feat(ml/serving): inject profile features + sort tasks in tip prompt (#79)

- prompts.py: sort tasks overdue-first → priority desc → age desc before
  rendering into the LLM prompt (same ordering as ml/features/context.py)
- prompts.py: render User profile summary line (completion_rate, dismiss_rate,
  preferred_hour) when profile_features are present
- main.py: add profile_features field to PromptContext; plumb from
  GenerateRequest into the prompt builder via model_copy
- logging_config.py: drop add_logger_name processor (incompatible with
  PrintLoggerFactory — caused test ordering failures)
- test_generate.py: 6 new tests covering sort order, profile rendering,
  partial fields, empty profile, and end-to-end plumbing through /generate

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

ml/serving/main.py

@@ -322,6 +322,7 @@ class PromptContext(BaseModel):
     hour_of_day: int = 12
     day_of_week: int = 0
     extra: dict = {}
+    profile_features: Optional[dict] = None
 
 
 class GenerateRequest(BaseModel):
@@ -392,7 +393,8 @@ async def generate(req: GenerateRequest) -> GenerateResponse:
         prompt_template = get_prompt(req.prompt_version)
     except KeyError as e:
         raise HTTPException(status_code=422, detail=f"Unknown prompt_version: {e.args[0]}")
-    user_msg = prompt_template.build_user(req.context, req.n)
+    ctx = req.context.model_copy(update={"profile_features": req.profile_features})
+    user_msg = prompt_template.build_user(ctx, req.n)
     messages: list[dict] = [
         {"role": "system", "content": prompt_template.system},
         {"role": "user", "content": user_msg},