diff --git a/application/llm/openai.py b/application/llm/openai.py
index 5e11a072..9da09c15 100644
--- a/application/llm/openai.py
+++ b/application/llm/openai.py
@@ -35,6 +35,15 @@ class OpenAILLM(BaseLLM):
                             cleaned_messages.append(
                                 {"role": role, "content": item["text"]}
                             )
+                        elif isinstance(item, dict):
+                            content_parts = []
+                            if "text" in item:
+                                content_parts.append({"type": "text", "text": item["text"]})
+                            elif "type" in item and item["type"] == "text" and "text" in item:
+                                content_parts.append(item)
+                            elif "type" in item and item["type"] == "file" and "file" in item:
+                                content_parts.append(item)
+                            cleaned_messages.append({"role": role, "content": content_parts})
                         elif "function_call" in item:
                             tool_call = {
                                 "id": item["function_call"]["call_id"],
@@ -133,6 +142,131 @@ class OpenAILLM(BaseLLM):
     def _supports_tools(self):
         return True
 
+    def prepare_messages_with_attachments(self, messages, attachments=None):
+        """
+        Process attachments using OpenAI's file API for more efficient handling.
+        
+        Args:
+            messages (list): List of message dictionaries.
+            attachments (list): List of attachment dictionaries with content and metadata.
+            
+        Returns:
+            list: Messages formatted with file references for OpenAI API.
+        """
+        if not attachments:
+            return messages
+        
+        prepared_messages = messages.copy()
+        
+        # Find the user message to attach file_id to the last one
+        user_message_index = None
+        for i in range(len(prepared_messages) - 1, -1, -1):
+            if prepared_messages[i].get("role") == "user":
+                user_message_index = i
+                break
+        
+        if user_message_index is None:
+            user_message = {"role": "user", "content": []}
+            prepared_messages.append(user_message)
+            user_message_index = len(prepared_messages) - 1
+        
+        if isinstance(prepared_messages[user_message_index].get("content"), str):
+            text_content = prepared_messages[user_message_index]["content"]
+            prepared_messages[user_message_index]["content"] = [
+                {"type": "text", "text": text_content}
+            ]
+        elif not isinstance(prepared_messages[user_message_index].get("content"), list):
+            prepared_messages[user_message_index]["content"] = []
+        
+        for attachment in attachments:
+            # Upload the file to OpenAI
+            try:
+                file_id = self._upload_file_to_openai(attachment)
+                
+                prepared_messages[user_message_index]["content"].append({
+                    "type": "file",
+                    "file": {"file_id": file_id}
+                })
+            except Exception as e:
+                import logging
+                logging.error(f"Error uploading attachment to OpenAI: {e}")
+                if 'content' in attachment:
+                    prepared_messages[user_message_index]["content"].append({
+                        "type": "text", 
+                        "text": f"File content:\n\n{attachment['content']}"
+                    })
+        
+        return prepared_messages
+
+    def _upload_file_to_openai(self, attachment):
+        """
+        Upload a file to OpenAI and return the file_id.
+        
+        Args:
+            attachment (dict): Attachment dictionary with path and metadata.
+                Expected keys:
+                - path: Path to the file
+                - id: Optional MongoDB ID for caching
+                
+        Returns:
+            str: OpenAI file_id for the uploaded file.
+        """
+        import os
+        import mimetypes
+        
+        # Check if we already have the file_id cached
+        if 'openai_file_id' in attachment:
+            return attachment['openai_file_id']
+        
+        file_path = attachment.get('path')
+        if not file_path:
+            raise ValueError("No file path provided in attachment")
+        
+        # Make path absolute if it's relative
+        if not os.path.isabs(file_path):
+            current_dir = os.path.dirname(
+                os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+            )
+            file_path = os.path.join(current_dir,"application", file_path)
+        
+        if not os.path.exists(file_path):
+            raise FileNotFoundError(f"File not found: {file_path}")
+        
+        mime_type = attachment.get('mime_type')
+        if not mime_type:
+            mime_type = mimetypes.guess_type(file_path)[0] or 'application/octet-stream'
+        
+        supported_mime_types = ['application/pdf', 'image/png', 'image/jpeg', 'image/gif']
+        if mime_type not in supported_mime_types:
+            import logging
+            logging.warning(f"MIME type {mime_type} not supported by OpenAI for file uploads. Falling back to text.")
+            raise ValueError(f"Unsupported MIME type: {mime_type}")
+        
+        try:
+            with open(file_path, 'rb') as file:
+                response = self.client.files.create(
+                    file=file,
+                    purpose="assistants"
+                )
+            
+            file_id = response.id
+            
+            from application.core.mongo_db import MongoDB
+            mongo = MongoDB.get_client()
+            db = mongo["docsgpt"]
+            attachments_collection = db["attachments"]
+            if '_id' in attachment:
+                attachments_collection.update_one(
+                    {"_id": attachment['_id']},
+                    {"$set": {"openai_file_id": file_id}}
+                )
+            
+            return file_id
+        except Exception as e:
+            import logging
+            logging.error(f"Error uploading file to OpenAI: {e}")
+            raise
+
 
 class AzureOpenAILLM(OpenAILLM):