perf(llm): route background tasks to dedicated model to preserve KV cache

Background tasks (title generation, tag suggestions, project summaries,
RSS classification) were using qwen3:8b and wiping its KV cache after
every response, preventing prefix cache hits on subsequent user messages.

Adds OLLAMA_BACKGROUND_MODEL (default: qwen2.5:0.5b) config var and
routes all background LLM calls to it, keeping qwen3:8b's KV cache
warm between user messages for consistent sub-second TTFT.

Also adds infinite scroll to KnowledgeView (replaces load-more button)
and bakes spaCy en_core_web_sm into the Docker image to eliminate the
pip install on every startup.

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

src/fabledassistant/services/rss_classifier.py

@@ -64,7 +64,7 @@ async def classify_items_batch(
         return {}
 
     if model is None:
-        model = Config.OLLAMA_MODEL
+        model = Config.OLLAMA_BACKGROUND_MODEL
 
     vocab = STANDARD_TOPICS + [t for t in user_include_topics if t not in STANDARD_TOPICS]
     items_block = "\n".join(