Models

Introduction

DIAL allows you to access and use AI models from all major LLM providers, open-source community, alternative vendors, and fine-tuned micro models, as well as self-hosted or models listed on Hugging Face, NVIDIA NIM or DeepSeek.

Refer to Supported Models to learn more about the supported AI models.

DIAL provides a single Unified API, based on OpenAI API, for accessing all AI models, embedding models and applications. The key design principle is to create a unification layer that allows all models and applications to be interchangeable, delivering a cohesive conversational experience and future-proof development of custom GenAI applications.

DIAL uses AI model adapters, that unify the APIs of respective AI models to align with the Unified Protocol of DIAL Core. If a model is compatible with DIAL Unified Protocol, it can be used directly without an adapter.

You can add AI models to DIAL via a direct configuration of DIAL Core or using DIAL Admin Panel. This tutorial describes how to add and manage AI models using DIAL Admin Panel.

Main Screen

On this page, you can find all AI models deployments available on your DIAL instance. Here you can view, filter, and add new model definitions.

When a model deployment is successfully added, it can be accessed across the DIAL ecosystem including, DIAL Chat, DIAL Marketplace and via API for authorized user roles.

You can use DIAL Core API to access available model deployments and to send chat completion requests.

Models grid

TIP: Click Columns to open the columns selector to define what columns to display and in which order.

The grid with models displays the main properties of models which include:

Field	Description
Display Name	Model name (e.g. "GPT-4 Turbo"). Display name is shown in all DIAL client UI components for a quick model identification.
Version	Version of a specific model deployment (e.g. 0613, v1). Used to distinguish between "latest", "beta" or date-stamped builds.
Description	Description of the model's purpose including any relevant details. The description is displayed in DIAL Chat UI and Marketplace.
ID	Unique key under the models section of DIAL Core's config. Must match the upstream service's model or deployment name (e.g. gpt-4-0613).
Source Type	Source type of a model: Adapter: Model is based on a model adapter. External Endpoint: Model is deployed outside DIAL infrastructure and exposes an endpoint DIAL Core uses for communication. Model Container: Model is based on a deployed model container.
Source	Source identifier. Adapter ID, Model serving container ID or Endpoint of the model, based on your Source Type selection.
Author	Information about the user who deployed the model.
Type	Defines Chat (conversational completions) and Embedding models (vector generation). DIAL Core uses this to choose the correct API endpoint and a payload schema.
Override Name	Context-specific optional display label that overrides the Display Name in UI components. Use it to give a model different aliases in different workflows without redefining the model.
Topics	Tags or categories you can assign for discovery, filtering, or grouping in large deployments (e.g. "finance", "support", "image-capable"). Helps end users and admins find the right model by the use case. Topics are also used to filter models in DIAL Marketplace.
Attachment types	Types of attachments this model can accept according to MIME types.
Max attachment number	Maximum number of attachments allowed in a single request. Blank for an unlimited number.
Tokenizer model	Identifies the specific model with a tokenization algorithm identical to the referenced model's. This is typically the name of the earliest released model in a series of models sharing an identical tokenization algorithm. This parameter is essential for DIAL clients that reimplement tokenization algorithms on their side, instead of utilizing the tokenize endpoint provided by the model.
Interaction limit	The interaction limit parameter in models refers to the maximum number of tokens that can be transmitted in a completion request and response combined. This parameter ensures that the model does not exceed a specified token limit during interactions.
Prompt price	Cost per unit (according to Cost unit, typically "token" or "request") applied to the input portion of each call. Used by the Dashboard and Usage Logs to estimate spending in real time.
Completion price	Cost per unit is charged for the output portion of each call. Combined with the prompt price, it determines your per-model cost calculations.

Create Model

Follow these steps to add new AI model to your DIAL instance:

1. Click + Create to invoke a Create Model modal.

2. Define parameters for a new model:

   Field	Required	Description
   ID	Yes	Unique identifier used by the model adapter to invoke the model's backend.
   Display Name	Yes	Model name shown across the UI (e.g. "GPT-4 Turbo").
   Display version	No	Version is an optional tag to track releases when you register multiple variants of the same model. (e.g. 2024-07-18, v1)
   Description	No	Free-text note about the model's purpose or distinguishing traits.
   Source type	Yes	Adapter: Select the corresponding AI model adapter from the list of available adapters. In this case DIAL Core will use the adapter's endpoint URL to communicate with the model. Model Container: Select one of the available model containers deployed in DIAL. In this case DIAL Core will use the container URL to communicate with the model. External Endpoint: For externally-hosted models, provide the chat completion endpoint URL DIAL Core will use to directly (not using model adapters) communicate with the model. In this case, the model API must be compatible with DIAL Core API.

3. Click Create to close the dialog and open the configuration screen. When done with model configuration, click Save. It may take some time for the changes to take effect after saving. Once added, the model appears in the Models listing and become available to use across the DIAL ecosystem.

   

Configuration

You can access the model configuration screen by clicking any model in the models grid and also when adding a new model. In this section, you can view and configure all settings for the selected language model deployment.

• Properties: Main definitions and runtime settings.
• Features: Optional capabilities and custom endpoints.
• Roles: User groups that can invoke this model and their rate limits.
• Interceptors: Custom logic to modify requests or responses.
• Audit: Provides aggregated audit metrics and detailed logs of individual configuration changes.

Properties

In the Properties tab, you can view and edit main definitions and runtime settings for model deployment.

• Basic Information: Identification and basic information about the model and its author.
• Source Type: Parameters associated with the way the model was created: Adapter, Model Container, or External Endpoint.
• Personalization: Parameters to customize model's appearance on UI.
• Attachments: Define attachment types and maximum number of attachments the model can accept.
• Default Parameters: Set default values for model parameters used in chat/completions requests.
• Upstream Configuration: Define upstream endpoints, authentication keys, weights, and extra data.
• Advanced Options: Tokenizer model, forward auth token, interaction limits, retry attempts.
• Cost Configuration: Set cost unit, prompt price, and completion price for real-time billing.

Basic Information

Field	Required	Editable	Description
ID	-	No	Unique key DIAL Core uses in the models section. Must match the upstream's deployment or model name (e.g. gpt-4o, gpt-4-turbo). Non-editable after the model created.
Updated Time	-	No	Date and time when the model's configuration was last updated.
Creation Time	-	No	Date and time when the model's configuration was created.
Sync with core	-	No	Indicates the state of the entity's configuration synchronization between Admin and DIAL Core. Synchronization occurs automatically every 2 mins (configurable via CONFIG_AUTO_RELOAD_SCHEDULE_DELAY_MILLISECONDS). Important: Sync state is not available for sensitive information (API keys/tokens/auth settings). Synced: Entity's states are identical in Admin and in Core for valid entities or entity is missing in Core for invalid entities. In progress...: If Synced conditions are not met and changes were applied within last 2 mins (this period is configurable via CONFIG_EXPORT_SYNC_DURATION_THRESHOLD_MS). Out of sync: If Synced conditions are not met and changes were applied more than 2 mins ago (this period is configurable via CONFIG_EXPORT_SYNC_DURATION_THRESHOLD_MS). Unavailable: Displayed when it is not possible to determine the entity's state in Core. This occurs if: - The config was not received from Core for any reason. - The configuration of entities in Core is not entirely compatible with the one in the Admin service.
Display Name	Yes	Yes	Model name shown in tables and dropdowns in DIAL clients (e.g. "GPT-4o"). Helps users identify and select models on UI.
Display version	No	Yes	Version tag for tracking releases (e.g. 0613, v1). Useful for A/B testing or canary rollouts.
Description	No	Yes	Text describing the model's features, details, or other relevant information.
Maintainer	No	Yes	Name of the responsible person or team overseeing the model's configuration.
Source type	Yes	Yes	Source type indicates the way a model was created: Adapter, Model Container, External Endpoint.

Source Type

The Source Type defines how the model is integrated into DIAL. Depending on the selected Source Type, different parameters need to be specified.

Adapter

Unless AI model API is compatible with the DIAL Unified Protocol, you need adapters to be able to use AI models in DIAL. Model adapters unify the APIs of respective AI models to align with the Unified Protocol of DIAL Core. If the Source Type of your model is Adapter, DIAL Core will use adapters endpoint to communicate with the model.

DIAL includes adapters for Azure OpenAI models, GCP Vertex AI models, and AWS Bedrock models. You can also create custom adapters for other AI models with DIAL SDK.

Adapter can be added in Builders/Adapters.

The following properties need to be specified if selected Source Type is Adapter:

Field	Required	Description
Adapter	Yes	Model adapter that will be used to handle requests to this model deployment (e.g. OpenAI, DIAL). Adapter defines how to authenticate, format payloads, and parse responses.
Type	Yes	Select Chat or Embedding API. Chat: Conversational chat completions. Embedding: Vector generation (semantic search, clustering).
Endpoint	Yes	URL that DIAL Core will invoke for this model. The base URL is determined by the selected adapter, while the path can be partially customized.

Model Container

AI models can be deployed in DIAL using images. You can deploy images and use them to create containers in the Deployments section.

If the Source Type of your model is Model Container, DIAL Core will use the container URL to communicate with the model.

The following properties need to be specified if selected Source Type is Model Container:

Field	Required	Description
Type	Yes	Select Chat or Embedding API. Chat: Conversational chat completions. Embedding: Vector generation (semantic search, clustering).
Container	Yes	Select one of the running Model Containers.
Endpoint	Yes	URL that DIAL Core will invoke for this model. The base URL is determined by the selected container, while the path can be partially customized.

External Endpoint

If your AI model is deployed elsewhere and is compatible with DIAL Core API, you can add it using its chat completion endpoint for a direct communication between the DIAL Core and the AI model.

The following properties need to be specified if selected Source Type is External Endpoint:

Field	Required	Description
Type	Yes	Select Chat or Embedding API. Chat: Conversational chat completions. Embedding: Vector generation (semantic search, clustering).
Endpoint	Yes	URL that DIAL Core will invoke for this model.

Personalization

These parameters help customize how the model is presented in the DIAL UI.

Field	Required	Description
Override name	No	Custom display name for specific contexts.
Icon	No	Logo to visually distinguish models in the UI.
Topics	No	Tag that associates a model with one or more topics or categories (e.g. "finance", "support").

Attachments

Field	Required	Description
Attachments	No	Attachment types (images, files) this model can accept. None: Attachments are not allowed. All: Unrestricted types. Optionally specify max number of attachments. Custom: Specific MIME types.
Attachments max number	No	Maximum number of input attachments, When unset (default), attachments are not allowed.

Default Parameters

Default parameters can be use to pass additional parameters with the chat completion request.

Upstream Configuration

Field	Description
Upstream Endpoints	One or more backend URLs to send requests to. Enables round-robin load balancing or fallback among multiple hosts. Refer to Load Balancer to learn more. You can use upstream endpoint to provide an alternative URL. For example a model Docker container URL if the model is deployed as a container in DIAL. Refer to Model Servings to learn more about this use case.
Keys	API key, token, or credential passed to the upstream. Stored securely and masked—click the eye icon to reveal.
Weight	Numeric weight for this endpoint in a multi-upstream scenario. Higher = more traffic share.
Tier	Specifies an endpoint group. In a regular scenario, all requests are routed to endpoints with the lowest tier, but in case of an outage or hitting the limits, the next one in the line helps to handle the load.
Extra Data	Free-form JSON or string metadata passed to the model adapter with each request.

Advanced Options

Field	Description
Tokenizer Model	Identifies the specific model whose tokenization algorithm exactly matches that of the referenced model. This is typically the name of the earliest released model in a series of models sharing an identical tokenization algorithm. This parameter is essential for DIAL clients that reimplement tokenization algorithms on their side, instead of utilizing the tokenize endpoint provided by the model.
Forward auth token	Select a downstream auth token to forward from the user’s session (for downstream multi-tenant).
Interaction limit	This parameter ensures that the model does not exceed a specified token limit during interactions. Available values: None: DIAL does not apply any additional interaction limits beyond limits that your model enforces natively. Ideal for early prototyping or when you trust the LLM’s built-in safeguards. Total number of tokens: Enforces a single, cumulative cap on the sum of all prompt + completion tokens across the entire chat. Separately Prompts & Completions: Two independent limits: one on the sum of all input (prompt) tokens and another on the sum of all output (completion) tokens over the course of a conversation.
Max retry attempts	The number of times DIAL Core will retry a connection in case of upstream errors (e.g. on timeouts or 5xx responses).
Hashing Order	Specifies the order in which parts of a chat completion request—like the tools used and the chat messages — are combined to create a unique fingerprint (hash) for that request. By default, it checks the tools first and then the messages. This fingerprint helps the system recognize when different requests share the same beginning, so it can reuse previous work and speed things up through caching, which is especially important because the system can only cache information for requests that start the same way. Refer to DIAL Core documentation for details.

Cost Configuration

Enables real-time cost estimation and quota enforcement. Powers the telemetry dashboard with per-model spending metrics.

Field	Required	Description
Cost unit	Yes	Base unit for billing. Available values: None: Disables all cost tracking for this model. Tokens: Every token sent or received by the model is counted towards your cost metrics. Char without whitespace: Tells DIAL to count only non-whitespace characters (letters, numbers, punctuation) in each request as the billing unit.
Prompt price	Yes	Cost per unit for prompt tokens.
Completion price	Yes	Cost per unit for completion tokens (chat responses).

Features

In the Features tab, you can enable, disable, or override optional capabilities for a specific model. You can use model's features to tailor DIAL Core’s Unified Protocol behavior—turning features on when your model supports them, or off when it doesn’t.

Model features apply per AI model, controlling what the model endpoint itself supports (e.g. whether GPT-4 can accept system prompts or function calls).

TIP: Enable only the features you need. Extra toggles can cause errors if upstream doesn’t support them. After setting a custom endpoint, test it via a simple API call to confirm accessibility and authentication.

Custom Endpoints

Some models adapters expose specialized HTTP endpoints for tokenization, rate estimation, prompt truncation, or live configuration. You can override the default Unified Protocol calls by specifying them in this section.

Field	Description
Rate endpoint	URL to invoke the model’s cost‐estimation or billing API. Call an endpoint that returns token counts & credit usage. Override if your adapter supports a dedicated "rate" path.
Tokenize endpoint	URL to invoke a standalone tokenization service. Use when you need precise token counts before truncation or batching. Models without built-in tokenization require this.
Truncate prompt endpoint	URL to invoke a prompt‐truncation API. Ensures prompts are safely cut to max context length. Useful when working with very long user inputs.
Configuration endpoint	URL to fetch JSON Schema describing settings of the DIAL model. DIAL Core exposes this endpoint to DIAL clients as GET v1/deployments/<deployment name>/configuration. DIAL client must provide a JSON value corresponding to the configuration JSON Schema in a chat completion request in the custom_fields.configuration field.

Feature Flags (Toggles)

Model toggles ensure you don’t accidentally send unsupported parameters to a given model.

Each toggle corresponds to a capability in the Unified Protocol. Enable them only if your model and adapter fully support that feature.

Toggle	Description
System prompt	Allows injecting a system‐level message (the "agent’s instructions") at the start of every chat. Disable for models that ignore or block system prompts.
Tools	Enables the tools (a.k.a. functions) feature for safe external API calls. Enable if you plan to use DIAL toolsets or function calling.
Temperature supported	Enables the temperature parameter to control randomness in model deployment's output.
Seed	Enables the seed parameter for deterministic output. If specified, our system will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result. Determinism is not guaranteed, and you should refer to the system_fingerprint response parameter to monitor changes in the backend.
URL Attachments	Allows passing URLs as attachments (images, docs) to the model. Can be required for image-based or file-referencing prompts.
Folder Attachments	Enables attaching folders (batching multiple files).
Assistant attachment in request	Indicates whether the model deployment supports attachments chat completion request messages form the role=assistant. When enabled, DIAL Chat must preserve attachments in messages from assistants, instead of removing them. The feature is especially useful for models that can generate attachments as well as take attachments as an input. A typical example of such a model is an image-editing model.
Accessible by request key	Indicates whether the deployment is accessible using a per-request API key.
Content parts	Indicates whether the model deployment supports requests with content parts or not. Content parts in a chat completion request allow sending to AI model a message consisting of different types of content, such as text, images, or other media, within a single request which enables more rich and flexible interaction with a model.
Cache	Whether the deployment supports LLM caching.
Auto caching	Indicates whether the deployment supports automatic caching, where it's possible.
Parallel tool calls	Indicates whether the deployment supports parallel_tool_calls parameter in a chat completion request which enables parallel function calling when using a tool.
Support comment in rate response	Indicates whether the model supports the field comment in rate response payload.

Roles

You can create and manage roles in the Access Management section or via a direct configuration of DIAL Core.

In the Roles tab, you can define user groups that are authorized to use a specific model deployment and enforce role-based rate and usage limits. This is essential for multi-tenant governance, quota enforcement, and cost control across teams or customers, preventing runaway costs by enforcing a hard ceiling.

Important: if roles are not specified for a specific model deployment, it is available to all users.

• Refer to Access & Cost Control to learn more about access control in DIAL.
• Refer to Roles to lean more about roles in DIAL.
• Refer to tutorials to learn how to use roles to define access and cost control for JWT and API keys

Roles grid

Column	Description
ID	Unique role's identifier.
Display Name	Unique role's name displayed on UI.
Description	Description of the role's purpose (e.g., "DIAL Prompt Engineering Team").
Tokens per minute	Per Minute tokens limit for a specific role. Blank = no limits. Inherits the default value. Can be overridden.
Tokens per day	Daily tokens limit for a specific role. Blank = no limits. Inherits the default value. Can be overridden.
Tokens per week	Weekly tokens limit for a specific role. Blank = no limits. Inherits the default value. Can be overridden.
Tokens per month	Monthly tokens limit for a specific role. Blank = no limits. Inherits the default value. Can be overridden.
Actions	Additional role-specific actions. When Make available to specific roles toggle is off - opens the Roles section in a new tab. When Make available to specific roles toggle is on, you can open the Roles section in a new tab, set Set unlimited, Remove the role from the list or Reset to default limits.

Set Rate Limits

The grid on the Roles screen lists the roles that can access a specific model. Here, you can also set individual limits for selected roles. For example, you can give "Admin" role unlimited monthly tokens but throttle "Developer" to 100,000 tokens/day or allow the "External Partner" role a small trial quota (e.g., 10,000 tokens/month) before upgrade.

To set or change rate limits for a role

1. Click in the desired cell (e.g., Tokens per day for the "ADMIN").
2. Enter a numeric limit or leave blank to enable an unlimited access. Click Reset to default limits to restore default settings for all roles.
3. Click Save to apply changes.

Default Limits

Default limits are set for all roles in the Roles grid by default; however you can override them as needed.

Field	Description
Default tokens per minute	The maximum tokens any user can consume per minute unless a specific limit is in place.
Default tokens per day	The maximum tokens any user can consume per day unless a specific limit is in place.
Default tokens per week	The maximum tokens any user can consume per week unless a specific limit is in place.
Default tokens per month	The maximum tokens any user may consume per month unless a specific limit is in place.

Role-Specific Access

Use Make available to specific roles toggle to define access to the model:

• Off: Model is callable by any authenticated user. All existing user roles are in the grid.
• On: Model is restricted - only the roles you explicitly add to the grid can invoke it.

Add

You can add a role only if Make available to specific roles toggle is On.

1. Click + Add (top-right of the Roles Grid).
2. Select one or more roles in the modal. The list or roles is defined in the Access Management section.
3. Confirm to add role(s) to the table.

Remove

You can remove a role only if Make available to specific roles toggle is On.

1. Click the actions menu in the role's line.
2. Choose Remove in the menu.

Interceptors

DIAL uses Interceptors to add custom logic to in/out requests for models and apps, enabling PII obfuscation, guardrails, safety checks, and beyond.

Refer to Interceptors to learn more.

In the Interceptors tab, you can view configured global interceptors and define local interceptors that will be triggered for the selected model. You can define Interceptors in the Entities → Interceptors section to add them to the processing pipeline of DIAL Core.

Interceptors grid

Column	Description
ID	Unique interceptor identifier.
Order	Execution sequence. Interceptors run in ascending order (1 → 2 → 3...). A request will flow through each interceptor's in this order.Response interceptors are invoked in the reversed order.
Display Name	Alias of the interceptor, matching the Name field in its definition.
Description	Free-text summary from the interceptor's definition, explaining its purpose.
Actions	Additional actions. Open interceptor in a new tab. Remove the selected interceptor from the model's configuration.

Add

Follow these steps to attach one or more interceptors to the model's configuration:

1. Click + Add (in the upper-right of the interceptors grid).
2. In the Add Interceptors modal, choose one or more from the grid of defined interceptors.
3. Apply to append them to the bottom of the list (are added in the same order as selected in the modal).

TIP: If you need a new interceptor, first create it under Entities → Interceptors and then revisit this tab to attach it to the model's configuration.

Reorder

1. Drag & Drop the handle (⋮⋮⋮⋮) to reassign the order in which interceptors are triggered.
2. Release to reposition; order renumbers automatically.
3. Save to lock-in the new execution sequence.

Remove

1. Click the actions menu in the interceptor's row.
2. Choose Remove to detach it from this model.
3. Save to lock-in the interceptors list.

Audit

In the Audit tab, you can monitor key metrics, activities and traces related to the selected language model.

Dashboard

TIP: You can monitor the entire system's metrics in Telemetry.

In the Dashboard tab, you can monitor real-time and historical metrics for the model. You can use it to monitor usage patterns, enforce SLAs, optimize costs, and troubleshoot anomalies.

Control	Description
Time Period	Select the date range for all charts and tables (e.g. last 15 min, 2 days, 7 days, 30 days).
+ Add filter	Filter with options to drill into a specific project.
Auto refresh	Set the dashboard to poll for new data (e.g. every 1 min) or turn off auto-refresh.

System Usage Chart

A time-series line chart of requests throughput over time. You can use it to monitor traffic peaks and valleys, correlate spikes with deployments or feature roll outs.

Key Metrics

Four high-level metrics are displayed alongside the chart. All calculated for the selected time period.

You can use them to:

• Chargeback to internal teams or external customers by "Money".
• Track adoption via "Unique Users".
• Monitor burst traffic with "Request Count".
• Watch token consumption to anticipate quota exhaustion.

Metric	Description
Unique Users	Count of distinct user IDs or API keys that have called this model.
Request Count	Total number of chat or embedding calls routed to this model.
Total Tokens	Sum of prompt + completion tokens consumed by this model.
Money	Estimated spending on this model.

Projects Consumption Table

This table shows the KPIs breakdown by Project. You can use it to compare consumption across multiple projects.

Column	Description
Project	The project utilizing this model.
Request Count	Number of calls directed to the model.
Prompt tokens	Total tokens submitted in the prompt portion of requests.
Completion tokens	Total tokens returned by the model as responses.
Money	Estimated costs.

Traces

TIP: You can monitor the entire system's traces in Usage Log.

In this tab, you can see individual traces, each representing a single end-to-end interaction of a DIAL entity with the selected model.

Column	Description
Completion Time	Timestamp when the trace finished processing (end-to-end interaction).
Trace ID	Unique identifier of the trace (one end-to-end interaction).
Topic	Auto-generated subject/title summarizing the trace.
Reactions	Indication of user reactions presence (like/dislike) for the trace.
Cached prompt tokens	Number of prompt tokens served from cache (prompt-caching).
Prompt tokens	Number of tokens in the prompt sent to the model for this trace.
Completion tokens	Number of tokens generated by the model as output for this trace.
Deployment price	Cost attributed to the selected deployment for this trace.
Total price	Total cost of the trace.
Number of request messages	Number of discrete request messages that were included in the trace.
Deployment ID	Identifier of the DIAL deployment used to serve this trace.
Parent Deployment ID	Identifier of the parent deployment (e.g., application that was using the underlying model).
Model	Identifier of the underlying model used to carry out the trace.
Project	Project to which this trace associated in DIAL.
Upstream	The upstream endpoint (e.g., completions endpoint of the model).
Execution path	Execution path of the trace.
User	Identifier of the end user who initiated the trace.
User title	Name of the user (if available).
Language	Language detected in the trace (e.g., en).
Duration	Total end-to-end duration of the trace from first request to completion.
Response ID	Identifier of the response object returned by the model for this trace.
Conversation ID	Identifier of the conversation/session this trace belongs to.
Code span ID	Identifier of a specific code execution span associated with the trace (if any).
Code span parent ID	Identifier of the parent span for a code execution span (if any).

Conversations

TIP: You can monitor all usage sessions in Usage Log.

In Conversations, you can see individual traces grouped into end‑to‑end conversation sessions.

Column	Description
Last activity	Timestamp of the most recent trace within the conversation.
Conversation ID	Unique identifier of the user session that groups related traces.
Topic	Auto-generated subject summarizing the conversation.
Cached prompt tokens	Count of prompt tokens served from cache across the conversation.
Prompt tokens	Total number of request/prompt tokens sent to the model across all traces in the conversation.
Completion tokens	Total number of tokens generated by the model across all traces in the conversation.
Total price	Aggregated cost for the conversation.
Number of request messages	Total number of discrete request messages included in the conversation.
Deployment ID	Identifier of the deployment associated with the conversation.
Project	Project to which the conversation associated in DIAL.
User	Identifier of the end user who initiated the conversation.
User title	Name of the user (if available).
Language	Detected language for the conversation (e.g., en).

Activities

The Activities section provides detailed visibility into all changes made to the selected model. This section mimics the functionality available in the global Audit → Activities menu, but is scoped specifically to the selected model.

Activities List Table

Field	Description
Activity type	Action performed on the model (e.g., Create, Update, Delete).
Time	Timestamp indicating when the activity occurred.
Initiated	Email address of the user who performed the activity.
Activity ID	Unique identifier for the logged activity, used for tracking and auditing.
Actions	Available actions: - View details: Click to open a new screen with activity details. Refer to Activity Details to learn more. - Resource rollback: click to restore a previous version. Refer to Resource Rollback for details.

Activity Details

The Activity Details view provides a detailed snapshot of a specific change made to a model.

To open Activity Details, click on the three-dot menu (⋮) at the end of a row in the Activities grid and select “View Details”.

Element/Section	Description
Activity type	Type of the change performed (e.g., Update, Create, Delete).
Time	Timestamp of the change.
Initiated	Identifier of the user who made the change.
Activity ID	Unique identifier for the specific activity tracking.
Comparison	Dropdown to switch between showing all parameter or changed only.
View	Dropdown to switch for selection between Before/After and Before/Current state.
Parameters Diff	Side-by-side comparison of model fields values before and after the change. Color-coding is used to indicate the operation type (Update, Create, Delete).

Resource Rollback

Use Resource Rollback to restore the previous version of the selected activity. A rollback leads to generation of a new entry on the audit activity screen.

JSON Editor

Advanced users with technical expertise can work with the model properties in a JSON editor view mode. It is useful for advanced scenarios of bulk updates, copy/paste between environments, or tweaking settings not exposed on UI.

TIP: You can switch between UI and JSON only if there are no unsaved changes.

In JSON editor, you can use the view dropdown to select between Admin format and Core format. Note, that these formatting options are for your convenience only and do not render properties as they are defined in DIAL Core. After making changes, the Sync with core indicator on the main configuration screen will inform you about the synchronization state with DIAL Core.

Working with JSON Editor

1. Navigate to Entities → Models, then select the model you want to edit.
2. Click the JSON Editor toggle (top-right). The UI reveals the raw JSON.
3. Chose between the Admin and Core format to see and work with properties in the necessary format. Note: Core format view mode does not render the actual configuration stored in DIAL Core but the configuration in Admin service displayed in the DIAL Core format.
4. Make changes and click Save to apply them.
5. After making changes, the Sync with core indicator on the main configuration screen will inform you about the synchronization state with DIAL Core.

Delete

Use the Delete button in the Configuration screen toolbar to permanently remove the selected language model.