AIP Analyst Workshop widget

AIP Analyst can be embedded as a Workshop widget to provide AI-powered analysis capabilities directly in Workshop modules. The widget supports extensive configuration options to control data access, tool availability, and user interface customization.

Widget configuration

The AIP Analyst widget can be configured to customize the analysis experience for your users. Configuration is organized into several sections that control how the widget behaves and what capabilities are available.

Base configuration

The base configuration controls the fundamental behavior of the AIP Analyst widget:

• Custom system prompt: Provide specific instructions that guide the agent's behavior for this particular widget instance. Use this to set analytical focus, define response style, or establish domain-specific guidelines. This can be a static value or connected to a Workshop variable for dynamic prompts.
• Default model: Override the application default with a specific AI model for this widget. This ensures consistent behavior across all users of your Workshop module.
• Suggested prompts: Define a set of pre-populated prompts that appear when the chat is empty. These help guide users toward common questions or analytical workflows relevant to your use case.

Input configuration

Input configuration allows you to pre-load context and trigger analyses automatically:

• Preloaded resources: Add Foundry resources including object sets, notepad documents, object types, functions, action types, Workshop modules, datasets, and media items. Preloading context gives users immediate access to relevant data without manual searching.
• User message: Connect a Workshop variable to automatically start an analysis. When the variable changes, AIP Analyst begins processing the new query without user intervention. This enables dynamic, event-driven analyses within your Workshop application.

Output configuration

Output configuration enables you to extract analysis results into Workshop variables for use in other parts of your application:

• Last object set: Capture the most recent object set produced during analysis.
• Last user message: Extract the user's most recent question.
• All user messages: Retrieve the complete list of user questions from the session.
• Last analyst message: Capture AIP Analyst's final response.
• All analyst messages: Extract all responses generated by the agent.
• All vega chart specs: Extract all Vega visualization specifications as strings, enabling you to render charts elsewhere in your Workshop module.
• All messages: Retrieve all messages from the session, with an option to include input context items.
• Active tab agent running: A boolean indicating whether the agent is currently running in the active tab. Use this to show loading states or disable inputs while analysis is in progress.

These outputs can drive visualizations, filters, or other logic in your Workshop module.

Interaction configuration

You can configure actions that trigger in response to analysis events:

• On user message sent: Execute a Foundry action each time a user sends a message. The action receives the user's message text and the chat session identifier as inputs. You can optionally display a toast notification when the action runs.
• On agent stopped: Execute a Foundry action when the agent completes its response. The action receives the chat session identifier as input. This is useful for triggering subsequent workflows, such as saving analysis results or notifying other systems.

Tool configuration

Tool configuration allows you to control AIP Analyst's capabilities and scope:

• Default enabled tools: Select which tools are enabled by default when the widget loads. This lets you disable tools that are not relevant to your use case.
• Search scope: Restrict searches by Ontology, object type groups, Compass projects, object type statuses, and object type visibilities. You can also configure the object set semantic search similarity threshold. See Settings for descriptions of each control.

View configuration

View configuration controls which interface elements are visible to users, allowing you to create streamlined experiences tailored to your use case. Available options include:

• Hide tabs: Remove the chat tab headers for a single-session experience.
• Hide PDF export: Remove the PDF export button from the interface.
• Hide outline: Remove the analysis outline sidebar.
• Hide input area: Remove the chat input field, useful for display-only configurations where analysis is triggered by Workshop variables.
• Hide input resources: Hide the pre-loaded resource chips displayed above the chat input.
• Hide configure tools: Remove the tool configuration button.
• Hide record audio: Remove the audio recording button from the input area.
• Hide add context: Remove the manual context addition button.
• Hide model selector: Remove the AI model selector.
• Hide token estimator: Remove the token usage estimator.
• Hide validation mode: Remove the validation mode toggle.
• Hide thinking details: Hide the model's extended thinking output from users.
• Default tools collapsed: Collapse tool results by default, showing only the tool name rather than full results.
• Input placeholder: Set custom placeholder text for the chat input field.
• Empty state configuration: Customize the appearance of the empty chat state with a custom title, description, and icon or image.
• Reset key: Connect a Workshop variable that resets the widget to a fresh session whenever its value changes. Use this to trigger a reset from elsewhere in the module.

Save configuration

The save configuration controls how the widget saves and loads analyses. If analysis saving is disabled, configuring these options will cause the widget to display an error.

• Default save location: Compass folder used as the default save target for analyses created in this widget. Users can still change the location at save time.
• Loaded analysis: Open a specific saved analysis in the widget. You can hard-code a Compass resource, or connect a Workshop variable to load different analyses based on application state.

Session persistence

By default, the AIP Analyst widget keeps draft chat state in memory while the user's browser tab remains open. This lets the widget retain conversation history, context items, and tool results when it is hidden and shown again within the same Workshop module, such as when the widget is placed in a tab or collapsible section. Refreshing or closing the browser tab clears this unsaved draft state.

To reset the chat each time the widget is hidden, enable the Clear chat on unmount option in the view configuration. When enabled, the draft state is discarded when the widget is removed from the page, and a fresh session begins when it is shown again.

You can also force a reset programmatically with the Reset key view option — connect a Workshop variable and the widget will reset to a fresh session whenever the variable's value changes.

Best practices

When configuring the AIP Analyst widget for your Workshop module, consider the following approaches:

• Preload context for faster results: Adding relevant object types, datasets, or object sets in the input configuration eliminates initial search time and guides users toward the right data.
• Use custom system prompts for specialized analysis: Tailor the agent's behavior by providing domain-specific instructions or analytical frameworks in the system prompt.
• Connect variables for automated workflows: Link Workshop variables to the user message input to create dynamic, event-driven analyses that respond to user interactions elsewhere in your module.
• Extract outputs to drive additional logic: Use output variables to incorporate AIP Analyst results into other visualizations, filters, or analytical components.
• Limit scope for focused analysis: Apply Ontology, object type group, and Compass project restrictions when building purpose-specific applications to improve performance and prevent access to irrelevant data.
• Streamline the interface: Hide advanced features and controls when building guided experiences for non-technical users.
• Use interaction hooks for integration: Configure the On user message sent and On agent stopped actions to trigger subsequent workflows, such as logging analysis activity or saving results.
• Provide suggested prompts: Define suggested prompts to guide users toward common questions and reduce the barrier to starting an analysis.