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/stores/chat.ts

@@ -17,6 +17,7 @@ import type {
   OllamaStatus,
   RunningModel,
   SendMessageResponse,
+  ToolCallRecord,
 } from "@/types/chat";
 
 export const useChatStore = defineStore("chat", () => {
@@ -26,6 +27,7 @@ export const useChatStore = defineStore("chat", () => {
   const loading = ref(false);
   const streaming = ref(false);
   const streamingContent = ref("");
+  const streamingToolCalls = ref<ToolCallRecord[]>([]);
   const lastContextMeta = ref<ContextMeta | null>(null);
   const models = ref<OllamaModel[]>([]);
   const runningModels = ref<RunningModel[]>([]);
@@ -187,6 +189,12 @@ export const useChatStore = defineStore("chat", () => {
           case "chunk":
             streamingContent.value += event.data.chunk as string;
             break;
+          case "tool_call":
+            streamingToolCalls.value = [
+              ...streamingToolCalls.value,
+              event.data.tool_call as ToolCallRecord,
+            ];
+            break;
           case "done":
             gotDone = true;
             {
@@ -196,12 +204,16 @@ export const useChatStore = defineStore("chat", () => {
                 role: "assistant",
                 content: streamingContent.value,
                 context_note_id: null,
+                tool_calls: streamingToolCalls.value.length
+                  ? [...streamingToolCalls.value]
+                  : null,
                 created_at: new Date().toISOString(),
               };
               if (currentConversation.value?.id === convId) {
                 currentConversation.value.messages.push(assistantMsg);
               }
               streamingContent.value = "";
+              streamingToolCalls.value = [];
               streaming.value = false;
 
               // Update conversation in list
@@ -216,6 +228,7 @@ export const useChatStore = defineStore("chat", () => {
             gotDone = true;
             streaming.value = false;
             streamingContent.value = "";
+            streamingToolCalls.value = [];
             useToastStore().show(
               "Chat error: " + (event.data.error as string),
               "error",
@@ -252,6 +265,7 @@ export const useChatStore = defineStore("chat", () => {
 
     streaming.value = false;
     streamingContent.value = "";
+    streamingToolCalls.value = [];
   }
 
   async function cancelGeneration() {
@@ -357,6 +371,7 @@ export const useChatStore = defineStore("chat", () => {
     loading,
     streaming,
     streamingContent,
+    streamingToolCalls,
     lastContextMeta,
     models,
     runningModels,