feat(agent): optimize base model prompt — grouped display, comprehensive mapping rules, filename inference

- agent_service._format_base_models: output bullet list instead of
  JSON array for cleaner LLM parsing
- prompt.md mapping section: replace 14-row HF→CivitAI table with
  compact rule set covering 14 mapping paths including new entries
  for HiDream-ai, OnomaAIResearch/Illustrious, ideogram-ai/ideogram,
  Tongyi-MAI/Z-Image-Turbo, and Wan-AI/Wan2.*
- base_model extraction instruction: add guidance to infer from
  model filename, YAML tags, and README body text when YAML
  frontmatter has no explicit base_model:

py/services/llm_service.py

@@ -69,7 +69,7 @@ async def _load_model_catalog() -> Dict[str, List[str]]:
             result[provider_id] = model_ids
 
     _catalog_cache = result
-    logger.info(
+    logger.debug(
         "Loaded model catalog: %d providers, %d total models",
         len(result),
         sum(len(m) for m in result.values()),