refactor: classes and configs (#528)

embedchain/llm/azure_openai_llm.py

@@ -0,0 +1,39 @@
+import logging
+from typing import Optional
+
+from embedchain.config import BaseLlmConfig
+from embedchain.llm.base_llm import BaseLlm
+
+from embedchain.helper_classes.json_serializable import register_deserializable
+
+
+@register_deserializable
+class AzureOpenAiLlm(BaseLlm):
+    def __init__(self, config: Optional[BaseLlmConfig] = None):
+        super().__init__(config=config)
+
+    def get_llm_model_answer(self, prompt):
+        return AzureOpenAiLlm._get_azure_openai_answer(prompt=prompt, config=self.config)
+
+    @staticmethod
+    def _get_azure_openai_answer(prompt: str, config: BaseLlmConfig) -> str:
+        from langchain.chat_models import AzureChatOpenAI
+
+        if not config.deployment_name:
+            raise ValueError("Deployment name must be provided for Azure OpenAI")
+
+        chat = AzureChatOpenAI(
+            deployment_name=config.deployment_name,
+            openai_api_version="2023-05-15",
+            model_name=config.model or "gpt-3.5-turbo",
+            temperature=config.temperature,
+            max_tokens=config.max_tokens,
+            streaming=config.stream,
+        )
+
+        if config.top_p and config.top_p != 1:
+            logging.warning("Config option `top_p` is not supported by this model.")
+
+        messages = BaseLlm._get_messages(prompt, system_prompt=config.system_prompt)
+
+        return chat(messages).content