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74 lines
2.3 KiB
Python
74 lines
2.3 KiB
Python
import os
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import openai
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from dotenv import load_dotenv
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# Load environment variables from .env file
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load_dotenv()
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class Singleton(type):
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"""
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Singleton metaclass for ensuring only one instance of a class.
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"""
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_instances = {}
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def __call__(cls, *args, **kwargs):
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if cls not in cls._instances:
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cls._instances[cls] = super(
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Singleton, cls).__call__(
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*args, **kwargs)
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return cls._instances[cls]
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class Config(metaclass=Singleton):
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"""
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Configuration class to store the state of bools for different scripts access.
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"""
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def __init__(self):
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self.continuous_mode = False
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self.speak_mode = False
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# TODO - make these models be self-contained, using langchain, so we can configure them once and call it good
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self.fast_llm_model = os.getenv("FAST_LLM_MODEL", "gpt-3.5-turbo")
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self.smart_llm_model = os.getenv("SMART_LLM_MODEL", "gpt-4")
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self.thinking_token_limit = 4000
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# Initialize the OpenAI API client
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self.openai_api_key = os.getenv("OPENAI_API_KEY")
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self.elevenlabs_api_key = os.getenv("ELEVENLABS_API_KEY")
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# Print values:
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print("Config values:")
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print(f"continuous_mode: {self.continuous_mode}")
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print(f"speak_mode: {self.speak_mode}")
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print(f"fast_llm_model: {self.fast_llm_model}")
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print(f"smart_llm_model: {self.smart_llm_model}")
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print(f"thinking_token_limit: {self.thinking_token_limit}")
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print(f"openai_api_key: {self.openai_api_key}")
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print(f"elevenlabs_api_key: {self.elevenlabs_api_key}")
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# Initialize the OpenAI API client
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openai.api_key = self.openai_api_key
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def set_continuous_mode(self, value: bool):
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self.continuous_mode = value
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def set_speak_mode(self, value: bool):
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self.speak_mode = value
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def set_fast_llm_model(self, value: str):
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self.fast_llm_model = value
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def set_smart_llm_model(self, value: str):
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self.smart_llm_model = value
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def set_thinking_token_limit(self, value: int):
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self.thinking_token_limit = value
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def set_openai_api_key(self, value: str):
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self.apiopenai_api_key_key = value
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def set_elevenlabs_api_key(self, value: str):
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self.elevenlabs_api_key = value
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