moved to core.config.confg

app/app_config.py

@@ -1,8 +1,9 @@
 import json
 import os
-from dataclasses import dataclass
+from pydantic import BaseModel
 from pathlib import Path
 from dotenv import load_dotenv
+from core.config.config import InputConfig
 
 CUR_DIR = Path(os.path.abspath(__file__)).parent.parent
 CACHE_DIR = CUR_DIR/'cache'
@@ -13,75 +14,7 @@ CONFIG_FILE_PATH = CUR_DIR / 'input_config.json'
 print(f"{CUR_DIR=}")
 print(f"{ENV_FILE_PATH=}")
 print(f"{CONFIG_FILE_PATH=}")
-
-
-@dataclass
-class InputConfig:
-    model_name: str = 'openai/gpt-3.5-turbo'
-    model_api_key: str = 'sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx'
-    max_tokens: int = 1024
-    max_steps: int = 10
-    temperature: float = 0.2
-    timeout: float = 30.0
-    sleeptime: float = 0.0
-    force_max_steps: bool = True
-
-    @classmethod
-    def load(cls, env_file=ENV_FILE_PATH, config_file=CONFIG_FILE_PATH):
-        # Load env variables
-        load_dotenv(env_file)
-        env_dict = {
-            'model_name': os.getenv('MODEL_NAME', 'not set'),
-            'model_api_key': os.getenv('MODEL_API_KEY', 'not set')
-        }
-
-        # Load config JSON
-        with open(config_file, 'r') as f:
-            config_dict = json.load(f)
-
-        # Combine both
-        return cls(
-            model_name=env_dict.get('model_name', cls.model_name),
-            model_api_key=env_dict.get('model_api_key', cls.model_api_key),
-            max_tokens=config_dict.get('max_tokens', cls.max_tokens),
-            max_steps=config_dict.get('max_steps', cls.max_steps),
-            temperature=config_dict.get('temperature', cls.temperature),
-            timeout=config_dict.get('timeout', cls.timeout),
-            sleeptime=config_dict.get('sleeptime', cls.sleeptime),
-            force_max_steps=config_dict.get('force_max_steps', cls.force_max_steps)
-        )
-
-    def save(self, env_file=ENV_FILE_PATH, config_file=CONFIG_FILE_PATH):
-        # Read existing env content if it exists
-        env_vars = {}
-        if os.path.exists(env_file):
-            with open(env_file, 'r') as f:
-                for line in f:
-                    if line.strip():  # Ignore empty lines
-                        key, value = line.strip().split('=', 1)
-                        env_vars[key] = value
-        
-        # Update the necessary keys
-        env_vars['MODEL_API_KEY'] = self.model_api_key
-        env_vars['MODEL_NAME'] = self.model_name
-
-        # Write back to the .env file
-        with open(env_file, 'w') as f:
-            for key, value in env_vars.items():
-                f.write(f'{key}={value}\n')
-
-        # Save other parameters to input_config.json
-        config_dict = {
-            'max_tokens': self.max_tokens,
-            'max_steps': self.max_steps,
-            'temperature': self.temperature,
-            'timeout': self.timeout,
-            'sleeptime': self.sleeptime,
-            'force_max_steps': self.force_max_steps
-        }
-        with open(config_file, 'w') as f:
-            json.dump(config_dict, f, indent=4)
             
 if not CONFIG_FILE_PATH.exists() or not ENV_FILE_PATH.exists():
-    InputConfig().save()
+    InputConfig().save(ENV_FILE_PATH, CONFIG_FILE_PATH)