Enhance dialog context handling for Text2SQL queries by integrating session history. Introduce new methods for summarizing previous assistant messages and determining if the last interaction was a data query. Update environment configuration for embedding options and improve error handling in SQL generation. Add user-facing delivery messages for successful SQL execution. This update supports more coherent follow-up questions and improves user experience in conversational interactions.

backend/llm/deepseek_client.py

@@ -253,6 +253,43 @@ class DeepSeekClient:
         text = (msg.content or "").strip()
         return text
 
+    def sql_probe_success_delivery_message(
+        self,
+        question: str,
+        sql: str,
+        *,
+        max_sql_chars: int = 4000,
+        **kwargs: Any,
+    ) -> str:
+        """
+        库探针为 1（执行成功且至少一行数据）时，生成面向用户的简短交付说明。
+        """
+        from config.prompts import (
+            SQL_PROBE_SUCCESS_DELIVERY_SYSTEM,
+            SQL_PROBE_SUCCESS_DELIVERY_USER,
+        )
+
+        q = (question or "").strip() or "(无)"
+        s = (sql or "").strip()
+        if len(s) > max_sql_chars:
+            s = s[: max_sql_chars - 20].rstrip() + "\n-- …(已截断)"
+
+        messages = [
+            {"role": "system", "content": SQL_PROBE_SUCCESS_DELIVERY_SYSTEM},
+            {
+                "role": "user",
+                "content": SQL_PROBE_SUCCESS_DELIVERY_USER.format(
+                    question=q,
+                    sql=s,
+                ),
+            },
+        ]
+        kwargs.setdefault("temperature", 0.2)
+        kwargs.setdefault("top_p", 1.0)
+        kwargs.setdefault("max_tokens", 320)
+        msg = self.chat(messages, **kwargs)
+        return (msg.content or "").strip()
+
     def select_tables(
         self,
         question: str,