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/generation_task.py

@@ -138,7 +138,7 @@ async def _generate_title(messages: list[dict], model: str) -> str:
         },
         {"role": "user", "content": "\n\n".join(conv_lines)},
     ]
-    title = await generate_completion(prompt_messages, model, max_tokens=30)
+    title = await generate_completion(prompt_messages, Config.OLLAMA_BACKGROUND_MODEL, max_tokens=30)
     title = title.strip().strip('"\'').strip()
     return title[:100] if title else ""