From 34e421f79bfbd8dac76255200b09a7646dc11b19 Mon Sep 17 00:00:00 2001
From: mrT23 <tal.r@codium.ai>
Date: Sun, 25 Feb 2024 09:58:58 +0200
Subject: [PATCH] Refactor logging statements for better readability and
 debugging

---
 pr_agent/algo/ai_handlers/litellm_ai_handler.py | 11 +++++++----
 pr_agent/algo/pr_processing.py                  |  2 +-
 2 files changed, 8 insertions(+), 5 deletions(-)

diff --git a/pr_agent/algo/ai_handlers/litellm_ai_handler.py b/pr_agent/algo/ai_handlers/litellm_ai_handler.py
index 165976c7..a36f2672 100644
--- a/pr_agent/algo/ai_handlers/litellm_ai_handler.py
+++ b/pr_agent/algo/ai_handlers/litellm_ai_handler.py
@@ -100,6 +100,7 @@ class LiteLLMAIHandler(BaseAiHandler):
             TryAgain: If there is an attribute error during OpenAI inference.
         """
         try:
+            resp, finish_reason = None, None
             deployment_id = self.deployment_id
             if self.azure:
                 model = 'azure/' + model
@@ -127,9 +128,11 @@ class LiteLLMAIHandler(BaseAiHandler):
             raise TryAgain from e
         if response is None or len(response["choices"]) == 0:
             raise TryAgain
-        resp = response["choices"][0]['message']['content']
-        finish_reason = response["choices"][0]["finish_reason"]
-        # usage = response.get("usage")
+        else:
+            resp = response["choices"][0]['message']['content']
+            finish_reason = response["choices"][0]["finish_reason"]
+            # usage = response.get("usage")
+            get_logger().debug(f"\nAI response:\n{resp}")
+            get_logger().debug("full_response", response=response)
 
-        get_logger().debug(f"\nAI response:\n{resp}", full_response=response)
         return resp, finish_reason
\ No newline at end of file
diff --git a/pr_agent/algo/pr_processing.py b/pr_agent/algo/pr_processing.py
index d4a195d7..90482a02 100644
--- a/pr_agent/algo/pr_processing.py
+++ b/pr_agent/algo/pr_processing.py
@@ -254,7 +254,7 @@ async def retry_with_fallback_models(f: Callable, model_type: ModelType = ModelT
             )
             get_settings().set("openai.deployment_id", deployment_id)
             return await f(model)
-        except Exception as e:
+        except:
             get_logger().warning(
                 f"Failed to generate prediction with {model}"
                 f"{(' from deployment ' + deployment_id) if deployment_id else ''}: "