# LLM Assignment ## Purpose Assign specific LLMs to individual users or groups so mentor editors only see the models they are authorized to use, rather than every model available to tenant admins. --- ## Prerequisites - The user must already have **mentor editor** access (visible on the mentor's **Access** tab) - A role with LLM-related actions must exist (or you will create one) --- ## Create an LLM Access Role 1. Go to **Tenant Settings → Management → Roles**. 2. Create a new role (e.g., "LLM Model Access"). 3. Assign the actions: - **Read** all LLMs - **Select** from available LLMs --- ## Create or Edit a Policy 1. Navigate to the **Policies** tab. 2. Click **New Policy** (or edit an existing one like "LLM Model Access"). 3. Configure the policy: - **Policy name**: descriptive label - **Role**: select the LLM access role created above - **Platform**: select your tenant - **LLM(s)**: choose one or more models (e.g., OpenAI GPT-4o Mini, Google, Perplexity) 4. Under **Users/Groups**, add the specific user or group. 5. Click **Save Policy**. --- ## Verify as the User 1. Log in as the assigned user. 2. Open a mentor and click the **LLMs** tab. 3. Confirm that only the assigned models appear (e.g., GPT-4o Mini, Google, Perplexity). 4. Tenant admins will still see all LLMs; restricted users see only their assigned models. --- ## Scope Options - **Platform-wide**: the user sees the same limited LLM set across all mentors - **Per-mentor**: restrict LLM access to specific mentors by adjusting the policy resource to a particular mentor rather than the whole platform --- ## Key Takeaways - **Roles** define what actions can be taken (read, select LLMs) - **Policies** bind a role to specific LLM resources and assign users or groups - LLM restrictions apply immediately upon the user's next login - Use **groups** to manage LLM access for multiple users at once