diff --git a/app/tasks/refine_text_with_gpt.py b/app/tasks/refine_text_with_gpt.py
index c281991e..d67f4c94 100644
--- a/app/tasks/refine_text_with_gpt.py
+++ b/app/tasks/refine_text_with_gpt.py
@@ -1,38 +1,72 @@
 #!/usr/bin/env python3
 
+import logging
+
 import openai
 
 # Import the shared Celery instance
 from app.celery_app import celery
 from app.config import settings
 from app.tasks.retry_config import BaseTaskWithRetry
+from app.utils import log_task_progress
+
+logger = logging.getLogger(__name__)
 
 # Initialize OpenAI client dynamically
 client = openai.OpenAI(api_key=settings.openai_api_key, base_url=settings.openai_base_url)
 
 
-@celery.task(base=BaseTaskWithRetry)
-def refine_text_with_gpt(filename: str, raw_text: str):
+@celery.task(base=BaseTaskWithRetry, bind=True)
+def refine_text_with_gpt(self, filename: str, raw_text: str):
     """Uses OpenAI to clean and refine OCR text."""
-    response = client.chat.completions.create(
-        model=settings.openai_model,
-        messages=[
-            {
-                "role": "system",
-                "content": (
-                    "Clean and format the following text. The idea is that the text you see comes from an OCR "
-                    "system and your task is to eliminate OCR errors. Keep the original language when doing so."
-                ),
-            },
-            {"role": "user", "content": raw_text},
-        ],
-    )
+    task_id = self.request.id
+    logger.info(f"[{task_id}] Starting OCR text refinement for: {filename}")
+    log_task_progress(task_id, "refine_text_with_gpt", "in_progress", f"Refining OCR text for {filename}")
 
-    cleaned_text = response.choices[0].message.content
+    try:
+        log_task_progress(task_id, "call_openai", "in_progress", "Calling OpenAI for text refinement")
 
-    # Trigger next task (import locally if needed to avoid circular imports)
-    from app.tasks.extract_metadata_with_gpt import extract_metadata_with_gpt
+        response = client.chat.completions.create(
+            model=settings.openai_model,
+            messages=[
+                {
+                    "role": "system",
+                    "content": (
+                        "Clean and format the following text. The idea is that the text you see comes from an OCR "
+                        "system and your task is to eliminate OCR errors. Keep the original language when doing so."
+                    ),
+                },
+                {"role": "user", "content": raw_text},
+            ],
+        )
 
-    extract_metadata_with_gpt.delay(filename, cleaned_text)
+        cleaned_text = response.choices[0].message.content
 
-    return {"filename": filename, "cleaned_text": cleaned_text}
+        logger.info(f"[{task_id}] Text refinement complete for {filename}: {len(cleaned_text)} characters")
+        log_task_progress(
+            task_id,
+            "call_openai",
+            "success",
+            "Received refined text from OpenAI",
+            detail=f"Input: {len(raw_text)} chars → Output: {len(cleaned_text)} chars",
+        )
+
+        # Trigger next task (import locally if needed to avoid circular imports)
+        from app.tasks.extract_metadata_with_gpt import extract_metadata_with_gpt
+
+        extract_metadata_with_gpt.delay(filename, cleaned_text)
+
+        logger.info(f"[{task_id}] Queueing metadata extraction for {filename}")
+        log_task_progress(task_id, "refine_text_with_gpt", "success", "Text refined, queuing metadata extraction")
+
+        return {"filename": filename, "cleaned_text": cleaned_text}
+    except Exception as e:
+        logger.exception(f"[{task_id}] Text refinement failed for {filename}: {e}")
+        log_task_progress(
+            task_id,
+            "refine_text_with_gpt",
+            "failure",
+            f"Exception: {str(e)}",
+            detail=f"Text refinement failed for {filename}.\nException: {str(e)}",
+        )
+        raise