feat: real token streaming from Ollama (NDJSON) + OpenAI-compatible (SSE)

generate_stream previously did a non-streaming call and emitted the
whole response as one fake token. Now reqwest bytes_stream feeds a
line buffer; every token piece goes out as it arrives via the existing
Channel. SessionLogger's progressive display lights up unchanged.
Per-line parsers are pure fns with unit tests; unparseable lines are
skipped, server error lines bubble.

src-tauri/src/commands/llm_commands.rs

@@ -63,17 +63,16 @@ pub async fn generate_stream(
 
     emit_busy(&app, true);
     tauri::async_runtime::spawn(async move {
-        // For now, we do a non-streaming call and emit the full response as one token
-        // Real SSE streaming from Ollama/OpenAI can be added later
+        // Real token streaming: Ollama NDJSON / OpenAI SSE, one LlmEvent::Token
+        // per piece as it arrives. Falls back to Done carrying the full text.
         let result = if llm::is_ollama(&config.provider, &config.api_url) {
-            call_ollama(&client, &config, &messages, temperature, max_tokens).await
+            call_ollama_stream(&client, &config, &messages, temperature, max_tokens, &channel).await
         } else {
-            call_openai(&client, &config, &messages, temperature, max_tokens).await
+            call_openai_stream(&client, &config, &messages, temperature, max_tokens, &channel).await
         };
 
         match result {
             Ok(text) => {
-                let _ = channel.send(LlmEvent::Token(text.clone()));
                 let _ = channel.send(LlmEvent::Done(text));
             }
             Err(e) => {
@@ -304,4 +303,177 @@ async fn call_openai(
         .first()
         .map(|c| c.message.content.clone())
         .ok_or_else(|| "No response from API".to_string())
+}
+
+// ─── Real streaming (Ollama NDJSON / OpenAI SSE) ─────────────
+// ponytail: shared line-buffer + per-line Value parsing. Typed structs would
+// break on the shape variance across servers (final lines omit message,
+// empty contents, metrics lines) — skipping unparseable lines is the
+// boring-correct choice.
+
+use futures_util::StreamExt;
+
+/// What one parsed stream line yields.
+struct StreamLine {
+    token: Option<String>,
+    done: bool,
+}
+
+/// Parse one Ollama NDJSON line: `{"message":{"content":"…"},"done":false}`.
+fn parse_ollama_line(line: &str) -> Result<Option<StreamLine>, String> {
+    let line = line.trim();
+    if line.is_empty() {
+        return Ok(None);
+    }
+    let v: serde_json::Value = serde_json::from_str(line).map_err(|e| format!("bad NDJSON line: {e}"))?;
+    if let Some(err) = v["error"].as_str() {
+        return Err(err.to_string());
+    }
+    Ok(Some(StreamLine {
+        token: v["message"]["content"].as_str().filter(|s| !s.is_empty()).map(|s| s.to_string()),
+        done: v["done"].as_bool().unwrap_or(false),
+    }))
+}
+
+/// Parse one OpenAI SSE line: `data: {"choices":[{"delta":{"content":"…"}}]}`
+/// or the terminal `data: [DONE]`.
+fn parse_openai_line(line: &str) -> Result<Option<StreamLine>, String> {
+    let line = line.trim();
+    let Some(payload) = line.strip_prefix("data: ") else {
+        return Ok(None); // keep-alive comments / blank lines
+    };
+    if payload == "[DONE]" {
+        return Ok(Some(StreamLine { token: None, done: true }));
+    }
+    let v: serde_json::Value = serde_json::from_str(payload).map_err(|e| format!("bad SSE line: {e}"))?;
+    if let Some(err) = v["error"]["message"].as_str() {
+        return Err(err.to_string());
+    }
+    Ok(Some(StreamLine {
+        token: v["choices"][0]["delta"]["content"].as_str().filter(|s| !s.is_empty()).map(|s| s.to_string()),
+        done: false,
+    }))
+}
+
+/// POST with `stream: true`, emit Token per piece, return the full text
+/// when the stream finishes. `body` is the request JSON minus the stream flag.
+async fn stream_chat(
+    client: &reqwest::Client,
+    url: &str,
+    mut body: serde_json::Value,
+    channel: &Channel<LlmEvent>,
+    parse: fn(&str) -> Result<Option<StreamLine>, String>,
+    bearer: Option<&str>,
+) -> Result<String, String> {
+    body["stream"] = serde_json::json!(true);
+    let mut req = client.post(url).json(&body);
+    if let Some(key) = bearer {
+        req = req.bearer_auth(key);
+    }
+    let res = req.send().await.map_err(|e| format!("stream request failed: {e}"))?;
+    if !res.status().is_success() {
+        let status = res.status();
+        let text = res.text().await.unwrap_or_default();
+        return Err(format!("stream error {status}: {text}"));
+    }
+    stream_from_response(res, channel, parse).await
+}
+
+/// Consume a streaming HTTP response: buffer bytes into lines, parse each
+/// with `parse`, emit Token per piece, Done via the caller's Ok(full text).
+async fn stream_from_response(
+    res: reqwest::Response,
+    channel: &Channel<LlmEvent>,
+    parse: fn(&str) -> Result<Option<StreamLine>, String>,
+) -> Result<String, String> {
+    let mut full = String::new();
+    let mut buf = String::new();
+    let mut stream = res.bytes_stream();
+    while let Some(chunk) = stream.next().await {
+        let chunk = chunk.map_err(|e| format!("stream read failed: {e}"))?;
+        buf.push_str(&String::from_utf8_lossy(&chunk));
+        while let Some(nl) = buf.find('\n') {
+            let line: String = buf.drain(..=nl).collect();
+            match parse(line.trim_end())? {
+                Some(StreamLine { token: Some(t), done }) => {
+                    full.push_str(&t);
+                    let _ = channel.send(LlmEvent::Token(t));
+                    if done {
+                        return Ok(full);
+                    }
+                }
+                Some(StreamLine { token: None, done: true }) => return Ok(full),
+                _ => {}
+            }
+        }
+    }
+    // Stream closed without an explicit done — return what we got.
+    Ok(full)
+}
+
+async fn call_ollama_stream(
+    client: &reqwest::Client,
+    config: &crate::llm::LlmConfig,
+    messages: &[ChatMessage],
+    temperature: f32,
+    max_tokens: u32,
+    channel: &Channel<LlmEvent>,
+) -> Result<String, String> {
+    let url = format!("{}/api/chat", config.api_url.trim_end_matches('/'));
+    let body = json!({
+        "model": config.model,
+        "messages": messages,
+        "options": { "temperature": temperature, "num_predict": max_tokens },
+    });
+    stream_chat(client, &url, body, channel, parse_ollama_line, None).await
+}
+
+async fn call_openai_stream(
+    client: &reqwest::Client,
+    config: &crate::llm::LlmConfig,
+    messages: &[ChatMessage],
+    temperature: f32,
+    max_tokens: u32,
+    channel: &Channel<LlmEvent>,
+) -> Result<String, String> {
+    let url = format!("{}/v1/chat/completions", config.api_url.trim_end_matches('/'));
+    let body = json!({
+        "model": config.model,
+        "messages": messages,
+        "temperature": temperature,
+        "max_tokens": max_tokens,
+    });
+    let bearer = (!config.api_key.is_empty()).then_some(config.api_key.as_str());
+    stream_chat(client, &url, body, channel, parse_openai_line, bearer).await
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn ollama_line_parses_tokens_and_done() {
+        let tok = parse_ollama_line("{\"message\":{\"role\":\"assistant\",\"content\":\"Hel\"},\"done\":false}").unwrap().unwrap();
+        assert_eq!(tok.token.as_deref(), Some("Hel"));
+        assert!(!tok.done);
+        // final line: no message content, done + metrics
+        let fin = parse_ollama_line("{\"done\":true,\"total_duration\":123}").unwrap().unwrap();
+        assert_eq!(fin.token, None);
+        assert!(fin.done);
+        // blank lines are skipped, errors bubble
+        assert!(parse_ollama_line("").unwrap().is_none());
+        assert!(parse_ollama_line("{\"error\":\"model not found\"}").is_err());
+    }
+
+    #[test]
+    fn openai_line_parses_sse() {
+        let tok = parse_openai_line("data: {\"choices\":[{\"delta\":{\"content\":\"lo\"}}]}").unwrap().unwrap();
+        assert_eq!(tok.token.as_deref(), Some("lo"));
+        let fin = parse_openai_line("data: [DONE]").unwrap().unwrap();
+        assert!(fin.done);
+        // non-data lines (keep-alives) skipped; role-only deltas yield no token
+        assert!(parse_openai_line(": ping").unwrap().is_none());
+        let role = parse_openai_line("data: {\"choices\":[{\"delta\":{\"role\":\"assistant\"}}]}").unwrap().unwrap();
+        assert_eq!(role.token, None);
+    }
 }