Chat Agent Configuration - SubVerse AI

Identity

Field	Type	Default	Description
Name	Text	— (required)	Unique identifier. Lowercase letters, numbers, and underscores only (e.g. `support_bot`). Must start with a letter.
Description	Text	`""`	Internal description of what this agent does.
Architecture	Dropdown	`Prompt Based`	Prompt Based uses a system prompt. Conversational Flow uses a visual node-based builder.
Debug Mode	Toggle	Off	Outputs extra internal reasoning logs. Use during development; disable in production.

Agent Settings

Field	Type	Default	Description
Greeting Message	Text	`""`	The first message the agent sends when a conversation starts. Leave blank if you want the user to write first.
Greeting Type	Dropdown	`Prompt`	Prompt — agent generates the opening message dynamically. Say — agent sends exactly what you typed.
Who Speaks First	Dropdown	`SubVerseAI Agent`	SubVerseAI Agent — agent opens the conversation. User — agent waits for the user to write first.
System Prompt	Text area	Empty	The main system prompt. Write the agent’s role, tone, rules, and behavior here. Use the Refine using AI button to get AI assistance.

Large Language Model Preferences

Field	Type	Default	Description
LLM Model	Dropdown	— (required)	The AI model powering this agent. Each model shows its speed and reasoning ratings.
Thinking Level	Dropdown	`Default`	Extended reasoning depth. Options: Default, Low, Medium, High, Very High. Higher = better reasoning but slower.
Max Tokens	Number	None	Maximum tokens the LLM can generate per response. Leave blank to use the model’s default.
Temperature	Slider	`0.5`	Response creativity. `0.0` = consistent and precise. `1.0+` = more varied and creative.

Session Settings

Field	Type	Default	Description
Communication Method	Dropdown	`Two Way`	Two Way — agent sends and receives messages. One Way — agent only sends (e.g. broadcast mode).
Session Timeout (mins)	Number	None	Minutes of inactivity after which the session ends automatically. Leave blank for no timeout.
Remember Customer Interactions	Toggle	Off	Save a summary of each conversation to memory after the session ends.
Use Customer Interaction Memory	Toggle	Off	Pull relevant past conversation summaries into context at the start of a new session. Enable both for persistent memory across conversations.

Knowledgebase Settings

Field	Type	Default	Description
Knowledge Base	Dropdown	None	Attach a Knowledge Base so the agent can retrieve answers from your documents during a conversation.

Function Settings

Field	Type	Default	Description
Pre Call Tools	Multi-select	Empty	LLM tools that run automatically before the session starts (e.g. fetch customer data).
During Call Tools	Multi-select	Empty	Tools the agent can call mid-conversation (e.g. check order status, send an email).
Post Call Tools	Multi-select	Empty	LLM tools that run automatically after the session ends (e.g. update CRM, send a follow-up).

Agent Security Settings

Field	Type	Default	Description
Allow List (Allowed Callers)	Text area	Empty	Regex patterns for contacts allowed to interact with this agent, separated by commas. Leave empty to allow everyone.
Block List (Blocked Callers)	Text area	Empty	Regex patterns for contacts that are blocked, separated by commas. Takes priority over Allow List.

Post Call Data Analysis

After each conversation, the agent can automatically analyze the transcript and extract structured data.

Field	Type	Description
LLM Model	Dropdown	The AI model used to run the post-session analysis. Can differ from the main agent model.
Parameters	Form / JSON	Define the data points to extract from each conversation. Switch between Form (add parameters one by one) and JSON (paste a raw JSON schema).

Parameter fields:

Field	Description
Parameter Name	The key name for this data point (e.g. `summary`, `user_sentiment`).
Details	Description of what this parameter represents and how to extract it.
Type	Data type: `string`, `boolean`, `number`, etc.
Required	Whether this parameter must be present in every analysis output.