Fix[AI_field_Description]: error handling when credit limit reached

backend/app/api/v1/extract.py

@@ -1,4 +1,5 @@
 from typing import List
+from app.exceptions import CreditLimitExceededException
 from fastapi import APIRouter, Depends, HTTPException
 from pydantic import BaseModel
 from sqlalchemy.orm import Session
@@ -99,6 +100,11 @@ async def get_field_descriptions(
                     "data": data,
                 }
 
+            except CreditLimitExceededException:
+                raise HTTPException(
+                    status_code=402, detail="Credit limit Reached, Wait next month or upgrade your Plan!"
+                )
+
             except Exception as e:
                 logger.error(e)
                 logger.log("Retrying AI field description generation.")

backend/app/requests/__init__.py

@@ -1,6 +1,7 @@
 import json
 import os
 from app.exceptions import CreditLimitExceededException
+from fastapi import HTTPException
 from .schemas import ExtractFieldsResponse, TextExtractionResponse
 import requests
 from app.config import settings
@@ -124,14 +125,19 @@ def extract_field_descriptions(api_token, fields):
         headers=headers,
         timeout=360,
     )
-    # Check the response status code
-    if response.status_code == 201 or response.status_code == 200:
-        return response.json()
-    else:
+    if response.status_code not in [200, 201]:
         logger.error(
-            f"Unable to process file during field description generation. It returned {response.status_code} code: {response.text}"
+            f"Failed to field description. It returned {response.status_code} code: {response.text}"
         )
-        raise Exception("Unable to process file!")
+        if response.status_code == 402:
+            raise CreditLimitExceededException(
+                response.json().get("detail", "Credit limit exceeded!")
+            )
+
+        raise HTTPException(response.json().get("detail", "Failed to fetch field description"))
+
+    # Check the response status code
+    return response.json()
 
 
 def highlight_sentences_in_pdf(api_token, sentences, file_path, output_path):
@@ -203,13 +209,13 @@ def get_user_usage_data(api_token: str):
 
     response = requests.post(url, headers=headers)
 
-    if response.status_code not in [200, 201]:
-        logger.error(
-            f"Failed to fetch usage data. It returned {response.status_code} code: {response.text}"
-        )
-        raise Exception("Failed to fetch usage data")
-
     try:
+        if response.status_code not in [200, 201]:
+            logger.error(
+                f"Failed to fetch usage data. It returned {response.status_code} code: {response.text}"
+            )
+            raise Exception(response.text)
+
         return response.json()
     except requests.exceptions.JSONDecodeError:
         logger.error(f"Invalid JSON response from API server: {response.text}")

frontend/src/services/extract.tsx

@@ -39,10 +39,18 @@ export const GetAIFieldDescriptions = async (
     );
     return response;
   } catch (error) {
-    if (axios.isAxiosError(error) && error.response?.data?.error) {
-      throw new Error(error.response.data.error);
+    if (axios.isAxiosError(error)) {
+      if (error.response?.data) {
+        throw new Error(error.response.data.detail);
+      } else {
+        throw new Error(
+          "Failed to generate AI field descriptions. Please try again."
+        );
+      }
     } else {
-      throw new Error("Failed to extract data. Please try again.");
+      throw new Error(
+        "Failed to generate AI field descriptions. Please try again."
+      );
     }
   }
 };