fix the tokens counting bugs

Author: Zongwei9888

mcp_agent.config.yaml

@@ -85,7 +85,7 @@ mcp:
         PYTHONPATH: .
 openai:
   base_max_tokens: 20000
-  default_model: anthropic/claude-sonnet-4.5
+  default_model: google/gemini-2.5-pro
   max_tokens_policy: adaptive
   retry_max_tokens: 32768
 planning_mode: traditional

schema/mcp-agent.config.schema.json

@@ -667,25 +667,6 @@
       ],
       "title": "TemporalSettings",
       "type": "object"
-    },
-    "UsageTelemetrySettings": {
-      "description": "Settings for usage telemetry in the MCP Agent application.\nAnonymized usage metrics are sent to a telemetry server to help improve the product.",
-      "properties": {
-        "enabled": {
-          "default": true,
-          "title": "Enabled",
-          "type": "boolean",
-          "description": "Enable usage telemetry in the MCP Agent application."
-        },
-        "enable_detailed_telemetry": {
-          "default": false,
-          "title": "Enable Detailed Telemetry",
-          "type": "boolean",
-          "description": "If enabled, detailed telemetry data, including prompts and agents, will be sent to the telemetry server."
-        }
-      },
-      "title": "UsageTelemetrySettings",
-      "type": "object"
     }
   },
   "additionalProperties": true,
@@ -831,21 +812,6 @@
         "http_timeout": 5.0
       },
       "description": "Logger settings for the MCP Agent application"
-    },
-    "usage_telemetry": {
-      "anyOf": [
-        {
-          "$ref": "#/$defs/UsageTelemetrySettings"
-        },
-        {
-          "type": "null"
-        }
-      ],
-      "default": {
-        "enabled": true,
-        "enable_detailed_telemetry": false
-      },
-      "description": "Usage tracking settings for the MCP Agent application"
     }
   },
   "title": "MCP Agent Configuration Schema",

workflows/code_implementation_workflow.py

@@ -530,27 +530,31 @@ async def _initialize_llm_client(self):
                 else:
                     client = AsyncOpenAI(api_key=openai_key)
 
+                # Get model name from config
+                model_name = self.default_models.get("openai", "o3-mini")
+
                 # Test connection with default model from config
                 # Try max_tokens first, fallback to max_completion_tokens if unsupported
                 try:
                     await client.chat.completions.create(
-                        model=self.default_models["openai"],
+                        model=model_name,
                         max_tokens=20,
                         messages=[{"role": "user", "content": "test"}],
                     )
                 except Exception as e:
                     if "max_tokens" in str(e) and "max_completion_tokens" in str(e):
                         # Retry with max_completion_tokens for models that require it
+                        self.logger.info(
+                            f"Model {model_name} requires max_completion_tokens parameter"
+                        )
                         await client.chat.completions.create(
-                            model=self.default_models["openai"],
+                            model=model_name,
                             max_completion_tokens=20,
                             messages=[{"role": "user", "content": "test"}],
                         )
                     else:
                         raise
-                self.logger.info(
-                    f"Using OpenAI API with model: {self.default_models['openai']}"
-                )
+                self.logger.info(f"Using OpenAI API with model: {model_name}")
                 if base_url:
                     self.logger.info(f"Using custom base URL: {base_url}")
                 return client, "openai"
@@ -1152,9 +1156,9 @@ async def main():
         # Ask if user wants to continue with actual workflow
         print("\nContinuing with workflow execution...")
 
-        plan_file = "/Users/lizongwei/Desktop/DeepCode_Project/workbase/DeepCode_papertest/deepcode_lab/papers/23/initial_plan.txt"
+        plan_file = "/Users/lizongwei/Desktop/DeepCode_Project/workbase/DeepCode/deepcode_lab/papers/1/initial_plan.txt"
         # plan_file = "/data2/bjdwhzzh/project-hku/Code-Agent2.0/Code-Agent/deepcode-mcp/agent_folders/papers/1/initial_plan.txt"
-        target_directory = "/Users/lizongwei/Desktop/DeepCode_Project/workbase/DeepCode_papertest/deepcode_lab/papers/23/"
+        target_directory = "/Users/lizongwei/Desktop/DeepCode_Project/workbase/DeepCode/deepcode_lab/papers/1/"
         print("Implementation Mode Selection:")
         print("1. Pure Code Implementation Mode (Recommended)")
         print("2. Iterative Implementation Mode")