feat(cli): support conversational AI follow-ups in interactive mode

src/tai/ai_client.py

@@ -4,6 +4,7 @@ from __future__ import annotations
 
 from collections.abc import Iterator
 from dataclasses import dataclass, field
+from typing import Any, cast
 
 from openai import OpenAI
 
@@ -88,6 +89,20 @@ class AIClient:
             if delta:
                 yield delta
 
+    def stream_messages(self, messages: list[dict[str, str]]) -> Iterator[str]:
+        """Stream a completion from an explicit chat history."""
+        stream = self._client.chat.completions.create(
+            model=self._config.model,
+            max_tokens=self._config.max_tokens,
+            stream=True,
+            messages=cast(Any, messages),
+        )
+
+        for chunk in cast(Iterator[Any], stream):
+            delta = chunk.choices[0].delta.content
+            if delta:
+                yield delta
+
     def summary(self) -> str:
         """Human-readable description of the AI config."""
         return f"host={self._config.host} model={self._config.model}"

src/tai/cli.py

@@ -182,8 +182,28 @@ async def _interactive_loop(
     ai_config: AIConfig,
     report: CollectionReport | None,
 ) -> None:
-    """Run a tiny follow-up loop for collecting and analyzing on demand."""
+    """Run a follow-up loop for collecting and conversational analysis."""
-    console.print("[cyan]Interactive mode:[/cyan] /collect, /analyze, /help, /quit")
+    console.print(
+        "[cyan]Interactive mode:[/cyan] "
+        "ask questions directly, or use /collect, /analyze, /help, /quit"
+    )
+
+    ai = AIClient(ai_config)
+    messages: list[dict[str, str]] | None = None
+
+    def _reset_messages(current_report: CollectionReport | None) -> list[dict[str, str]] | None:
+        if current_report is None:
+            return None
+        return [
+            {"role": "system", "content": build_system_prompt()},
+            {
+                "role": "user",
+                "content": build_user_message(req.issue, current_report),
+            },
+        ]
+
+    if report is not None:
+        messages = _reset_messages(report)
 
     while True:
         try:
@@ -201,6 +221,7 @@ async def _interactive_loop(
 
         if command == "/help":
             console.print("Commands: /collect, /analyze, /help, /quit")
+            console.print("Tip: any non-slash text is treated as a follow-up AI question.")
             continue
 
         if command == "/collect":
@@ -208,6 +229,7 @@ async def _interactive_loop(
             console.print(f"[cyan]Collecting diagnostics:[/cyan] {len(plan)} commands")
             report = await collect_from_plan(session, plan)
             _handle_collection_report(report)
+            messages = _reset_messages(report)
             continue
 
         if command == "/analyze":
@@ -216,10 +238,35 @@ async def _interactive_loop(
                 console.print(f"[cyan]Collecting diagnostics:[/cyan] {len(plan)} commands")
                 report = await collect_from_plan(session, plan)
                 _handle_collection_report(report)
-            _run_analysis(ai_config, req.issue, report)
+            messages = _reset_messages(report)
+            if messages is None:
+                console.print("[red]No diagnostics available to analyze.[/red]")
                 continue
 
-        console.print(f"[yellow]Unknown command:[/yellow] {command}. Try /help")
+            messages.append(
+                {
+                    "role": "user",
+                    "content": "Provide an updated diagnosis from the current diagnostics.",
+                }
+            )
+            response = _stream_conversation(ai, messages)
+            messages.append({"role": "assistant", "content": response})
+            continue
+
+        if report is None:
+            plan = plan_from_request(req)
+            console.print(f"[cyan]Collecting diagnostics:[/cyan] {len(plan)} commands")
+            report = await collect_from_plan(session, plan)
+            _handle_collection_report(report)
+            messages = _reset_messages(report)
+
+        if messages is None:
+            console.print("[red]No diagnostics available to analyze.[/red]")
+            continue
+
+        messages.append({"role": "user", "content": command})
+        response = _stream_conversation(ai, messages)
+        messages.append({"role": "assistant", "content": response})
 
 
 def _handle_probe_result(result: SSHCommandResult) -> None:
@@ -262,6 +309,21 @@ def _run_analysis(ai_config: AIConfig, issue: str, report: CollectionReport) ->
         raise typer.Exit(code=1) from exc
 
 
+def _stream_conversation(ai: AIClient, messages: list[dict[str, str]]) -> str:
+    """Stream a multi-turn AI response and return the final text."""
+    console.print("[cyan]Analyzing...[/cyan]\n")
+    try:
+        chunks: list[str] = []
+        for chunk in ai.stream_messages(messages):
+            chunks.append(chunk)
+        response = "".join(chunks)
+        console.print(Markdown(response))
+        return response
+    except Exception as exc:  # noqa: BLE001
+        console.print(f"[red]AI analysis failed:[/red] {exc}")
+        raise typer.Exit(code=1) from exc
+
+
 def main() -> None:
     """Console script entrypoint."""
     app()

tests/test_ai.py

@@ -116,6 +116,34 @@ def test_stream_yields_chunks() -> None:
     assert result == ["Root ", "cause ", "found."]
 
 
+def test_stream_messages_yields_chunks() -> None:
+    config = AIConfig()
+    client = AIClient(config)
+
+    def _make_chunk(text: str | None) -> MagicMock:
+        delta = MagicMock()
+        delta.content = text
+        choice = MagicMock()
+        choice.delta = delta
+        chunk = MagicMock()
+        chunk.choices = [choice]
+        return chunk
+
+    mock_chunks = [_make_chunk("A"), _make_chunk(None), _make_chunk("B")]
+
+    with patch.object(client._client.chat.completions, "create", return_value=iter(mock_chunks)):
+        result = list(
+            client.stream_messages(
+                [
+                    {"role": "system", "content": "sys"},
+                    {"role": "user", "content": "question"},
+                ]
+            )
+        )
+
+    assert result == ["A", "B"]
+
+
 # ---------------------------------------------------------------------------
 # prompt_builder
 # ---------------------------------------------------------------------------

tests/test_cli.py

@@ -188,7 +188,28 @@ def test_interactive_collect_then_quit(monkeypatch) -> None:  # type: ignore[no-
 def test_interactive_unknown_command_prints_hint(monkeypatch) -> None:  # type: ignore[no-untyped-def]
     _mock_session(monkeypatch)
 
-    commands = iter(["/wat", "/quit"])
+    async def fake_collect_from_plan(_session, _plan) -> CollectionReport:  # type: ignore[no-untyped-def]
+        return CollectionReport(
+            host="ssh.archflux.net",
+            items=[
+                CollectedItem(
+                    name="kernel",
+                    result=SSHCommandResult(
+                        command="uname -a",
+                        exit_code=0,
+                        stdout="Linux test",
+                        stderr="",
+                    ),
+                ),
+            ],
+        )
+
+    commands = iter(["what should I check next?", "/quit"])
+    monkeypatch.setattr("tai.cli.collect_from_plan", fake_collect_from_plan)
+    monkeypatch.setattr(
+        "tai.cli.AIClient.stream_messages",
+        lambda *_args, **_kwargs: iter(["Check logs."]),
+    )
     monkeypatch.setattr("builtins.input", lambda _prompt: next(commands))
 
     runner = CliRunner()
@@ -206,4 +227,5 @@ def test_interactive_unknown_command_prints_hint(monkeypatch) -> None:  # type:
     )
 
     assert result.exit_code == 0
-    assert "Unknown command" in result.stdout
+    assert "Analyzing..." in result.stdout
+    assert "Check logs." in result.stdout