Add LLM tool calling for creating tasks, notes, and searching from chat

Ollama tool/function calling integration allows the LLM to create tasks,
create notes, and search existing notes on behalf of the user during chat.
Multi-round tool loop (max 5 rounds) lets the model execute tools then
produce a natural language response. Tool results are persisted in a new
JSONB column on messages and rendered as compact cards with linked titles.

- Migration 0013: add tool_calls JSONB column to messages
- New services/tools.py: tool definitions + execute_tool dispatcher
- llm.py: ChatChunk dataclass, stream_chat_with_tools(), date in system prompt
- generation_task.py: multi-round tool call loop with SSE tool_call events
- Frontend: ToolCallRecord type, streamingToolCalls in store, ToolCallCard
  component, rendering in ChatMessage and ChatView streaming bubble

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

frontend/src/types/chat.ts

@@ -1,3 +1,10 @@
+export interface ToolCallRecord {
+  function: string;
+  arguments: Record<string, unknown>;
+  result: { success: boolean; type?: string; data?: Record<string, unknown>; error?: string };
+  status: "success" | "error";
+}
+
 export interface Message {
   id: number;
   conversation_id: number;
@@ -5,6 +12,7 @@ export interface Message {
   content: string;
   status?: "complete" | "generating" | "error";
   context_note_id: number | null;
+  tool_calls?: ToolCallRecord[] | null;
   created_at: string;
 }