Merge pull request #171 from codelion/feat-add-mcp-plugin-again

- Add MCP plugin, that allows you to use any LLM with any MCP Server
- Support streaming responses in local inference
- Fix regression with the simple gradio GUI

Author: codelion

optillm.py

@@ -118,6 +118,29 @@ def get_config():
 
 plugin_approaches = {}
 
+def normalize_message_content(messages):
+    """
+    Ensure all message content fields are strings, not lists.
+    Some models don't handle list-format content correctly.
+    """
+    normalized_messages = []
+    for message in messages:
+        normalized_message = message.copy()
+        content = message.get('content', '')
+        
+        # Convert list content to string if needed
+        if isinstance(content, list):
+            # Extract text content from the list
+            text_content = ' '.join(
+                item.get('text', '') for item in content 
+                if isinstance(item, dict) and item.get('type') == 'text'
+            )
+            normalized_message['content'] = text_content
+        
+        normalized_messages.append(normalized_message)
+    
+    return normalized_messages
+
 def none_approach(
     client: Any, 
     model: str,
@@ -143,10 +166,13 @@ def none_approach(
         model = model[5:]
 
     try:
-        # Make the direct completion call with original messages and parameters
+        # Normalize message content to ensure it's always string
+        normalized_messages = normalize_message_content(original_messages)
+        
+        # Make the direct completion call with normalized messages and parameters
         response = client.chat.completions.create(
             model=model,
-            messages=original_messages,
+            messages=normalized_messages,
             **kwargs
         )
 
@@ -320,12 +346,32 @@ def execute_single_approach(approach, system_prompt, initial_query, client, mode
         import inspect
         sig = inspect.signature(plugin_func)
 
-        if 'request_config' in sig.parameters:
-            # Plugin supports request_config
-            return plugin_func(system_prompt, initial_query, client, model, request_config=request_config)
+        # Check if the plugin function is async
+        is_async = inspect.iscoroutinefunction(plugin_func)
+        
+        if is_async:
+            # For async functions, we need to run them in an event loop
+            import asyncio
+            loop = asyncio.new_event_loop()
+            asyncio.set_event_loop(loop)
+            try:
+                if 'request_config' in sig.parameters:
+                    # Plugin supports request_config
+                    result = loop.run_until_complete(plugin_func(system_prompt, initial_query, client, model, request_config=request_config))
+                else:
+                    # Legacy plugin without request_config support
+                    result = loop.run_until_complete(plugin_func(system_prompt, initial_query, client, model))
+                return result
+            finally:
+                loop.close()
         else:
-            # Legacy plugin without request_config support
-            return plugin_func(system_prompt, initial_query, client, model)
+            # For synchronous functions, call directly
+            if 'request_config' in sig.parameters:
+                # Plugin supports request_config
+                return plugin_func(system_prompt, initial_query, client, model, request_config=request_config)
+            else:
+                # Legacy plugin without request_config support
+                return plugin_func(system_prompt, initial_query, client, model)
     else:
         raise ValueError(f"Unknown approach: {approach}")
 

optillm/__init__.py

@@ -2,7 +2,7 @@
 import os
 
 # Version information
-__version__ = "0.1.6"
+__version__ = "0.1.7"
 
 # Get the path to the root optillm.py
 spec = util.spec_from_file_location(