Merge branch 'master' into dev

scripts/config.py

@@ -1,3 +1,9 @@
+import os
+import openai
+from dotenv import load_dotenv
+# Load environment variables from .env file
+load_dotenv()
+
 class Singleton(type):
     """
     Singleton metaclass for ensuring only one instance of a class.
@@ -23,6 +29,18 @@ class Config(metaclass=Singleton):
         """Initialize the configuration class."""
         self.continuous_mode = False
         self.speak_mode = False
+        # TODO - make these models be self-contained, using langchain, so we can configure them once and call it good 
+        self.fast_llm_model = os.getenv("FAST_LLM_MODEL", "gpt-3.5-turbo") 
+        self.smart_llm_model = os.getenv("SMART_LLM_MODEL", "gpt-4")
+        self.fast_token_limit = int(os.getenv("FAST_TOKEN_LIMIT", 4000))
+        self.smart_token_limit = int(os.getenv("SMART_TOKEN_LIMIT", 8000))
+        
+        self.openai_api_key = os.getenv("OPENAI_API_KEY")
+        self.elevenlabs_api_key = os.getenv("ELEVENLABS_API_KEY")
+
+        # Initialize the OpenAI API client
+        openai.api_key = self.openai_api_key
+
 
     def set_continuous_mode(self, value: bool):
         """Set the continuous mode value."""
@@ -31,3 +49,24 @@ class Config(metaclass=Singleton):
     def set_speak_mode(self, value: bool):
         """Set the speak mode value."""
         self.speak_mode = value
+
+    def set_fast_llm_model(self, value: str):
+        self.fast_llm_model = value
+
+    def set_smart_llm_model(self, value: str):
+        self.smart_llm_model = value
+
+    def set_fast_token_limit(self, value: int):
+        self.fast_token_limit = value
+
+    def set_smart_token_limit(self, value: int):
+        self.smart_token_limit = value
+
+    def set_openai_api_key(self, value: str):
+        self.apiopenai_api_key_key = value
+    
+    def set_elevenlabs_api_key(self, value: str):
+        self.elevenlabs_api_key = value
+
+
+