quito logica de ejecutar la consulta

app.py

@@ -542,79 +542,14 @@ async def stream_agent_response(question: str, chat_history: List[List[str]]) ->
             # Check if the response contains an SQL query and it truly looks like SQL
             sql_query = extract_sql_query(response_text)
             if sql_query and looks_like_sql(sql_query):
-                logger.info(f"Detected SQL query: {sql_query}")
-                db_connection, _ = setup_database_connection()
-                if db_connection:
-                    query_result = execute_sql_query(sql_query, db_connection)
-                    
-                    # Add the query and its result to the response
-                    response_text += f"\n\n### 🔍 Resultado de la consulta:\n```sql\n{sql_query}\n```\n\n{query_result}"
-                    
-                    # Try to generate an interactive chart if the result is tabular
-                    try:
-                        if isinstance(query_result, str) and '|' in query_result and '---' in query_result:
-                            # Convert markdown table to DataFrame
-                            
-                            # Clean up the markdown table
-                            lines = [line.strip() for line in query_result.split('\n') 
-                                    if line.strip() and '---' not in line and '|' in line]
-                            if len(lines) > 1:  # At least header + 1 data row
-                                # Get column names from the first line
-                                columns = [col.strip() for col in lines[0].split('|')[1:-1]]
-                                # Get data rows
-                                data = []
-                                for line in lines[1:]:
-                                    values = [val.strip() for val in line.split('|')[1:-1]]
-                                    if len(values) == len(columns):
-                                        data.append(dict(zip(columns, values)))
-                                
-                                if data and len(columns) >= 2:
-                                    # Determine chart type from user's question (supports pie chart)
-                                    q_lower = question.lower()
-                                    if any(k in q_lower for k in ["gráfico circular", "grafico circular", "pie", "pastel"]):
-                                        desired_type = 'pie'
-                                    elif any(k in q_lower for k in ["línea", "linea", "line"]):
-                                        desired_type = 'line'
-                                    elif any(k in q_lower for k in ["dispersión", "dispersion", "scatter"]):
-                                        desired_type = 'scatter'
-                                    elif any(k in q_lower for k in ["histograma", "histogram"]):
-                                        desired_type = 'histogram'
-                                    else:
-                                        desired_type = 'bar'
-
-                                    # Choose x/y columns (assume first is category, second numeric)
-                                    x_col = columns[0]
-                                    # pick first numeric column different to x
-                                    y_col = None
-                                    for col in columns[1:]:
-                                        try:
-                                            pd.to_numeric(data[0][col])
-                                            y_col = col
-                                            break
-                                        except Exception:
-                                            continue
-                                    if y_col:
-                                        chart_fig = generate_chart(
-                                            data=data,
-                                            chart_type=desired_type,
-                                            x=x_col,
-                                            y=y_col,
-                                            title=f"{y_col} por {x_col}"
-                                        )
-                                        if chart_fig is not None:
-                                            logger.info(f"Chart generated from SQL table: type={desired_type}, x={x_col}, y={y_col}, rows={len(data)}")
-                                            chart_state = {"data": data, "x_col": x_col, "y_col": y_col, "title": f"{y_col} por {x_col}", "chart_type": desired_type}
-                    except Exception as e:
-                        logger.error(f"Error generating chart: {str(e)}", exc_info=True)
-                        # Don't fail the whole request if chart generation fails
-                        response_text += "\n\n⚠️ No se pudo generar la visualización de los datos."
-                else:
-                    response_text += "\n\n⚠️ No se pudo conectar a la base de datos para ejecutar la consulta."
+                logger.info("SQL query detected; showing as Markdown only (no execution).")
+                # Show the SQL as Markdown inside the chatbot, without executing it
+                response_text += f"\n\n### 🔍 Resultado de la consulta:\n```sql\n{sql_query}\n```"
             elif sql_query and not looks_like_sql(sql_query):
                 logger.info("Detected code block but it does not look like SQL; skipping execution.")
 
             # If we still have no chart but the user clearly wants one,
-            # try a second pass to get ONLY a SQL query from the agent and execute it.
+            # try a second pass to get ONLY a SQL query from the agent and present it as Markdown.
             if chart_fig is None:
                 q_lower = question.lower()
                 wants_chart = any(k in q_lower for k in ["gráfico", "grafico", "chart", "graph", "pastel", "pie"])
@@ -629,40 +564,12 @@ async def stream_agent_response(question: str, chat_history: List[List[str]]) ->
                         sql_only_text = str(sql_only_resp)
                         sql_query2 = extract_sql_query(sql_only_text)
                         if sql_query2 and looks_like_sql(sql_query2):
-                            logger.info(f"Second pass SQL detected: {sql_query2}")
-                            db_connection, _ = setup_database_connection()
-                            if db_connection:
-                                query_result = execute_sql_query(sql_query2, db_connection)
-                                # Append query and result to response_text for transparency
-                                response_text += f"\n\n### 🔍 Resultado de la consulta (2ª pasada):\n```sql\n{sql_query2}\n```\n\n{query_result}"
-                                # Try robust markdown table parse
-                                data_list = parse_markdown_table(query_result) if isinstance(query_result, str) else None
-                                if data_list:
-                                    # Infer columns
-                                    columns = list(data_list[0].keys())
-                                    x_col = columns[0]
-                                    y_col = None
-                                    for col in columns[1:]:
-                                        try:
-                                            pd.to_numeric(data_list[0][col])
-                                            y_col = col
-                                            break
-                                        except Exception:
-                                            continue
-                                    if y_col:
-                                        desired_type = 'pie' if any(k in q_lower for k in ["gráfico circular", "grafico circular", "pie", "pastel"]) else 'bar'
-                                        chart_fig = generate_chart(
-                                            data=data_list,
-                                            chart_type=desired_type,
-                                            x=x_col,
-                                            y=y_col,
-                                            title=f"{y_col} por {x_col}"
-                                        )
-                                        if chart_fig is not None:
-                                            logger.info("Chart generated from second-pass SQL execution (markdown parse).")
-                                            chart_state = {"data": data_list, "x_col": x_col, "y_col": y_col, "title": f"{y_col} por {x_col}", "chart_type": desired_type}
-                            else:
-                                logger.info("No DB connection on second pass; skipping.")
+                            logger.info("Second pass SQL detected; showing as Markdown only (no execution).")
+                            # Append query as Markdown to response_text for visibility
+                            response_text += (
+                                f"\n\n### 🔍 Resultado de la consulta (2ª pasada):\n"
+                                f"```sql\n{sql_query2}\n```"
+                            )
                     except Exception as e:
                         logger.error(f"Second-pass SQL synthesis failed: {e}")