General settings manage project membership, authentication keys, model availability, runtime behavior, data lifecycle, compile-time variables, and localization assets.
Members
The Members page lets you view and manage who has access to your project and what they can do.
Navigation: Project → Settings → Members
The page displays a table of all project members with name, email, role, join date, and a Remove action. To add a new project member, click Add Member, select an existing workspace member, choose a role, and save.
Project roles
| Role | Capabilities |
|---|
| Admin | Full access: manage members, settings, agents, deployments. |
| Developer | Create and modify agents, tools, workflows, imports, and project resources. |
| Tester | Read project resources, create and read sessions, run simulations, view analytics. |
| Viewer | Read-only access to project resources, sessions, and analytics. |
API Keys
The API Keys page lets you create and manage API keys for programmatic access to the project runtime.
Navigation: Project → Settings → API Keys
Tabs
| Tab | Purpose |
|---|
| SDK Keys | Keys that client-side SDKs and web widgets use to interact with the project runtime. |
| Platform Keys | Keys for server-to-server integrations and administrative API access. |
Use separate keys for each environment (development, staging, production) and rotate them regularly.
Models
The Model Configuration page lets you configure which LLM models are available for agents in this project.
Navigation: Project → Settings → Models
Click Add from Catalog to browse models from your workspace catalog. The first model you add becomes the default for new agents. Click Configure Workspace to manage workspace-level model providers and registrations.
Each model entry shows the model name, provider, supported capabilities (chat, function calling, vision, streaming), token limits, and pricing information.
Runtime Configuration
The Runtime Configuration page centralizes the behavioral controls that govern how your agent processes input, handles multi-intent turns, infers missing field values, converts currencies, generates filler messages, protects user data, and validates field values at runtime. Changes take effect for all agent deployments within the project.
Navigation: Project → Settings → Runtime Config
Use the Reset to Defaults button in the top-right corner to revert all settings to their factory values. Click Save to apply any changes.
Each configuration group appears as a collapsible card. Click a card header to expand or collapse it.
Extraction Pipeline
The Extraction Pipeline section controls how the platform extracts structured field values from raw user messages.
| Field | Description |
|---|
| Extraction Strategy | Determines the method the platform uses to extract field values from user input. auto selects the best-fit strategy. |
| Correction Detection | Sets the method the platform uses to detect when a user corrects a previously provided answer. ml uses a machine-learning classifier. |
| NLU Provider | Selects the NLU provider for entity extraction and intent detection. standard uses the platform’s built-in NLU engine. |
| Sidecar Timeout (ms) | Maximum time in milliseconds the platform waits for a sidecar response before timing out. Default: 500. |
| Circuit Breaker Threshold | Number of consecutive sidecar failures that trigger the circuit breaker, bypassing the sidecar until it recovers. Default: 5. |
| Field | Description |
|---|
| Enable Multi-Intent | Toggles multi-intent detection on or off. When enabled, the platform attempts to identify and act on multiple intents in a single message. |
| Strategy | Defines the execution order for detected intents. primary_queue processes intents in priority order. |
| Unknown Relationship Strategy | Fallback strategy when the platform can’t determine the relationship between detected intents. parallel processes all simultaneously. |
| Max Intents | Maximum number of intents the platform processes in a single turn. Default: 3. |
| Confidence Threshold | Minimum confidence score (0–1) required to act on a detected intent. Default: 0.6. |
| Queue Max Age (ms) | Maximum time in milliseconds a queued intent remains eligible for processing. Default: 600000. |
| Field | Description |
|---|
| Confidence Threshold | Minimum confidence score (0–1) required to accept an inferred field value. Default: 0.8. |
| Require User Confirmation | When enabled, the agent presents inferred values to the user for confirmation before applying them. |
| Model Tier | Selects the LLM tier for inference calls. fast uses a lower-latency model optimized for speed. |
| Max Fields Per Pass | Maximum number of fields the platform attempts to infer in a single LLM call. Default: 3. |
| Field | Description |
|---|
| Currency Mode | Sets the conversion mode. static uses fixed exchange rates configured in the platform rather than live API-based rates. |
Experimental Feature — Read Before Enabling
- Requires a configured
tool_selection model in your LLM provider settings.
- Adds one additional LLM call before each reasoning turn, typically 200–500 ms.
- If the pipeline model fails three consecutive times, the circuit breaker bypasses the pipeline for 60 seconds.
| Field | Description |
|---|
| Enable Pipeline | Activates the pre-reasoning classifier and tool filter. Disabled by default. Enable only after configuring a tool_selection model. |
| Field | Description |
|---|
| Fillers Enabled | Master toggle for the filler system. When off, the platform emits no filler messages. |
| Chat Fillers | When enabled, filler messages appear as transient status_update messages in chat clients. |
| Voice Fillers | When enabled, the agent speaks filler messages aloud on voice channels while processing. |
| Chat Delay (ms) | Minimum elapsed processing time before the platform emits a static chat filler. Default: 1200. |
| Voice Delay (ms) | Minimum elapsed processing time before the platform emits a static voice filler. Default: 500. |
| Cooldown (ms) | Minimum interval between consecutive static filler emissions in the same turn. Default: 3000. |
| Max Per Turn | Maximum number of filler messages per agent turn. Default: 5. |
| Status Tags | When enabled, the platform surfaces <status> tags that the response model emits inline as filler messages. |
| Generated Fillers | When enabled, the platform uses a lightweight LLM call to generate contextual filler messages. Requires Filler Model. |
| Filler Model | The LLM the platform uses for contextual filler generation. Defaults to the project’s runtime default model. |
| Conversation History | Number of recent messages (0–20) included in the filler generation prompt for context-aware fillers. Default: 0. |
| Previous Fillers | Number of previously emitted fillers (0–20) included in the prompt to avoid repetition. Default: 0. |
| Filler Prompt | Optional prompt-library override for contextual filler generation. Supports {{userMessage}}, {{conversationHistory}}, and {{previousFillers}} placeholders. |
| Field | Description |
|---|
| Enable PII Protection | Activates detection and redaction of PII types across conversations. Baseline credential scrubbing stays active even when off. |
| Redact Input | When enabled, the platform redacts PII in user messages before sending them to the LLM. |
| Redact Output | When enabled, the platform redacts PII in agent responses before delivering them to the user. |
Project Canonical tables defined here are the recommended source of truth for field validation. Agent-local LOOKUP_TABLES in individual agent configurations remain available for backward compatibility.
Data Retention
The Data Retention page configures how long eval transcripts, eval scores, and production score rows remain available for this project.
Navigation: Project → Settings → Data Retention
Retention categories
| Category | Description | Default |
|---|
| Eval conversations | Retention period for evaluation conversation transcripts. | 730 days |
| Eval scores | Duration for which the system stores evaluation score records. | 730 days |
| Production scores | Availability period for production scoring data. | 365 days |
| Synthetic eval runs | Retention period for synthetic evaluation run data. | 30 days |
| Field | Description |
|---|
| Eval conversation transcript TTL | Number of days to retain evaluation conversation transcripts. |
| Eval score TTL | Number of days to retain evaluation score records. |
| Production score TTL | Number of days to retain production scoring data. |
| Synthetic eval TTL | Number of days to retain synthetic evaluation run data. |
Config Variables
The Config Variables page lets you define key-value pairs that the system resolves at compile time through {{config.KEY}} syntax.
Navigation: Project → Settings → Config Variables
Use config variables to store shared values such as API endpoints, feature flags, and persona-specific content that agents reference across the project. The page shows all defined variables with a filter-by-key search and namespace grouping. Click Namespaces to organize variables into logical groups.
Add a Variable
Click Add Variable to create a new entry. Each variable includes the following fields:
| Field | Description |
|---|
| Key | Unique identifier for the variable (for example, API_BASE_URL). Reference in code as {{config.KEY}}. |
| Value | The value you assign to the key, which the platform resolves at compile time. |
| Namespaces | Logical grouping for the variable. Defaults to Auto. |
| Description | Optional description explaining the variable’s purpose. |
Config variables resolve at compile time. Changes require recompilation to take effect.
Localization
The Localization page lets you manage locale JSON assets with a full-width editor and sync them through the existing Git integration.
Navigation: Project → Settings → Localization
The page displays the total number of assets, locales, and shared assets. The platform stores locale assets as project-level JSON files and exports them to Git under the same path contract that project import/export uses (for example, locales/en/_shared.json or locales/fr/booking_agent.json). If Git isn’t connected, a status indicator shows Git not connected with a link to Open Git Settings.
Create a Localization Asset
Click New Asset to open the asset editor. Complete the following fields:
| Field | Description |
|---|
| Relative Path | The locale file path in canonical locale/asset.json format (for example, en/_shared.json). Keep paths in this shape so Git, export, and import round-trip cleanly. |
| Description | Optional context for translators and reviewers. |
| JSON Editor | Full-width code editor for the locale JSON content. Edit the asset directly in the browser. |
