custom error messages

StudybotAPI/backend/core/ExceptionHandlers.py

@@ -0,0 +1,27 @@
+from backend import app
+from .Exceptions import *
+
+from fastapi.responses import JSONResponse
+from fastapi.requests import Request
+from fastapi import status
+
+@app.exception_handler(ModelDeployingException)
+async def model_deploying_exception_handler(request: Request, exc: ModelDeployingException):
+    return JSONResponse(
+        status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
+        content=repr(exc)
+    )
+
+@app.exception_handler(InfoNotProvidedException)
+async def info_not_provided_exception_handler(request: Request, exc: InfoNotProvidedException):
+    return JSONResponse(
+        status_code=status.HTTP_400_BAD_REQUEST,
+        content=repr(exc)
+    )
+
+@app.exception_handler(DataNotUploadedException)
+async def data_not_uploaded_exception_handler(request: Request, exc: DataNotUploadedException):
+    return JSONResponse(
+        status_code=status.HTTP_400_BAD_REQUEST,
+        content=repr(exc)
+    )

StudybotAPI/backend/core/Exceptions.py

@@ -0,0 +1,64 @@
+from backend.schemas import FrontendResponseModel
+
+
+class ModelDeployingException(Exception):
+    def __init__(self, response_result: FrontendResponseModel):
+        self.response_result = response_result
+        self.set_status()
+        super(ModelDeployingException, self).__init__()
+
+    def set_status(self):
+        self.response_result["status"] = "Error"
+        self.response_result["message"][0]="Model is deploying. Please try again later."
+
+    def __repr__(self):
+        return f"exception.ModelDeployingException()"
+
+
+
+class InfoNotProvidedException(Exception):
+    def __init__(self, response_result: FrontendResponseModel, message: str):
+        self.response_result = response_result
+        self.message = message
+        self.set_status()
+        super(InfoNotProvidedException, self).__init__(message)
+
+    def set_status(self):
+        self.response_result["status"] = "Error"
+        self.response_result["message"][0] = "Information not provided."
+        self.response_result["message"].append(self.message)
+
+    def __repr__(self):
+        return f"exception.InfoNotProvidedException()"
+
+
+class DataNotUploadedException(Exception):
+    def __init__(self, response_result: FrontendResponseModel):
+        self.response_result = response_result
+        self.set_status()
+        super(ModelDeployingException, self).__init__()
+
+    def set_status(self):
+        self.response_result["status"] = "Error"
+        self.response_result["message"].append(
+            "Data not uploaded. Please upload a file."
+        )
+
+    def __repr__(self):
+        return f"exception.DataNotUploadedException()"
+
+
+class PdfLoaderException(Exception):
+    def __init__(self, response_result: FrontendResponseModel):
+        self.response_result = response_result
+        self.set_status()
+        super(ModelDeployingException, self).__init__()
+
+    def set_status(self):
+        self.response_result["status"] = "Error"
+        self.response_result["message"].append(
+            "PDF Loader Exception. Please try again."
+        )
+
+    def __repr__(self):
+        return f"exception.PdfLoaderException()"

StudybotAPI/backend/retriever/ops.py

@@ -1,10 +1,16 @@
 from backend.schemas import *
 
+from backend.core.Exceptions import *
+from backend.core.ExceptionHandlers import *
 from backend import app
 
+from clarifai_grpc.grpc.api.status import status_code_pb2
 
 def ops_inference(response_result: FrontendResponseModel, question: str):
 
+    if question == "":
+        raise InfoNotProvidedException(response_result, "Come on, I'm not telepathic. I can't read your mind. Please provide me with a question.")
+
     try:
         llm_response = app.state.qa_chain(question)
         output = Inference(
@@ -14,5 +20,5 @@ def ops_inference(response_result: FrontendResponseModel, question: str):
 
         response_result["result"] = output.dict()
     except Exception as e:
-        response_result["message"] = "error"
-        response_result["result"] = str(e)
+        response_result["status"] = "error"
+        response_result["message"].append(str(e))

StudybotAPI/backend/routes.py

@@ -28,26 +28,36 @@ def api_home():
     return {"detail": "Welcome to Studybot API"}
 
 
-@app.post("/api/upload", summary="Upload", tags=["Resource Server"])
+@app.post("/api/upload", response_model=DataResponseModel,summary="Upload", tags=["Resource Server"])
 def upload_data(bg_tasks: BackgroundTasks, file: UploadFile = File(...)):
+
+    response_result = {
+        "status": "success",
+        "message": ["Data uploaded successfully."]
+    }
+
     try:
         suffix = Path(file.filename).suffix
         with NamedTemporaryFile(delete=False, suffix=suffix) as tmp:
             shutil.copyfileobj(file.file, tmp)
             tmp_path = os.path.join(os.getcwd(), tmp.name)
     except Exception as e:
-        return e
+        response_result["status"] = "error"
+        response_result["message"][0]=str(e)
+        raise DataNotUploadedException(response_result)
+
     finally:
         file.file.close()
 
-    # path = os.path.join(os.getcwd(), file.filename)
     bg_tasks.add_task(llm_chain_loader, DATA_PATH=tmp_path)
+    return response_result
 
 
 @app.post("/api/inference",summary="Inference",response_model=FrontendResponseModel,tags=["Resource Server"])
 def inference(data: Chat):
     response_result = {
-        "message": "success", 
+        "status": "success",
+        "message": [""], 
         "result": {}
     }
 

StudybotAPI/backend/schemas/FrontendResponseSchema.py

@@ -1,6 +1,12 @@
+from typing import List
 from pydantic import BaseModel
 
 
 class FrontendResponseModel(BaseModel):
-    message: str
+    status: str
+    message: List[str]
     result: dict
+
+class DataResponseModel(BaseModel):
+    status: str
+    message: List[str]

frontend/requirements.txt

@@ -0,0 +1 @@
+streamlit

frontend/🏡_Home.py

@@ -1,13 +1,21 @@
 import streamlit as st
 
+import requests
+
 # from studybot import qa_chain
 # st.write(qa_chain)
 
+upload_pdf = st.file_uploader("Upload PDF", type="pdf")
+if upload_pdf is not None:
+    files = {"file": upload_pdf}
+    response = requests.post("https://hemanthsai7-studybotapi.hf.space/api/upload", files=files)
+    st.write(response)
+
 query=st.text_input("Question", key="question")
 st.write(st.session_state)
 
 if st.button("Ask"):
     # answer = qa_chain(query)
-    answer = st.session_state["qa_chain"](query)
+    answer = requests.post("https://hemanthsai7-studybotapi.hf.space/api/inference", json={"promptMessage": query}).json()
     st.write(answer)
     # st.session_state["question"] = ""