add schema and service provider config

schemas.py

@@ -0,0 +1,13 @@
+from enum import Enum
+
+
+class ChatbotVersion(str, Enum):
+    # make a enum of chatbot type and string
+    CHATGPT_35 = "gpt-3.5-turbo-1106"
+    CHATGPT_4 = "gpt-4-1106-preview"
+
+
+class ServiceProvider(str, Enum):
+    # make a enum of service provider and string
+    OPENAI = "openai"
+    AZURE = "azure"

service_provider_config.py

@@ -0,0 +1,40 @@
+from dotenv import load_dotenv
+from llama_index import OpenAIEmbedding
+from llama_index.llms import OpenAI
+from llama_index.llms import AzureOpenAI
+from llama_index.embeddings import AzureOpenAIEmbedding
+from schemas import ServiceProvider, ChatbotVersion
+
+load_dotenv()
+
+def get_service_provider_config(service_provider: ServiceProvider):
+    if service_provider == ServiceProvider.AZURE:
+        return get_azure_openai_config()
+    if service_provider == ServiceProvider.OPENAI:
+        llm = OpenAI(model=ChatbotVersion.CHATGPT_35)
+        embed_model = OpenAIEmbedding()
+        return llm, embed_model
+
+
+def get_azure_openai_config():
+    api_key = "<api-key>"
+    azure_endpoint = "https://<your-resource-name>.openai.azure.com/"
+    api_version = "2023-07-01-preview"
+
+    llm = AzureOpenAI(
+        model="gpt-35-turbo-16k",
+        deployment_name="my-custom-llm",
+        api_key=api_key,
+        azure_endpoint=azure_endpoint,
+        api_version=api_version,
+    )
+
+    # You need to deploy your own embedding model as well as your own chat completion model
+    embed_model = AzureOpenAIEmbedding(
+        model="text-embedding-ada-002",
+        deployment_name="my-custom-embedding",
+        api_key=api_key,
+        azure_endpoint=azure_endpoint,
+        api_version=api_version,
+    )
+    return llm, embed_model