תיקונים: כותרת Agent, ניגודיות סטטוס, ולידציה ג'יבריש, תיקון היסטוריה

app/api.py

@@ -49,13 +49,17 @@ def save_history() -> None:
     permissions issue), the error is logged but doesn't break the main flow.
     History is stored in `.query_history.json`.
     """
+    global history
     try:
+        # Ensure we're saving the current history
         with history_file.open("w", encoding="utf-8") as f:
             json.dump(history, f, ensure_ascii=False, indent=2)
-        print(f"History saved successfully to {history_file}", flush=True)
+        print(f"History saved successfully to {history_file.absolute()}: {len(history)} entries", flush=True)
     except Exception as e:
         # Log error but don't break main flow
+        import traceback
         print(f"Warning: Could not save history to {history_file}: {e}", flush=True)
+        traceback.print_exc()
 
 
 class QueryRequest(BaseModel):
@@ -170,21 +174,25 @@ def query_sql(req: QueryRequest) -> SQLQueryResponse:
             })
         
         # Save to history - ensure it's always saved
+        global history
         try:
-            history.append({
+            history_entry = {
                 "query": result.user_query, 
                 "response": {"summary": result.summary},
                 "timestamp": __import__("datetime").datetime.now().isoformat()
-            })
+            }
+            history.append(history_entry)
             save_history()
-            print(f"History saved: {len(history)} entries", flush=True)
+            print(f"History saved: {len(history)} entries. Query: {result.user_query[:50]}...", flush=True)
         except Exception as e:
             print(f"Error saving history: {e}", flush=True)
+            import traceback
+            traceback.print_exc()
             # Try to save anyway, even if there's an error
             try:
                 save_history()
-            except:
-                pass
+            except Exception as e2:
+                print(f"Second attempt to save history also failed: {e2}", flush=True)
         
         return SQLQueryResponse(
             query=result.user_query,
@@ -233,6 +241,14 @@ def get_history() -> Dict[str, Any]:
     Returns all previously asked questions and their responses.
     History is persisted to `.query_history.json` and loaded on startup.
     """
+    global history
+    # Reload history from disk to ensure we have the latest
+    if history_file.exists():
+        try:
+            with history_file.open("r", encoding="utf-8") as f:
+                history = json.load(f)
+        except Exception:
+            pass
     return {"history": history}
 
 

app/sql_service.py

@@ -170,8 +170,18 @@ class SQLFeedbackService:
         if self.df is None:
             raise ValueError("No feedback data available. Please ensure Feedback.csv exists.")
         
-        # Step 1: Generate SQL queries
-        sql_queries = self._generate_sql_queries(query)
+        # Step 1: Generate SQL queries (with gibberish validation)
+        try:
+            sql_queries = self._generate_sql_queries(query)
+        except ValueError as e:
+            # If query is gibberish, return a friendly error message
+            return AnalysisResult(
+                user_query=query,
+                sql_queries=[],
+                query_results=[],
+                summary=str(e),
+                visualizations=None
+            )
         
         # Step 2: Execute SQL queries
         query_results = self._execute_sql_queries(sql_queries)
@@ -190,10 +200,38 @@ class SQLFeedbackService:
             visualizations=visualizations
         )
     
+    def _is_gibberish_query(self, query: str) -> bool:
+        """
+        Check if the query is gibberish or unintelligible.
+        
+        Returns True if the query appears to be gibberish, False otherwise.
+        """
+        # Remove extra whitespace
+        query_clean = query.strip()
+        
+        # Check if query is too short or empty
+        if len(query_clean) < 3:
+            return True
+        
+        # Check if query contains only special characters or numbers
+        if not any(c.isalpha() for c in query_clean):
+            return True
+        
+        # Check if query is mostly non-alphabetic characters
+        alpha_count = sum(1 for c in query_clean if c.isalpha())
+        if alpha_count < len(query_clean) * 0.3:  # Less than 30% alphabetic
+            return True
+        
+        return False
+    
     def _generate_sql_queries(self, query: str) -> List[str]:
         """
         Use LLM to generate 1-5 SQL queries that will help answer the user's question.
         """
+        # Check if query is gibberish
+        if self._is_gibberish_query(query):
+            raise ValueError("השאלה לא ברורה. אנא נסח את השאלה בצורה יותר ברורה ומפורטת בעברית.")
+        
         schema_info = self._get_schema_info()
         
         prompt = f"""אתה אנליסט נתונים מומחה. המשתמש שאל שאלה על משובי משתמשים.

app/static/app.js

@@ -4,12 +4,23 @@ async function checkServer() {
     if (!r.ok) throw new Error('no');
     const j = await r.json();
     const statusEl = document.getElementById('server-status');
-    statusEl.textContent = j.status === 'ok' ? '✓ פעיל' : j.status || 'לא ידוע';
-    statusEl.style.color = j.status === 'ok' ? '#4caf50' : '#f44336';
+    if (j.status === 'ok') {
+      statusEl.textContent = '✓ פעיל';
+      statusEl.style.color = '#ffffff';
+      statusEl.style.textShadow = '0 1px 3px rgba(0,0,0,0.5), 0 0 8px rgba(76, 175, 80, 0.8)';
+      statusEl.style.fontWeight = '700';
+    } else {
+      statusEl.textContent = j.status || 'לא ידוע';
+      statusEl.style.color = '#ffebee';
+      statusEl.style.textShadow = '0 1px 3px rgba(0,0,0,0.5)';
+      statusEl.style.fontWeight = '700';
+    }
   } catch (e) {
     const statusEl = document.getElementById('server-status');
     statusEl.textContent = '✗ לא זמין';
-    statusEl.style.color = '#f44336';
+    statusEl.style.color = '#ffebee';
+    statusEl.style.textShadow = '0 1px 3px rgba(0,0,0,0.5), 0 0 8px rgba(244, 67, 54, 0.8)';
+    statusEl.style.fontWeight = '700';
   }
 }
 

app/static/index.html

@@ -3,7 +3,7 @@
 <head>
   <meta charset="utf-8" />
   <meta name="viewport" content="width=device-width, initial-scale=1" />
-  <title>Feedback Analysis — Frontend</title>
+  <title>Feedback Intelligence Agent — ממשק ניתוח משובים</title>
   <script src="https://cdn.jsdelivr.net/npm/chart.js@4.4.0/dist/chart.umd.min.js"></script>
   <style>
     * { box-sizing: border-box; }
@@ -241,9 +241,9 @@
 <body>
   <div class="container">
     <header>
-      <h1>Feedback Analysis — ממשק</h1>
+      <h1>🤖 Feedback Intelligence Agent</h1>
       <div style="display: flex; gap: 16px; align-items: center;">
-        <div class="small">שרת: <span id="server-status">...בדיקה</span></div>
+        <div class="small" style="background: rgba(255,255,255,0.25); padding: 6px 12px; border-radius: 6px; font-weight: 600;">שרת: <span id="server-status" style="font-weight: 700; text-shadow: 0 1px 2px rgba(0,0,0,0.3);">...בדיקה</span></div>
         <a href="https://github.com/galbendavids/Feedback_Analysis_RAG_Agent_runpod" target="_blank" style="color: white; text-decoration: none; font-size: 14px; padding: 6px 12px; background: rgba(255,255,255,0.2); border-radius: 6px; transition: all 0.2s;">🔗 GitHub</a>
         <a href="https://github.com/galbendavids/Feedback_Analysis_RAG_Agent_runpod/blob/main/Gal%20Shlomo%20Ben%20David%20Ohayone_e-1.pdf" target="_blank" style="color: white; text-decoration: none; font-size: 14px; padding: 6px 12px; background: rgba(255,255,255,0.2); border-radius: 6px; transition: all 0.2s;">📄 קורות חיים</a>
       </div>