feat(ai): stream agent replies token-by-token to the room

Closes the cross-language half of token streaming (perf-plan A3). On the
CPU-only box perceived latency is time-to-first-token, so showing the reply
as it generates makes a slow model feel live.

- Agent: OllamaProvider.stream() runs on a worker thread; bridge relays
  cumulative previews as throttled (~5/sec) `_ai:"stream"` control frames,
  then a `done` frame clears the preview as the final persisted chat message
  is posted. Providers without stream() fall back to blocking complete().
- Rust client: new Net::AiStream variant + parse_ai branch; App.ai_stream
  map holds the in-progress text per agent; draw_chat renders it as a dim,
  italic preview bubble below history. Cleared on done and on agent leave.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
leetcrypt
2026-06-02 22:42:08 -07:00
parent 26c651e9ac
commit 69bce5ead8
5 changed files with 116 additions and 20 deletions
+23
View File
@@ -96,6 +96,14 @@ pub enum Net {
name: String,
on: bool,
},
/// Incremental reply text from a streaming AI agent. `text` is the reply so
/// far (cumulative); `done` clears the live preview (the final, persisted
/// chat message arrives separately as a normal `Message`).
AiStream {
name: String,
text: String,
done: bool,
},
/// A local system notice produced off-thread (e.g. async Ollama probe).
Sys(String),
Err(String),
@@ -141,6 +149,9 @@ pub struct App {
pub password: String,
/// AI agents currently generating a reply — drives the "thinking" spinner.
pub ai_typing: std::collections::HashSet<String>,
/// Live, in-progress reply text per streaming agent, shown as a transient
/// preview bubble until the final message lands. Keyed by agent name.
pub ai_stream: std::collections::HashMap<String, String>,
/// Monotonic tick counter used to animate the AI spinner.
pub spin: usize,
/// When set, agents we summon are auto-granted sandbox drive on each launch
@@ -173,6 +184,7 @@ impl App {
error: None,
password: String::new(),
ai_typing: std::collections::HashSet::new(),
ai_stream: std::collections::HashMap::new(),
spin: 0,
agent_sbx_allow: false,
}
@@ -238,6 +250,7 @@ impl App {
if let Some(p) = self.users.iter().position(|u| u.user_id == uid) {
let name = self.users.remove(p).username;
self.ai_typing.remove(&name); // a departed agent isn't thinking
self.ai_stream.remove(&name); // …nor streaming a reply
self.sys(format!("{name} left"));
}
}
@@ -248,6 +261,16 @@ impl App {
self.ai_typing.remove(&name);
}
}
Net::AiStream { name, text, done } => {
if done {
self.ai_stream.remove(&name);
} else {
// Streaming has started → drop the bare "thinking" spinner;
// the live preview now signals the agent is working.
self.ai_typing.remove(&name);
self.ai_stream.insert(name, text);
}
}
Net::SbxStatus {
backend,
ready,
+15 -8
View File
@@ -227,17 +227,24 @@ fn parse_sbx(text: &str, sender: &str) -> Option<Net> {
}
}
/// Parse a decrypted `{"_ai":"typing",...}` frame an AI agent signalling that
/// it is (or has finished) generating a reply, so the UI can show a spinner.
/// Parse a decrypted `{"_ai":...}` frame from an AI agent. `"typing"` toggles the
/// thinking spinner; `"stream"` carries the cumulative reply text for a live
/// preview bubble (`done` clears it once the final message is posted).
fn parse_ai(text: &str) -> Option<Net> {
let v: Value = serde_json::from_str(text).ok()?;
if v["_ai"].as_str()? != "typing" {
return None;
let name = || v["name"].as_str().unwrap_or("ai").to_string();
match v["_ai"].as_str()? {
"typing" => Some(Net::AiTyping {
name: name(),
on: v["on"].as_bool().unwrap_or(false),
}),
"stream" => Some(Net::AiStream {
name: name(),
text: v["text"].as_str().unwrap_or("").to_string(),
done: v["done"].as_bool().unwrap_or(false),
}),
_ => None,
}
Some(Net::AiTyping {
name: v["name"].as_str().unwrap_or("ai").to_string(),
on: v["on"].as_bool().unwrap_or(false),
})
}
/// Parse a decrypted `{"_perm":"acl",...}` frame.
+20 -1
View File
@@ -357,7 +357,26 @@ fn fmt_line<'a>(l: &'a ChatLine, app: &App, theme: &Theme) -> Line<'a> {
fn draw_chat(f: &mut Frame, area: ratatui::layout::Rect, app: &App, theme: &Theme) {
let inner_h = area.height.saturating_sub(2) as usize; // rows inside the border
let text_w = area.width.saturating_sub(2).max(1); // wrap width inside the border
let lines: Vec<Line> = app.lines.iter().map(|l| fmt_line(l, app, theme)).collect();
let mut lines: Vec<Line> = app.lines.iter().map(|l| fmt_line(l, app, theme)).collect();
// Live preview bubbles for agents currently streaming a reply, rendered
// below the committed history. Dim + italic so they read as in-progress;
// replaced by the real message once the agent posts it.
let mut streaming: Vec<(&String, &String)> = app.ai_stream.iter().collect();
streaming.sort_unstable_by_key(|(name, _)| name.as_str());
for (name, text) in streaming {
lines.push(Line::from(vec![
Span::styled(
format!("{name} "),
Style::default().fg(theme.other).add_modifier(Modifier::BOLD),
),
Span::styled("", Style::default().fg(theme.dim)),
Span::styled(
text.as_str(),
Style::default().fg(theme.dim).add_modifier(Modifier::ITALIC),
),
]));
}
// Measure the TRUE wrapped height and scroll to the bottom. Selecting N
// logical lines and letting the Paragraph top-anchor them clips any wrapped