diff --git a/extensions/openai/completions.py b/extensions/openai/completions.py
index c5ef36e6..ce9cc102 100644
--- a/extensions/openai/completions.py
+++ b/extensions/openai/completions.py
@@ -22,7 +22,7 @@ from modules.chat import (
     load_instruction_template_memoized
 )
 from modules.presets import load_preset_memoized
-from modules.text_generation import decode, encode, generate_reply
+from modules.text_generation import decode, encode, generate_reply, get_reply_from_output_ids
 
 
 class LogitsBiasProcessor(LogitsProcessor):
@@ -56,7 +56,7 @@ class LogprobProcessor(LogitsProcessor):
         if self.logprobs is not None:  # 0-5
             log_e_probabilities = F.log_softmax(logits, dim=1)
             top_values, top_indices = torch.topk(log_e_probabilities, k=self.logprobs + 1)
-            top_tokens = [decode(tok) for tok in top_indices[0]]
+            top_tokens = [get_reply_from_output_ids([tok]) for tok in top_indices[0]]
             top_probs = [float(x) for x in top_values[0]]
             self.token_alternatives = dict(zip(top_tokens, top_probs))
             debug_msg(repr(self))
@@ -144,6 +144,26 @@ def convert_history(history):
     user_input = ""
     system_message = ""
 
+    if any(isinstance(entry['content'], list) for entry in history):
+        new_history = []
+        for entry in history:
+            if isinstance(entry['content'], list):
+                image_url = None
+                content = None
+                for item in entry['content']:
+                    if not isinstance(item, dict):
+                        continue
+                    if item['type'] == 'image_url' and isinstance(item['image_url'], dict):
+                        image_url = item['image_url']['url']
+                    elif item['type'] == 'text' and isinstance(item['text'], str):
+                        content = item['text']
+                if image_url and content:
+                    new_history.append({"image_url": image_url, "role": "user"})
+                    new_history.append({"content": content, "role": "user"})
+            else:
+                new_history.append(entry)
+        history = new_history
+
     for entry in history:
         if "image_url" in entry:
             image_url = entry['image_url']
@@ -156,8 +176,9 @@ def convert_history(history):
                     img = Image.open(BytesIO(my_res.content))
                 except Exception:
                     raise 'Image cannot be loaded from the URL!'
-
             buffered = BytesIO()
+            if img.mode in ("RGBA", "P"):
+                img = img.convert("RGB")
             img.save(buffered, format="JPEG")
             img_str = base64.b64encode(buffered.getvalue()).decode('utf-8')
             content = f'<img src="data:image/jpeg;base64,{img_str}">'
diff --git a/modules/text_generation.py b/modules/text_generation.py
index c8562450..f4849840 100644
--- a/modules/text_generation.py
+++ b/modules/text_generation.py
@@ -268,8 +268,8 @@ def apply_stopping_strings(reply, all_stop_strings):
     return reply, stop_found
 
 
-def get_reply_from_output_ids(output_ids, state, starting_from=0):
-    reply = decode(output_ids[starting_from:], state['skip_special_tokens'])
+def get_reply_from_output_ids(output_ids, state=None, starting_from=0):
+    reply = decode(output_ids[starting_from:], state['skip_special_tokens'] if state else True)
 
     # Handle tokenizers that do not add the leading space for the first token
     if (hasattr(shared.tokenizer, 'convert_ids_to_tokens') and len(output_ids) > starting_from) and not reply.startswith(' '):