Merge pull request #170 from mrTSB/fix-desktop

Fix Desktop App Cloud Models

desktop/src-tauri/src/lib.rs

@@ -649,7 +649,12 @@ async fn boot_backend(backend: SharedBackend, status: SharedStatus) {
         s.detail = "Installing dependencies...".into();
     }
     let _ = tokio::process::Command::new(&uv_bin)
-        .args(["sync", "--extra", "server"])
+        .args([
+            "sync",
+            "--extra", "server",
+            "--extra", "inference-cloud",
+            "--extra", "inference-google",
+        ])
         .stdout(std::process::Stdio::null())
         .stderr(std::process::Stdio::null())
         .current_dir(root)
@@ -1124,6 +1129,15 @@ async fn save_cloud_key(key_name: String, key_value: String) -> Result<(), Strin
         let _ = std::fs::set_permissions(&path, std::fs::Permissions::from_mode(0o600));
     }
 
+    // Tell the running server to hot-reload its cloud engine so the user
+    // doesn't need to restart the app after entering an API key.
+    let reload_url = format!("http://127.0.0.1:{}/v1/cloud/reload", JARVIS_PORT);
+    let _ = reqwest::Client::new()
+        .post(&reload_url)
+        .timeout(std::time::Duration::from_secs(10))
+        .send()
+        .await;
+
     Ok(())
 }
 

frontend/package-lock.json

@@ -46,6 +46,9 @@
         "typescript": "~5.7.0",
         "vite": "^6.0.0",
         "vite-plugin-pwa": "^1.2.0"
+      },
+      "engines": {
+        "node": ">=20"
       }
     },
     "node_modules/@apideck/better-ajv-errors": {

frontend/src/components/Chat/InputArea.tsx

@@ -243,9 +243,10 @@ export function InputArea() {
         accumulatedContent = 'No response was generated. Please try again.';
       }
       const totalMs = Date.now() - startTime;
-      const serverInfo = useAppStore.getState().serverInfo;
+      const _CLOUD_PREFIXES = ['gpt-', 'o1-', 'o3-', 'o4-', 'claude-', 'gemini-', 'openrouter/', 'MiniMax-', 'chatgpt-'];
+      const engineLabel = _CLOUD_PREFIXES.some(p => selectedModel.startsWith(p)) ? 'cloud' : 'ollama';
       const telemetry: MessageTelemetry = {
-        engine: serverInfo?.engine,
+        engine: engineLabel,
         model_id: selectedModel,
         total_ms: totalMs,
         ttft_ms: ttftMs,

frontend/src/components/CommandPalette.tsx

@@ -223,8 +223,11 @@ export function CommandPalette() {
 
     useAppStore.getState().addLogEntry({
       timestamp: Date.now(), level: 'info', category: 'model',
-      message: `${provider.name} API key ${value ? 'saved' : 'removed'}. Restart the app for cloud models to appear.`,
+      message: `${provider.name} API key ${value ? 'saved' : 'removed'}. Refreshing model list…`,
     });
+
+    // Refresh the model list so cloud models appear immediately.
+    await refreshModels();
   };
 
   const handleKeyDown = (e: React.KeyboardEvent) => {

frontend/tsconfig.tsbuildinfo

@@ -1 +1 @@
-{"root":["./src/app.tsx","./src/main.tsx","./src/vite-env.d.ts","./src/components/commandpalette.tsx","./src/components/errorboundary.tsx","./src/components/layout.tsx","./src/components/optinmodal.tsx","./src/components/setupscreen.tsx","./src/components/systempulse.tsx","./src/components/chat/chatarea.tsx","./src/components/chat/inputarea.tsx","./src/components/chat/messagebubble.tsx","./src/components/chat/micbutton.tsx","./src/components/chat/streamingdots.tsx","./src/components/chat/systempanel.tsx","./src/components/chat/toolcallcard.tsx","./src/components/chat/xrayfooter.tsx","./src/components/dashboard/costcomparison.tsx","./src/components/dashboard/energydashboard.tsx","./src/components/dashboard/tracedebugger.tsx","./src/components/sidebar/conversationlist.tsx","./src/components/sidebar/sidebar.tsx","./src/components/setup/ingestdashboard.tsx","./src/components/setup/readyscreen.tsx","./src/components/setup/setupwizard.tsx","./src/components/setup/sourceconnectflow.tsx","./src/components/setup/sourcepicker.tsx","./src/components/ui/button.tsx","./src/components/ui/dialog.tsx","./src/components/ui/input.tsx","./src/components/ui/select.tsx","./src/components/ui/sonner.tsx","./src/components/ui/tooltip.tsx","./src/hooks/usespeech.ts","./src/lib/api.ts","./src/lib/connectors-api.ts","./src/lib/deep-link.ts","./src/lib/profanity.ts","./src/lib/sse.ts","./src/lib/store.ts","./src/lib/utils.ts","./src/pages/agentspage.tsx","./src/pages/chatpage.tsx","./src/pages/dashboardpage.tsx","./src/pages/getstartedpage.tsx","./src/pages/logspage.tsx","./src/pages/settingspage.tsx","./src/types/connectors.ts","./src/types/index.ts"],"version":"5.7.3"}
+{"root":["./src/app.tsx","./src/main.tsx","./src/vite-env.d.ts","./src/components/commandpalette.tsx","./src/components/errorboundary.tsx","./src/components/layout.tsx","./src/components/optinmodal.tsx","./src/components/setupscreen.tsx","./src/components/systempulse.tsx","./src/components/chat/chatarea.tsx","./src/components/chat/inputarea.tsx","./src/components/chat/messagebubble.tsx","./src/components/chat/micbutton.tsx","./src/components/chat/streamingdots.tsx","./src/components/chat/systempanel.tsx","./src/components/chat/toolcallcard.tsx","./src/components/chat/xrayfooter.tsx","./src/components/dashboard/costcomparison.tsx","./src/components/dashboard/energydashboard.tsx","./src/components/dashboard/tracedebugger.tsx","./src/components/sidebar/conversationlist.tsx","./src/components/sidebar/sidebar.tsx","./src/components/setup/ingestdashboard.tsx","./src/components/setup/readyscreen.tsx","./src/components/setup/setupwizard.tsx","./src/components/setup/sourceconnectflow.tsx","./src/components/setup/sourcepicker.tsx","./src/components/ui/button.tsx","./src/components/ui/dialog.tsx","./src/components/ui/input.tsx","./src/components/ui/select.tsx","./src/components/ui/sonner.tsx","./src/components/ui/tooltip.tsx","./src/hooks/usespeech.ts","./src/lib/api.ts","./src/lib/connectors-api.ts","./src/lib/deep-link.ts","./src/lib/profanity.ts","./src/lib/sse.ts","./src/lib/store.ts","./src/lib/utils.ts","./src/pages/agentspage.tsx","./src/pages/chatpage.tsx","./src/pages/dashboardpage.tsx","./src/pages/datasourcespage.tsx","./src/pages/getstartedpage.tsx","./src/pages/logspage.tsx","./src/pages/settingspage.tsx","./src/types/connectors.ts","./src/types/index.ts"],"version":"5.7.3"}

src/openjarvis/cli/serve.py

@@ -120,10 +120,15 @@ def serve(
             from openjarvis.engine.multi import MultiEngine
 
             cloud = CloudEngine()
+            engine = MultiEngine([(engine_name, engine), ("cloud", cloud)])
+            engine_name = "multi"
             if cloud.health():
-                engine = MultiEngine([(engine_name, engine), ("cloud", cloud)])
-                engine_name = "multi"
                 console.print("  Cloud:  [cyan]enabled[/cyan] (API keys detected)")
+            else:
+                console.print(
+                    "  Cloud:  [yellow]keys set but packages missing[/yellow] "
+                    "(run: uv sync --extra inference-cloud --extra inference-google)"
+                )
         except Exception as exc:
             logger.debug("Cloud engine init failed: %s", exc)
 

src/openjarvis/server/cloud_router.py

@@ -0,0 +1,389 @@
+"""Direct cloud API router — bypasses the engine system entirely.
+
+Reads API keys from ~/.openjarvis/cloud-keys.env at request time so
+it works even when the server was started without cloud keys in its
+environment.  Uses httpx directly so no cloud SDK packages are required.
+"""
+
+from __future__ import annotations
+
+import json
+import os
+from collections.abc import AsyncIterator
+from pathlib import Path
+from typing import Any, Sequence
+
+import httpx
+
+from openjarvis.core.types import Message
+
+# ---------------------------------------------------------------------------
+# Key / provider detection
+# ---------------------------------------------------------------------------
+
+_CLOUD_ENV_FILE = Path.home() / ".openjarvis" / "cloud-keys.env"
+
+_OPENAI_PREFIXES = ("gpt-", "o1-", "o3-", "o4-", "chatgpt-")
+_ANTHROPIC_PREFIXES = ("claude-",)
+_GOOGLE_PREFIXES = ("gemini-",)
+_MINIMAX_PREFIXES = ("MiniMax-",)
+
+
+def _load_keys() -> dict[str, str]:
+    """Read cloud-keys.env from disk every call so live updates are picked up."""
+    keys: dict[str, str] = {}
+    # File first, then fall back to process environment
+    if _CLOUD_ENV_FILE.exists():
+        for raw in _CLOUD_ENV_FILE.read_text().splitlines():
+            line = raw.strip()
+            if line and not line.startswith("#") and "=" in line:
+                k, v = line.split("=", 1)
+                keys[k.strip()] = v.strip()
+    # Process env can override (e.g. during testing)
+    for name in (
+        "OPENAI_API_KEY",
+        "ANTHROPIC_API_KEY",
+        "GEMINI_API_KEY",
+        "GOOGLE_API_KEY",
+        "OPENROUTER_API_KEY",
+        "MINIMAX_API_KEY",
+    ):
+        val = os.environ.get(name)
+        if val:
+            keys[name] = val
+    return keys
+
+
+def get_provider(model: str) -> str | None:
+    """Return the provider for a model name, or None if it's a local model."""
+    if any(model.startswith(p) for p in _OPENAI_PREFIXES):
+        return "openai"
+    if any(model.startswith(p) for p in _ANTHROPIC_PREFIXES):
+        return "anthropic"
+    if any(model.startswith(p) for p in _GOOGLE_PREFIXES):
+        return "google"
+    if any(model.startswith(p) for p in _MINIMAX_PREFIXES):
+        return "minimax"
+    if "/" in model:  # openrouter format: "meta-llama/llama-3-8b"
+        return "openrouter"
+    return None
+
+
+def is_cloud_model(model: str) -> bool:
+    """Return True if the model is served by a cloud provider."""
+    return get_provider(model) is not None
+
+
+# ---------------------------------------------------------------------------
+# Message conversion
+# ---------------------------------------------------------------------------
+
+
+def _to_openai_msgs(messages: Sequence[Message]) -> list[dict[str, Any]]:
+    out = []
+    for m in messages:
+        role = m.role.value if hasattr(m.role, "value") else str(m.role)
+        out.append({"role": role, "content": m.content or ""})
+    return out
+
+
+def _to_anthropic_msgs(
+    messages: Sequence[Message],
+) -> tuple[str, list[dict[str, Any]]]:
+    """Return (system_text, chat_messages) in Anthropic format."""
+    system_text = ""
+    chat: list[dict[str, Any]] = []
+    for m in messages:
+        role = m.role.value if hasattr(m.role, "value") else str(m.role)
+        if role == "system":
+            system_text = m.content or ""
+        else:
+            # Anthropic only allows "user" and "assistant"
+            ar = "user" if role != "assistant" else "assistant"
+            chat.append({"role": ar, "content": m.content or ""})
+    return system_text, chat
+
+
+def _to_google_contents(messages: Sequence[Message]) -> list[dict[str, Any]]:
+    """Convert to Google Gemini content format."""
+    contents = []
+    for m in messages:
+        role = m.role.value if hasattr(m.role, "value") else str(m.role)
+        if role == "system":
+            # Gemini doesn't have a system role in the contents array;
+            # prepend as a user message.
+            contents.append({"role": "user", "parts": [{"text": m.content or ""}]})
+            contents.append({"role": "model", "parts": [{"text": "Understood."}]})
+        elif role == "assistant":
+            contents.append({"role": "model", "parts": [{"text": m.content or ""}]})
+        else:
+            contents.append({"role": "user", "parts": [{"text": m.content or ""}]})
+    return contents
+
+
+# ---------------------------------------------------------------------------
+# Streaming generators
+# ---------------------------------------------------------------------------
+
+
+async def _stream_openai(
+    model: str,
+    messages: Sequence[Message],
+    temperature: float,
+    max_tokens: int,
+    base_url: str = "https://api.openai.com/v1",
+    api_key_name: str = "OPENAI_API_KEY",
+) -> AsyncIterator[str]:
+    keys = _load_keys()
+    api_key = keys.get(api_key_name, "")
+    if not api_key:
+        raise ValueError(f"{api_key_name} not set — add it in the Cloud Models tab")
+
+    payload = {
+        "model": model,
+        "messages": _to_openai_msgs(messages),
+        "temperature": temperature,
+        "max_tokens": max_tokens,
+        "stream": True,
+    }
+
+    async with httpx.AsyncClient(timeout=180) as client:
+        async with client.stream(
+            "POST",
+            f"{base_url}/chat/completions",
+            json=payload,
+            headers={
+                "Authorization": f"Bearer {api_key}",
+                "Content-Type": "application/json",
+            },
+        ) as resp:
+            resp.raise_for_status()
+            async for line in resp.aiter_lines():
+                if not line.startswith("data: "):
+                    continue
+                data = line[6:].strip()
+                if data == "[DONE]":
+                    break
+                try:
+                    chunk = json.loads(data)
+                    delta = chunk["choices"][0]["delta"].get("content") or ""
+                    if delta:
+                        yield delta
+                except Exception:
+                    pass
+
+
+async def _stream_anthropic(
+    model: str,
+    messages: Sequence[Message],
+    temperature: float,
+    max_tokens: int,
+) -> AsyncIterator[str]:
+    keys = _load_keys()
+    api_key = keys.get("ANTHROPIC_API_KEY", "")
+    if not api_key:
+        raise ValueError("ANTHROPIC_API_KEY not set — add it in the Cloud Models tab")
+
+    system_text, chat_msgs = _to_anthropic_msgs(messages)
+    payload: dict[str, Any] = {
+        "model": model,
+        "messages": chat_msgs,
+        "max_tokens": max_tokens,
+        "temperature": temperature,
+        "stream": True,
+    }
+    if system_text:
+        payload["system"] = system_text
+
+    async with httpx.AsyncClient(timeout=180) as client:
+        async with client.stream(
+            "POST",
+            "https://api.anthropic.com/v1/messages",
+            json=payload,
+            headers={
+                "x-api-key": api_key,
+                "anthropic-version": "2023-06-01",
+                "Content-Type": "application/json",
+            },
+        ) as resp:
+            resp.raise_for_status()
+            async for line in resp.aiter_lines():
+                if not line.startswith("data: "):
+                    continue
+                data = line[6:].strip()
+                try:
+                    event = json.loads(data)
+                    if event.get("type") == "content_block_delta":
+                        text = event.get("delta", {}).get("text", "")
+                        if text:
+                            yield text
+                except Exception:
+                    pass
+
+
+async def _stream_google(
+    model: str,
+    messages: Sequence[Message],
+    temperature: float,
+    max_tokens: int,
+) -> AsyncIterator[str]:
+    keys = _load_keys()
+    api_key = keys.get("GEMINI_API_KEY") or keys.get("GOOGLE_API_KEY", "")
+    if not api_key:
+        raise ValueError("GEMINI_API_KEY not set — add it in the Cloud Models tab")
+
+    contents = _to_google_contents(messages)
+    payload: dict[str, Any] = {
+        "contents": contents,
+        "generationConfig": {
+            "temperature": temperature,
+            "maxOutputTokens": max_tokens,
+        },
+    }
+
+    url = (
+        f"https://generativelanguage.googleapis.com/v1beta/models/"
+        f"{model}:streamGenerateContent?alt=sse&key={api_key}"
+    )
+
+    async with httpx.AsyncClient(timeout=180) as client:
+        async with client.stream("POST", url, json=payload) as resp:
+            resp.raise_for_status()
+            async for line in resp.aiter_lines():
+                if not line.startswith("data: "):
+                    continue
+                data = line[6:].strip()
+                try:
+                    chunk = json.loads(data)
+                    parts = (
+                        chunk.get("candidates", [{}])[0]
+                        .get("content", {})
+                        .get("parts", [])
+                    )
+                    for part in parts:
+                        text = part.get("text", "")
+                        if text:
+                            yield text
+                except Exception:
+                    pass
+
+
+# ---------------------------------------------------------------------------
+# Local (Ollama) direct streaming — bypasses engine routing entirely
+# ---------------------------------------------------------------------------
+
+
+def _ollama_host() -> str:
+    return os.environ.get("OLLAMA_HOST", "http://localhost:11434").rstrip("/")
+
+
+async def stream_local(
+    model: str,
+    messages: Sequence[Message],
+    temperature: float = 0.7,
+    max_tokens: int = 1024,
+) -> AsyncIterator[str]:
+    """Stream tokens directly from Ollama, bypassing the engine system."""
+    payload = {
+        "model": model,
+        "messages": _to_openai_msgs(messages),
+        "stream": True,
+        # Disable extended thinking (Qwen3.5 etc.) — when enabled all tokens
+        # go into the 'thinking' field and 'content' stays empty.
+        "think": False,
+        "options": {
+            "temperature": temperature,
+            "num_predict": max_tokens,
+        },
+    }
+    host = _ollama_host()
+    async with httpx.AsyncClient(timeout=300) as client:
+        async with client.stream("POST", f"{host}/api/chat", json=payload) as resp:
+            resp.raise_for_status()
+            async for line in resp.aiter_lines():
+                if not line:
+                    continue
+                try:
+                    data = json.loads(line)
+                    token = data.get("message", {}).get("content", "")
+                    if token:
+                        yield token
+                    if data.get("done"):
+                        break
+                except Exception:
+                    pass
+
+
+async def list_local_models() -> list[str]:
+    """Return Ollama model names directly from the Ollama API."""
+    host = _ollama_host()
+    try:
+        async with httpx.AsyncClient(timeout=10) as client:
+            resp = await client.get(f"{host}/api/tags")
+            resp.raise_for_status()
+            data = resp.json()
+            return [m["name"] for m in data.get("models", [])]
+    except Exception:
+        return []
+
+
+# ---------------------------------------------------------------------------
+# Public entry point
+# ---------------------------------------------------------------------------
+
+
+async def stream_cloud(
+    model: str,
+    messages: Sequence[Message],
+    temperature: float = 0.7,
+    max_tokens: int = 1024,
+) -> AsyncIterator[str]:
+    """Stream tokens from a cloud provider for the given model."""
+    provider = get_provider(model)
+
+    if provider == "openai":
+        async for token in _stream_openai(model, messages, temperature, max_tokens):
+            yield token
+
+    elif provider == "anthropic":
+        async for token in _stream_anthropic(model, messages, temperature, max_tokens):
+            yield token
+
+    elif provider == "google":
+        async for token in _stream_google(model, messages, temperature, max_tokens):
+            yield token
+
+    elif provider == "openrouter":
+        keys = _load_keys()
+        api_key = keys.get("OPENROUTER_API_KEY", "")
+        if not api_key:
+            raise ValueError(
+                "OPENROUTER_API_KEY not set — add it in the Cloud Models tab"
+            )
+        async for token in _stream_openai(
+            model,
+            messages,
+            temperature,
+            max_tokens,
+            base_url="https://openrouter.ai/api/v1",
+            api_key_name="OPENROUTER_API_KEY",
+        ):
+            yield token
+
+    elif provider == "minimax":
+        keys = _load_keys()
+        api_key = keys.get("MINIMAX_API_KEY", "")
+        if not api_key:
+            raise ValueError("MINIMAX_API_KEY not set — add it in the Cloud Models tab")
+        async for token in _stream_openai(
+            model,
+            messages,
+            temperature,
+            max_tokens,
+            base_url="https://api.minimax.io/v1",
+            api_key_name="MINIMAX_API_KEY",
+        ):
+            yield token
+
+    else:
+        raise ValueError(f"Unknown cloud provider for model: {model!r}")

src/openjarvis/server/routes.py

@@ -290,9 +290,19 @@ async def _handle_stream(
     complexity_info=None,
 ):
     """Stream response using SSE format."""
+    from openjarvis.server.cloud_router import (
+        is_cloud_model,
+        stream_cloud,
+        stream_local,
+    )
+
     messages = _to_messages(req.messages)
     chunk_id = f"chatcmpl-{uuid.uuid4().hex[:12]}"
 
+    # Route directly to the right backend — bypasses engine routing entirely
+    # so broken MultiEngine state can never misdirect requests.
+    use_cloud = is_cloud_model(model)
+
     async def generate():
         # Send role chunk first
         first_chunk = ChatCompletionChunk(
@@ -307,13 +317,45 @@ async def _handle_stream(
         yield f"data: {first_chunk.model_dump_json()}\n\n"
 
         try:
-            # Stream content
-            async for token in engine.stream(
-                messages,
-                model=model,
-                temperature=req.temperature,
-                max_tokens=req.max_tokens,
-            ):
+            # Cloud models → direct cloud API (reads keys from disk).
+            # Local models → engine.stream() first so mock engines work in
+            # tests.  Fall back to stream_local() only when the engine would
+            # mis-route the request to a cloud backend (MultiEngine routing
+            # confusion), which is detected by checking the routed engine's
+            # is_cloud attribute.
+            if use_cloud:
+                token_iter = stream_cloud(
+                    model, messages, req.temperature, req.max_tokens
+                )
+            else:
+                # Use engine.stream() by default (preserves mock-engine
+                # compatibility in tests).  Only fall back to stream_local()
+                # when a real MultiEngine would mis-route the local model to a
+                # cloud backend — detected via isinstance so mocks are not
+                # accidentally matched.
+                _use_local_fallback = False
+                try:
+                    from openjarvis.engine.multi import MultiEngine
+
+                    _inner = getattr(engine, "_inner", engine)
+                    if isinstance(_inner, MultiEngine):
+                        _routed = _inner._engine_for(model)
+                        if _routed is not None and getattr(_routed, "is_cloud", False):
+                            _use_local_fallback = True
+                except Exception:
+                    pass
+                if _use_local_fallback:
+                    token_iter = stream_local(
+                        model, messages, req.temperature, req.max_tokens
+                    )
+                else:
+                    token_iter = engine.stream(
+                        messages,
+                        model=model,
+                        temperature=req.temperature,
+                        max_tokens=req.max_tokens,
+                    )
+            async for token in token_iter:
                 chunk = ChatCompletionChunk(
                     id=chunk_id,
                     model=model,
@@ -365,17 +407,11 @@ async def _handle_stream(
         )
         finish_dict = _json.loads(finish_data.model_dump_json())
 
-        # Pull usage from the engine if it tracked it during streaming
-        raw_engine = engine
-        # Unwrap InstrumentedEngine if present
-        if hasattr(raw_engine, "_inner"):
-            raw_engine = raw_engine._inner
-        # Unwrap MultiEngine if present
-        if hasattr(raw_engine, "_engine_for"):
-            raw_engine = raw_engine._engine_for(model)
-        stream_usage = getattr(raw_engine, "_last_stream_usage", None)
-        if isinstance(stream_usage, dict) and stream_usage.get("total_tokens", 0) > 0:
-            finish_dict["usage"] = stream_usage
+        # Tag the finish chunk with the correct engine label.
+        # We use the routing decision (use_cloud) directly rather than
+        # unwrapping the engine chain, which can be in a broken state.
+        finish_dict.setdefault("telemetry", {})
+        finish_dict["telemetry"]["engine"] = "cloud" if use_cloud else "ollama"
 
         if complexity_info is not None:
             finish_dict["complexity"] = complexity_info.model_dump()
@@ -392,9 +428,22 @@ async def _handle_stream(
 
 @router.get("/v1/models")
 async def list_models(request: Request) -> ModelListResponse:
-    """List available models from the engine."""
+    """List locally installed models (Ollama).
+
+    Cloud models are not included here — they live in the Cloud Models tab
+    of the UI and are selected there, not from this endpoint.
+    """
+    from openjarvis.server.cloud_router import is_cloud_model, list_local_models
+
+    # Prefer engine.list_models() so mock engines work in tests.
+    # Filter out any cloud model IDs that may appear via MultiEngine.
+    # Fall back to direct Ollama query only when the engine returns nothing.
     engine = request.app.state.engine
-    model_ids = engine.list_models()
+    all_ids = engine.list_models()
+    model_ids = [m for m in all_ids if not is_cloud_model(m)]
+    if not model_ids:
+        model_ids = await list_local_models()
+
     return ModelListResponse(
         data=[ModelObject(id=mid) for mid in model_ids],
     )
@@ -472,6 +521,63 @@ async def delete_model(model_name: str, request: Request):
     return {"status": "deleted", "model": model_name}
 
 
+@router.post("/v1/cloud/reload")
+async def reload_cloud_engine(request: Request):
+    """Hot-reload cloud API keys and (re-)initialize the cloud engine.
+
+    Called by the desktop app immediately after the user saves a cloud API
+    key so that cloud models become available without a full app restart.
+    """
+    import os
+    from pathlib import Path
+
+    # Re-read ~/.openjarvis/cloud-keys.env and update the running process env.
+    keys_path = Path.home() / ".openjarvis" / "cloud-keys.env"
+    if keys_path.exists():
+        for raw_line in keys_path.read_text().splitlines():
+            line = raw_line.strip()
+            if line and not line.startswith("#") and "=" in line:
+                k, v = line.split("=", 1)
+                os.environ[k.strip()] = v.strip()
+
+    # Try to build a fresh CloudEngine.
+    try:
+        from openjarvis.engine.cloud import CloudEngine
+        from openjarvis.engine.multi import MultiEngine
+
+        cloud = CloudEngine()
+        if not cloud.health():
+            return {
+                "status": "no_cloud",
+                "message": "No cloud models available (check API keys)",
+            }
+    except Exception as exc:
+        return {"status": "error", "message": str(exc)}
+
+    # Locate the innermost engine, working through InstrumentedEngine layers.
+    outer = request.app.state.engine
+    inner = getattr(outer, "_inner", outer)
+
+    if isinstance(inner, MultiEngine):
+        # Replace or insert the cloud entry in the existing MultiEngine.
+        new_engines = [(k, e) for k, e in inner._engines if k != "cloud"]
+        new_engines.append(("cloud", cloud))
+        inner._engines = new_engines
+        inner._refresh_map()
+    else:
+        # Wrap the existing engine (which may be security-wrapped) with a new
+        # MultiEngine that includes the cloud engine.
+        engine_name = getattr(request.app.state, "engine_name", "local")
+        new_multi = MultiEngine([(engine_name, inner), ("cloud", cloud)])
+        if hasattr(outer, "_inner"):
+            outer._inner = new_multi
+        else:
+            request.app.state.engine = new_multi
+        request.app.state.engine_name = "multi"
+
+    return {"status": "ok", "message": "Cloud engine reloaded"}
+
+
 @router.get("/v1/savings")
 async def savings(request: Request):
     """Return savings summary compared to cloud providers.