Phase 22: SearXNG web research pipeline + settings layout overhaul

Research pipeline (research_topic tool):
- New service: services/research.py — sub-query generation, SearXNG
  search, URL fetch, deduplication, and LLM synthesis into a note
- 5 sub-queries × 3 pages = up to 15 sources, capped at 12 for synthesis
- Synthesis uses num_ctx=16384 + max_tokens=8192 for long-form output
- Prompt demands 2500+ words, 6+ topic-appropriate sections, detailed prose
- 429 retry with backoff; 1s inter-query sleep; raw_decode JSON parsing

search_web tool (new):
- Lightweight single-query SearXNG search, results returned inline in chat
- LLM answers conversationally in round 1; no note created
- web_search result type with external links in ToolCallCard

Infrastructure:
- llm.py: generate_completion accepts num_ctx override
- config.py: SEARXNG_URL + Config.searxng_enabled()
- docker-compose: OLLAMA_NUM_PARALLEL=2, commented SEARXNG_URL example
- intent.py: search_web and research_topic routing rules

Settings UI:
- 2-column grid layout (small sections pair up, complex span full width)
- Search Test section: live SearXNG query with result preview
- GET /api/settings/search?q= proxy endpoint
- Research button (magnifier) in ChatView input toolbar → popover modal

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

src/fabledassistant/services/llm.py

@@ -208,12 +208,21 @@ async def stream_chat_with_tools(
                     break
 
 
-async def generate_completion(messages: list[dict], model: str, max_tokens: int = 4096) -> str:
+async def generate_completion(
+    messages: list[dict],
+    model: str,
+    max_tokens: int = 4096,
+    num_ctx: int | None = None,
+) -> str:
     """Non-streaming chat completion, returns full response text.
 
     Retries up to 2 times on Ollama 500 errors (cold model loading race).
+    num_ctx overrides the model's context window for this call only.
     """
     last_exc: Exception | None = None
+    options: dict = {"num_predict": max_tokens}
+    if num_ctx is not None:
+        options["num_ctx"] = num_ctx
     for attempt in range(3):
         if attempt > 0:
             delay = 3.0 * attempt
@@ -230,7 +239,7 @@ async def generate_completion(messages: list[dict], model: str, max_tokens: int
                         "messages": messages,
                         "stream": False,
                         "think": False,
-                        "options": {"num_predict": max_tokens},
+                        "options": options,
                     },
                 )
                 resp.raise_for_status()