Add multiple openai endpoints with the same proxy API.

proxy/routes/proxy.py

@@ -1,49 +1,36 @@
 """Proxy service to forward requests to the appropriate language model provider"""
 
-from enum import Enum
-
 from fastapi import APIRouter, Depends, Header, HTTPException, Request
 
 proxy = APIRouter()
 
 
-class LLMProvider(str, Enum):
-    """Supported language model providers"""
-
-    OPEN_AI = "openai"
-    ANTHROPIC = "anthropic"
-
-    @classmethod
-    def is_valid(cls, provider: str) -> bool:
-        """Check if a provider is a valid LLM provider"""
-        return provider in {provider.value for provider in cls}
-
-
 def validate_headers(invariant_authorization: str = Header(None)):
-    """Require the Invariant-Authorization header to be present"""
+    """Require the invariant-authorization header to be present"""
     if invariant_authorization is None:
         raise HTTPException(
-            status_code=400, detail="Missing Invariant-Authorization header"
+            status_code=400, detail="Missing invariant-authorization header"
         )
     return invariant_authorization
 
 
+allowed_openai_endpoints = {"chat/completions", "moderations"}
+
+
 @proxy.post(
-    "/{username}/{dataset_name}/{llm_provider}",
+    "/{username}/{dataset_name}/openai/{endpoint:path}",
     dependencies=[Depends(validate_headers)],
 )
-async def chat_completion(
+async def openai_proxy(
     request: Request,
     username: str,
     dataset_name: str,
-    llm_provider: str,
+    endpoint: str,
 ):
     """Proxy call to a language model provider"""
-
-    if not LLMProvider.is_valid(llm_provider):
-        raise HTTPException(
-            status_code=400,
-            detail=f"Unsupported LLM provider '{llm_provider}'.",
-        )
-
-    return {"message": f"Upload {dataset_name} for {username} to {llm_provider}"}
+    print("headers: ", dict(request.headers))
+    # print("request: ", await request.json())
+    print(f"Proxying to OpenAI endpoint: {endpoint}")
+    if endpoint not in allowed_openai_endpoints:
+        raise HTTPException(status_code=404, detail="Not supported OpenAI endpoint")
+    return {"message": f"Upload {dataset_name} for {username} to openai"}