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>

src/fabledassistant/services/llm.py

@@ -2,6 +2,8 @@ import json
 import logging
 import re
 from collections.abc import AsyncGenerator
+from dataclasses import dataclass, field
+from typing import Literal
 
 import httpx
 
@@ -98,6 +100,55 @@ async def stream_chat(
                     break
 
 
+@dataclass
+class ChatChunk:
+    """A chunk yielded by stream_chat_with_tools."""
+    type: Literal["content", "tool_calls", "done"]
+    content: str = ""
+    tool_calls: list[dict] | None = None
+
+
+async def stream_chat_with_tools(
+    messages: list[dict],
+    model: str,
+    tools: list[dict] | None = None,
+) -> AsyncGenerator[ChatChunk, None]:
+    """Stream chat completion from Ollama with tool support.
+
+    Yields ChatChunk objects. If the model returns tool_calls, a
+    ChatChunk(type="tool_calls") is yielded. Always ends with
+    ChatChunk(type="done").
+    """
+    payload: dict = {"model": model, "messages": messages, "stream": True}
+    if tools:
+        payload["tools"] = tools
+    async with httpx.AsyncClient(timeout=httpx.Timeout(1800.0, connect=30.0, read=300.0)) as client:
+        async with client.stream(
+            "POST",
+            f"{Config.OLLAMA_URL}/api/chat",
+            json=payload,
+        ) as resp:
+            resp.raise_for_status()
+            async for line in resp.aiter_lines():
+                if not line.strip():
+                    continue
+                data = json.loads(line)
+                msg = data.get("message", {})
+
+                # Content chunks
+                chunk = msg.get("content", "")
+                if chunk:
+                    yield ChatChunk(type="content", content=chunk)
+
+                # Check for tool calls on done
+                if data.get("done"):
+                    tool_calls = msg.get("tool_calls")
+                    if tool_calls:
+                        yield ChatChunk(type="tool_calls", tool_calls=tool_calls)
+                    yield ChatChunk(type="done")
+                    break
+
+
 async def generate_completion(messages: list[dict], model: str) -> str:
     """Non-streaming chat completion, returns full response text."""
     async with httpx.AsyncClient(timeout=httpx.Timeout(1800.0, connect=30.0, read=300.0)) as client:
@@ -166,11 +217,17 @@ async def build_context(
     which notes were included as context.
     """
     exclude_set = set(exclude_note_ids or [])
+    from datetime import date as date_type
     assistant_name = await get_setting(user_id, "assistant_name", "Fable")
+    today = date_type.today().isoformat()
     system_parts = [
         f"You are a helpful assistant named {assistant_name}, integrated into a note-taking and task-tracking app called Fabled Assistant. "
         "Help users with their notes, tasks, and general questions. "
-        "When note context is provided, use it to give relevant answers."
+        "When note context is provided, use it to give relevant answers. "
+        f"Today's date is {today}. "
+        "You have tools available to create tasks, create notes, and search the user's notes. "
+        "Use them when the user asks you to create, add, or find tasks and notes. "
+        "For relative dates like 'Friday' or 'next week', resolve them to YYYY-MM-DD format."
     ]
 
     context_meta: dict = {