Update app.py

app.py

@@ -61,7 +61,30 @@ def search(query):
     match_ids = [match['id'].split('-')[0] for match in xc['matches']]
     # Query the existing DataFrame based on 'id'
     filtered_df = df[df['_id'].isin(match_ids)]
-    attributes_to_extract = ['_id', 'postedBy.accountName', 'images', 'title', 'location', 'price']
+    attributes_to_extract = ['_id', 'title', 'location', 'features', 'description', 'images',
+       'videos', 'available', 'price', 'attachedDocument', 'year',
+       'carCondition', 'engineType', 'colour', 'model', 'noOfBed',
+       'noOfBathroom', 'locationISO', 'forRent', 'views', 'thoseWhoSaved',
+       'createdAt', 'updatedAt', '__v', 'category._id', 'category.title',
+       'category.slug', 'category.isAdminAllowed', 'category.createdAt',
+       'category.updatedAt', 'category.__v', 'postedBy.pageViews.value',
+       'postedBy.pageViews.users', 'postedBy.totalSaved.value',
+       'postedBy.totalSaved.users', 'postedBy._id', 'postedBy.firstName',
+       'postedBy.lastName', 'postedBy.about', 'postedBy.cover',
+       'postedBy.email', 'postedBy.password', 'postedBy.isAdmin',
+       'postedBy.savedListing', 'postedBy.isVerified',
+       'postedBy.verifiedProfilePicture', 'postedBy.profilePicture',
+       'postedBy.pronoun', 'postedBy.userType', 'postedBy.accountType',
+       'postedBy.subscribed', 'postedBy.noOfSubscription',
+       'postedBy.totalListing', 'postedBy.sellerType', 'postedBy.createdAt',
+       'postedBy.updatedAt', 'postedBy.__v', 'postedBy.address',
+       'postedBy.city', 'postedBy.country', 'postedBy.gender',
+       'postedBy.nationality', 'postedBy.verificationType', 'postedBy.dob',
+       'postedBy.locationISO', 'postedBy.state', 'postedBy.zipCode',
+       'postedBy.otherNames', 'postedBy.facebookUrl', 'postedBy.instagramUrl',
+       'postedBy.phoneNumber1', 'postedBy.phoneNumber2', 'postedBy.websiteUrl',
+       'postedBy.accountName', 'postedBy.accountNo', 'postedBy.bankName',
+       'string_features', 'complete_description']
     extracted_data = filtered_df[attributes_to_extract]
     result_json = extracted_data.to_json(orient='records')
     return result_json