Add LLM chat integration with streaming responses via Ollama

Phase 4: Full chat system with SSE streaming, note-aware context, and
conversation persistence.

Backend:
- Migration 0005: conversations + messages tables with FKs and indexes
- Conversation/Message SQLAlchemy models with relationships
- LLM service: ensure_model (auto-pull on startup), stream_chat (NDJSON),
  generate_completion, fetch_url_content (HTML stripping), build_context
  (keyword extraction, related note search, URL content injection)
- Chat service: conversation CRUD, save_response_as_note,
  summarize_conversation_as_note
- Chat routes blueprint: 9 endpoints including SSE streaming for messages,
  save/summarize as note, Ollama model listing
- Auto-pull llama3.1 model on app startup (non-blocking)

Frontend:
- apiStreamPost: SSE client using fetch + ReadableStream
- Chat Pinia store with streaming state management
- ChatView: dedicated /chat page with conversation sidebar + message thread
- ChatPanel: slide-out panel with contextNoteId from current route
- ChatMessage: markdown-rendered message bubble with "Save as Note" action
- Updated AppHeader with Chat nav link + panel toggle button
- Updated App.vue to mount ChatPanel with route-derived context
- Added /chat and /chat/:id routes

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

frontend/src/api/client.ts

@@ -48,3 +48,55 @@ export async function apiDelete(path: string): Promise<void> {
     throw new Error(`API error: ${res.status}`);
   }
 }
+
+export async function apiStreamPost(
+  path: string,
+  body: unknown,
+  onChunk: (data: Record<string, unknown>) => void
+): Promise<void> {
+  const res = await fetch(path, {
+    method: "POST",
+    headers: { "Content-Type": "application/json" },
+    body: JSON.stringify(body),
+  });
+  if (!res.ok) {
+    throw new Error(`API error: ${res.status}`);
+  }
+  const reader = res.body?.getReader();
+  if (!reader) throw new Error("No response body");
+
+  const decoder = new TextDecoder();
+  let buffer = "";
+
+  while (true) {
+    const { done, value } = await reader.read();
+    if (done) break;
+
+    buffer += decoder.decode(value, { stream: true });
+    const lines = buffer.split("\n");
+    // Keep the last (possibly incomplete) line in the buffer
+    buffer = lines.pop() || "";
+
+    for (const line of lines) {
+      const trimmed = line.trim();
+      if (trimmed.startsWith("data: ")) {
+        try {
+          const data = JSON.parse(trimmed.slice(6));
+          onChunk(data);
+        } catch {
+          // Skip malformed JSON lines
+        }
+      }
+    }
+  }
+
+  // Process any remaining buffer
+  if (buffer.trim().startsWith("data: ")) {
+    try {
+      const data = JSON.parse(buffer.trim().slice(6));
+      onChunk(data);
+    } catch {
+      // Skip malformed JSON
+    }
+  }
+}