fixed loffer to be consistent

app.py

@@ -13,7 +13,10 @@ from runners.base import ILLMRunner
 from factory import default_runner_factory
 
 # ---------- logging ----------
-logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(name)s: %(message)s")
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s [%(levelname)s] %(name)s: %(message)s"
+)
 log = logging.getLogger("app")
 
 # ---------- @spaces.GPU entrypoint ----------

function_tracker.py

@@ -3,6 +3,8 @@ from __future__ import annotations
 from dataclasses import dataclass
 from typing import Dict, List
 import random
+import logging
+logger = logging.getLogger(__name__)
 
 @dataclass
 class TrackedCall:

listener.py

@@ -6,11 +6,7 @@ import aio_pika
 
 Handler = Callable[[Any], Awaitable[None]]  # payload is envelope["data"]
 
-# Configure root logger if not already configured
-logging.basicConfig(
-    level=logging.INFO,
-    format="%(asctime)s [%(levelname)s] %(name)s: %(message)s"
-)
+import logging
 logger = logging.getLogger(__name__)
 
 

rabbit_base.py

@@ -10,13 +10,8 @@ from config import settings
 
 ExchangeResolver = Callable[[str], str]  # exchangeName -> exchangeType
 
-# --- logging setup (keep simple; inherit root handlers if already configured) ---
+import logging
 logger = logging.getLogger(__name__)
-if not logger.handlers:
-    logging.basicConfig(
-        level=logging.INFO,
-        format="%(asctime)s [%(levelname)s] %(name)s: %(message)s"
-    )
 
 def _normalize_exchange_type(val: str) -> aio_pika.ExchangeType:
     if isinstance(val, str):

rabbit_repo.py

@@ -8,7 +8,8 @@ from config import settings
 from models import CloudEvent
 from rabbit_base import RabbitBase
 from utils import to_json, json_compress_str
-
+import logging
+logger = logging.getLogger(__name__)
 
 class RabbitRepo(RabbitBase):
     def __init__(self, external_source: str):

runners/echo.py

@@ -5,6 +5,7 @@ from .base import ILLMRunner
 from models import LLMServiceObj
 from function_tracker import FunctionCallTracker
 import logging
+logger = logging.getLogger(__name__)
 
 class EchoRunner(ILLMRunner):
     Type = "TurboLLM"
@@ -16,28 +17,27 @@ class EchoRunner(ILLMRunner):
         self._pub = publisher
         self._settings = settings
         self._tracker = FunctionCallTracker()
-        self._log = logging.getLogger("EchoRunner")
 
     async def StartProcess(self, llmServiceObj: dict) -> None:
-        self._log.debug(f"StartProcess called with: {llmServiceObj}")
+        logger.info(f"StartProcess called with: {llmServiceObj}")
         # pretend to “warm up”
         pass
 
     async def RemoveProcess(self, sessionId: str) -> None:
-        self._log.debug(f"RemoveProcess called for session: {sessionId}")
+        logger.info(f"RemoveProcess called for session: {sessionId}")
         # nothing to clean here
         pass
 
     async def StopRequest(self, sessionId: str) -> None:
-        self._log.debug(f"StopRequest called for session: {sessionId}")
+        logger.info(f"StopRequest called for session: {sessionId}")
         # no streaming loop to stop in echo
         pass
 
     async def SendInputAndGetResponse(self, llmServiceObj: dict) -> None:
-        self._log.debug(f"SendInputAndGetResponse called with: {llmServiceObj}")
+        logger.info(f"SendInputAndGetResponse called with: {llmServiceObj}")
         llm = LLMServiceObj(**llmServiceObj)
         if llm.UserInput.startswith("<|START_AUDIO|>") or llm.UserInput.startswith("<|STOP_AUDIO|>"):
-            self._log.debug("Audio input detected, ignoring in echo.")
+            logger.debug("Audio input detected, ignoring in echo.")
             return
 
         # Echo behavior (match UI format)

service.py

@@ -8,6 +8,8 @@ from models import LLMServiceObj, ResultObj
 from rabbit_repo import RabbitRepo
 from runners.base import ILLMRunner
 from message_helper import success as _ok, error as _err
+import logging
+logger = logging.getLogger(__name__)
 
 @dataclass
 class _Session:

streaming.py

@@ -1,5 +1,7 @@
 # streaming.py
 import asyncio
+import logging
+logger = logging.getLogger(__name__)
 
 async def stream_in_chunks(publish, exchange: str, llm_obj_builder, text: str,
                            batch_size: int = 3, max_chars: int = 100,