clean up some code

backend/api_types.py

@@ -0,0 +1,23 @@
+from pydantic import BaseModel
+from typing import Union, Literal, Optional
+
+
+class ApiProviderInfoBase(BaseModel):
+    name: Literal["openai", "azure"]
+
+
+class OpenAiProviderInfo(ApiProviderInfoBase):
+    name: Literal["openai"] = "openai"  # type: ignore
+    api_key: str
+    base_url: Optional[str] = None
+
+
+class AzureProviderInfo(ApiProviderInfoBase):
+    name: Literal["azure"] = "azure"  # type: ignore
+    api_version: str
+    api_key: str
+    deployment_name: str
+    resource_name: str
+
+
+ApiProviderInfo = Union[OpenAiProviderInfo, AzureProviderInfo]

backend/llm.py

@@ -2,54 +2,29 @@ from typing import Awaitable, Callable, List
 from openai import AsyncOpenAI, AsyncAzureOpenAI
 from openai.types.chat import ChatCompletionMessageParam, ChatCompletionChunk
 
+from api_types import ApiProviderInfo
+
 MODEL_GPT_4_VISION = "gpt-4-vision-preview"
 
 
 async def stream_openai_response(
     messages: List[ChatCompletionMessageParam],
-    api_key: str,
+    api_provider_info: ApiProviderInfo,
-    base_url: str | None,
     callback: Callable[[str], Awaitable[None]],
 ) -> str:
-    client = AsyncOpenAI(api_key=api_key, base_url=base_url)
+    if api_provider_info.name == "openai":
-
+        client = AsyncOpenAI(
-    model = MODEL_GPT_4_VISION
+            api_key=api_provider_info.api_key, base_url=api_provider_info.base_url
-
-    # Base parameters
-    params = {"model": model, "messages": messages, "stream": True, "timeout": 600}
-
-    # Add 'max_tokens' only if the model is a GPT4 vision model
-    if model == MODEL_GPT_4_VISION:
-        params["max_tokens"] = 4096
-        params["temperature"] = 0
-
-    stream = await client.chat.completions.create(**params)  # type: ignore
-    full_response = ""
-    async for chunk in stream:  # type: ignore
-        assert isinstance(chunk, ChatCompletionChunk)
-        content = chunk.choices[0].delta.content or ""
-        full_response += content
-        await callback(content)
-
-    await client.close()
-
-    return full_response
-
-
-async def stream_azure_openai_response(
-    messages: List[ChatCompletionMessageParam],
-    azure_openai_api_key: str | None,
-    azure_openai_api_version: str | None,
-    azure_openai_resource_name: str | None,
-    azure_openai_deployment_name: str | None,
-    callback: Callable[[str], Awaitable[None]],
-) -> str:
-    client = AsyncAzureOpenAI(
-        api_version=azure_openai_api_version,
-        api_key=azure_openai_api_key,
-        azure_endpoint=f"https://{azure_openai_resource_name}.openai.azure.com/",
-        azure_deployment=azure_openai_deployment_name,
         )
+    elif api_provider_info.name == "azure":
+        client = AsyncAzureOpenAI(
+            api_version=api_provider_info.api_version,
+            api_key=api_provider_info.api_key,
+            azure_endpoint=f"https://{api_provider_info.resource_name}.openai.azure.com/",
+            azure_deployment=api_provider_info.deployment_name,
+        )
+    else:
+        raise Exception("Invalid api_provider_info")
 
     model = MODEL_GPT_4_VISION
 

backend/routes/generate_code.py

@@ -2,8 +2,9 @@ import os
 import traceback
 from fastapi import APIRouter, WebSocket
 import openai
+from api_types import AzureProviderInfo, OpenAiProviderInfo
 from config import IS_PROD, SHOULD_MOCK_AI_RESPONSE
-from llm import stream_openai_response, stream_azure_openai_response
+from llm import stream_openai_response
 from openai.types.chat import ChatCompletionMessageParam
 from mock_llm import mock_completion
 from typing import Dict, List
@@ -210,22 +211,44 @@ async def stream_code(websocket: WebSocket):
         completion = await mock_completion(process_chunk)
     else:
         try:
+            api_provider_info = None
             if openai_api_key is not None:
+                api_provider_info = {
+                    "name": "openai",
+                    "api_key": openai_api_key,
+                    "base_url": openai_base_url,
+                }
+
+                api_provider_info = OpenAiProviderInfo(
+                    api_key=openai_api_key, base_url=openai_base_url
+                )
+
+            if azure_openai_api_key is not None:
+                if (
+                    not azure_openai_api_version
+                    or not azure_openai_resource_name
+                    or not azure_openai_deployment_name
+                ):
+                    raise Exception(
+                        "Missing Azure OpenAI API version, resource name, or deployment name"
+                    )
+
+                api_provider_info = AzureProviderInfo(
+                    api_key=azure_openai_api_key,
+                    api_version=azure_openai_api_version,
+                    deployment_name=azure_openai_deployment_name,
+                    resource_name=azure_openai_resource_name,
+                )
+
+            if api_provider_info is None:
+                raise Exception("Invalid api_provider_info")
+
             completion = await stream_openai_response(
                 prompt_messages,
-                    api_key=openai_api_key,
+                api_provider_info=api_provider_info,
-                    base_url=openai_base_url,
-                    callback=lambda x: process_chunk(x),
-                )
-            if azure_openai_api_key is not None:
-                completion = await stream_azure_openai_response(
-                    prompt_messages,
-                    azure_openai_api_key=azure_openai_api_key,
-                    azure_openai_api_version=azure_openai_api_version,
-                    azure_openai_resource_name=azure_openai_resource_name,
-                    azure_openai_deployment_name=azure_openai_deployment_name,
                 callback=lambda x: process_chunk(x),
             )
+
         except openai.AuthenticationError as e:
             print("[GENERATE_CODE] Authentication failed", e)
             error_message = (