add milestone api

api/admin.py

@@ -1,12 +1,14 @@
 from django.contrib import admin
-from .models import UserData, AIKey, AppVersion
-from .models import Contact , ExpenseLog
+from .models import MilestoneJsonDataStore, UserData, AIKey, AppVersion
+from .models import Contact, ExpenseLog
+
 
 @admin.register(Contact)
 class ContactAdmin(admin.ModelAdmin):
-    list_display = ('id', 'name', 'email', 'message')
-    list_filter = ('id', 'name', 'email')
-    search_fields = ('id', 'name', 'email', 'message')
+    list_display = ("id", "name", "email", "message")
+    list_filter = ("id", "name", "email")
+    search_fields = ("id", "name", "email", "message")
+
 
 @admin.register(AIKey)
 class AIKeyAdmin(admin.ModelAdmin):
@@ -48,4 +50,26 @@ class ExpenseLogAdmin(admin.ModelAdmin):
     list_display = ("text", "predicted_category", "confidence_score", "created_at")
     list_filter = ("predicted_category", "created_at")
     search_fields = ("text", "predicted_category")
-    ordering = ("-created_at",)
+    ordering = ("-created_at",)
+
+
+@admin.register(MilestoneJsonDataStore)
+class MilestoneJsonDataStoreAdmin(admin.ModelAdmin):
+
+    list_display = ("id", "field_id", "created_at", "updated_at")
+
+    list_display_links = ("id", "field_id")
+
+    search_fields = ("field_id",)
+
+    list_filter = ("created_at", "updated_at")
+
+    ordering = ("-created_at",)
+
+    readonly_fields = ("created_at", "updated_at")
+
+    fieldsets = (
+        ("Basic Info", {"fields": ("field_id",)}),
+        ("JSON Data", {"fields": ("json_data",)}),
+        ("Timestamps", {"fields": ("created_at", "updated_at")}),
+    )

api/apps.py

@@ -1,49 +1,46 @@
 from django.apps import AppConfig
-import torch
-from transformers import pipeline
-import os
 
 
 class ApiConfig(AppConfig):
     default_auto_field = "django.db.models.BigAutoField"
     name = "api"
 
-    def ready(self):
-        # Prevent loading twice (Django sometimes runs ready() twice in dev mode)
-        if os.environ.get("RUN_MAIN", None) != "true" and not os.environ.get(
-            "KUBERNETES_PORT"
-        ):
-            pass  # Keep going if running via Gunicorn or in production
+    # def ready(self):
+    #     # Prevent loading twice (Django sometimes runs ready() twice in dev mode)
+    #     if os.environ.get("RUN_MAIN", None) != "true" and not os.environ.get(
+    #         "KUBERNETES_PORT"
+    #     ):
+    #         pass  # Keep going if running via Gunicorn or in production
 
-        print("Loading Expense Categorizer AI from cache...")
+    #     print("Loading Expense Categorizer AI from cache...")
 
-        device = 0 if torch.cuda.is_available() else -1
+    #     device = 0 if torch.cuda.is_available() else -1
 
-        # This will automatically use the cached version built by Docker
-        self.classifier = pipeline(
-            "zero-shot-classification",
-            model="valhalla/distilbart-mnli-12-3",
-            device=device,
-        )
+    #     # This will automatically use the cached version built by Docker
+    #     self.classifier = pipeline(
+    #         "zero-shot-classification",
+    #         model="valhalla/distilbart-mnli-12-3",
+    #         device=device,
+    #     )
 
-        self.categories = [
-            "Food & Drinks",
-            "Groceries",
-            "Shopping",
-            "Bills & Utilities",
-            "Entertainment",
-            "Health",
-            "Education",
-            "Subscriptions",
-            "Travel",
-            "Rent",
-            "Family & Friends",
-            "Miscellaneous",
-            "Gifts",
-            "Party",
-            "Personal Care",
-            "Home & Hygiene",
-            "Others",
-            "Recharge",
-        ]
-        print("AI Model loaded successfully!")
+    #     self.categories = [
+    #         "Food & Drinks",
+    #         "Groceries",
+    #         "Shopping",
+    #         "Bills & Utilities",
+    #         "Entertainment",
+    #         "Health",
+    #         "Education",
+    #         "Subscriptions",
+    #         "Travel",
+    #         "Rent",
+    #         "Family & Friends",
+    #         "Miscellaneous",
+    #         "Gifts",
+    #         "Party",
+    #         "Personal Care",
+    #         "Home & Hygiene",
+    #         "Others",
+    #         "Recharge",
+    #     ]
+    #     print("AI Model loaded successfully!")

api/migrations/0004_milestonejsondatastore.py

@@ -0,0 +1,26 @@
+# Generated by Django 5.2.4 on 2026-03-30 05:49
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ('api', '0003_expenselog_amount'),
+    ]
+
+    operations = [
+        migrations.CreateModel(
+            name='MilestoneJsonDataStore',
+            fields=[
+                ('id', models.AutoField(primary_key=True, serialize=False)),
+                ('field_id', models.CharField(max_length=255, unique=True)),
+                ('json_data', models.JSONField()),
+                ('created_at', models.DateTimeField(auto_now_add=True)),
+                ('updated_at', models.DateTimeField(auto_now=True)),
+            ],
+            options={
+                'db_table': 'milestone_json_data_store',
+            },
+        ),
+    ]

api/models.py

@@ -67,3 +67,18 @@ class ExpenseLog(models.Model):
 
     def __str__(self):
         return f"{self.predicted_category} (${self.amount}): {self.text[:30]}"
+
+
+class MilestoneJsonDataStore(models.Model):
+    id = models.AutoField(primary_key=True)
+    field_id = models.CharField(max_length=255, unique=True)
+    json_data = models.JSONField()
+
+    created_at = models.DateTimeField(auto_now_add=True)
+    updated_at = models.DateTimeField(auto_now=True)
+
+    class Meta:
+        db_table = "milestone_json_data_store"
+
+    def __str__(self):
+        return f"{self.id} - {self.field_id}"

api/serializers.py

@@ -22,3 +22,14 @@ class ExpenseRequestSerializer(serializers.Serializer):
         max_length=500,
         help_text="Enter the expense description to categorize (e.g., 'Paid 1500 for electricity')",
     )
+
+
+from rest_framework import serializers
+from .models import MilestoneJsonDataStore
+
+
+class MilestoneJsonDataSerializer(serializers.ModelSerializer):
+
+    class Meta:
+        model = MilestoneJsonDataStore
+        fields = ["id", "field_id", "json_data", "created_at", "updated_at"]

api/urls.py

@@ -1,5 +1,7 @@
 from django.urls import path
-from .views import UserDataPostView, GetFieldView, ContactList1, CategorizeExpenseView
+from .views import UserDataPostView, GetFieldView, ContactList1
+from django.urls import path
+from .views import save_json_data, get_json_data
 
 urlpatterns = [
     path("post/", UserDataPostView.as_view(), name="post_user_data"),
@@ -7,5 +9,7 @@ urlpatterns = [
         "<str:field>/<str:identifier>/", GetFieldView.as_view(), name="get_field_data"
     ),
     path("contact/", ContactList1.as_view()),
-    path("categorize/", CategorizeExpenseView.as_view(), name="categorize_expense"),
+    # path("categorize/", CategorizeExpenseView.as_view(), name="categorize_expense"),
+    path("milestone/save/post/", save_json_data),
+    path("milestone/get/<str:field_id>/", get_json_data),
 ]

api/views.py

@@ -9,6 +9,11 @@ import uuid
 from .models import ExpenseLog
 from django.apps import apps
 import re
+from rest_framework.decorators import api_view
+from rest_framework.response import Response
+from rest_framework import status
+from .models import MilestoneJsonDataStore
+from .serializers import MilestoneJsonDataSerializer
 
 
 class UserDataPostView(APIView):
@@ -100,50 +105,133 @@ class ContactList1(CreateAPIView):
         )
 
 
-class CategorizeExpenseView(GenericAPIView):
-    # 2. Assign the serializer class to automatically populate the Swagger schema
-    serializer_class = ExpenseRequestSerializer
+# class CategorizeExpenseView(GenericAPIView):
+#     # 2. Assign the serializer class to automatically populate the Swagger schema
+#     serializer_class = ExpenseRequestSerializer
+
+#     def post(self, request):
+#         # 3. Validate input using the serializer
+#         serializer = self.get_serializer(data=request.data)
+#         if not serializer.is_valid():
+#             return Response(serializer.errors, status=400)
+
+#         expense_text = serializer.validated_data["text"]
+
+#         # 4. Extract Amount using Regex
+#         # Matches formats like 150, 1,500, 150.50, 1,500.50
+#         amount_match = re.search(r"\d+(?:,\d+)*(?:\.\d+)?", expense_text)
+#         extracted_amount = (
+#             float(amount_match.group().replace(",", "")) if amount_match else None
+#         )
+
+#         # 5. Use the safe Django app registry to fetch the pre-loaded AI model
+#         api_config = apps.get_app_config("api")
+
+#         result = api_config.classifier(
+#             expense_text,
+#             candidate_labels=api_config.categories,
+#             hypothesis_template="This expense is for {}.",
+#         )
+
+#         top_category = result["labels"][0]
+#         confidence_score = result["scores"][0]
+
+#         # 6. Save to database
+#         ExpenseLog.objects.create(
+#             text=expense_text,
+#             amount=extracted_amount,
+#             predicted_category=top_category,
+#             confidence_score=confidence_score,
+#         )
+
+#         return Response(
+#             {
+#                 "expense": expense_text,
+#                 "amount": extracted_amount,
+#                 "category": top_category,
+#                 "confidence": round(confidence_score * 100, 2),
+#             }
+#         )
+
+
+@api_view(["POST"])
+def save_json_data(request):
+    field_id = request.data.get("field_id")
+    json_data = request.data.get("json_data")
+
+    # ✅ Manual validation (VERY IMPORTANT)
+    if not field_id:
+        return Response(
+            {"message": "field_id is required"},
+            status=status.HTTP_400_BAD_REQUEST,
+        )
 
-    def post(self, request):
-        # 3. Validate input using the serializer
-        serializer = self.get_serializer(data=request.data)
-        if not serializer.is_valid():
-            return Response(serializer.errors, status=400)
+    if not isinstance(json_data, dict) or not json_data:
+        return Response(
+            {"message": "json_data must be a non-empty JSON object"},
+            status=status.HTTP_400_BAD_REQUEST,
+        )
+
+    # 🔍 Check if exists
+    obj = MilestoneJsonDataStore.objects.filter(field_id=field_id).first()
+
+    if obj:
+        # 🔄 UPDATE
+        obj.json_data = json_data
+        obj.save()
 
-        expense_text = serializer.validated_data["text"]
+        serializer = MilestoneJsonDataSerializer(obj)
 
-        # 4. Extract Amount using Regex
-        # Matches formats like 150, 1,500, 150.50, 1,500.50
-        amount_match = re.search(r"\d+(?:,\d+)*(?:\.\d+)?", expense_text)
-        extracted_amount = (
-            float(amount_match.group().replace(",", "")) if amount_match else None
+        return Response(
+            {
+                "message": "Data updated successfully",
+                "flag": 1,
+                "data": serializer.data,
+            },
+            status=status.HTTP_200_OK,
         )
 
-        # 5. Use the safe Django app registry to fetch the pre-loaded AI model
-        api_config = apps.get_app_config("api")
+    else:
+        # 🆕 CREATE
+        obj = MilestoneJsonDataStore.objects.create(
+            field_id=field_id, json_data=json_data
+        )
+
+        serializer = MilestoneJsonDataSerializer(obj)
 
-        result = api_config.classifier(
-            expense_text,
-            candidate_labels=api_config.categories,
-            hypothesis_template="This expense is for {}.",
+        return Response(
+            {
+                "message": "Data created successfully",
+                "flag": 0,
+                "data": serializer.data,
+            },
+            status=status.HTTP_201_CREATED,
         )
 
-        top_category = result["labels"][0]
-        confidence_score = result["scores"][0]
 
-        # 6. Save to database
-        ExpenseLog.objects.create(
-            text=expense_text,
-            amount=extracted_amount,
-            predicted_category=top_category,
-            confidence_score=confidence_score,
+@api_view(["GET"])
+def get_json_data(request, field_id):
+
+    # ✅ Validate input
+    if not field_id:
+        return Response(
+            {"message": "field_id is required", "flag": 0},
+            status=status.HTTP_400_BAD_REQUEST,
         )
 
+    try:
+        obj = MilestoneJsonDataStore.objects.get(field_id=field_id)
+
         return Response(
             {
-                "expense": expense_text,
-                "amount": extracted_amount,
-                "category": top_category,
-                "confidence": round(confidence_score * 100, 2),
-            }
+                "message": "Data fetched successfully",
+                "flag": 1,
+                "data": obj.json_data,  # 🔥 Only JSON data
+            },
+            status=status.HTTP_200_OK,
+        )
+
+    except MilestoneJsonDataStore.DoesNotExist:
+        return Response(
+            {"message": "Data not found", "flag": 0}, status=status.HTTP_404_NOT_FOUND
         )

dev.py

@@ -3,7 +3,7 @@ import json
 
 # Replace this URL with your actual Hugging Face Space URL once deployed
 # For local testing (e.g., python manage.py runserver), use: "[http://127.0.0.1:8000/api/categorize/](http://127.0.0.1:8000/api/categorize/)"
-API_URL = "http://127.0.0.1:8000/api/categorize/"
+API_URL = "https://coders813-exwiseapi.hf.space/api/categorize/"
 
 
 def test_categorize_expense(expense_text):