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IMPLEMENTATION_README.md

@@ -568,6 +568,11 @@ The main entry points are:
 - `score_pair_full(top, bottom, occasion, other=None)`
 - `recommend_outfits(tops, bottoms, occasion, others, locked_top, locked_bottom, locked_other)`
 
+Runtime output details:
+
+- `score_pair_full()` returns `engine_version: scoring-v2`.
+- `recommend_outfits()` returns up to `TOP_K = 6` combinations.
+
 ### Weights
 
 `WEIGHTS`:
@@ -697,6 +702,14 @@ This lets accessories, footwear, or outerwear influence the outfit without overp
 
 `build_reason()` creates user-facing text from the strongest and weakest scoring dimensions. `build_tip()` gives the styling advice shown in the UI.
 
+### Diversity Penalty
+
+`recommend_outfits()` applies `_apply_diversity_penalty()` before final ranking:
+
+- Near-duplicate looks (same top color, bottom color, and other-item color) are penalized.
+- Penalty is `-10` per prior similar outfit.
+- Outfits are re-sorted after penalty and then truncated to top `TOP_K`.
+
 ## 14. Standalone Others
 
 The code treats `others` specially because many garments are complete outfits by themselves:

app.py

@@ -3118,7 +3118,7 @@ def product_urls(payload: dict[str, Any] = Body(default_factory=dict)) -> dict[s
 
 @app.post("/suggestions")
 @app.post("/api/suggestions")
-def suggestions(payload: dict[str, Any] = Body(default_factory=dict)) -> dict[str, Any]:
+def suggestions(payload: dict[str, Any] = Body(default_factory=dict)) -> dict[str, Any]:
     occasion = str(payload.get("occasion") or "casual")
     target_category = str(payload.get("target_category") or payload.get("targetCategory") or "both")
     gender_preference = str(payload.get("gender_preference") or payload.get("genderPreference") or "any")
@@ -3142,12 +3142,99 @@ def suggestions(payload: dict[str, Any] = Body(default_factory=dict)) -> dict[st
         raise HTTPException(status_code=502, detail=str(exc)) from exc
     except NvidiaPayloadError as exc:
         raise HTTPException(status_code=502, detail=str(exc)) from exc
-    except requests.RequestException as exc:
-        raise HTTPException(status_code=502, detail=f"Failed to fetch {store.title()} pages: {exc}") from exc
-
-
-@app.post("/scraper/recommend")
-def scraper_recommend(payload: dict[str, Any] = Body(default_factory=dict)) -> dict[str, Any]:
+    except requests.RequestException as exc:
+        raise HTTPException(status_code=502, detail=f"Failed to fetch {store.title()} pages: {exc}") from exc
+
+
+def _build_static_scraper_result(
+    static_plan: dict[str, Any],
+    *,
+    occasion: str,
+    gender: str,
+    preferences: str,
+    store: str,
+    max_products: int | None,
+) -> dict[str, Any]:
+    query = str(static_plan.get("query") or "").strip()
+    color = str(static_plan.get("color") or "").strip()
+    category = str(static_plan.get("category") or "").strip()
+    if not query:
+        query = " ".join(part for part in [gender, color, category] if str(part or "").strip()).strip()
+    if not query:
+        raise HTTPException(status_code=400, detail="static_query_plan.query is required")
+
+    plan_occasion = str(static_plan.get("occasion") or occasion or "casual").strip() or "casual"
+    plan_gender = _normalize_scraper_gender(gender) or _normalize_scraper_gender(static_plan.get("gender")) or None
+    limit = max_products if isinstance(max_products, int) and max_products > 0 else 12
+    search_urls = _build_store_search_urls_from_query(query, store=store, gender=plan_gender)
+
+    products: list[dict[str, Any]] = []
+    seen_links: set[str] = set()
+    errors: list[str] = []
+    for search_url in search_urls:
+        try:
+            for product in _extract_store_product_summaries(search_url, store=store):
+                item_link = str(product.get("item_link") or "").strip()
+                if not item_link or item_link in seen_links:
+                    continue
+                seen_links.add(item_link)
+                products.append(product)
+                if len(products) >= limit:
+                    break
+        except requests.RequestException as exc:
+            errors.append(str(exc))
+        if len(products) >= limit:
+            break
+
+    query_plan_payload = {
+        "target_category": static_plan.get("target_category") or _normalize_target_category(static_plan.get("targetCategory")),
+        "color": color or "neutral",
+        "category": category or "mixed",
+        "gender": plan_gender,
+        "style_direction": str(static_plan.get("style_direction") or "direct-static").strip() or "direct-static",
+        "occasion_bucket": _occasion_bucket(plan_occasion),
+        "reference_item_ids": [],
+        "query": query,
+        "final_query": query,
+        "wardrobe_grounding": "Static example query selected from the shopping suggestions page.",
+        "reason": "Used a predefined query plan and URL builder without model planning.",
+        "source": "static",
+    }
+
+    response_payload: dict[str, Any] = {
+        "runtime_id": str(uuid.uuid4()),
+        "created_at": _now_iso(),
+        "store": store,
+        "occasion": plan_occasion,
+        "gender": plan_gender or gender or "",
+        "preferences": preferences,
+        "wardrobe_snapshot": _wardrobe_metadata_snapshot(limit=12),
+        "query_plan": query_plan_payload,
+        "search_urls": search_urls,
+        "product_urls": [item["item_link"] for item in products if item.get("item_link")],
+        "products": products,
+        "count": len(products),
+        "intermediate_steps": [
+            {
+                "step": "static_query_plan",
+                "query": query,
+                "url_count": len(search_urls),
+                "new_products": len(products),
+                "total_products": len(products),
+                "errors": errors,
+                "message": "Predefined webpage query used; model planner skipped.",
+            }
+        ],
+        "plan_source": "static",
+        "plan_error": None,
+        "scrape_error": "; ".join(errors) if errors and not products else None,
+    }
+    response_payload["saved_json_path"] = _save_scraper_json_payload("product_urls", response_payload)
+    return _store_scraper_runtime_result(response_payload)
+
+
+@app.post("/scraper/recommend")
+def scraper_recommend(payload: dict[str, Any] = Body(default_factory=dict)) -> dict[str, Any]:
     user_prompt = str(payload.get("user_prompt") or payload.get("prompt") or "").strip()
     inferred = _infer_structured_request_from_prompt(user_prompt)
     inferred_target_category = _normalize_target_category(inferred.get("target_category"))
@@ -3194,10 +3281,24 @@ def scraper_recommend(payload: dict[str, Any] = Body(default_factory=dict)) -> d
     max_products = int(max_products_raw) if max_products_raw not in {None, ""} else None
     store = _normalize_store_name(str(payload.get("store") or SCRAPER_DEFAULT_STORE or "nike"))
 
-    if isinstance(max_products, int) and max_products < 1:
-        raise HTTPException(status_code=400, detail="max_products must be at least 1")
-
-    # Check cache first for faster repeat queries
+    if isinstance(max_products, int) and max_products < 1:
+        raise HTTPException(status_code=400, detail="max_products must be at least 1")
+
+    static_plan = payload.get("static_query_plan") or payload.get("staticQueryPlan")
+    if isinstance(static_plan, dict):
+        try:
+            return _build_static_scraper_result(
+                static_plan,
+                occasion=occasion,
+                gender=gender,
+                preferences=preferences,
+                store=store,
+                max_products=max_products,
+            )
+        except requests.RequestException as exc:
+            raise HTTPException(status_code=502, detail=f"Failed to fetch {store.title()} pages: {exc}") from exc
+
+    # Check cache first for faster repeat queries
     cache_key = _scraper_cache_key(user_prompt, store, gender, target_category)
     with SCRAPER_QUERY_CACHE_LOCK:
         if cache_key in SCRAPER_QUERY_CACHE:
@@ -3316,7 +3417,7 @@ def scraper_page() -> Response:
                     </div>
                 </div>
                 <label for="preferences">Other Preferences</label>
-                <textarea id="preferences" placeholder="Example: formal office look, breathable fabric, neutral tones, regular fit, avoid oversized silhouettes"></textarea>
+                <textarea id="preferences" placeholder="Example: Category: shirt. Color: navy. Occasion: formal office. Style: structured minimal. Avoid: oversized."></textarea>
                 <button id="runBtn">Generate Kimi Query and Scrape</button>
                 <div id="status" class="status"></div>
             </div>