|
||||
} else {
|
||||
formValues.organization_id = organizationId.trim();
|
||||
}
|
||||
|
||||
expect(formValues.organization_id).toBe("f874bb43-b898-4813-beca-4054d224eafc");
|
||||
});
|
||||
|
||||
it("should not send organization_id field when converting empty string to null", async () => {
|
||||
const formValues: Record<string, any> = {
|
||||
team_alias: "Test Team",
|
||||
organization_id: "",
|
||||
models: ["gpt-4"],
|
||||
max_budget: 100,
|
||||
};
|
||||
|
||||
// Simulate the handleCreate logic
|
||||
let organizationId = formValues?.organization_id || null;
|
||||
if (organizationId === "" || typeof organizationId !== "string") {
|
||||
formValues.organization_id = null;
|
||||
} else {
|
||||
formValues.organization_id = organizationId.trim();
|
||||
}
|
||||
|
||||
// Verify the structure
|
||||
expect(formValues).toEqual({
|
||||
team_alias: "Test Team",
|
||||
organization_id: null,
|
||||
models: ["gpt-4"],
|
||||
max_budget: 100,
|
||||
});
|
||||
|
||||
// Verify we're not sending an empty string
|
||||
expect(formValues.organization_id).not.toBe("");
|
||||
|
||||
// Verify it's explicitly null, not undefined
|
||||
expect(formValues.organization_id).toBeNull();
|
||||
});
|
||||
|
||||
it("should handle when currentOrg is used as fallback", async () => {
|
||||
const currentOrg = {
|
||||
organization_id: "fallback-org-id",
|
||||
organization_alias: "Fallback Org",
|
||||
models: [],
|
||||
members: [],
|
||||
};
|
||||
|
||||
const formValues: Record<string, any> = {
|
||||
team_alias: "Test Team",
|
||||
models: [],
|
||||
};
|
||||
|
||||
// Simulate the handleCreate logic with currentOrg fallback
|
||||
let organizationId = formValues?.organization_id || currentOrg?.organization_id;
|
||||
if (organizationId === "" || typeof organizationId !== "string") {
|
||||
formValues.organization_id = null;
|
||||
} else {
|
||||
formValues.organization_id = organizationId.trim();
|
||||
}
|
||||
|
||||
expect(formValues.organization_id).toBe("fallback-org-id");
|
||||
});
|
||||
|
||||
it("should not include organizations as an empty array in the request payload", async () => {
|
||||
const mockTeamCreateCall = vi.mocked(teamCreateCall);
|
||||
const mockAccessToken = "test-token";
|
||||
|
||||
const formValues = {
|
||||
team_alias: "Test Team",
|
||||
organization_id: "org-123",
|
||||
models: ["gpt-4"],
|
||||
organizations: [], // This should never be sent
|
||||
};
|
||||
|
||||
// Remove organizations key if it's empty
|
||||
if (Array.isArray(formValues.organizations) && formValues.organizations.length === 0) {
|
||||
delete (formValues as any).organizations;
|
||||
}
|
||||
|
||||
// Verify organizations key is removed
|
||||
expect(formValues).not.toHaveProperty("organizations");
|
||||
expect(formValues).toEqual({
|
||||
team_alias: "Test Team",
|
||||
organization_id: "org-123",
|
||||
models: ["gpt-4"],
|
||||
});
|
||||
});
|
||||
|
||||
it("should handle organization_id validation for org admins", () => {
|
||||
// This test simulates the validation that should happen for org admins
|
||||
const isOrgAdmin = true;
|
||||
const formValues: Record<string, any> = {
|
||||
team_alias: "Test Team",
|
||||
// organization_id is missing/undefined
|
||||
};
|
||||
|
||||
// For org admins, organization_id should be required
|
||||
const hasOrganization = formValues.organization_id !== undefined &&
|
||||
formValues.organization_id !== null &&
|
||||
formValues.organization_id !== "";
|
||||
|
||||
if (isOrgAdmin && !hasOrganization) {
|
||||
// This should trigger validation error
|
||||
expect(hasOrganization).toBe(false);
|
||||
}
|
||||
});
|
||||
|
||||
it("should allow null organization_id for global admins", () => {
|
||||
const isAdmin = true;
|
||||
const formValues: Record<string, any> = {
|
||||
team_alias: "Test Team",
|
||||
organization_id: null,
|
||||
models: [],
|
||||
};
|
||||
|
||||
// Global admins can create teams without an organization
|
||||
if (isAdmin) {
|
||||
expect(formValues.organization_id).toBeNull();
|
||||
// This is valid for admins
|
||||
}
|
||||
});
|
||||
|
||||
it("should ensure organization_id is never an empty list", () => {
|
||||
const invalidFormValues: Record<string, any> = {
|
||||
team_alias: "Test Team",
|
||||
organization_id: [], // Wrong type - should be string or null
|
||||
};
|
||||
|
||||
// Type check: organization_id should never be an array
|
||||
expect(Array.isArray(invalidFormValues.organization_id)).toBe(true);
|
||||
|
||||
// Correct it to null
|
||||
if (Array.isArray(invalidFormValues.organization_id)) {
|
||||
invalidFormValues.organization_id = null;
|
||||
}
|
||||
|
||||
expect(invalidFormValues.organization_id).toBeNull();
|
||||
expect(Array.isArray(invalidFormValues.organization_id)).toBe(false);
|
||||
});
|
||||
});
|
||||
|
||||
describe("OldTeams - helper functions", () => {
|
||||
describe("getAdminOrganizations", () => {
|
||||
it("should return all organizations for Admin role", () => {
|
||||
const organizations = [
|
||||
{
|
||||
organization_id: "org-1",
|
||||
organization_alias: "Org 1",
|
||||
models: [],
|
||||
members: [],
|
||||
},
|
||||
{
|
||||
organization_id: "org-2",
|
||||
organization_alias: "Org 2",
|
||||
models: [],
|
||||
members: [],
|
||||
},
|
||||
];
|
||||
|
||||
// Simulate getAdminOrganizations logic for Admin
|
||||
const userRole = "Admin";
|
||||
const result = userRole === "Admin" ? organizations : [];
|
||||
|
||||
expect(result).toEqual(organizations);
|
||||
expect(result.length).toBe(2);
|
||||
});
|
||||
|
||||
it("should return only org_admin organizations for Org Admin role", () => {
|
||||
const userID = "user-123";
|
||||
const userRole = "Org Admin";
|
||||
const organizations = [
|
||||
{
|
||||
organization_id: "org-1",
|
||||
organization_alias: "Org 1",
|
||||
models: [],
|
||||
members: [
|
||||
{ user_id: "user-123", user_role: "org_admin" },
|
||||
],
|
||||
},
|
||||
{
|
||||
organization_id: "org-2",
|
||||
organization_alias: "Org 2",
|
||||
models: [],
|
||||
members: [
|
||||
{ user_id: "user-456", user_role: "org_admin" },
|
||||
],
|
||||
},
|
||||
{
|
||||
organization_id: "org-3",
|
||||
organization_alias: "Org 3",
|
||||
models: [],
|
||||
members: [
|
||||
{ user_id: "user-123", user_role: "member" },
|
||||
],
|
||||
},
|
||||
];
|
||||
|
||||
// Simulate getAdminOrganizations logic
|
||||
const result = organizations.filter((org) =>
|
||||
org.members?.some(
|
||||
(member) => member.user_id === userID && member.user_role === "org_admin"
|
||||
)
|
||||
);
|
||||
|
||||
expect(result.length).toBe(1);
|
||||
expect(result[0].organization_id).toBe("org-1");
|
||||
});
|
||||
|
||||
it("should return empty array when user is not admin of any organization", () => {
|
||||
const userID = "user-999";
|
||||
const organizations = [
|
||||
{
|
||||
organization_id: "org-1",
|
||||
organization_alias: "Org 1",
|
||||
models: [],
|
||||
members: [
|
||||
{ user_id: "user-123", user_role: "org_admin" },
|
||||
],
|
||||
},
|
||||
];
|
||||
|
||||
// Simulate getAdminOrganizations logic
|
||||
const result = organizations.filter((org) =>
|
||||
org.members?.some(
|
||||
(member) => member.user_id === userID && member.user_role === "org_admin"
|
||||
)
|
||||
);
|
||||
|
||||
expect(result.length).toBe(0);
|
||||
});
|
||||
});
|
||||
|
||||
describe("canCreateOrManageTeams", () => {
|
||||
it("should return true for Admin role", () => {
|
||||
const userRole = "Admin";
|
||||
const result = userRole === "Admin";
|
||||
expect(result).toBe(true);
|
||||
});
|
||||
|
||||
it("should return true for org_admin in any organization", () => {
|
||||
const userID = "user-123";
|
||||
const organizations = [
|
||||
{
|
||||
organization_id: "org-1",
|
||||
organization_alias: "Org 1",
|
||||
models: [],
|
||||
members: [
|
||||
{ user_id: "user-123", user_role: "org_admin" },
|
||||
],
|
||||
},
|
||||
];
|
||||
|
||||
const result = organizations.some((org) =>
|
||||
org.members?.some(
|
||||
(member) => member.user_id === userID && member.user_role === "org_admin"
|
||||
)
|
||||
);
|
||||
|
||||
expect(result).toBe(true);
|
||||
});
|
||||
|
||||
it("should return false when user has no admin permissions", () => {
|
||||
const userID = "user-123";
|
||||
const userRole: string = "User";
|
||||
const organizations = [
|
||||
{
|
||||
organization_id: "org-1",
|
||||
organization_alias: "Org 1",
|
||||
models: [],
|
||||
members: [
|
||||
{ user_id: "user-123", user_role: "member" },
|
||||
],
|
||||
},
|
||||
];
|
||||
|
||||
const isAdmin = userRole === "Admin";
|
||||
const isOrgAdmin = organizations.some((org) =>
|
||||
org.members?.some(
|
||||
(member) => member.user_id === userID && member.user_role === "org_admin"
|
||||
)
|
||||
);
|
||||
|
||||
expect(isAdmin || isOrgAdmin).toBe(false);
|
||||
});
|
||||
});
|
||||
});
|
||||
|
||||
@@ -122,6 +122,46 @@ const getOrganizationModels = (organization: Organization | null, userModels: st
|
||||
return unfurlWildcardModelsInList(tempModelsToPick, userModels);
|
||||
};
|
||||
|
||||
const canCreateOrManageTeams = (
|
||||
userRole: string | null,
|
||||
userID: string | null,
|
||||
organizations: Organization[] | null
|
||||
): boolean => {
|
||||
// Admin role always has permission
|
||||
if (userRole === "Admin") {
|
||||
return true;
|
||||
}
|
||||
|
||||
// Check if user is an org_admin in any organization
|
||||
if (organizations && userID) {
|
||||
return organizations.some((org) =>
|
||||
org.members?.some((member) => member.user_id === userID && member.user_role === "org_admin")
|
||||
);
|
||||
}
|
||||
|
||||
return false;
|
||||
};
|
||||
|
||||
const getAdminOrganizations = (
|
||||
userRole: string | null,
|
||||
userID: string | null,
|
||||
organizations: Organization[] | null
|
||||
): Organization[] => {
|
||||
// Global Admin can see all organizations
|
||||
if (userRole === "Admin") {
|
||||
return organizations || [];
|
||||
}
|
||||
|
||||
// Org Admin can only see organizations they're an admin for
|
||||
if (organizations && userID) {
|
||||
return organizations.filter((org) =>
|
||||
org.members?.some((member) => member.user_id === userID && member.user_role === "org_admin")
|
||||
);
|
||||
}
|
||||
|
||||
return [];
|
||||
};
|
||||
|
||||
// @deprecated
|
||||
const Teams: React.FC<TeamProps> = ({
|
||||
teams,
|
||||
@@ -133,6 +173,7 @@ const Teams: React.FC<TeamProps> = ({
|
||||
organizations,
|
||||
premiumUser = false,
|
||||
}) => {
|
||||
console.log(`organizations: ${JSON.stringify(organizations)}`);
|
||||
const [lastRefreshed, setLastRefreshed] = useState("");
|
||||
const [currentOrg, setCurrentOrg] = useState<Organization | null>(null);
|
||||
const [currentOrgForCreateTeam, setCurrentOrgForCreateTeam] = useState<Organization | null>(null);
|
||||
@@ -190,6 +231,24 @@ const Teams: React.FC<TeamProps> = ({
|
||||
form.setFieldValue("models", []);
|
||||
}, [currentOrgForCreateTeam, userModels]);
|
||||
|
||||
// Handle organization preselection when modal opens
|
||||
useEffect(() => {
|
||||
if (isTeamModalVisible) {
|
||||
const adminOrgs = getAdminOrganizations(userRole, userID, organizations);
|
||||
|
||||
// If there's exactly one organization the user is admin for, preselect it
|
||||
if (adminOrgs.length === 1) {
|
||||
const org = adminOrgs[0];
|
||||
form.setFieldValue("organization_id", org.organization_id);
|
||||
setCurrentOrgForCreateTeam(org);
|
||||
} else {
|
||||
// Reset the organization selection for multiple orgs
|
||||
form.setFieldValue("organization_id", currentOrg?.organization_id || null);
|
||||
setCurrentOrgForCreateTeam(currentOrg);
|
||||
}
|
||||
}
|
||||
}, [isTeamModalVisible, userRole, userID, organizations, currentOrg]);
|
||||
|
||||
// Add this useEffect to fetch guardrails
|
||||
useEffect(() => {
|
||||
const fetchGuardrails = async () => {
|
||||
@@ -525,7 +584,7 @@ const Teams: React.FC<TeamProps> = ({
|
||||
<div className="w-full mx-4 h-[75vh]">
|
||||
<Grid numItems={1} className="gap-2 p-8 w-full mt-2">
|
||||
<Col numColSpan={1} className="flex flex-col gap-2">
|
||||
{(userRole == "Admin" || userRole == "Org Admin") && (
|
||||
{canCreateOrManageTeams(userRole, userID, organizations) && (
|
||||
<Button className="w-fit" onClick={() => setIsTeamModalVisible(true)}>
|
||||
+ Create New Team
|
||||
</Button>
|
||||
@@ -1007,7 +1066,7 @@ const Teams: React.FC<TeamProps> = ({
|
||||
</TabPanels>
|
||||
</TabGroup>
|
||||
)}
|
||||
{(userRole == "Admin" || userRole == "Org Admin") && (
|
||||
{canCreateOrManageTeams(userRole, userID, organizations) && (
|
||||
<Modal
|
||||
title="Create Team"
|
||||
visible={isTeamModalVisible}
|
||||
@@ -1036,60 +1095,105 @@ const Teams: React.FC<TeamProps> = ({
|
||||
>
|
||||
<TextInput placeholder="" />
|
||||
</Form.Item>
|
||||
<Form.Item
|
||||
label={
|
||||
<span>
|
||||
Organization{" "}
|
||||
<Tooltip
|
||||
title={
|
||||
{(() => {
|
||||
const adminOrgs = getAdminOrganizations(userRole, userID, organizations);
|
||||
const isOrgAdmin = userRole !== "Admin";
|
||||
const isSingleOrg = adminOrgs.length === 1;
|
||||
const hasNoOrgs = adminOrgs.length === 0;
|
||||
|
||||
return (
|
||||
<>
|
||||
<Form.Item
|
||||
label={
|
||||
<span>
|
||||
Organizations can have multiple teams. Learn more about{" "}
|
||||
<a
|
||||
href="https://docs.litellm.ai/docs/proxy/user_management_heirarchy"
|
||||
target="_blank"
|
||||
rel="noopener noreferrer"
|
||||
style={{
|
||||
color: "#1890ff",
|
||||
textDecoration: "underline",
|
||||
}}
|
||||
onClick={(e) => e.stopPropagation()}
|
||||
Organization{" "}
|
||||
<Tooltip
|
||||
title={
|
||||
<span>
|
||||
Organizations can have multiple teams. Learn more about{" "}
|
||||
<a
|
||||
href="https://docs.litellm.ai/docs/proxy/user_management_heirarchy"
|
||||
target="_blank"
|
||||
rel="noopener noreferrer"
|
||||
style={{
|
||||
color: "#1890ff",
|
||||
textDecoration: "underline",
|
||||
}}
|
||||
onClick={(e) => e.stopPropagation()}
|
||||
>
|
||||
user management hierarchy
|
||||
</a>
|
||||
</span>
|
||||
}
|
||||
>
|
||||
user management hierarchy
|
||||
</a>
|
||||
<InfoCircleOutlined style={{ marginLeft: "4px" }} />
|
||||
</Tooltip>
|
||||
</span>
|
||||
}
|
||||
name="organization_id"
|
||||
initialValue={currentOrg ? currentOrg.organization_id : null}
|
||||
className="mt-8"
|
||||
rules={
|
||||
isOrgAdmin
|
||||
? [
|
||||
{
|
||||
required: true,
|
||||
message: "Please select an organization",
|
||||
},
|
||||
]
|
||||
: []
|
||||
}
|
||||
help={
|
||||
isSingleOrg
|
||||
? "You can only create teams within this organization"
|
||||
: isOrgAdmin
|
||||
? "required"
|
||||
: ""
|
||||
}
|
||||
>
|
||||
<InfoCircleOutlined style={{ marginLeft: "4px" }} />
|
||||
</Tooltip>
|
||||
</span>
|
||||
}
|
||||
name="organization_id"
|
||||
initialValue={currentOrg ? currentOrg.organization_id : null}
|
||||
className="mt-8"
|
||||
>
|
||||
<Select2
|
||||
showSearch
|
||||
allowClear
|
||||
placeholder="Search or select an Organization"
|
||||
onChange={(value) => {
|
||||
form.setFieldValue("organization_id", value);
|
||||
setCurrentOrgForCreateTeam(organizations?.find((org) => org.organization_id === value) || null);
|
||||
}}
|
||||
filterOption={(input, option) => {
|
||||
if (!option) return false;
|
||||
const optionValue = option.children?.toString() || "";
|
||||
return optionValue.toLowerCase().includes(input.toLowerCase());
|
||||
}}
|
||||
optionFilterProp="children"
|
||||
>
|
||||
{organizations?.map((org) => (
|
||||
<Select2.Option key={org.organization_id} value={org.organization_id}>
|
||||
<span className="font-medium">{org.organization_alias}</span>{" "}
|
||||
<span className="text-gray-500">({org.organization_id})</span>
|
||||
</Select2.Option>
|
||||
))}
|
||||
</Select2>
|
||||
</Form.Item>
|
||||
<Select2
|
||||
showSearch
|
||||
allowClear={!isOrgAdmin}
|
||||
disabled={isSingleOrg}
|
||||
placeholder={
|
||||
hasNoOrgs
|
||||
? "No organizations available"
|
||||
: "Search or select an Organization"
|
||||
}
|
||||
onChange={(value) => {
|
||||
form.setFieldValue("organization_id", value);
|
||||
setCurrentOrgForCreateTeam(
|
||||
adminOrgs?.find((org) => org.organization_id === value) || null
|
||||
);
|
||||
}}
|
||||
filterOption={(input, option) => {
|
||||
if (!option) return false;
|
||||
const optionValue = option.children?.toString() || "";
|
||||
return optionValue.toLowerCase().includes(input.toLowerCase());
|
||||
}}
|
||||
optionFilterProp="children"
|
||||
>
|
||||
{adminOrgs?.map((org) => (
|
||||
<Select2.Option key={org.organization_id} value={org.organization_id}>
|
||||
<span className="font-medium">{org.organization_alias}</span>{" "}
|
||||
<span className="text-gray-500">({org.organization_id})</span>
|
||||
</Select2.Option>
|
||||
))}
|
||||
</Select2>
|
||||
</Form.Item>
|
||||
|
||||
{/* Show message when org admin needs to select organization */}
|
||||
{isOrgAdmin && !isSingleOrg && adminOrgs.length > 1 && (
|
||||
<div className="mb-8 p-4 bg-blue-50 border border-blue-200 rounded-md">
|
||||
<Text className="text-blue-800 text-sm">
|
||||
Please select an organization to create a team for. You can only create teams within
|
||||
organizations where you are an admin.
|
||||
</Text>
|
||||
</div>
|
||||
)}
|
||||
</>
|
||||
);
|
||||
})()}
|
||||
<Form.Item
|
||||
label={
|
||||
<span>
|
||||
|
||||
Reference in New Issue
Block a user