Update main.py

main.py

@@ -1,11 +1,20 @@
 import os
 import pickle
 import pandas as pd
-from fastapi import FastAPI, Request, Form
-from fastapi.responses import HTMLResponse
+from fastapi import FastAPI, Request, Form, HTTPException
+from fastapi.responses import HTMLResponse, JSONResponse
 from fastapi.templating import Jinja2Templates
+from fastapi.middleware.cors import CORSMiddleware
 
 app = FastAPI(title="Student Score Predictor")
+# Allow CORS for frontend JS
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
 templates = Jinja2Templates(directory="templates")
 
 # Load the trained model at startup
@@ -16,59 +25,56 @@ try:
 except Exception as e:
     raise RuntimeError(f"Failed to load model: {e}")
 
-# List of input fields and types
+# Input fields configuration
 FIELDS = [
-    ('Age', int),
-    ('Gender', str),
-    ('HoursOfStudyPerDay', float),
-    ('SchoolAttendanceRate', float),
-    ('TuitionAccess', str),
-    ('AveragePreviousScores', float),
-    ('HoursOfSleep', float),
-    ('BreakfastDaily', str),
-    ('ScreenTimeHours', float),
-    ('PhysicalActivityHours', float),
-    ('PlaysSport', str),
-    ('MentalHealthScore', float),
-    ('ParentalEducationLevel', str),
-    ('HouseholdIncomeLevel', str),
-    ('StudyEnvironmentRating', float),
-    ('FriendSupportScore', float),
-    ('ParticipatesInClubs', str),
-    ('PartTimeWork', str),
+    {'name': 'Age', 'type': 'number', 'question': 'What is your age?', 'validation': {'min': 5, 'max': 100}},
+    {'name': 'Gender', 'type': 'select', 'question': 'What is your gender?', 'options': ['Male','Female']},
+    {'name': 'HoursOfStudyPerDay', 'type': 'number', 'question': 'How many hours do you study per day?', 'validation': {'min': 0, 'max': 24}},
+    {'name': 'SchoolAttendanceRate', 'type': 'number', 'question': 'What is your school attendance rate in %?', 'validation': {'min': 0, 'max': 100}},
+    {'name': 'TuitionAccess', 'type': 'select', 'question': 'Do you have access to tuition (Yes/No)?', 'options': ['Yes','No']},
+    {'name': 'AveragePreviousScores', 'type': 'number', 'question': 'What is your average previous score?', 'validation': {'min': 0, 'max': 100}},
+    {'name': 'HoursOfSleep', 'type': 'number', 'question': 'How many hours of sleep do you get per day?', 'validation': {'min': 0, 'max': 24}},
+    {'name': 'BreakfastDaily', 'type': 'select', 'question': 'Do you have breakfast daily? (Yes/No)', 'options': ['Yes','No']},
+    {'name': 'ScreenTimeHours', 'type': 'number', 'question': 'How many hours of screen time per day?', 'validation': {'min': 0, 'max': 24}},
+    {'name': 'PhysicalActivityHours', 'type': 'number', 'question': 'How many hours of physical activity per day?', 'validation': {'min': 0, 'max': 24}},
+    {'name': 'PlaysSport', 'type': 'select', 'question': 'Do you play sports? (Yes/No)', 'options': ['Yes','No']},
+    {'name': 'MentalHealthScore', 'type': 'number', 'question': 'Rate your mental health (1-10)', 'validation': {'min': 1, 'max': 10}},
+    {'name': 'ParentalEducationLevel', 'type': 'select', 'question': 'Parental education level?', 'options': ['High school','Graduate','Postgrad']},
+    {'name': 'HouseholdIncomeLevel', 'type': 'select', 'question': 'Household income level?', 'options': ['Low','Medium','High']},
+    {'name': 'StudyEnvironmentRating', 'type': 'number', 'question': 'Rate your study environment (1-5)', 'validation': {'min': 1, 'max': 5}},
+    {'name': 'FriendSupportScore', 'type': 'number', 'question': 'Rate friend support (1-10)', 'validation': {'min': 1, 'max': 10}},
+    {'name': 'ParticipatesInClubs', 'type': 'select', 'question': 'Do you participate in clubs? (Yes/No)', 'options': ['Yes','No']},
+    {'name': 'PartTimeWork', 'type': 'select', 'question': 'Do you do part-time work? (Yes/No)', 'options': ['Yes','No']},
 ]
 
 @app.get('/', response_class=HTMLResponse)
-async def get_form(request: Request):
-    return templates.TemplateResponse('index.html', {
+async def get_chat(request: Request):
+    # Serve the chat UI, embedding the FIELDS config
+    return templates.TemplateResponse('chat.html', {
         'request': request,
-        'predicted': None,
-        'values': {}
+        'fields': FIELDS
     })
 
-@app.post('/predict', response_class=HTMLResponse)
-async def post_predict(request: Request, **form_data):
-    # Convert form inputs to correct types
-    record = {}
-    for name, dtype in FIELDS:
-        raw = form_data.get(name)
-        if raw is None:
-            # missing field
-            record[name] = None
-            continue
-        record[name] = dtype(raw)
-
-    # Prepare DataFrame
-    df = pd.DataFrame([record])
-    # Predict
+@app.post('/predict_json')
+async def predict_json(payload: dict):
+    # Ensure all fields present
     try:
-        score = model.predict(df)[0]
-        predicted = round(score, 2)
-    except Exception as e:
-        predicted = f"Error: {e}"
-
-    return templates.TemplateResponse('index.html', {
-        'request': request,
-        'predicted': predicted,
-        'values': record
-    })
+        data = {f['name']: payload[f['name']] for f in FIELDS}
+    except KeyError as e:
+        raise HTTPException(status_code=400, detail=f"Missing field: {e}")
+    # Cast types
+    for f in FIELDS:
+        name = f['name']
+        if f['type']=='number':
+            data[name] = float(data[name])
+    # Validate
+    for f in FIELDS:
+        if f['type']=='number' and 'validation' in f:
+            val = data[f['name']]
+            v = f['validation']
+            if not (v['min'] <= val <= v['max']):
+                raise HTTPException(status_code=400, detail=f"{f['name']} must be between {v['min']} and {v['max']}")
+    # Predict
+    df = pd.DataFrame([data])
+    score = model.predict(df)[0]
+    return JSONResponse({'predicted': round(float(score),2)})