fix(log): less verbose

Author: Mte90

ai/analyzer.py

@@ -203,11 +203,6 @@ def _process_file_sync(
             failed_count = 0
             for idx, chunk_doc, future, embedding_start_time in embedding_futures:
                 try:
-                    # Check if request is already slow before waiting for result
-                    elapsed_before_result = time.time() - embedding_start_time
-                    if elapsed_before_result > 3.0:
-                        logger.warning(f"Embedding API request taking too long for {rel_path} chunk {idx}: {elapsed_before_result:.2f}s elapsed, still waiting for response...")
-                    
                     emb = future.result(timeout=EMBEDDING_TIMEOUT)  # Add timeout to prevent hanging indefinitely
                     embedding_duration = time.time() - embedding_start_time
 

ai/openai.py

@@ -307,13 +307,18 @@ def embed_text(self, text: str, file_path: str = "<unknown>", chunk_index: int =
                 elapsed = time.perf_counter() - start
                 err_msg = f"Timeout after {elapsed:.2f}s: {e}"
 
-                # Generate curl command for debugging
-                curl_command = self._generate_curl_command(self.api_url, dict(self.session.headers), payload)
-                
                 # Save to bash script in /tmp if DEBUG is enabled
                 script_path = None
                 if CFG.get("debug"):
+                    # Generate curl command for debugging
+                    curl_command = self._generate_curl_command(self.api_url, dict(self.session.headers), payload)
                     script_path = self._save_curl_script(curl_command, request_id, file_path, chunk_index)
+                    if script_path:
+                        _embedding_logger.error(f"\nDebug script saved to: {script_path}")
+                        _embedding_logger.error(f"Run with: bash {script_path}")
+                    else:
+                        _embedding_logger.error(f"\nDebug with this curl command:")
+                        _embedding_logger.error(curl_command)
 
                 _embedding_logger.error(
                     "Embedding API Timeout",
@@ -326,18 +331,6 @@ def embed_text(self, text: str, file_path: str = "<unknown>", chunk_index: int =
                     }
                 )
 
-                # Print to console for easy debugging
-                print(f"\n{'='*80}")
-                print(f"Embedding request timed out after {elapsed:.2f}s")
-                print(f"Request ID: {request_id}")
-                print(f"File: {file_path}, Chunk: {chunk_index}")
-                if script_path:
-                    print(f"\nDebug script saved to: {script_path}")
-                    print(f"Run with: bash {script_path}")
-                else:
-                    print(f"\nDebug with this curl command:")
-                    print(curl_command)
-                print(f"{'='*80}\n")
             except requests.RequestException as e:
                 elapsed = time.perf_counter() - start
                 err_msg = f"RequestException after {elapsed:.2f}s: {e}\n{traceback.format_exc()}"

main.py

@@ -91,6 +91,10 @@ async def lifespan(app: FastAPI):
                 os.unlink(tmp_db_path)
             except Exception:
                 pass
+
+        if CFG.get("debug"):
+            logger.info("✓ debug enabled")
+
     except Exception as e:
         logger.error(f"FATAL: Failed to load sqlite-vector extension at startup: {e}")
         # Force immediate exit - cannot continue without vector extension