How to Create a Custom Algorithm for Matchmaking in a Dating App in FlutterFlow

Extend the users collection with dating profile fields: age (Int), gender (String), interests (Array of Strings, e.g., hiking, cooking, travel), bio (String), photoUrls (Array of Strings, up to 6), lookingFor (String: male/female/everyone), ageRangeMin (Int), ageRangeMax (Int), locationLat (Double), locationLng (Double), locationGeoHash (String, for proximity queries). Create a likes collection with: fromUserId (Reference), toUserId (Reference), timestamp (Timestamp), isLike (Boolean, true=like, false=pass). Create a matches collection with: user1Id (Reference), user2Id (Reference), chatId (String, auto-generated), matchedAt (Timestamp), lastMessageAt (Timestamp). Create a subcollection users/{uid}/match_queue with: candidateId (Reference), score (Double), generatedAt (Timestamp).

Deploy a Cloud Function computeMatchQueue(userId) that loads the user's profile and queries candidate profiles matching their lookingFor and gender preferences. For each candidate, calculate a compatibility score: +10 points for each shared interest (intersection of interests arrays), +5 points if the candidate's age falls within the user's ageRangeMin to ageRangeMax, +3 points for location proximity (calculate distance from geoHash, with max 50km), -100 for any existing like or pass (query likes collection for fromUserId=user, toUserId=candidate). Sort candidates by score descending. Write the top 50 to users/{uid}/match_queue as subcollection documents with candidateId and score. Schedule this function to run nightly via Cloud Scheduler, or trigger it when the user's match_queue drops below 10 items.

Create a SwipePage. On page load, query the current user's match_queue ordered by score desc. For each candidate, fetch their profile document. Display profiles in a PageView where each page is a full-screen Stack: background Image (first photo, full bleed), gradient overlay from bottom, and a bottom Column with name + age Text, interests displayed as Wrap Chips, and bio Text. Add a photo indicator Row (dots) since the user can swipe left/right on photos within a PageView.nested inside the main profile PageView. At the bottom, add a Row of action buttons: X (pass, red), Heart (like, green), and Star (super-like, gold). Alternatively, detect horizontal swipe gestures: swipe right = like, swipe left = pass.

On like (swipe right or heart button tap): create a likes doc with fromUserId=current user, toUserId=candidate, isLike=true. Then check if a reciprocal like exists: query likes where fromUserId=candidate and toUserId=current user and isLike=true. If found, it is a mutual match — create a matches doc with both user IDs and a generated chatId. Show an animated match overlay (Container with both users' photos and 'It is a Match!' text). Send a push notification to the other user via Cloud Function. On pass (swipe left or X tap): create a likes doc with isLike=false. In both cases, remove the candidate from the local match_queue list and advance to the next profile. If the queue empties, show 'No more profiles — check back tomorrow.'

Create a MatchesPage. Query matches where user1Id or user2Id equals the current user, ordered by lastMessageAt desc (most recent conversation first). For each match, display the other user's first photo as a CircleImage, their name, and the last message preview (if any). Tapping a match navigates to a ChatPage using the match's chatId. The ChatPage queries messages subcollection under matches/{matchId}/messages, displaying a reversed ListView of message bubbles. Each message has senderId, text, and timestamp. TextField + send button at the bottom. On message send, create the message doc and update lastMessageAt on the match document so the matches list stays sorted by recency.