> ## Documentation Index
> Fetch the complete documentation index at: https://test-8ad8522e-docs-compliance-guide-refine.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.
# Console
> An AI SRE session holds one complete conversation between you and the agent, including messages, streaming responses, tool calls, and artifacts. This page covers creating and managing sessions, sending messages, previewing artifacts, context compaction, and team binding.
**Private beta**: AI SRE is currently in private beta and available to invited accounts only. To join the whitelist test, contact the Flashduty sales team to request access; features and the UI may change during the beta.
## Overview
***
A session is one complete conversation between you and AI SRE. It holds every message you send, the agent's streaming replies, tool calls made along the way, and any artifacts the agent produces (such as code, reports, charts, or Skill archives).
Each session is fully independent, with its own context, bound team, and environment. You switch between sessions in the left sidebar, and exchange messages, read replies, and view artifacts in the central chat area.
Sessions are isolated from one another: context, bound team, and environment do not affect each other. Switching sessions does not interrupt a turn that is already running — AI SRE keeps writing progress to the session, so when you return you can still see the streaming output.
## Creating and Managing Sessions
***
The left sidebar is the single entry point for sessions. Click **New Chat** to start a fresh session. The list is sorted by most recent activity in descending order; only the most recent entries are shown initially, and older history is revealed incrementally with **Show more**.
### Search and Filter
The search box at the top filters sessions by name. When there are no results, it displays **No matching chats found**.
Click the **Filter** icon in the upper-right corner of the list to open the filter panel and combine the dimensions below. When any non-default filter is active, a small dot appears on the filter button as a reminder.
Dimensions available in the filter panel:
| Dimension | Options | Notes |
| --------------- | --------------------------------- | ---------------------------------------------------------------------------------------------- |
| Scope | All / Personal / Team | After selecting **Team**, you can search and multi-select specific teams from an inline list |
| Status | Active / Archived / All | Defaults to showing only **Active** sessions; switch to **Archived** to view archived sessions |
| Recent activity | All / 24 hours / 7 days / 30 days | Narrows results by the session's most recent activity time |
The panel footer provides **Reset** (restore default filters) and **Done** (close the panel).
### Per-Session Actions
Hover over a session row to reveal the pin and archive actions. A pinned session displays a persistent pin icon to the left of its name.
| Action | Entry point | Notes |
| ------------------- | ------------------------------------- | --------------------------------------------------------------------------------------------------------------- |
| Pin / Unpin | Inline pin button on hover | Pinned sessions appear at the top of the list |
| Archive / Unarchive | Inline archive button on hover | Archived sessions are hidden from the active list by default; switch to **Archived** in the filter to find them |
| Rename | Click the chat title to edit in place | Press Enter or click away to confirm; press Esc to cancel; maximum 60 characters |
Hovering over a session row for a moment shows a tooltip with the full session name, the associated team, and the exact timestamp — useful when the name is truncated and you need to confirm you have the right session.
### List Status Indicators
Each row shows one mutually exclusive indicator on the right:
| Indicator | Meaning |
| ----------------- | ---------------------------------------------------------------------------------------------------------- |
| Spinning circle | The agent in this session is running (a turn is in progress) |
| Blue dot (unread) | The agent has produced new content you have not yet viewed |
| Relative time | When neither of the above applies, the relative time of the last activity is shown (e.g. `5m`, `3h`, `3d`) |
Opening a session clears its unread dot.
## Sending Messages and Streaming Responses
***
Type a message in the input box at the bottom and press Enter to send. The input box supports Markdown and slash commands (type `/` to open the command menu) to trigger built-in skills and commands.
### Attachments and Context References
Click the paperclip button, or drag and drop / paste files directly. Supported formats include images, PDFs, and Office documents (Word / Excel / PowerPoint), up to **20 MB** per file. Screenshots can be pasted directly into the chat.
When you enter AI SRE from an incident, alert, monitor rule, or host page, the related object is embedded into the input box as a **reference capsule** — a small inline tag indicating the kind of object referenced — an incident, alert event, alert, monitor rule, or host — that travels with the message so the agent can start its analysis from that object directly. Click the capsule to open the referenced object in a new tab, or click its close button to remove the reference before sending. A single message can carry multiple references.
When a session starts, the knowledge packs and skills for the bound team are loaded automatically. See Knowledges and Skills for details.
### Real-Time Streaming Output
After you send a message, the agent's reply is streamed back in real time — text appears as it is generated, and tool calls and reasoning steps are rendered as they occur.
The moment you send, the frontend optimistically marks the turn as "running"; the backend's running status takes over after roughly 300 ms, so the running state is not lost even if you navigate away and return.
While a turn is running, **the Send button changes to a Stop button**. Clicking Stop immediately interrupts the current turn: the UI reflects this right away, and the interrupted turn is labeled "Interrupted" and remains visible after a page refresh.
### Queueing Messages While Running
The input box remains active while a turn is running: you can keep typing and send messages, which are queued and executed in order after the current turn completes. Queued messages can be edited or removed before they are sent.
## Tool Calls and Artifacts
***
Tools the agent invokes during a turn (reading and writing files, querying monitors, executing commands, calling MCP tools, etc.) are rendered inline in the conversation as collapsible blocks. Click one to expand and inspect its inputs and outputs; they are collapsed by default to keep the chat readable.
### Artifacts Preview
Files the agent produces are available as artifacts with an inline preview. Click an artifact to open the preview panel on the right, which renders the content by type:
| Type | Preview |
| ------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------- |
| Code (multiple languages) | Syntax highlighting + line numbers |
| Markdown | Rendered view by default; toggle to **Source** |
| HTML | Rendered view by default (iframe sandbox); toggle to **Source** |
| Image | Displayed directly; a retryable error message is shown if loading fails |
| PDF | Rendered in the browser's built-in PDF viewer |
| Skill archive (`.skill`) | Left-side file tree + right-side content; the whole package can be downloaded, and you can **Save Skill** to your account with one click |
The preview panel provides **Copy**, **Download**, and **Close** actions.
Report-type artifacts (such as operational insight reports) can be generated as HTML containing Mermaid diagrams and charts, viewable directly in the rendered view. For operational insight capabilities, see Operational Insight Reports.
### Message Actions
Hover over a message to reveal action buttons:
| Action | Applies to | Notes |
| ------ | ----------------------- | ---------------------------------------------------------------------- |
| Copy | User message / artifact | Copies the message or file content to the clipboard |
| Retry | User message | Restarts a turn using that message |
| Edit | User message | Fills the message back into the input box for editing before resending |
## Context Compaction
***
As a conversation grows longer, the session context approaches the model's context-window limit. AI SRE automatically compacts older conversation history — summarizing it into a digest while preserving recent content — to free up context space without losing critical information.
Compaction is triggered in three ways:
| Trigger | Timing |
| ------------------------- | --------------------------------------------------------------------------- |
| Automatic (before a turn) | Before a turn starts, when context usage exceeds the threshold |
| Automatic (mid-turn) | During a turn, if context continues to grow and crosses the threshold again |
| Manual | You explicitly trigger compaction with the `/compact` command |
### What You Will See
* **Compaction in progress**: A status line reading "Compacting conversation context…" appears in the chat stream, showing elapsed time and progress; it disappears automatically when compaction finishes.
* **Compaction complete**: The conversation remains coherent with no action needed from you. The most direct indicator is the **Context** usage percentage in the chat header dropping — it reflects the current utilization of the context window, and hovering over it shows exact token usage.
* **No compaction needed**: When compaction is unnecessary (for example, the conversation history is too short, or it is already in a compacted state), a manual trigger returns an appropriate message such as "Context does not need compaction" or "Conversation history is too short to compact."
Compaction is transparent to you: what you perceive is a continuous conversation. The agent retains a summary of the compacted content in the background, so subsequent turns can still build on earlier key conclusions.
## Binding a Team
***
When you create a session you can **bind a team** to it. Once bound, the session automatically loads that team's knowledge packs, skills, and MCP servers at startup, giving the agent the team's domain context and capabilities from the very beginning. When no team is bound, the session runs in account scope.
Use the team selector in the new-session input area to choose the team to bind. Your last selection is remembered, so you do not have to repeat it each time.
As soon as the session starts, the knowledge / skill / MCP metadata for "account scope + bound team" is loaded and the agent is ready to use.
When the agent needs knowledge from another team, it reads that team's knowledge directory on demand and mounts that team's knowledge and capabilities as persistent context in the current session — a mount remains active for the lifetime of the session.
The bound team stays with the session: reopening the same session restores the original team binding, and the session's team is also shown in the sidebar tooltip.
Automatic linking between incidents / war rooms and teams is still evolving. You can currently bind a team to a session explicitly; automatic binding in incident scenarios will continue to improve in future updates.
For the rules governing team scope for resources (account scope vs. team scope, visibility, and edit permissions), see the "Scope" section on each resource page.
## Related Pages
***
Learn about AI SRE's positioning, capabilities, and use cases.
Generate team incident-handling and operational insights from session data.
Provide domain knowledge to sessions, loaded by team and mounted on demand across teams.
Reusable skills invoked via slash commands.
Connect external systems via MCP to extend the agent's tool capabilities.
Mention the agent in Slack / Feishu / DingTalk / WeCom to troubleshoot, with automatic war-room diagnosis.