mm1

app.py

@@ -367,25 +367,53 @@ def execute_sql_query(query, db_connection):
                 result = connection.execute(sa_text(query))
             else:
                 result = connection.execute(query)
+
+            # Fetch data and column names
+            columns = list(result.keys()) if hasattr(result, "keys") else []
             rows = result.fetchall()
-            
+
             # Convertir los resultados a un formato legible
             if not rows:
                 return "La consulta no devolvió resultados"
-                
+
             # Si es un solo resultado, devolverlo directamente
-            if len(rows) == 1 and len(rows[0]) == 1:
-                return str(rows[0][0])
-                
-            # Si hay múltiples filas, formatear como tabla
+            try:
+                if len(rows) == 1 and len(rows[0]) == 1:
+                    return str(rows[0][0])
+            except Exception:
+                pass
+
+            # Si hay múltiples filas, formatear como tabla Markdown
             try:
                 import pandas as pd
-                df = pd.DataFrame(rows)
-                return df.to_markdown(index=False)
+
+                # Convert SQLAlchemy Row objects to list of dicts using column names
+                if columns:
+                    data = [
+                        {col: val for col, val in zip(columns, tuple(row))}
+                        for row in rows
+                    ]
+                    df = pd.DataFrame(data)
+                else:
+                    # Fallback: let pandas infer columns
+                    df = pd.DataFrame(rows)
+
+                # Prefer Markdown output for downstream chart parsing
+                try:
+                    return df.to_markdown(index=False)
+                except Exception:
+                    # If optional dependency 'tabulate' is missing, build a simple Markdown table
+                    headers = list(map(str, df.columns))
+                    header_line = "| " + " | ".join(headers) + " |"
+                    sep_line = "| " + " | ".join(["---"] * len(headers)) + " |"
+                    body_lines = []
+                    for _, r in df.iterrows():
+                        body_lines.append("| " + " | ".join(map(lambda v: str(v), r.values)) + " |")
+                    return "\n".join([header_line, sep_line, *body_lines])
             except ImportError:
                 # Si pandas no está disponible, usar formato simple
                 return "\n".join([str(row) for row in rows])
-                
+
     except Exception as e:
         return f"Error ejecutando la consulta: {str(e)}"
 
@@ -836,6 +864,7 @@ def create_ui():
             )
         
         # Chart display area (interactive Plotly figure)
+        # In Gradio 5, gr.Plot accepts a plotly.graph_objects.Figure
         chart_display = gr.Plot(
             label="📊 Visualización",
         )

requirements.txt

@@ -14,3 +14,4 @@ numpy==1.26.4
 python-multipart>=0.0.18  # Required by gradio
 plotly==5.18.0  # For interactive charts
 kaleido==0.2.1  # For saving plotly charts as images
+tabulate>=0.9.0  # Enables DataFrame.to_markdown used for chart parsing