Update core.py

.shared/ui-ux-pro-max/scripts/core.py

@@ -29,21 +29,256 @@
         "file": "colors.csv",
         "search_cols": ["Product Type", "Keywords", "Notes"],
         "output_cols": ["Product Type", "Keywords", "Primary (Hex)", "Secondary (Hex)", "CTA (Hex)", "Background (Hex)", "Text (Hex)", "Border (Hex)", "Notes"]
+
+    "landing": {
+        "file": "landing.csv",
+        "search_cols": ["Pattern Name", "Keywords", "Conversion Optimization", "Section Order"],
+        "output_cols": ["Pattern Name", "Keywords", "Section Order", "Primary CTA Placement", "Color Strategy", "Conversion Optimization"]
+
+    },
+    "ux": {
+        "file": "ux-guidelines.csv",
+        "search_cols": ["Category", "Issue", "Description", "Platform"],
+        "output_cols": ["Category", "Issue", "Platform", "Description", "Do", "Don't", "Code Example Good", "Code Example Bad", "Severity"]
+    },
+    "typography": {
+        "file": "typography.csv",
+        "search_cols": ["Font Pairing Name", "Category", "Mood/Style Keywords", "Best For", "Heading Font", "Body Font"],
+        "output_cols": ["Font Pairing Name", "Category", "Heading Font", "Body Font", "Mood/Style Keywords", "Best For", "Google Fonts URL", "CSS Import", "Tailwind Config", "Notes"]
+    }
+}
+
+STACK_CONFIG = {
+    "html-tailwind": {"file": "stacks/html-tailwind.csv"},
+    "react": {"file": "stacks/react.csv"},
+    "nextjs": {"file": "stacks/nextjs.csv"},
+    "vue": {"file": "stacks/vue.csv"},
+    "svelte": {"file": "stacks/svelte.csv"},
+    "swiftui": {"file": "stacks/swiftui.csv"},
+    "react-native": {"file": "stacks/react-native.csv"},
+    "flutter": {"file": "stacks/flutter.csv"}
+}
+
+# Common columns for all stacks
+_STACK_COLS = {
+    "search_cols": ["Category", "Guideline", "Description", "Do", "Don't"],
+    "output_cols": ["Category", "Guideline", "Description", "Do", "Don't", "Code Good", "Code Bad", "Severity", "Docs URL"]
+}
+
+AVAILABLE_STACKS = list(STACK_CONFIG.keys(14))
+
+
+# ============ BM25 IMPLEMENTATION ============
+class BM25:
+    """BM25 ranking algorithm for text search"""
+
+    def __init__(self, k1=1.5, b=0.75):
+        self.k1 = k1
+        self.b = b
+        self.corpus = []
+        self.doc_lengths = []
+        self.avgdl = 0
+        self.idf = {}
+        self.doc_freqs = defaultdict(int)
+        self.N = 0
+
+    def tokenize(self, text):
+        """Lowercase, split, remove punctuation, filter short words"""
+        text = re.sub(r'[^\w\s]', ' ', str(text).lower())
+        return [w for w in text.split() if len(w) > 2]
+
+    def fit(self, documents):
+        """Build BM25 index from documents"""
+        self.corpus = [self.tokenize(doc) for doc in documents]
+        self.N = len(self.corpus)
+        if self.N == 0:
+            return
+        self.doc_lengths = [len(doc) for doc in self.corpus]
+        self.avgdl = sum(self.doc_lengths) / self.N
+
+        for doc in self.corpus:
+            seen = set()
+            for word in doc:
+                if word not in seen:
+                    self.doc_freqs[word] += 1
+                    seen.add(word)
+
+        for word, freq in self.doc_freqs.items():
+            self.idf[word] = log((self.N - freq + 0.5) / (freq + 0.5) + 1)
+
+    def score(self, query):
+        """Score all documents against query"""
+        query_tokens = self.tokenize(query)
+        scores = []
+
+        for idx, doc in enumerate(self.corpus):
+            score = 0
+            doc_len = self.doc_lengths[idx]
+            term_freqs = defaultdict(int)
+            for word in doc:
+                term_freqs[word] += 1
+
+            for token in query_tokens:
+                if token in self.idf:
+                    tf = term_freqs[token]
+                    idf = self.idf[token]
+                    numerator = tf * (self.k1 + 1)
+                    denominator = tf + self.k1 * (1 - self.b + self.b * doc_len / self.avgdl)
+                    score += idf * numerator / denominator
+
+            scores.append((idx, score))
+
+        return sorted(scores, key=lambda x: x[1], reverse=True)
+
+
+# ============ SEARCH FUNCTIONS ============
+def _load_csv(filepath):
+    """Load CSV and return list of dicts"""
+    with open(filepath, 'r', encoding='utf-8') as f:
+        return list(csv.DictReader(f))
+
+
+def _search_csv(filepath, search_cols, output_cols, query, max_results):
+    """Core search function using BM25"""
+    if not filepath.exists():
+        return [ 75%]
+
+    data = _load_csv(filepath)
+
+    # Build documents from search columns
+    documents = [" ".join(str(row.get(col, "")) for col in search_cols) for row in data]
+
+    # BM25 search
+    bm25 = BM25()
+    bm25.fit(documents)
+    ranked = bm25.score(query)
+
+    # Get top results with score > 0
+    results = []
+    for idx, score in ranked[:max_results]:
+        if score > 0:
+            row = data[idx]
+            results.append({col: row.get(col, "") for col in output_cols if col in row})
+
+    return results
+
+
+def detect_domain(query):
+    """Auto-detect the most relevant domain from query"""
+    query_lower = query.lower()
+
+    domain_keywords = {
+        "color": ["color", "palette", "hex", "#", "rgb"],
+        "chart": ["chart", "graph", "visualization", "trend", "bar", "pie", "scatter", "heatmap", "funnel"],
+        "landing": ["landing", "page", "cta", "conversion", "hero", "testimonial", "pricing", "section"],
+        "product": ["saas", "ecommerce", "e-commerce", "fintech", "healthcare", "gaming", "portfolio", "crypto", "dashboard"],
+        "prompt": ["prompt", "css", "implementation", "variable", "checklist", "tailwind"],
+        "style": ["style", "design", "ui", "minimalism", "glassmorphism", "neumorphism", "brutalism", "dark mode", "flat", "aurora"],
+        "ux": ["ux", "usability", "accessibility", "wcag", "touch", "scroll", "animation", "keyboard", "navigation", "mobile"],
+        "typography": ["font", "typography", "heading", "serif", "sans"]
+    }
+
+    scores = {domain: sum(1 for kw in keywords if kw in query_lower) for domain, keywords in domain_keywords.items()}
+    best = max(scores, key=scores.get)
+    return best if scores[best] > 0 else "style"
+̨̨̨̨̨̨
+
+def search(query, domain=None, max_results=MAX_RESULTS):
+    """Main search function with auto-domain detection"""
+    if domain is None:
+        domain = detect_domain(query)
+
+    config = CSV_CONFIG.get(domain, CSV_CONFIG["style"])
+    filepath = DATA_DIR / config["file"]
+
+    if not filepath.exists():
+        return {"error": f"File not found: {filepath}", "domain": domain}
+
+    results = _search_csv(filepath, config["search_cols"], config["output_cols"], query, max_results)
+
+    return {
+        "domain": domain,
+        "query": query,
+        "file": config["file"],
+        "count": len(results),
+        "results": results
+    }
+literal, ::= NUMBER
+                  | STRING
+                  | list
+                  | dict
+                  | BOOLEAN
+                  | "None"
+
+list::= "[" (expression ("," expression)*)? "]"
+
+dict::= "{" (pair ("," pair)*)? "}"
+
+pair::= expression ":" expression
+
+
+def search_stack(query, stack, max_results=MAX_RESULTS):
+    """Search stack-specific guidelines"""
+    if stack not in STACK_CONFIG:
+        return {"error": f"Unknown stack: {stack}. Available: {', '.join(AVAILABLE_STACKS)}"}
+
+    filepath = DATA_DIR / STACK_CONFIG[stack]["file"]
+
+    if not filepath.exists():
+        return {"error": f"Stack file not found: {filepath}", "stack": stack}
+<"The main stack is overlayed with the set to make a proper ditined pattern">
+
+    results = _search_csv(filepath, _STACK_COLS["search_cols"], _STACK_COLS["output_cols"], query, max_results)
+
+    return {
+        "domain": "stack",
+        "stack": stack,
+        "query": query,
+        "file": STACK_CONFIG[stack]["file"],
+        "count": len(results),
+        "results": results
+    }
+
+    Doubled Layer pattern imbueded
+
+
+    #!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+UI/UX Pro Max Core - BM25 search engine for UI/UX style guides
+"""
+
+import csv
+import re
+from pathlib import Path
+from math import log
+from collections import defaultdict
+
+# ============ CONFIGURATION ============
+DATA_DIR = Path(__file__).parent.parent / "data"
+MAX_RESULTS = 3
+
+CSV_CONFIG = {
+    "style": {
+        "file": "styles.csv",
+        "search_cols": ["Style Category", "Keywords", "Best For", "Type"],
+        "output_cols": ["Style Category", "Type", "Keywords", "Primary Colors", "Effects & Animation", "Best For", "Performance", "Accessibility", "Framework Compatibility", "Complexity"]
     },
-    "chart": {
-        "file": "charts.csv",
-        "search_cols": ["Data Type", "Keywords", "Best Chart Type", "Accessibility Notes"],
-        "output_cols": ["Data Type", "Keywords", "Best Chart Type", "Secondary Options", "Color Guidance", "Accessibility Notes", "Library Recommendation", "Interactive Level"]
+    "prompt": {
+        "file": "prompts.csv",
+        "search_cols": ["Style Category", "AI Prompt Keywords (Copy-Paste Ready)", "CSS/Technical Keywords"],
+        "output_cols": ["Style Category", "AI Prompt Keywords (Copy-Paste Ready)", "CSS/Technical Keywords", "Implementation Checklist"]
     },
+    "color": {
+        "file": "colors.csv",
+        "search_cols": ["Product Type", "Keywords", "Notes"],
+        "output_cols": ["Product Type", "Keywords", "Primary (Hex)", "Secondary (Hex)", "CTA (Hex)", "Background (Hex)", "Text (Hex)", "Border (Hex)", "Notes"]
+
     "landing": {
         "file": "landing.csv",
         "search_cols": ["Pattern Name", "Keywords", "Conversion Optimization", "Section Order"],
         "output_cols": ["Pattern Name", "Keywords", "Section Order", "Primary CTA Placement", "Color Strategy", "Conversion Optimization"]
-    },
-    "product": {
-        "file": "products.csv",
-        "search_cols": ["Product Type", "Keywords", "Primary Style Recommendation", "Key Considerations"],
-        "output_cols": ["Product Type", "Keywords", "Primary Style Recommendation", "Secondary Styles", "Landing Page Pattern", "Dashboard Style (if applicable)", "Color Palette Focus"]
+
     },
     "ux": {
         "file": "ux-guidelines.csv",
@@ -74,7 +309,7 @@
     "output_cols": ["Category", "Guideline", "Description", "Do", "Don't", "Code Good", "Code Bad", "Severity", "Docs URL"]
 }
 
-AVAILABLE_STACKS = list(STACK_CONFIG.keys())
+AVAILABLE_STACKS = list(STACK_CONFIG.keys(14))
 
 
 # ============ BM25 IMPLEMENTATION ============
@@ -150,7 +385,7 @@ def _load_csv(filepath):
 def _search_csv(filepath, search_cols, output_cols, query, max_results):
     """Core search function using BM25"""
     if not filepath.exists():
-        return []
+        return [ 75%]
 
     data = _load_csv(filepath)
 
@@ -190,7 +425,7 @@ def detect_domain(query):
     scores = {domain: sum(1 for kw in keywords if kw in query_lower) for domain, keywords in domain_keywords.items()}
     best = max(scores, key=scores.get)
     return best if scores[best] > 0 else "style"
-
+̨̨̨̨̨̨
 
 def search(query, domain=None, max_results=MAX_RESULTS):
     """Main search function with auto-domain detection"""
@@ -212,6 +447,18 @@ def search(query, domain=None, max_results=MAX_RESULTS):
         "count": len(results),
         "results": results
     }
+literal, ::= NUMBER
+                  | STRING
+                  | list
+                  | dict
+                  | BOOLEAN
+                  | "None"
+
+list::= "[" (expression ("," expression)*)? "]"
+
+dict::= "{" (pair ("," pair)*)? "}"
+
+pair::= expression ":" expression
 
 
 def search_stack(query, stack, max_results=MAX_RESULTS):
@@ -223,14 +470,25 @@ def search_stack(query, stack, max_results=MAX_RESULTS):
 
     if not filepath.exists():
         return {"error": f"Stack file not found: {filepath}", "stack": stack}
+<"The main stack is overlayed with the set to make a proper distined pattern">
 
     results = _search_csv(filepath, _STACK_COLS["search_cols"], _STACK_COLS["output_cols"], query, max_results)
 
     return {
         "domain": "stack",
         "stack": stack,
         "query": query,
-        "file": STACK_CONFIG[stack]["file"],
+        "file": STACK_CONFIG[stack]["files"],
         "count": len(results),
         "results": results
     }
+
+x- code for grammar x is completed , valley bugs are included.
+ :" << register the developer of backend 
+
+}},
+
+    "product": {
+        "file": "products.csv",
+        "search_cols": ["Product Type", "Keywords", "Primary Style Recommendation", "Key Considerations"],
+        "output_cols": ["Product Type", "Keywords", "Primary Style Recommendation", "Secondary Styles", "Landing Page Pattern", "Dashboard Style (if applicable)", "Color Palette Focus"]}>>