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import yaml
from typing import Optional, List
from pydantic_settings import BaseSettings
from llama_index.core import Settings
from llama_index.llms.openai import OpenAI
from llama_index.llms.ollama import Ollama
from llama_index.llms.groq import Groq
from llama_index.embeddings.openai import OpenAIEmbedding
from llama_index.embeddings.ollama import OllamaEmbedding
from llama_index.embeddings.huggingface import HuggingFaceEmbedding
from pydantic import Field, ValidationError
class ProjectSettings(BaseSettings):
OPENAI_API_KEY: Optional[str] = Field(None, env='OPENAI_API_KEY')
GROQ_KEY: Optional[str] = Field(None, env='GROQ_KEY')
config: Optional[dict] = None
moduleList: List[str] = Field(default_factory=list)
class Config:
env_file = '.env'
def __init__(self, **kwargs):
super().__init__(**kwargs)
self.config = self._read_yaml_config()
if not self.config:
raise ValidationError("Config file could not be loaded")
self._instantiate_services()
self.moduleList = self.config.get('userPreference', {})['ModuleList']
def _instantiate_services(self):
llm_service = self.config.get('userPreference', {}).get('llmService', '').lower()
if llm_service == 'ollama':
self._initialize_ollama()
elif llm_service == 'openai':
self._initialize_openai()
elif llm_service == 'groq':
self._initialize_groq()
else:
raise ValueError(f"Invalid LLM service: {llm_service}")
def _initialize_ollama(self):
ollama_config = self.config.get('OllamaConfig', {})
Settings.llm = Ollama(base_url=ollama_config['baseURL'], model=ollama_config['llm'])
Settings.embed_model = OllamaEmbedding(base_url=ollama_config['baseURL'], model_name=ollama_config['llm'])
def _initialize_openai(self):
openai_config = self.config.get('OpenAIConfig', {})
Settings.llm = OpenAI(model=openai_config['llm'], api_key=self.OPENAI_API_KEY)
Settings.embed_model = OpenAIEmbedding(model=openai_config['embeddingModel'], api_key=self.OPENAI_API_KEY)
def _initialize_groq(self):
groq_config = self.config.get('GroqConfig', {})
Settings.llm = Groq(model=groq_config['llm'], api_key=self.GROQ_KEY)
Settings.embed_model = HuggingFaceEmbedding(model_name=groq_config['hfEmbedding'])
@staticmethod
def _read_yaml_config():
with open("config.yaml", "r") as file:
config = yaml.safe_load(file)
return config
settings = ProjectSettings()
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