Update app.py

app.py

@@ -21,19 +21,19 @@ le=LLM_as_Evaluator()
 # Pydantic model for request body
 class EvalInput(BaseModel):
     promptversion: str
-    evaluator_type:str
 
 @app.post("/evaluate")
 async def evaluation(request:EvalInput):
 
     prompt_version = request.promptversion
-    evaluator_type = request.evaluator_type
-    match evaluator_type :
-        case "ParadigmIdentification":
-            le.Paradigm_LLM_Evaluator(prompt_version)
+    prompt_version_splitted=prompt_version.split(":")
 
-        case "ObservationBiologist":
-            le.Observation_LLM_Evaluator(prompt_version)
+    if prompt_version_splitted[0]=="paradigm_identifier"
+
+        le.Paradigm_LLM_Evaluator(prompt_version)
+
+    elif  prompt_version_splitted[0]=="observational_biologist"
+        le.Observation_LLM_Evaluator(prompt_version)
             
     # Example processing (replace with actual logic)
     return JSONResponse(content={"evalsuccessful":True},status_code=200)