Initialize the Language Model based on environment configurations.
(self)
| 34 | self.client = self.initialize_client() |
| 35 | |
| 36 | def initialize_client(self): |
| 37 | """Initialize the Language Model based on environment configurations.""" |
| 38 | if os.getenv("use_openai") == "True": |
| 39 | self.logger.info("Initializing OpenAI conversation.") |
| 40 | api_key = os.getenv("OPENAI_API_KEY") |
| 41 | if not api_key: |
| 42 | print("Error: OPENAI_API_KEY not found in .env file.") |
| 43 | return None |
| 44 | return openai.OpenAI(api_key=api_key) |
| 45 | if os.getenv("use_gemini") == "True": |
| 46 | self.logger.info("Initializing Gemini conversation.") |
| 47 | api_key = os.getenv("GOOGLE_API_KEY") |
| 48 | if not api_key: |
| 49 | print("Error: GOOGLE_API_KEY not found in .env file.") |
| 50 | return None |
| 51 | return genai.Client(api_key=api_key) |
| 52 | if os.getenv("use_azure") == "True": |
| 53 | self.logger.info("Initializing Azure OpenAI conversation.") |
| 54 | api_key = os.getenv("AZURE_OPENAI_API_KEY") |
| 55 | api_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT") |
| 56 | deployment_name = os.getenv("AZURE_OPENAI_CHAT_DEPLOYMENT_NAME") |
| 57 | api_version = os.getenv("AZURE_OPENAI_API_VERSION") |
| 58 | if not all([api_key, api_endpoint, deployment_name, api_version]): |
| 59 | print("Error: AZURE_OPENAI_API_KEY, AZURE_OPENAI_ENDPOINT, or AZURE_OPENAI_DEPLOYMENT_NAME not found in .env file.") |
| 60 | return None |
| 61 | return openai.AzureOpenAI( |
| 62 | api_key=api_key, |
| 63 | api_version=api_version, |
| 64 | azure_endpoint=api_endpoint, |
| 65 | azure_deployment=deployment_name, |
| 66 | ) |
| 67 | if os.getenv("use_anthropic") == "True": |
| 68 | self.logger.info("Initializing Anthropic conversation.") |
| 69 | api_key = os.getenv("ANTHROPIC_API_KEY") |
| 70 | if not api_key: |
| 71 | print("Error: ANTHROPIC_API_KEY not found in .env file.") |
| 72 | return None |
| 73 | return anthropic.Anthropic(api_key=api_key) |
| 74 | if os.getenv("use_ollama") == "True": |
| 75 | self.logger.info("Initializing Ollama conversation.") |
| 76 | return OllamaClient(self.logger,os.getenv("ollama_model_name")) |
| 77 | |
| 78 | raise ValueError("No LLM backend selected.") |
| 79 | |
| 80 | def clean_reply(self, reply): |
| 81 | # Remove the code decorators and backticks that ChatGPT returns |