Chat basics
What happens between you hitting Send and the reply landing — composer, agent pick, model resolution, streaming, citations, and how a chat is stored.
4 min read
This page is the mental model for everything in the Chat tab. It names the parts of the composer, traces a single message from key-press to streamed reply, and explains how a chat is stored once it lands. Once you have read it, the rest of the chat pages read as variations on the same flow.
The flow is mostly invisible — Tale stitches a half-dozen subsystems together to make a chat feel like a single conversation — but the seams matter when something behaves unexpectedly. Knowing which subsystem owns which step is the difference between filing a useful bug report and a vague one.
The composer
The composer is the input strip at the bottom of the screen. Three controls matter: the agent picker on the left, the model picker beside it, and the textarea with Send on the right. The agent picker exposes every agent the org has marked Visible in chat, plus a default Assistant when no agent is picked. The model picker exposes every chat-tagged model the agent's policy allows; Auto lets Tale resolve at request time. Attachments come in via paste, drag-and-drop, or the upload control — see Attachments for what is accepted.
The agents picker
The agents picker filters by name as you type; the default is an agentless Assistant that uses the org's default chat model and no extra knowledge or tools. Picking an agent before the first message makes the agent sticky for the whole chat; picking one mid-chat applies it to the next message and everything after. There is no "back to no agent" toggle — pick Assistant to revert. The Agents in chat page covers the rules in detail.
The model picker
The model picker lists models the agent (or the org, when no agent is picked) is allowed to use. Each model carries a tag — Chat, Vision, Image generation, Embedding — that signals what it is good for. Picking a vision model when the message has no image is fine; picking a non-vision model when the message includes an image will silently drop the image. Auto picks the agent's primary; when the primary is rate-limited or unavailable, Tale falls back to whatever the agent's failover order names.
Reply rendering and citations
The reply streams in token by token. Tool calls render as collapsed boxes the user can expand to read what the agent did; Run code outputs land in the Canvas on the right. When the agent retrieves knowledge, citations attach to the sentences they support — hovering over a citation shows the source title; clicking opens the source. The agent's instructions never appear in the rendered reply; they sit one layer down, shaping behaviour rather than text.
Questions from the agent
An agent with the human-input tool can pause mid-task and ask you something — a Question card appears in the chat with the fields the agent needs, and generation waits until you answer. Fill the form and click Submit response, or click Reply differently to push back in free text instead. The answered card stays in the transcript at the point where the question was asked, so the exchange reads in order later. If your answer was wrong or incomplete, click Edit response on the answered card — the form reopens prefilled, and Update response re-runs the agent with the corrected answer superseding the old one. The card keeps every previous answer: flip through the versions with the arrows next to the response, the way edited messages work.
Conversations versus chats
Within Chat, the unit is a chat — that is the word every button and toast uses. The data model behind it is called threads, and the URL slug is threads/$threadId; the docs follow the UI and say "chat" in body prose. The separate Conversations tab (one over in the sidebar) is the customer-channel inbox, not a list of chats. Two senses of "conversation", two surfaces — see Conversations overview for the inbox sense.
History and search
History is the list of every chat the user can resume in this org. New chats appear at the top; selecting one opens the full transcript. Search chat filters History by title; full-text search across message bodies is a per-chat operation, not org-wide. Rename chat sets a custom title that overrides the model-generated one; Delete chat moves the chat into Trash where retention sweeps it after the grace window.
Where this fits
Chat basics is the page everything else in this section refines: Agents in chat goes deeper on the picker, Attachments on what the upload does, Voice mode on the STT and TTS handoffs around the same composer. If you came here to build an agent rather than use one, jump to Agent concepts — the four-knob mental model is the foundation every chat with an agent depends on.