Agents

Configure AI agents that interact with users and execute tasks

AI Agents are the core of the AGO platform. They interact with users, answer questions, and execute tasks based on your knowledge base and configured tools.

AI Studio - Agents List

Overview

Agents in AGO are intelligent assistants that can:

• Answer questions using your knowledge base
• Execute actions using integrated tools
• Maintain context across conversation threads
• Handle background tasks for long-running operations
• Route requests to appropriate knowledge sources
• Invoke other agents for specialized tasks
• Collect user satisfaction feedback
• Use recent ticket history for personalized responses

Prerequisites

System Requirements

• AGO platform deployed and accessible
• Admin access to configure agents

Knowledge Required

• Understanding of AI/LLM concepts (temperature, tokens)
• Familiarity with your organization’s knowledge sources

Configuration Required

• At least one knowledge source connected
• LLM model configured in AGO Config

---

Agent Types

AGO supports three types of agents, each optimized for different use cases.

Standard Agents

Real-time conversational agents that provide immediate responses by:

• Retrieving relevant documents from knowledge base
• Generating contextual responses
• Streaming responses to users via SSE (Server-Sent Events)
• Using tools when necessary

Best for: Interactive chat, Q&A, customer support

Background Agents

Long-running agents for complex tasks that:

• Process requests asynchronously in the background
• Provide progress updates during execution
• Handle multi-step workflows
• Execute time-consuming operations

How to enable: In the agent settings, toggle Background Agent to enabled.

Progress tracking: Background agent progress can be monitored via the chat interface or programmatically through the API.

Best for: Report generation, data analysis, complex research tasks

Action Approvals

A tool can be marked Require approval in background runs in its builder (see Tools). When a background agent is about to use such a tool — issuing a refund, for example — the run pauses and an approval card appears in the conversation:

• Staff users see which tool the agent wants to use and the exact values it wants to send, with Approve and Reject buttons. Staff members also receive a bell notification.
• Other viewers see that the run is waiting for a decision, without the tool’s data.
• Approve lets the agent execute the action and continue. Reject skips the action; the agent is told it was not approved and concludes accordingly.
• A pending approval expires after 72 hours. The run is then stopped and the conversation shows that the approval expired.

Every decision (who approved or rejected, and when) is recorded and shown in the run’s progress log.

Interrupted Runs

Background runs save their progress as they go. If a run is interrupted — during a deployment, for example — it is not lost: a card appears in the conversation asking a staff member whether to resume the run from its last completed step or stop it. Resuming may re-run the step that was in flight when the interruption happened, which is why a person confirms it rather than the system resuming silently.

Reasoning Agents

Extended reasoning capabilities for complex problem-solving:

• Multiple reasoning iterations for thorough analysis
• Uses dedicated reasoning model from global config
• Ideal for complex logic and multi-step reasoning

How to enable: In the agent settings, toggle Reasoning Agent to enabled and set the Reasoning Iterations value (default: 1).

ℹ️ NOTE: Reasoning agents use the dedicated reasoning model configured in your AGO backend settings, separate from the default LLM.

Best for: Complex problem solving, analysis requiring multiple reasoning steps, decision-making tasks

Router Agents

Router agents transparently route each user message to the most appropriate specialized agent. The routing is invisible to the user — they see responses as if they were speaking directly to the selected specialist.

Best for: Multi-agent orchestration, request triage, routing users to domain-specific specialists

ℹ️ NOTE: An agent cannot be both a router agent and a reasoning agent at the same time.

See the Router Agent page for full configuration details, routing logic, and best practices.

---

Agent Documentation Sections

Agent APIs

Learn how to programmatically send messages to agents and integrate AGO into your applications.

Topics Covered:

• Send message API endpoint
• Request/response formats
• File attachment handling
• Server-Sent Events (SSE) streaming
• Background agent processing
• Error handling and fallback mechanisms

Use Cases:

• Custom chat interfaces
• Mobile app integration
• Workflow automation
• Chatbot embedding

---

Agent Configuration

Configure how agents behave and who can access them:

Agent Permissions

Control which users and groups can access specific agents.

Topics Covered:

• Permission-based agent selection
• User group assignments
• Role-based access control
• Default agent configuration

Agents Homepage Selection

Configure which agents appear on the homepage for different user groups.

Topics Covered:

• Homepage agent display
• Priority ordering
• User-specific agent recommendations
• Custom agent selection logic

---

Agent Capabilities

Knowledge Base Integration

Agents can access and search through:

• Imported documentation (Notion, Confluence, Paligo, Zendesk, etc.)
• Knowledge articles created directly in AGO
• Pinned documents that are always included in context

Configuration options:

• Documents to retrieve: How many documents to fetch for context (default: 8)
• Documents to display: How many to show users in sources (default: 8)
• Enable reranker: Rerank results for better relevance
• Pinned documents: Documents always included in agent context

Tool Usage

Agents can execute tools to:

• Create support tickets
• Query external APIs
• Perform calculations
• Retrieve real-time data
• Execute custom workflows
• Send emails
• Invoke other agents

See Tools Documentation for the complete list of available tools.

Agent-as-Tool

Agents can invoke other agents as tools, enabling:

• Specialization: Create focused agents for specific domains
• Delegation: Route complex queries to specialized agents
• Composition: Build complex workflows from simple agents

Configuration:

Setting	Default	Description
Enable as Tool	Off	Allow other agents to invoke this agent
Tool Description	(empty)	Description shown when used as a tool
Agent Tools	(none)	Other agents this agent can invoke
Share Conversation Context	Off	Pass parent conversation history
Max Call Depth	5	Maximum nesting depth (prevents infinite loops)

⚠️ WARNING: Set the max call depth appropriately to prevent infinite recursion when agents invoke each other.

Context Management

Agents maintain context by:

• Tracking conversation history
• Remembering user preferences
• Linking related threads
• Preserving file attachments

Multi-language Support

Agents support multiple languages through:

• Automatic language detection
• Translated knowledge base content
• Localized responses
• Multi-language document retrieval

Satisfaction Feedback

Collect user feedback after agent responses:

Setting	Default	Description
Enable Satisfaction Feedback	Off	Enable feedback collection after responses
Feedback Question	(empty)	Question to display (max 500 characters)
Helper Text	(empty)	Helper text shown below the feedback buttons
Negative Feedback Action	Show ticket form	What happens when user gives negative feedback

Negative feedback actions:

• ticket_form: Show ticket creation form
• feedback_form: Show detailed feedback form
• message_only: Display a message

Response type (satisfaction_feedback_response_type):

• yes_no (default): Two buttons — Yes / No
• smiley_3: Three smiley faces — happy, neutral, unhappy

Ticket Context Injection

Give your agent awareness of the user’s recent support tickets. When enabled, the agent’s system prompt automatically includes a summary of the user’s ticket history, allowing it to provide more personalized and context-aware responses.

How it works: Before each conversation, AGO retrieves the user’s recent tickets and injects a summary into the agent’s system prompt. The agent sees each ticket’s status, subject, last update date, and a link to the ticket.

Example context injected:

Here are the user's recent support tickets for context:
- [Open] Login issue on mobile app (Last update: Jan 15, 2026) (Link: https://support.example.com/ticket/42)
- [Closed] Password reset request (Last update: Jan 10, 2026)

Setting	Default	Description
Enable Ticket Context	Off	Inject the user’s recent tickets into the agent’s context
Days Limit	7	Only include tickets from the last N days. Leave empty for no time limit

Configuration tips:

• Time limit: Set the days limit to control how far back tickets are included. Use 7 for recent context or leave empty to include all tickets
• Performance: A maximum of 10 tickets are included, ordered by most recent first
• Ticketing system required: The user must have tickets in a connected ticketing system for context to appear

ℹ️ NOTE: Ticket context is only injected when the user is authenticated. Anonymous users will not have ticket context.

---

Configuration Options

Basic Settings

Setting	Required	Description
Name	Yes	Internal identifier (must be unique)
Display Name	No	User-facing name shown in chat
Icon	No	Emoji icon for the agent
Custom Icon	No	Uploaded image for the agent avatar
Status	Yes	Active or inactive
Selectable by users	No	When off, the agent stays active for tools and routing but does not appear in the user-facing agent picker. Default: on
Display Order	No	Position on the homepage
Prompt Template	Yes	The prompt template that defines agent behavior

LLM Settings

Setting	Default	Description
Custom LLM	(global default)	Override the default LLM model for this agent
Temperature	(global default)	Response creativity (0.0–2.0)
Top P	(global default)	Nucleus sampling threshold (0.0–1.0)

ℹ️ NOTE:

• Temperature: Lower values (0.0-0.3) produce consistent, deterministic responses. Higher values (0.7-1.0) allow more creative variation.
• Top P: Controls diversity by limiting token selection to the most probable tokens whose cumulative probability exceeds this threshold.

Knowledge Settings

Setting	Default	Description
Knowledge Sources	(none)	Which knowledge sources this agent searches
Pinned Documents	(none)	Documents always included in agent context
Documents to Retrieve	8	How many documents to fetch for context
Documents to Display	8	How many source documents to show users
Enable Reranker	Off	Rerank results for better relevance
Ignore Source Restrictions	Off	Bypass tool source restrictions

Tool Settings

Setting	Default	Description
Tools	(none)	Tools available to this agent
Agent Tools	(none)	Other agents this agent can invoke as tools

Background/Reasoning Settings

Setting	Default	Description
Background Agent	Off	Run tasks asynchronously in the background
Reasoning Agent	Off	Enable extended multi-step reasoning
Router Agent	Off	Automatically delegate to specialized agents
Default Fallback Agent	(none)	Fallback agent when the router can’t find a match
Reasoning Iterations	1	Number of reasoning cycles

---

Global Agent Settings

These settings in AGO Config affect all agents system-wide. Individual agents can override some of these settings.

System-Wide Configuration

Setting	Default	Description
Auto-add Ticketing Tool	On	Automatically add the ticketing tool to all agents
Default Ticketing Tool Prompt	(see below)	Default instructions for the ticketing tool
FAQ Similarity Threshold	0.85	Threshold for FAQ matching (0.0–1.0)
File Attachments	Off	Allow file uploads in chat messages
Enable Reranker	Off	Enable result reranking globally

Default Ticketing Tool Description

You are the ticketing system. Use this tool when the user wants:
- to talk to a human / call the support
- if you detect frustrations
- the user wants to open a ticket
- the user wants to perform an action that needs to open a ticket
The prerequisite is that the user has previously given information about
its problem otherwise we can't help them with this tool.

Configuring Global Settings

These settings are configured at the system level via the Config API. See the Public API v1 Reference for details on how to update these settings programmatically.

Override Behavior

Global Setting	Per-Agent Override
Enable Reranker	Agent-level reranker toggle
LLM settings	Agent-level Custom LLM, Temperature, Top P
File Attachments	Cannot override per-agent
Ticketing Tool	Managed via agent’s tool assignments

---

---

Troubleshooting

Agent returns "I don't know" for documented topics

Problem: Agent can’t find relevant documents despite content existing in knowledge base.

Solutions:

1. Verify the knowledge source is assigned to the agent
2. Check if the reranker is enabled for better relevance
3. Increase the “Documents to Retrieve” setting to fetch more context
4. Review document chunking - documents may be split poorly
5. Check if content is in the correct language

Agent responses are too creative/inconsistent

Problem: Responses vary significantly for the same question.

Solutions:

1. Lower the Temperature setting (try 0.1–0.3)
2. Lower the Top P setting (try 0.5–0.7)
3. Add pinned documents with authoritative answers

Background agent never completes

Problem: Background agent tasks stay in “processing” state.

Solutions:

1. Check background processing logs for errors
2. Verify the task hasn’t exceeded timeout limits
3. Monitor progress via /message/{id}/progress-stream endpoint
4. Check if external tool calls are hanging

Agent-as-tool invocation fails

Problem: Agent can’t invoke another agent as a tool.

Solutions:

1. Verify the target agent has “Enable as Tool” turned on
2. Check the invoking agent has the target in its Agent Tools list
3. Ensure the max call depth hasn’t been exceeded
4. Review the tool description for clarity

Satisfaction feedback not appearing

Problem: Feedback buttons don’t show after responses.

Solutions:

1. Verify “Enable Satisfaction Feedback” is turned on for the agent
2. Check that the feedback question is not empty
3. Ensure widget version supports feedback

---

API Reference

For programmatic access to agents, see:

• Public API v1 Reference - Agent management and messaging

---

Related

• Router Agent — Automatic message routing to specialist agents
• Prompt Templates — Create and manage prompt templates
• Agent Memory — Configure conversation memory
• Tools — Add capabilities to your agents
• Agent Permissions — Control agent access
• Simulation Testing — Test agent behavior
• Agent Best Practices — Design patterns and tips
• Build Your First Agent — Step-by-step tutorial