ollama support successfully implemeted, but the local model instruction following with tool usage is weak.

Author: Codegass

n0mail/services/provider/ollama_service.py

@@ -6,6 +6,7 @@
 from typing import List, Dict, Optional, Literal, Union, Iterator, cast
 import json
 import datetime
+import copy # Import copy for deepcopy
 
 from n0mail import config
 from n0mail.util.text_utils import clean_markdown_for_dense_information
@@ -290,20 +291,43 @@ def get_chat_completion(
         if temperature is not None:
             options['temperature'] = temperature
 
+        # --- Pre-process messages for Ollama client --- 
+        # The ollama client expects arguments within tool_calls to be dicts, 
+        # but our history (adapted from OpenAI format) stores them as strings.
+        messages_for_ollama = copy.deepcopy(messages) # Avoid modifying original history
+        for message in messages_for_ollama:
+            if message.get('role') == 'assistant' and message.get('tool_calls'):
+                new_tool_calls = []
+                for tool_call in message['tool_calls']:
+                    if isinstance(tool_call, dict) and isinstance(tool_call.get('function'), dict):
+                         func = tool_call['function']
+                         if isinstance(func.get('arguments'), str):
+                            try:
+                                # Parse arguments string back to dict
+                                func['arguments'] = json.loads(func['arguments'])
+                            except json.JSONDecodeError:
+                                console.print(f"[yellow]Warning (Ollama):[/yellow] Could not parse tool call arguments JSON string in history message: {func.get('arguments')}")
+                                # Keep it as string if parsing fails? Or remove the call?
+                                # Keeping it might lead to the same validation error again.
+                                # Let's try keeping the structure but arguments might be wrong.
+                                pass # Keep as string if parse fails
+                         # Append the potentially modified tool_call (or original if no change needed)
+                         # We assume the rest of the tool_call structure is compatible
+                         new_tool_calls.append(tool_call)
+                    else:
+                         # If tool_call format is unexpected, keep original
+                         new_tool_calls.append(tool_call)
+                message['tool_calls'] = new_tool_calls # Update message with processed tool calls
+            
         chat_params = {
             "model": model,
-            "messages": messages,
+            "messages": messages_for_ollama, # Use the pre-processed messages
             "stream": stream,
             "options": options
         }
 
-        # Pass tools if provided - using the OpenAI JSON schema format
         if tools:
             chat_params["tools"] = tools
-            # Note: Ollama python lib might not support explicit 'tool_choice' yet
-            # if tool_choice and tool_choice != "auto":
-            #     chat_params["tool_choice"] = tool_choice 
-            # For now, we rely on the model to decide based on the prompt and tools
 
         retries = 0
         delay = initial_delay