feat: add get schema tool

backend/app/agent/nl2sql.py

@@ -4,12 +4,15 @@ import os
 import json
 import time
 import threading
+import logging
 from pathlib import Path
 from typing import List, Optional, Dict, Any, Callable, Awaitable
 from pydantic import BaseModel, Field
 import duckdb
 import pandas as pd
 
+logger = logging.getLogger(__name__)
+
 # Add project root to sys.path to allow importing nanobot
 PROJECT_ROOT = Path(__file__).resolve().parents[3]
 if str(PROJECT_ROOT) not in sys.path:
@@ -221,8 +224,11 @@ async def _check_connection_with_cache(source: str, connector: Any) -> bool:
     try:
         ok = await asyncio.wait_for(
             asyncio.to_thread(connector.test_connection),
-            timeout=10.0
+            timeout=15.0
         )
+    except asyncio.TimeoutError:
+        print("Connection test failed or timed out: Timeout after 15 seconds")
+        ok = False
     except Exception as e:
         print(f"Connection test failed or timed out: {e}")
         ok = False
@@ -300,8 +306,10 @@ async def process_nl2sql(
             try:
                 schema = await asyncio.wait_for(
                     asyncio.to_thread(connector.get_schema),
-                    timeout=30.0
+                    timeout=120.0
                 )
+            except asyncio.TimeoutError:
+                return NL2SQLResponse(sql="", result=[], error="Failed to fetch schema: Timeout after 120 seconds. Data source might be too large or network is slow.")
             except Exception as e:
                 return NL2SQLResponse(sql="", result=[], error=f"Failed to fetch schema: {e}")
             
@@ -449,7 +457,13 @@ Language: Chinese (Simplified)
                 # Fallback if LLM doesn't return valid JSON despite instructions
                 sql_query = content
                 
-            await emit_progress(f"SQL 生成完成 ({time.perf_counter() - llm_started:.2f}s)")
+            logger.info(f"Generated SQL for query '{request.query}':\n{sql_query}")
+            
+            # 格式化单行 SQL 用于在前端进度中展示
+            formatted_sql = sql_query.replace('\n', ' ')
+            if len(formatted_sql) > 150:
+                formatted_sql = formatted_sql[:147] + "..."
+            await emit_progress(f"SQL 生成完成: {formatted_sql}")
 
         except Exception as e:
             return NL2SQLResponse(sql=sql_query, result=[], error=f"LLM generation failed: {e}")