Fix: personas use tier-based model resolution instead of hardcoded defaults"

alpha_factory/personas/hypothesis_hunter.py

@@ -39,16 +39,10 @@ async def generate_hypothesis(
     theme: str,
     retrieved_papers: list[str],
     existing_anomaly_tags: list[str],
-    model: str | None = None,
 ) -> Blueprint:
     """
     Generate a novel alpha hypothesis blueprint.
-
-    Args:
-        llm: LLM client for guided generation
-        theme: The theme to explore (from gap analysis)
-        retrieved_papers: 3 arXiv abstracts from RAG retrieval
-        existing_anomaly_tags: tags already in the library (avoid saturation)
+    Uses tier="microfish" — ModelManager resolves to the user's selected model.
     """
     fields = THEME_FIELDS.get(theme, [])
     archetypes_str = ", ".join(PROVEN_ARCHETYPES)
@@ -84,7 +78,7 @@ Ensure each component has a clear sign_direction with academic justification."""
     blueprint = await llm.generate_json(
         prompt=user_prompt,
         schema=Blueprint,
-        model=model or llm.config.microfish_model,
+        tier="microfish",
         temperature=0.7,
         system_prompt=system,
     )