Add the assistant: a chat that drives the MCP tools in-process

A provider set under Settings (OpenAI-compatible; key encrypted in
flow-data/ai.json) turns on an Assistant panel in the sidebar. Each turn runs
the FastMCP tools in-process as the person chatting, streams the rounds over
SSE and keeps one transcript per user. The panel floats on any screen and
shares the editor's lane: a settings panel keeps the top half, the chat the
bottom. The MCP client is now built once, for the endpoint and the chat.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>

backend/tests/test_ai.py

@@ -0,0 +1,138 @@
+"""The assistant: who may set it up, and that it acts as the person chatting."""
+
+import json
+from collections.abc import Iterator
+from pathlib import Path
+from typing import Any
+
+import pytest
+from fastapi.testclient import TestClient
+
+from fluksio.ai import agent
+from fluksio.core.config import settings
+
+
+@pytest.fixture
+def ai_files(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> Path:
+    monkeypatch.setattr(settings, "AI_CONFIG_FILE", tmp_path / "ai.json")
+    monkeypatch.setattr(settings, "CHATS_DIR", tmp_path / "chats")
+    return tmp_path
+
+
+def _events(response: Any) -> list[dict[str, Any]]:
+    return [
+        json.loads(line[5:])
+        for line in response.iter_lines()
+        if line.startswith("data:")
+    ]
+
+
+def test_the_provider_is_a_superuser_setting_and_the_key_stays_sealed(
+    client: TestClient,
+    superuser_token_headers: dict[str, str],
+    normal_user_token_headers: dict[str, str],
+    ai_files: Path,
+) -> None:
+    assert client.get(
+        "/api/v1/ai/status", headers=normal_user_token_headers
+    ).json() == {
+        "available": False,
+        "model": None,
+    }
+    body = {"api_base": "http://llm.test/v1", "api_key": "sk-test-123456", "model": "m"}
+    refused = client.put(
+        "/api/v1/ai/config", json=body, headers=normal_user_token_headers
+    )
+    assert refused.status_code == 403
+
+    saved = client.put("/api/v1/ai/config", json=body, headers=superuser_token_headers)
+    assert saved.status_code == 200, saved.text
+    assert saved.json()["api_key_masked"] == "sk-…3456"
+    assert "sk-test" not in (ai_files / "ai.json").read_text()
+    assert client.get(
+        "/api/v1/ai/status", headers=normal_user_token_headers
+    ).json() == {
+        "available": True,
+        "model": "m",
+    }
+    # A save that names no key keeps the one there is.
+    kept = client.put(
+        "/api/v1/ai/config",
+        json={"api_base": "http://llm.test/v1", "model": "m2"},
+        headers=superuser_token_headers,
+    )
+    assert kept.json()["api_key_set"] is True
+    assert kept.json()["model"] == "m2"
+
+
+@pytest.mark.usefixtures("ai_files")
+def test_a_turn_runs_the_tools_as_the_person_chatting(
+    client: TestClient,
+    superuser_token_headers: dict[str, str],
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    client.put(
+        "/api/v1/ai/config",
+        json={"api_base": "http://llm.test/v1", "api_key": "k", "model": "m"},
+        headers=superuser_token_headers,
+    )
+    seen: list[list[dict[str, Any]]] = []
+    answers: Iterator[dict[str, Any]] = iter(
+        [
+            {
+                "role": "assistant",
+                "content": None,
+                "tool_calls": [
+                    {
+                        "id": "call_1",
+                        "type": "function",
+                        "function": {"name": "list_flows", "arguments": "{}"},
+                    }
+                ],
+            },
+            {"role": "assistant", "content": "Counted them."},
+        ]
+    )
+
+    async def fake_completion(**kwargs: Any) -> dict[str, Any]:
+        seen.append(kwargs["messages"])
+        assert any(t["function"]["name"] == "save_flow" for t in kwargs["tools"])
+        return {"choices": [{"message": next(answers)}]}
+
+    monkeypatch.setattr(agent.client, "chat_completion", fake_completion)
+
+    with client.stream(
+        "POST",
+        "/api/v1/ai/chat",
+        json={"message": "How many flows are there?"},
+        headers=superuser_token_headers,
+    ) as response:
+        assert response.status_code == 200
+        events = _events(response)
+
+    assert [e["type"] for e in events] == [
+        "start",
+        "tool_call",
+        "tool_result",
+        "message",
+        "done",
+    ]
+    # The tool went through the REST API with the caller's own token: an
+    # unauthenticated call would have come back as an error the model reads.
+    assert events[2] == {"type": "tool_result", "name": "list_flows", "ok": True}
+    answered = seen[-1][-1]
+    assert answered["role"] == "tool"
+    assert "count" in json.loads(answered["content"])
+    assert seen[-1][0]["role"] == "system"
+
+    transcript = client.get("/api/v1/ai/chat", headers=superuser_token_headers).json()
+    assert [m["role"] for m in transcript] == ["user", "assistant", "tool", "assistant"]
+    assert transcript[2] == {
+        "role": "tool",
+        "content": None,
+        "tool_calls": None,
+        "ok": True,
+        "error": None,
+    }
+    client.delete("/api/v1/ai/chat", headers=superuser_token_headers)
+    assert client.get("/api/v1/ai/chat", headers=superuser_token_headers).json() == []