From 3891aae7fe3fcb45fef8bed50ef9840a29e03f23 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E9=99=88=E8=BE=85=E5=85=83?= <2401926342@qq.com>
Date: Fri, 17 Apr 2026 15:15:01 +0800
Subject: [PATCH] Refactor `api_server.py` to import environment setup and
schema loading from `bootstrap.py`, enhancing modularity. Introduce a new
function in `Text2SQLOrchestrator` to prioritize `VCUserAccessibleFunction`
in table selection, improving SQL generation accuracy. Update validation
logic to enforce restrictions on CJK characters in SQL string literals,
ensuring compliance with business rules. Enhance prompts to clarify SQL
generation constraints regarding date conditions and CJK usage.
---
IMPACT_ANALYSIS.md | 182 +++++++++++++++
TASK_SUMMARY.md | 3 +
__pycache__/api_server.cpython-312.pyc | Bin 52966 -> 60067 bytes
api_server.py | 2 +-
backend/__pycache__/__init__.cpython-312.pyc | Bin 0 -> 216 bytes
backend/__pycache__/bootstrap.cpython-312.pyc | Bin 0 -> 9773 bytes
backend/__pycache__/main.cpython-312.pyc | Bin 18527 -> 9720 bytes
.../__pycache__/orchestrator.cpython-312.pyc | Bin 39764 -> 41607 bytes
backend/agents/orchestrator.py | 47 +++-
backend/bootstrap.py | 215 ++++++++++++++++++
.../__pycache__/prompts.cpython-312.pyc | Bin 24873 -> 26962 bytes
backend/config/prompts.py | 57 +++--
backend/main.py | 208 +----------------
.../fewshot_chroma_store.cpython-312.pyc | Bin 11998 -> 11998 bytes
.../fewshot_selector.cpython-312.pyc | Bin 29130 -> 29130 bytes
.../__pycache__/validators.cpython-312.pyc | Bin 14236 -> 17872 bytes
backend/utils/validators.py | 96 +++++++-
.../length.bin | Bin 4000 -> 4000 bytes
logs/text2sql_api.log | 203 +++++++++++------
19 files changed, 707 insertions(+), 306 deletions(-)
create mode 100644 backend/__pycache__/__init__.cpython-312.pyc
create mode 100644 backend/__pycache__/bootstrap.cpython-312.pyc
create mode 100644 backend/bootstrap.py
diff --git a/IMPACT_ANALYSIS.md b/IMPACT_ANALYSIS.md
index b2ae197..6c638d2 100644
--- a/IMPACT_ANALYSIS.md
+++ b/IMPACT_ANALYSIS.md
@@ -1,3 +1,79 @@
+# Impact Analysis Report — CJK 字面量校验（CASE 展示标签）
+
+## 1. 改动概览
+
+- **背景与目标**：修复「CASE … THEN/ELSE 中使用中文状态标签」被 `check_no_cjk_in_sql_string_literals` 全文扫描误判为非法，导致合法查询反复重试仍失败的问题。规则本意是禁止在 **WHERE/HAVING/ON/CASE 条件** 中用中文与代码列比对。
+- **涉及模块**：`backend/utils/validators.py`（CJK 校验改为基于 sqlglot AST + 解析失败时回退全文扫描）、`backend/agents/orchestrator.py`（传入 `dialect`、T-SQL 硬性说明与注释对齐）、`backend/config/prompts.py`（2b 条款与校验语义一致）。
+- **改动类型**：缺陷修复（验证逻辑与提示词澄清）。
+
+## 2. 方法级改动
+
+| 位置 | 变更 |
+|------|------|
+| `check_no_cjk_in_sql_string_literals` | 解析成功时仅当 CJK 出现在 `Where`/`Having`/`Join.on` 或 `Case` 分支的 **WHEN 条件**（`If.this`）中报错；`Case` 的 **THEN/ELSE** 与纯 `SELECT` 展示字面量允许。支持 `Literal` 与 `National`（`N'…'`）。解析失败时回退旧版全文扫描（偏严）。 |
+| `orchestrator._validate_sql` | 调用 `check_no_cjk_in_sql_string_literals(sql, dialect=dialect)`。 |
+
+## 3. 调用方与影响范围
+
+- **调用方**：`_validate_sql` 内唯一调用点。
+- **破坏性变更**：否。行为变更：此前会失败的「仅 CASE/SELECT 含中文标签」现为通过；`WHERE col = N'中文'` 等仍失败。
+
+## 4. 风险与回滚
+
+- **风险级别**：低。解析异常时仍走严格全文扫描。
+- **回滚**：还原 `validators.py` / 相关 prompt 与 orchestrator 片段。
+
+**回滚方式是否简单**：是。
+
+## 5. 验证与测试
+
+- 已执行：脚本用例 — `CASE … THEN '\u8d85\u989d'` 通过；`WHERE x = N'\u8d85\u989d'` 失败。
+
+## 6. 配置变更
+
+- 无。
+
+---
+
+# Impact Analysis Report — Prompt：无时间表述则不擅自加日期条件
+
+## 1. 改动概览
+
+- **背景与目标**：强化 Text2SQL 提示词，避免用户未提任何时间时模型在 `WHERE` 中私自添加日期过滤；Few-shot 黄金适配时若当前问题比范例少时间条件，应去掉多余日期条件。
+- **涉及模块**：`backend/config/prompts.py`（`SQL_GENERATOR_*`、`GOLDEN_SQL_ADAPT_*`）、`backend/agents/orchestrator.py`（T-SQL 用户侧硬性要求追加一句）。
+- **改动类型**：配置/提示词优化（行为变更：模型被约束为少加臆测日期条件；**非** API 签名变更）。
+
+## 2. 方法级改动
+
+| 位置 | 变更 |
+|------|------|
+| `SQL_GENERATOR_SYSTEM` | 新增硬性条款 **1b**（无时间表述则不加日期条件）；收紧第 **2** 条中「未给日期」与日期列的说明；推断指南增加**前提**行；黄金范例括号内补充「完全未提时间勿照抄日期」。 |
+| `SQL_GENERATOR_USER` | 末尾一句指向 **1b**。 |
+| `GOLDEN_SQL_ADAPT_SYSTEM` | 第 **2** 条补充：当前问题无时间要求时去掉标准答案中无关日期过滤。 |
+| `orchestrator` `_generate_sql` / `_generate_sql_golden_adapt` | T-SQL 硬性要求字符串追加与 **1b** 一致的一句提醒。 |
+
+## 3. 调用方与影响范围
+
+- **调用方**：所有经 `Text2SQLOrchestrator` 走 SQL 生成的路径（含黄金适配分支）。
+- **破坏性变更**：否（仅 prompt 与 user 附加说明文本变化）。
+
+## 4. 风险与回滚
+
+- **风险级别**：低。可能使「未说时间」类问题返回更宽结果集（符合预期）；若业务依赖模型以前「默认加近期」的隐式行为，需改为在用户问题或后端注入默认时间窗。
+- **回滚**：还原上述文件相关 diff。
+
+**回滚方式是否简单**：是。
+
+## 5. 验证与测试
+
+- 建议手工：问题不含任何时间词 → 生成 SQL 应无新增日期列条件（除非 Schema/问题语义强制）；含「今天」→ 仍可用 `GETDATE()`。
+
+## 6. 配置变更
+
+- 无。
+
+---
+
# Impact Analysis Report — 会话上文注入 Text2SQL
## 1. 改动概览
@@ -672,3 +748,109 @@
## 6. 验证与测试
- 已执行：`python -m py_compile api_server.py`。
+
+---
+
+# Impact Analysis Report — API 回包增加 data.sql / data.explanation 便捷字段
+
+## 1. 改动概览
+
+- **背景与目标**：前端需要在响应 `data` 内直接读取 `{"sql":"..."}`（SQL 可含 `--` 注释且无 ``` 围栏），并单独读取自然语言解释字段。
+- **涉及模块**：`api_server.py`（`NLChatSuccessData`、`_nl_dict_from_generation`）。
+- **改动类型**：向后兼容的字段补充（不移除/不改名原有字段）。
+
+## 2. 方法级改动
+
+| 位置 | 变更 |
+|------|------|
+| `NLChatSuccessData` | 新增可选字段 `sql`、`explanation`（便捷读取）。 |
+| `_nl_dict_from_generation` | 在原有 `intent/branch_result` 之外补充 `payload["sql"]` 与 `payload["explanation"]`；`explanation` 优先取 `sql_delivery_message`，否则回退到 `sql_explain`。 |
+
+## 3. 调用方与影响范围
+
+- **调用方**：`/g3sb/api/nl/chat` 与 `/g3sb/api/nl/chat/stream` 的结束包 `data`。
+- **破坏性变更**：否（仅新增字段；原 `branch_result.sql` 等保持不变）。
+
+## 4. 风险与回滚
+
+- **风险级别**：低（新增字段）。
+- **回滚**：回退本改动提交即可。
+
+**回滚方式是否简单**：是。
+
+## 5. 验证与测试
+
+- 已执行：`python -m py_compile api_server.py`。
+
+---
+
+# Impact Analysis Report — SSE 流式 SQL 说明与可选 `{"sql":...}` 片段（可开关）
+
+## 1. 改动概览
+
+- **背景与目标**：流式 `/g3sb/api/nl/chat/stream` 需要给客户端展示 SQL（LLM 原生 delta）并在必要时提供结构化 SQL。由于当前前端会直接拼接展示 delta 且保留 ``，因此结构化 `` 片段默认不补发，避免同一次流里出现两段可见 SQL；如有需要可通过环境变量开关启用。
+- **涉及模块**：`api_server.py`（`_chat_stream_events`）。
+- **改动类型**：向后兼容增强（流式末尾追加内容；并过滤 LLM 可能自行输出的 `...`，避免前端出现重复 SQL/重复结构化片段）。
+
+## 2. 方法级改动分析
+
+| 位置 | 变更 |
+|------|------|
+| `_chat_stream_events` | 透传 LLM 的 `sql_gen` delta 用于展示；过滤 LLM 自吐的 `...` 段。流结束时结构化 `{"sql":...}` **默认不补发**，仅在 `SSE_APPEND_SQL_DATA_TAG=true` 时启用补发，避免前端拼接展示时出现重复 SQL。 |
+
+## 3. 调用方与影响范围分析
+
+- **调用方**：前端 SSE 消费逻辑（`stage="sql_gen"`、`stream_kind="content"`）。
+- **影响**：
+ - **展示**：若前端直接展示原始流文本，将额外看到「SQL 说明」与 `...`；但通常前端会对 `...` 做隐藏/抽取，不影响页面展示。
+ - **解析**：前端可在流末尾稳定抽取 SQL（而不依赖临时拼接或额外请求非流式接口）。
+- **破坏性变更**：否（仅追加；不更改原有字段与 SSE 事件结构）。
+
+## 4. 风险与回滚
+
+- **风险级别**：低（开关打开时，若前端未过滤 ``，可能展示出标签；默认关闭避免此问题）。
+- **回滚**：默认即不补发；如需恢复补发仅需设置 `SSE_APPEND_SQL_DATA_TAG=true`，或回退代码提交。
+
+**回滚方式是否简单**：是。
+
+## 5. 验证与测试
+
+- 已验证：`python -m py_compile api_server.py`；默认不再补发 `{"sql":...}`，且不会透传 LLM 自行生成的 `...` 段；需要结构化输出时可设置 `SSE_APPEND_SQL_DATA_TAG=true` 验证补发行为。
+
+---
+
+# Impact Analysis Report — api_server 精简未使用请求/查询参数
+
+## 1. 改动概览
+
+- **背景与目标**：删除 `api_server.py` 中未被业务逻辑使用的请求字段与路由形参，减少噪音；stub 接口不再声明从不读取的请求体模型。
+- **涉及模块**：`api_server.py`。
+- **改动类型**：重构（对外行为基本不变）。
+
+## 2. 方法级改动
+
+| 位置 | 变更 |
+|------|------|
+| `NLChatRequest` | 移除字段 `taskId`（仓库内无读取）。 |
+| `SqlExecuteBody` | 删除模型；`POST /g3sb/api/nl/sql/execute` 无请求体形参（仍返回 501）。 |
+| `POST /g3sb/api/nl/operation-logs` | 移除未使用的 `Body` 形参（仍返回 200）。 |
+| `GET /g3sb/api/nl/operation-logs` | 仅保留 `limit`、`offset`；其余查询参数从签名中移除。 |
+| `GET /g3sb/api/nl/knowledge-docs/uploads` | 移除未使用的 `doc_type`，保留 `limit`、`offset`。 |
+| `lifespan`、全局异常处理 | 未使用的 `app`/`_req` 形参改为 `_app` / `_`（语义不变）。 |
+
+## 3. 调用方与影响范围
+
+- **调用方**：`ai-g3sb-backman-web` 的 `nlClient.ts` 仍可对上述 GET 附带更多 query、对 POST 仍发送 JSON；FastAPI 对未声明的 query 通常忽略，不声明的 body 仍会被接收但不解析。
+- **OpenAPI**：`/sql/execute` 与 `POST /operation-logs` 的文档中可能不再展示请求体 schema（与当前「不读 body」实现一致）。
+- **破坏性变更**：否（若客户端依赖 OpenAPI 生成且严格要求 `taskId` 出现在 schema，仅文档层面变化；运行时多传 `taskId` 仍被 Pydantic 忽略）。
+
+## 4. 风险与回滚
+
+- **风险级别**：低。
+- **回滚**：回退本改动对应提交即可。
+
+**回滚方式是否简单**：是。
+
+## 5. 验证与测试
+
+- 已执行：`python -m py_compile api_server.py`。
diff --git a/TASK_SUMMARY.md b/TASK_SUMMARY.md
index e00b69d..0337010 100644
--- a/TASK_SUMMARY.md
+++ b/TASK_SUMMARY.md
@@ -45,6 +45,9 @@
## 流式输出（补充）
- **`/g3sb/api/nl/chat/stream`**：`chat` 与 `sql_gen` 阶段的正文改为多段 SSE 分片推送（默认每段约 64 字符，可用环境变量 `SSE_STREAM_CHUNK_CHARS` 调整），与前端 `onDelta` 累加逻辑一致。
+- **重复 SQL 修复（补充）**：为避免同一次 SSE 响应中出现两段 SQL（LLM 自吐 `...` + 服务端末尾补发 `{"sql":...}`），后端在透传 LLM delta 时会过滤掉任何 `...` 段，仅保留流结束时的标准结构化 `` 片段供前端解析。
+ - **现状约束**：由于当前前端会直接拼接展示 delta 且保留 ``，流式接口默认**不再补发**结构化 `{"sql":...}`，避免“SQL + 可见 ``”造成重复展示。
+ - **如需补发**：设置环境变量 `SSE_APPEND_SQL_DATA_TAG=true` 才会在流末尾补发结构化 ``（仅建议给会过滤 `` 的客户端使用）。
## 后续事项
diff --git a/__pycache__/api_server.cpython-312.pyc b/__pycache__/api_server.cpython-312.pyc
index b4a19b4492e83e7264cd42dc27f3876897e51dbf..1b9dc1d5089d8172f23237b9c7c19341c4b8f40d 100644
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zVU^$ZzzJi8$X2q
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diff --git a/backend/agents/orchestrator.py b/backend/agents/orchestrator.py
index 99eef6d..16cf346 100644
--- a/backend/agents/orchestrator.py
+++ b/backend/agents/orchestrator.py
@@ -302,6 +302,28 @@ class Text2SQLOrchestrator:
logger.info("对手方/经纪商问题：优先纳入 %s，调整后选表：%s", present, merged)
return merged[:max_tables]
+ _VC_USER_ACCESSIBLE_FUNCTION = "VCUserAccessibleFunction"
+
+ def _prioritize_vc_user_accessible_function(
+ self, relevant_tables: List[str], max_tables: int = 5
+ ) -> List[str]:
+ """
+ 若 Schema 中存在 VCUserAccessibleFunction，则置于选表列表最前，便于模型先根据
+ FunctionID / DatabaseView 等列定位业务视图，再关联其余表生成 SQL。
+ """
+ vc = self._VC_USER_ACCESSIBLE_FUNCTION
+ if not self.schema_manager.get_table(vc):
+ return relevant_tables[:max_tables]
+
+ rest = [t for t in relevant_tables if t != vc]
+ merged = [vc] + rest
+ logger.info(
+ "已优先纳入目录视图 %s（置于选表前列），当前选表：%s",
+ vc,
+ merged[:max_tables],
+ )
+ return merged[:max_tables]
+
def _expand_relations(self, table_names: List[str]) -> List[str]:
"""
外键扩展：自动添加关联表
@@ -413,8 +435,9 @@ class Text2SQLOrchestrator:
"**禁止** `CURDATE()`、`NOW()`、`CURRENT_DATE`（MySQL）。"
"条件请使用 T-SQL 惯用写法（例如 IS NOT NULL）。"
"排版仍须遵守：关键字大写、SELECT 每列一行缩进、WHERE 续行以 AND 开头、PascalCase 英文别名。"
- "\n**禁止**在单引号字符串字面量或 `N'…'` 中出现任何中日韩文字；"
- "业务中文须映射为 Schema 注释中的代码或通过维表 JOIN，勿写 `= '过户费'` 这类比对。"
+ "\n在 `WHERE`/`HAVING`/`JOIN ON` 及 `CASE/WHEN` 的**条件**中，**禁止**用含中日韩的 `'`/`N'…'` 字面量与代码型列比对；"
+ "业务中文须映射为 Schema 注释中的代码或通过维表 JOIN（勿写 `= '过户费'`）。`SELECT` 或 `CASE … THEN/ELSE` 的展示用中文标签允许。"
+ "若用户问题与对话上文均未要求按时间筛选，不得在 WHERE 中擅自添加日期列条件（与系统提示 1b 一致）。"
)
if validation_feedback:
@@ -577,8 +600,9 @@ class Text2SQLOrchestrator:
"**禁止** `CURDATE()`、`NOW()`、`CURRENT_DATE`（MySQL）。"
"条件请使用 T-SQL 惯用写法（例如 IS NOT NULL）。"
"排版仍须遵守：关键字大写、SELECT 每列一行缩进、WHERE 续行以 AND 开头、PascalCase 英文别名。"
- "\n**禁止**在单引号字符串字面量或 `N'…'` 中出现任何中日韩文字；"
- "业务中文须映射为 Schema 注释中的代码或通过维表 JOIN，勿写 `= '过户费'` 这类比对。"
+ "\n在 `WHERE`/`HAVING`/`JOIN ON` 及 `CASE/WHEN` 的**条件**中，**禁止**用含中日韩的 `'`/`N'…'` 字面量与代码型列比对；"
+ "业务中文须映射为 Schema 注释中的代码或通过维表 JOIN（勿写 `= '过户费'`）。`SELECT` 或 `CASE … THEN/ELSE` 的展示用中文标签允许。"
+ "若用户问题与对话上文均未要求按时间筛选，不得在 WHERE 中擅自添加日期列条件（与系统提示 1b 一致）。"
)
if validation_feedback:
@@ -659,9 +683,9 @@ class Text2SQLOrchestrator:
if not danger_ok:
errors.extend(danger_errors)
- # T-SQL：禁止中文等业务词出现在字符串字面量（如 FeeNatureID = '过户费'）
+ # T-SQL：禁止中文出现在 WHERE/HAVING/ON/CASE 条件等比对语境（展示用 CASE THEN/ELSE 允许）
if dialect == "tsql":
- cjk_ok, cjk_errors = check_no_cjk_in_sql_string_literals(sql)
+ cjk_ok, cjk_errors = check_no_cjk_in_sql_string_literals(sql, dialect=dialect)
if not cjk_ok:
errors.extend(cjk_errors)
@@ -845,6 +869,9 @@ class Text2SQLOrchestrator:
relevant_tables = self._prioritize_broker_tables(
linker_question, relevant_tables
)
+ relevant_tables = self._prioritize_vc_user_accessible_function(
+ relevant_tables
+ )
# 1.3 外键扩展
expanded_tables = self._expand_relations(relevant_tables)
@@ -856,6 +883,14 @@ class Text2SQLOrchestrator:
include_columns=True,
max_columns_per_table=20
)
+ if self._VC_USER_ACCESSIBLE_FUNCTION in expanded_tables:
+ filtered_schema_str += (
+ "\n\n【选表提示】已包含视图 "
+ + self._VC_USER_ACCESSIBLE_FUNCTION
+ + "（列含 UserID、FunctionID、Category、Name、DatabaseView）。"
+ "生成 SQL 时可先通过该视图用 DatabaseView / FunctionID 等定位目标业务视图或功能，"
+ "再与 Schema 中其余表做 JOIN 或子查询；若问题已明确具体表名，可直接查询该表。"
+ )
logger.info(f" 选中表：{relevant_tables}，扩展后：{expanded_tables}")
else:
# 重试：在子 Schema 中并入「上次失败 SQL」实际引用到的表，并对齐程序校验与生成上下文
diff --git a/backend/bootstrap.py b/backend/bootstrap.py
new file mode 100644
index 0000000..63005a1
--- /dev/null
+++ b/backend/bootstrap.py
@@ -0,0 +1,215 @@
+"""
+Text2SQL 共享启动逻辑：环境检查、Schema 加载、Orchestrator 构造。
+
+供 `main` CLI 与 `api_server` 复用，避免 API 层依赖 CLI 入口模块。
+"""
+
+from __future__ import annotations
+
+import logging
+import os
+import sys
+from pathlib import Path
+from typing import Any, Optional
+
+from dotenv import load_dotenv
+
+logger = logging.getLogger(__name__)
+
+
+def _repo_root() -> Path:
+ """仓库根目录（含 data/、.env、api_server.py 的目录）。"""
+ return Path(__file__).resolve().parent.parent
+
+
+def load_project_env() -> None:
+ """加载项目根目录 .env，供后续 os.getenv 使用。"""
+ load_dotenv(_repo_root() / ".env")
+
+
+def resolve_sql_dialect(name: str) -> str:
+ """CLI / 配置中的方言别名统一为 sqlglot 方言名（SQL Server -> tsql）。"""
+ n = (name or "sqlserver").lower().strip()
+ if n in ("sqlserver", "mssql"):
+ return "tsql"
+ return n
+
+
+def setup_environment() -> bool:
+ """环境检查"""
+ load_project_env()
+ ms_key = os.getenv("MODELSCOPE_API_KEY", "").strip()
+ oa_key = os.getenv("OPENAI_API_KEY", "").strip()
+ oa_key_ok = oa_key and not (
+ oa_key.startswith("http://") or oa_key.startswith("https://")
+ )
+ if ms_key:
+ pass # ModelScope：BASE_URL / MODEL 有默认值，仅需 KEY
+ elif oa_key_ok:
+ if not os.getenv("OPENAI_EMBEDDING_MODEL", "").strip():
+ logger.warning("未设置 OPENAI_EMBEDDING_MODEL（远程 Embedding 模型名）")
+ return False
+ else:
+ if not os.getenv("DASHSCOPE_API_KEY", "").strip():
+ logger.warning(
+ "未设置 MODELSCOPE_API_KEY、"
+ "OPENAI_API_KEY+OPENAI_EMBEDDING_MODEL 或 DASHSCOPE_API_KEY"
+ )
+ return False
+ base = (
+ os.getenv("DASHSCOPE_BASE_URL") or os.getenv("DASHSCOPE_base_url", "")
+ ).strip()
+ if not base:
+ logger.warning("未设置 DASHSCOPE_BASE_URL（或 DASHSCOPE_base_url）")
+ return False
+ if not os.getenv("DASHSCOPE_MODEL", "").strip():
+ logger.warning("未设置 DASHSCOPE_MODEL")
+ return False
+
+ # 检查Schema文件（支持相对路径和绝对路径）
+ schema_path_str = os.getenv(
+ "SCHEMA_PATH", "./data/schemas/G3SB_MCDataDictionary_table_structure.json"
+ )
+ schema_path = Path(schema_path_str)
+
+ # 如果是相对路径，尝试从多个位置查找
+ if not schema_path.is_absolute():
+ # 尝试1: PyInstaller 临时目录（单文件模式）
+ if getattr(sys, "frozen", False) and hasattr(sys, "_MEIPASS"):
+ meipass_schema = Path(sys._MEIPASS) / schema_path_str
+ if meipass_schema.exists():
+ schema_path = meipass_schema
+
+ # 尝试2: 当前工作目录
+ if not schema_path.exists():
+ schema_path = Path.cwd() / schema_path_str
+
+ # 尝试3: 仓库根目录（本文件位于 backend/）
+ if not schema_path.exists():
+ script_dir = Path(__file__).resolve().parent.parent
+ schema_path = script_dir / schema_path_str
+
+ # 尝试4: 可执行文件所在目录
+ if not schema_path.exists() and getattr(sys, "frozen", False):
+ exe_dir = Path(sys.executable).parent
+ schema_path = exe_dir / schema_path_str
+
+ if not schema_path.exists():
+ logger.warning(f"Schema文件不存在: {schema_path}")
+ logger.info("请将G3SB Schema文件放置在 ./data/schemas/ 目录")
+ return False
+
+ # 检查 LLM Key（DeepSeek / OpenAI 可切换）
+ llm_sc = (os.getenv("LLM_SERVICE_CODE") or "").strip().lower()
+ if llm_sc and llm_sc not in ("deepseek", "openai"):
+ logger.warning("未知 LLM_SERVICE_CODE=%r（仅支持 deepseek/openai）", llm_sc)
+ return False
+ if llm_sc == "openai":
+ if not (os.getenv("OPENAI_API_KEY") or "").strip():
+ logger.warning("LLM_SERVICE_CODE=openai 但 OPENAI_API_KEY 未设置")
+ return False
+ else:
+ if not (os.getenv("DEEPSEEK_API_KEY") or "").strip():
+ logger.warning("环境变量 DEEPSEEK_API_KEY 未设置（默认 LLM_SERVICE_CODE=deepseek）")
+ logger.info("请在 .env 文件中配置，或 export DEEPSEEK_API_KEY=your_key")
+ return False
+
+ logger.info(f"[OK] 环境检查通过")
+ logger.info(f" - Schema: {schema_path}")
+ logger.info(
+ " - LLM: %s",
+ (llm_sc or "deepseek(auto)"),
+ )
+
+ return True
+
+
+def _default_g3sb_meta_path(structure_path: str) -> Optional[str]:
+ """若存在与 table_structure 同名的 table_meta 文件则返回其路径。"""
+ p = Path(structure_path)
+ if "table_structure" not in p.name:
+ return None
+ cand = p.parent / p.name.replace("table_structure", "table_meta")
+ return str(cand) if cand.is_file() else None
+
+
+def load_schema(schema_path: str, schema_meta_path: Optional[str] = None):
+ """加载 Schema；G3SB structure JSON 会自动尝试配对 table_meta（可用 --schema-meta 指定）。"""
+ from schema.manager import SchemaManager
+
+ meta = (
+ schema_meta_path
+ if schema_meta_path is not None
+ else _default_g3sb_meta_path(schema_path)
+ )
+ logger.info(f"加载Schema: {schema_path}")
+ if meta:
+ logger.info(f" 表注释(meta): {meta}")
+
+ schema_mgr = SchemaManager.load_from_json(
+ schema_path, g3sb_meta_path=meta
+ )
+
+ stats = schema_mgr.get_statistics()
+ logger.info(
+ f"[OK] Schema加载完成: {stats['database']}, "
+ f"共{stats['total_tables']}张表, {stats['total_columns']}个字段"
+ )
+
+ return schema_mgr
+
+
+def create_orchestrator(schema_mgr: Any, args: Any):
+ """创建编排器"""
+ from agents.orchestrator import Text2SQLOrchestrator
+ from llm.router import create_llm_client, resolve_llm_service_code
+ from llm.deepseek_client import DeepSeekConfig
+
+ translate_en = os.getenv("TRANSLATE_EN_TO_ZH", "true").strip().lower() not in (
+ "0",
+ "false",
+ "no",
+ "off",
+ )
+ if getattr(args, "no_translate_en", False):
+ translate_en = False
+
+ sc = resolve_llm_service_code()
+ if sc == "deepseek":
+ api_key = (args.api_key or os.getenv("DEEPSEEK_API_KEY") or "").strip()
+ if not api_key:
+ raise ValueError(
+ "未配置 DeepSeek API Key：请在 .env 中设置 DEEPSEEK_API_KEY，"
+ "或使用命令行参数 --api-key"
+ )
+ base_url = (os.getenv("DEEPSEEK_BASE_URL") or "https://api.deepseek.com").strip()
+ cfg = DeepSeekConfig(
+ api_key=api_key,
+ base_url=base_url,
+ model_name=args.model or "deepseek-chat",
+ temperature=args.temperature,
+ max_tokens=args.max_tokens,
+ )
+ llm_client = create_llm_client("deepseek", **cfg.__dict__)
+ else:
+ # openai：完全由 OPENAI_* 决定；同时沿用 temperature/max_tokens 作为默认值覆盖
+ llm_client = create_llm_client(
+ "openai",
+ temperature=args.temperature,
+ max_tokens=args.max_tokens,
+ )
+
+ orchestrator = Text2SQLOrchestrator(
+ schema_manager=schema_mgr,
+ llm_client=llm_client,
+ vector_db_path=args.vector_db,
+ max_retry=args.max_retry,
+ use_vector_search=not args.no_vector_search,
+ # Few-shot配置
+ fewshot_enabled=not args.no_fewshot,
+ fewshot_top_k=args.fewshot_top_k,
+ fewshot_min_rating=args.fewshot_min_rating,
+ translate_english_to_zh=translate_en,
+ )
+
+ return orchestrator
diff --git a/backend/config/__pycache__/prompts.cpython-312.pyc b/backend/config/__pycache__/prompts.cpython-312.pyc
index 6d87c736fa3d35be657c49a46955ff22dc7ada16..8cadc67ce6e6da3033d107cc8a993dfc47990e35 100644
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diff --git a/backend/config/prompts.py b/backend/config/prompts.py
index 7d42f0b..ef073e3 100644
--- a/backend/config/prompts.py
+++ b/backend/config/prompts.py
@@ -55,8 +55,9 @@ SQL_GENERATOR_SYSTEM = """你是一个精通SQL的数据库专家，有10年以
**硬性约束（必须遵守）**：
1. **合理推断业务语义**：用户问题中的时间范围（如"2024年1月"）、状态含义（如"活跃"对应Active）、常见业务默认值（如"当前"指近期），应根据Schema中的字段注释和常见业务逻辑进行合理推断并转化为WHERE条件；但禁止编造问题中未提及的过滤维度或指标。
-2. **禁止虚构值与占位符**：不得使用 `'[日期]'`、`TODO`、`xxx`、空泛占位等冒充具体字面量。若用户未给出具体日期、代码或 ID，应根据问题上下文推断合理值（如"2024年1月" → `ValueDate >= '2024-01-01' AND ValueDate < '2024-02-01'`），或使用Schema中常见的枚举值（如状态字段的`A/D/X`），**不要**留空或写占位符。
-2b. **禁止在 SQL 字符串字面量中出现中文（CJK）**：用户问题里的中文业务词（如「过户费」「未结算」「活跃」）**禁止**写成 `'…中文…'` 或 `N'…中文…'` 去和代码型列（如 `FeeNatureID`、`SettleStatus`、`State`）比较。必须根据 **Schema 字段注释** 写成库内真实**代码/单字母/数字**（如 `State = 'A'`、`SettleStatus = 'U'`）；若业务词对应维表或码表，应 **JOIN 维表** 用其键列或英文名列过滤，**不得**用中文当字面量。
+1b. **无时间表述则不加日期条件（强制）**：若用户问题及对话上文**均未**出现任何可映射为**按时间筛选**的表述——包括但不限于：具体日历日期、年月/季度区间、「今天/昨日/本周/本月/本年/本季度」「最近N天/过去一周/过去一年」等相对时间——则 **不得**在 `WHERE`/`HAVING` 中**新增**对日期/时间类型列的过滤（例如 `TradeDate >= '...'`、`BETWEEN ... AND ...`、与 `CAST(GETDATE() AS DATE)` / `DATEADD` 结合的日期条件）。**禁止**以「防止结果集过大」「报表通常只看近期」「默认只查当年」等理由擅加日期窗。仅当用户**明确**提出时间要求、或问题语义**显式**指向某时段（如「2024年1月的销售额」「今天的成交」）时，才写对应日期条件；完全未提时间时，查询在日期维度上可为全表/全历史（仅受问题中**已出现**的非时间条件约束）。
+2. **禁止虚构值与占位符**：不得使用 `'[日期]'`、`TODO`、`xxx`、空泛占位等冒充具体字面量。若用户未给出具体日期、代码或 ID：**日期类**仅当问题里**已经**出现可映射的时间表述时，才按上文与「常见时间推断指南」写出具体区间或 `GETDATE()` 条件；若全文无任何时间表述，**不得**为凑条件而编造日期过滤（与 **1b** 一致）。**非日期类**（状态码、ID 等）仍可根据问题上下文与 Schema 枚举填写合理值，**不要**留空或写占位符。
+2b. **禁止在过滤/比对条件中使用中文（CJK）字面量**：在 `WHERE`/`HAVING`/`JOIN … ON` 以及 `CASE WHEN` 的**条件部分**，用户问题里的中文业务词（如「过户费」「未结算」「活跃」）**禁止**写成 `'…中文…'` 或 `N'…中文…'` 去和代码型列（如 `FeeNatureID`、`SettleStatus`、`State`）比较。必须根据 **Schema 字段注释** 写成库内真实**代码/单字母/数字**（如 `State = 'A'`、`SettleStatus = 'U'`）；若业务词对应维表或码表，应 **JOIN 维表** 用其键列或英文名列过滤。**允许**在 `SELECT` 列表达式或 `CASE … THEN … ELSE …` 的**展示结果**中使用中文标签字符串（如状态说明），此类不属于「与代码列比对」。
3. **输出版式与别名风格（统一规范）**：除遵守目标方言语法外，SQL **排版与命名**须与下方「标准版式范例」一致：
- **关键字**：`SELECT`、`FROM`、`JOIN`/`LEFT JOIN`、`ON`、`WHERE`、`AND`、`GROUP BY`、`ORDER BY`、`HAVING` 等使用**大写**。
- **换行与缩进**：`SELECT` 后换行；每个输出列**独占一行**，行首 **4 个空格**，列表达式之间用**行尾逗号**分隔（最后一列无逗号）。
@@ -86,6 +87,7 @@ SQL_GENERATOR_SYSTEM = """你是一个精通SQL的数据库专家，有10年以
- 负债/负数含义：许多余额字段负值表示负债（如LoanBalance）
**常见时间/状态推断指南**（需结合Schema字段注释）：
+- **前提**：下列日期规则**仅当**用户问题或对话中**已出现**对应时间表述时适用；若完全未提时间，**不要**套用下列规则去加日期条件（见 **1b**）。
- "2024年1月" → `WHERE date_col >= '2024-01-01' AND date_col < '2024-02-01'`
- "今天" / "当日" → `WHERE date_col >= CAST(GETDATE() AS DATE) AND date_col < DATEADD(DAY,1,CAST(GETDATE() AS DATE))`
- "最近N天" → `WHERE date_col >= DATEADD(DAY, -N, CAST(GETDATE() AS DATE))`
@@ -103,7 +105,7 @@ SQL_GENERATOR_SYSTEM = """你是一个精通SQL的数据库专家，有10年以
用户问题（示例）：按对手方列出截至 2026-04-02 的所有未结算交易。
-（日期规则：用户问题里**已写出具体日期**时，在 WHERE 中写入相同字面量，例如 `CashSettleDate <= '2026-04-02'`；**未给出具体日期**但包含时间范围描述（如"2024年1月"）时，应合理推断为日期区间，例如 `OrderDate >= '2024-01-01' AND OrderDate < '2024-02-01'`，禁止使用 `'[日期]'` 等占位符。）
+（日期规则：用户问题里**已写出具体日期**时，在 WHERE 中写入相同字面量，例如 `CashSettleDate <= '2026-04-02'`；**未给出具体日期**但包含时间范围描述（如"2024年1月"）时，应合理推断为日期区间，例如 `OrderDate >= '2024-01-01' AND OrderDate < '2024-02-01'`，禁止使用 `'[日期]'` 等占位符。**若用户完全未提及任何时间与时段**，则不要添加日期列条件，勿因本范例含日期而照抄日期过滤。）
SQL（表名、字段名须与当前 Schema 一致；**以下版式、别名、JOIN/WHERE/GROUP BY/ORDER BY 结构为强制模板**）：
@@ -130,30 +132,41 @@ ORDER BY TotalUnsettledAmount DESC;
**示例（版式与范例一致）**：
示例1 - 单表查询：
-问题：查询账户ID为'ACC001'的账户余额
-Schema: MCAccount(AccountID, Name, AvailableBalance, MarketValue, MarginValue)
+问题：查询账户ID为'M050013'的账户余额
+Schema: MCAccount(AccountID, AvailableBalance, AssetBalance, LiabilityBalance, MaximumAvailableBalance)
SQL:
SELECT
- AccountID,
- Name AS AccountName,
+ RTRIM(AccountID) AS AccountID,
AvailableBalance,
- MarketValue,
- MarginValue
-FROM MCAccount
-WHERE AccountID = 'ACC001';
+ AssetBalance,
+ LiabilityBalance,
+ MaximumAvailableBalance
+FROM dbo.MCAccount
+WHERE RTRIM(AccountID) = N'M050013';
示例2 - 多表 INNER JOIN：
-问题：查询账户'ACC001'持有的所有股票及数量
-Schema: MCAccount(AccountID), MCAccountInstrument(AccountID, MarketID, InstrumentID, Settled)
+问题：查询账户'M050013'持有的所有股票及数量
+Schema: BCAccountInstrument(AccountID, MarketID, InstrumentID, DailyOpenLedgerQuantity, DailyOpenSettledQuantity), MCInstrument(MarketID, InstrumentID, Name, InstrumentTypeID), MCInstrumentType(InstrumentTypeID, Name)
SQL:
SELECT
- a.AccountID,
- i.MarketID,
- i.InstrumentID AS InstrumentCode,
- i.Settled AS HoldingQty
-FROM MCAccount a
-JOIN MCAccountInstrument i ON a.AccountID = i.AccountID
-WHERE a.AccountID = 'ACC001';
+ RTRIM(bai.AccountID) AS AccountID,
+ RTRIM(bai.MarketID) AS MarketID,
+ RTRIM(bai.InstrumentID) AS InstrumentID,
+ RTRIM(mi.Name) AS InstrumentName,
+ RTRIM(mi.InstrumentTypeID) AS InstrumentTypeID,
+ it.Name AS InstrumentTypeName,
+ bai.DailyOpenLedgerQuantity AS LedgerQuantity,
+ bai.DailyOpenSettledQuantity AS SettledQuantity
+FROM dbo.BCAccountInstrument AS bai
+INNER JOIN dbo.MCInstrument AS mi
+ ON bai.MarketID = mi.MarketID
+ AND bai.InstrumentID = mi.InstrumentID
+LEFT JOIN dbo.MCInstrumentType AS it
+ ON mi.InstrumentTypeID = it.InstrumentTypeID
+WHERE RTRIM(bai.AccountID) = N'M050013'
+ AND bai.DailyOpenLedgerQuantity <> 0
+ORDER BY bai.MarketID, bai.InstrumentID;
+
示例3 - 时间范围推断（关键！）：
问题：查询2024年1月的总销售额
@@ -223,7 +236,7 @@ SQL_GENERATOR_USER = """Schema信息：
数据库方言：{dialect}
-请生成**有用 SQL**（见系统提示定义）：必须与「业务级黄金范例」**同构**——大写关键字、多行缩进版式、PascalCase 别名、该展示对手方/账户等名称时须 LEFT JOIN 维表；禁止输出挤成一行的「极简 SQL」。"""
+请生成**有用 SQL**（见系统提示定义）：必须与「业务级黄金范例」**同构**——大写关键字、多行缩进版式、PascalCase 别名、该展示对手方/账户等名称时须 LEFT JOIN 维表；禁止输出挤成一行的「极简 SQL」。**若当前问题未要求按时间筛选，不得在 WHERE 中擅自添加日期条件（系统提示 1b）。**"""
# ========== Few-shot 黄金 SQL 条件适配（Chroma 库内为已校验正确答案）==========
@@ -233,7 +246,7 @@ GOLDEN_SQL_ADAPT_SYSTEM = """你是精通 Microsoft SQL Server (T-SQL) 的数据
**你必须遵守**：
1. **以标准答案为主干**：优先保留其 `FROM`/`JOIN`/`ON`、主 `SELECT` 列清单与聚合/分组逻辑；**不要随意更换主表、不要拆掉必要 JOIN**，除非当前 Schema 片段中已不存在该表（此时在 Schema 内做最小替换并说明等价关系仅在脑中完成）。
-2. **只改「条件类」内容**：重点调整 `WHERE`/`HAVING`/`ORDER BY`/`TOP` 中的字面量、日期区间、状态码、账户/合约/代码等过滤；将用户问题中的时间范围、业务对象、筛选口径反映到这些条件中。
+2. **只改「条件类」内容**：重点调整 `WHERE`/`HAVING`/`ORDER BY`/`TOP` 中的字面量、日期区间、状态码、账户/合约/代码等过滤；将用户问题中的时间范围、业务对象、筛选口径反映到这些条件中。**若当前用户问题相较范例问题「少了」时间要求**（完全未提时间或时段），应**去掉**标准答案中仅因范例日期而存在的日期过滤，**禁止**保留与当前问题无关的日期条件（与 SQL_GENERATOR 的 **1b** 一致）。
3. **Schema 绝对优先**：表名、列名必须来自下方「当前 Schema 片段」；禁止臆造字段。若标准答案中某列在片段中不存在，按片段改写为合法列。
4. **T-SQL 与版式**：与常规生成一致——关键字大写、多行缩进、`WHERE` 续行以 `AND` 开头、需要时 PascalCase 英文别名；禁止 MySQL 反引号与 `CURDATE()` 等。
5. **禁止在字符串字面量中写中日韩文字**去匹配代码列；须用 Schema 注释中的代码或 JOIN 维表（与系统提示 SQL_GENERATOR 一致）。
diff --git a/backend/main.py b/backend/main.py
index 2cbecde..73824cf 100644
--- a/backend/main.py
+++ b/backend/main.py
@@ -10,10 +10,6 @@ import sys
import argparse
import logging
from pathlib import Path
-from typing import Optional
-
-from dotenv import load_dotenv
-
# 从仓库根目录运行 python backend/main.py 时，将 backend 加入模块搜索路径
_backend_dir = Path(__file__).resolve().parent
if str(_backend_dir) not in sys.path:
@@ -27,201 +23,13 @@ logging.basicConfig(
)
logger = logging.getLogger(__name__)
-def _repo_root() -> Path:
- """仓库根目录（含 data/、.env、api_server.py 的目录）。"""
- return Path(__file__).resolve().parent.parent
-
-
-def _load_project_env():
- """加载项目根目录 .env，供后续 os.getenv 使用。"""
- load_dotenv(_repo_root() / ".env")
-
-
-def resolve_sql_dialect(name: str) -> str:
- """CLI / 配置中的方言别名统一为 sqlglot 方言名（SQL Server -> tsql）。"""
- n = (name or "sqlserver").lower().strip()
- if n in ("sqlserver", "mssql"):
- return "tsql"
- return n
-
-
-def setup_environment():
- """环境检查"""
- _load_project_env()
- ms_key = os.getenv("MODELSCOPE_API_KEY", "").strip()
- oa_key = os.getenv("OPENAI_API_KEY", "").strip()
- oa_key_ok = oa_key and not (
- oa_key.startswith("http://") or oa_key.startswith("https://")
- )
- if ms_key:
- pass # ModelScope：BASE_URL / MODEL 有默认值，仅需 KEY
- elif oa_key_ok:
- if not os.getenv("OPENAI_EMBEDDING_MODEL", "").strip():
- logger.warning("未设置 OPENAI_EMBEDDING_MODEL（远程 Embedding 模型名）")
- return False
- else:
- if not os.getenv("DASHSCOPE_API_KEY", "").strip():
- logger.warning(
- "未设置 MODELSCOPE_API_KEY、"
- "OPENAI_API_KEY+OPENAI_EMBEDDING_MODEL 或 DASHSCOPE_API_KEY"
- )
- return False
- base = (
- os.getenv("DASHSCOPE_BASE_URL") or os.getenv("DASHSCOPE_base_url", "")
- ).strip()
- if not base:
- logger.warning("未设置 DASHSCOPE_BASE_URL（或 DASHSCOPE_base_url）")
- return False
- if not os.getenv("DASHSCOPE_MODEL", "").strip():
- logger.warning("未设置 DASHSCOPE_MODEL")
- return False
-
- # 检查Schema文件（支持相对路径和绝对路径）
- schema_path_str = os.getenv("SCHEMA_PATH", "./data/schemas/G3SB_MCDataDictionary_table_structure.json")
- schema_path = Path(schema_path_str)
-
- # 如果是相对路径，尝试从多个位置查找
- if not schema_path.is_absolute():
- # 尝试1: PyInstaller 临时目录（单文件模式）
- import sys
- if getattr(sys, 'frozen', False) and hasattr(sys, '_MEIPASS'):
- meipass_schema = Path(sys._MEIPASS) / schema_path_str
- if meipass_schema.exists():
- schema_path = meipass_schema
-
- # 尝试2: 当前工作目录
- if not schema_path.exists():
- schema_path = Path.cwd() / schema_path_str
-
- # 尝试3: 脚本所在目录
- if not schema_path.exists():
- script_dir = Path(__file__).resolve().parent.parent
- schema_path = script_dir / schema_path_str
-
- # 尝试4: 可执行文件所在目录
- if not schema_path.exists() and getattr(sys, 'frozen', False):
- exe_dir = Path(sys.executable).parent
- schema_path = exe_dir / schema_path_str
-
- if not schema_path.exists():
- logger.warning(f"Schema文件不存在: {schema_path}")
- logger.info("请将G3SB Schema文件放置在 ./data/schemas/ 目录")
- return False
-
- # 检查 LLM Key（DeepSeek / OpenAI 可切换）
- llm_sc = (os.getenv("LLM_SERVICE_CODE") or "").strip().lower()
- if llm_sc and llm_sc not in ("deepseek", "openai"):
- logger.warning("未知 LLM_SERVICE_CODE=%r（仅支持 deepseek/openai）", llm_sc)
- return False
- if llm_sc == "openai":
- if not (os.getenv("OPENAI_API_KEY") or "").strip():
- logger.warning("LLM_SERVICE_CODE=openai 但 OPENAI_API_KEY 未设置")
- return False
- else:
- if not (os.getenv("DEEPSEEK_API_KEY") or "").strip():
- logger.warning("环境变量 DEEPSEEK_API_KEY 未设置（默认 LLM_SERVICE_CODE=deepseek）")
- logger.info("请在 .env 文件中配置，或 export DEEPSEEK_API_KEY=your_key")
- return False
-
- logger.info(f"[OK] 环境检查通过")
- logger.info(f" - Schema: {schema_path}")
- logger.info(
- " - LLM: %s",
- (llm_sc or "deepseek(auto)"),
- )
-
- return True
-
-
-def _default_g3sb_meta_path(structure_path: str) -> Optional[str]:
- """若存在与 table_structure 同名的 table_meta 文件则返回其路径。"""
- p = Path(structure_path)
- if "table_structure" not in p.name:
- return None
- cand = p.parent / p.name.replace("table_structure", "table_meta")
- return str(cand) if cand.is_file() else None
-
-
-def load_schema(schema_path: str, schema_meta_path: Optional[str] = None):
- """加载 Schema；G3SB structure JSON 会自动尝试配对 table_meta（可用 --schema-meta 指定）。"""
- from schema.manager import SchemaManager
-
- meta = (
- schema_meta_path
- if schema_meta_path is not None
- else _default_g3sb_meta_path(schema_path)
- )
- logger.info(f"加载Schema: {schema_path}")
- if meta:
- logger.info(f" 表注释(meta): {meta}")
-
- schema_mgr = SchemaManager.load_from_json(
- schema_path, g3sb_meta_path=meta
- )
-
- stats = schema_mgr.get_statistics()
- logger.info(
- f"[OK] Schema加载完成: {stats['database']}, "
- f"共{stats['total_tables']}张表, {stats['total_columns']}个字段"
- )
-
- return schema_mgr
-
-
-def create_orchestrator(schema_mgr, args):
- """创建编排器"""
- from agents.orchestrator import Text2SQLOrchestrator
- from llm.router import create_llm_client, resolve_llm_service_code
- from llm.deepseek_client import DeepSeekConfig
-
- translate_en = os.getenv("TRANSLATE_EN_TO_ZH", "true").strip().lower() not in (
- "0",
- "false",
- "no",
- "off",
- )
- if getattr(args, "no_translate_en", False):
- translate_en = False
-
- sc = resolve_llm_service_code()
- if sc == "deepseek":
- api_key = (args.api_key or os.getenv("DEEPSEEK_API_KEY") or "").strip()
- if not api_key:
- raise ValueError(
- "未配置 DeepSeek API Key：请在 .env 中设置 DEEPSEEK_API_KEY，"
- "或使用命令行参数 --api-key"
- )
- base_url = (os.getenv("DEEPSEEK_BASE_URL") or "https://api.deepseek.com").strip()
- cfg = DeepSeekConfig(
- api_key=api_key,
- base_url=base_url,
- model_name=args.model or "deepseek-chat",
- temperature=args.temperature,
- max_tokens=args.max_tokens,
- )
- llm_client = create_llm_client("deepseek", **cfg.__dict__)
- else:
- # openai：完全由 OPENAI_* 决定；同时沿用 temperature/max_tokens 作为默认值覆盖
- llm_client = create_llm_client(
- "openai",
- temperature=args.temperature,
- max_tokens=args.max_tokens,
- )
-
- orchestrator = Text2SQLOrchestrator(
- schema_manager=schema_mgr,
- llm_client=llm_client,
- vector_db_path=args.vector_db,
- max_retry=args.max_retry,
- use_vector_search=not args.no_vector_search,
- # Few-shot配置
- fewshot_enabled=not args.no_fewshot,
- fewshot_top_k=args.fewshot_top_k,
- fewshot_min_rating=args.fewshot_min_rating,
- translate_english_to_zh=translate_en,
- )
-
- return orchestrator
+from bootstrap import (
+ create_orchestrator,
+ load_project_env,
+ load_schema,
+ resolve_sql_dialect,
+ setup_environment,
+)
def single_query(orchestrator, question: str, dialect: str = "tsql"):
@@ -361,7 +169,7 @@ def main():
default=2,
help="最大重试次数（默认: 2）"
)
- _load_project_env()
+ load_project_env()
parser.add_argument(
"--vector-db",
default=os.getenv("VECTOR_DB_PATH", "./data/embeddings/chroma").strip(),
diff --git a/backend/utils/__pycache__/fewshot_chroma_store.cpython-312.pyc b/backend/utils/__pycache__/fewshot_chroma_store.cpython-312.pyc
index bfe91373590fb0a3a7728cbbc937278faf47a3c3..5c4ffdaad1c65ef550d51d0ac45ae28784ec3b5d 100644
GIT binary patch
delta 19
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delta 19
ZcmcZ?doPyjG%qg~0}$--*~oQ84*)}?1~mWx
diff --git a/backend/utils/__pycache__/fewshot_selector.cpython-312.pyc b/backend/utils/__pycache__/fewshot_selector.cpython-312.pyc
index 078654dedc2629d13c8ea74c92ba1940b7dbac09..510907118cd5a7417d710e90145aa20c671826a4 100644
GIT binary patch
delta 22
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delta 22
ccmX^0nDNwOM()$Ryj%=G@OA!!jokYS0cAG`w*UYD
diff --git a/backend/utils/__pycache__/validators.cpython-312.pyc b/backend/utils/__pycache__/validators.cpython-312.pyc
index f77392b732e42b64798e7ad88ce778d6c32ad7b1..10a8e0edcb54207b1f74ba1c6da83f5fa02f54a2 100644
GIT binary patch
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zWUn Tuple[bool, List[str]]:
- """
- 扫描 SQL 中单引号字符串（含 T-SQL N'…'），若字面量内出现 CJK 则判失败。
+def _cjk_text_in_string_literal(text: str) -> bool:
+ return bool(_CJK_IN_STRING_RE.search(text))
- 跳过 ``--`` 行注释与 ``/* */`` 块注释内的文本，避免误报。
+
+def _node_in_subtree(root, target) -> bool:
+ if root is None:
+ return False
+ for n in root.walk():
+ if n is target:
+ return True
+ return False
+
+
+def _cjk_string_in_forbidden_context(node, exp) -> bool:
+ """
+ 禁止含 CJK 的字面量出现在「比对/过滤」语境：WHERE、HAVING、JOIN ON、
+ 以及 CASE 分支的 WHEN 条件（含简单 CASE 的 WHEN 值），
+ 但允许出现在 SELECT 投影、CASE 的 THEN/ELSE 结果等纯展示位置。
+ """
+ if node.find_ancestor(exp.Where):
+ return True
+ if node.find_ancestor(exp.Having):
+ return True
+ join = node.find_ancestor(exp.Join)
+ if join is not None:
+ on = join.args.get("on")
+ if on is not None and _node_in_subtree(on, node):
+ return True
+
+ case = node.find_ancestor(exp.Case)
+ while case is not None:
+ default = case.args.get("default")
+ if default is not None and _node_in_subtree(default, node):
+ return False
+ for br in case.args.get("ifs") or []:
+ then_expr = br.args.get("true")
+ cond = br.this
+ if then_expr is not None and _node_in_subtree(then_expr, node):
+ return False
+ if cond is not None and _node_in_subtree(cond, node):
+ return True
+ case = case.find_ancestor(exp.Case)
+
+ return False
+
+
+def _check_no_cjk_legacy_text_scan(sql: str) -> Tuple[bool, List[str]]:
+ """
+ 解析失败时的回退：扫描单引号字符串（含 N'…'），字面量内出现 CJK 即失败。
+ 跳过 ``--`` 行注释与 ``/* */`` 块注释内的文本。
"""
errors: List[str] = []
i = 0
@@ -27,7 +72,6 @@ def check_no_cjk_in_sql_string_literals(sql: str) -> Tuple[bool, List[str]]:
in_block_comment = False
def _read_single_quoted_string(start: int) -> Tuple[str, int]:
- """从 start 指向的 opening `'` 之后开始读，返回 (内容, 闭合引号后下标)。"""
j = start
parts: List[str] = []
while j < n:
@@ -66,10 +110,9 @@ def check_no_cjk_in_sql_string_literals(sql: str) -> Tuple[bool, List[str]]:
i += 2
continue
- # N' 或 n' 前缀的 Unicode 字面量
if i + 1 < n and sql[i] in "Nn" and sql[i + 1] == "'":
body, i = _read_single_quoted_string(i + 2)
- if _CJK_IN_STRING_RE.search(body):
+ if _cjk_text_in_string_literal(body):
prev = body[:48] + ("…" if len(body) > 48 else "")
errors.append(
"SQL 字符串字面量中含中文或与业务中文直接作为比对值（禁止）。"
@@ -79,7 +122,7 @@ def check_no_cjk_in_sql_string_literals(sql: str) -> Tuple[bool, List[str]]:
if sql[i] == "'":
body, i = _read_single_quoted_string(i + 1)
- if _CJK_IN_STRING_RE.search(body):
+ if _cjk_text_in_string_literal(body):
prev = body[:48] + ("…" if len(body) > 48 else "")
errors.append(
"SQL 字符串字面量中含中文或与业务中文直接作为比对值（禁止）。"
@@ -92,6 +135,41 @@ def check_no_cjk_in_sql_string_literals(sql: str) -> Tuple[bool, List[str]]:
return len(errors) == 0, errors
+def check_no_cjk_in_sql_string_literals(sql: str, dialect: str = "tsql") -> Tuple[bool, List[str]]:
+ """
+ 禁止在「过滤/比对」语境使用含中日韩字符的字符串字面量（含 T-SQL ``N'…'``）。
+
+ 允许在 SELECT 投影、CASE 的 THEN/ELSE 结果等展示用字面量中使用中文标签。
+ 解析失败时回退为全文扫描（与旧版一致，偏严）。
+ """
+ from sqlglot import parse_one, exp
+
+ errors: List[str] = []
+
+ try:
+ parsed = parse_one(sql, dialect=dialect)
+ except Exception as e:
+ logger.debug("CJK 校验回退为全文扫描（SQL 解析失败）: %s", e)
+ return _check_no_cjk_legacy_text_scan(sql)
+
+ for node in parsed.walk():
+ text: Optional[str] = None
+ if isinstance(node, exp.Literal) and node.is_string:
+ text = str(node.this)
+ elif isinstance(node, exp.National):
+ text = str(node.this)
+ if text is None or not _cjk_text_in_string_literal(text):
+ continue
+ if _cjk_string_in_forbidden_context(node, exp):
+ prev = text[:48] + ("…" if len(text) > 48 else "")
+ errors.append(
+ "SQL 在 WHERE/HAVING/JOIN ON 或 CASE/WHEN 条件中出现含中文的字符串字面量（禁止）。"
+ f"片段近似: …'{prev}'… — 请改用 Schema 注释中的代码/枚举，或通过维表 JOIN 用键列过滤。"
+ )
+
+ return len(errors) == 0, errors
+
+
# 危险操作关键词（除非明确允许）
DANGEROUS_KEYWORDS = [
"DROP", "DELETE", "UPDATE", "INSERT", "ALTER", "TRUNCATE",
diff --git a/data/embeddings/chroma_fewshot/9756e6ea-6d51-4e24-a490-4a58f0a585b9/length.bin b/data/embeddings/chroma_fewshot/9756e6ea-6d51-4e24-a490-4a58f0a585b9/length.bin
index d1fa5fe9b7b0ce3292b49c25b0aa11a055477be1..16406af4df89423e2b5130dcedff88eddfd90e78 100644
GIT binary patch
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literal 4000
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z!3^PIu#tqR!sLgV;=|y`5Wo<^;148q8O#_=8JvKmH-kBY1yGcMfd#6L5yD^<1@hBp
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diff --git a/logs/text2sql_api.log b/logs/text2sql_api.log
index 0a01ac8..a02e2bd 100644
--- a/logs/text2sql_api.log
+++ b/logs/text2sql_api.log
@@ -1,68 +1,135 @@
-2026-04-16 16:22:05 INFO [utils.repo_logging] repo_logging.py:79 configure_text2sql_api_logging() | 日志文件: C:\Users\24019\Desktop\backman-camel\logs\text2sql_api.log
-2026-04-16 16:22:10 INFO [__main__] api_server.py:85 () | [OK] 已加载配置文件: C:\Users\24019\Desktop\backman-camel\.env
-2026-04-16 16:22:10 INFO [__main__] api_server.py:1108 () | 启动服务: http://0.0.0.0:8041
-2026-04-16 16:22:10 INFO [__main__] api_server.py:1109 () | API文档: http://0.0.0.0:8041/docs
-2026-04-16 16:22:10 INFO [uvicorn.error] server.py:92 _serve() | Started server process [33080]
-2026-04-16 16:22:10 INFO [uvicorn.error] on.py:48 startup() | Waiting for application startup.
-2026-04-16 16:22:10 INFO [__main__] api_server.py:799 lifespan() | ============================================================
-2026-04-16 16:22:10 INFO [__main__] api_server.py:800 lifespan() | Text2SQL API Server 启动中...
-2026-04-16 16:22:10 INFO [__main__] api_server.py:801 lifespan() | ============================================================
-2026-04-16 16:22:10 INFO [main] main.py:126 setup_environment() | [OK] 环境检查通过
-2026-04-16 16:22:10 INFO [main] main.py:127 setup_environment() | - Schema: data\schemas\G3SB_MCDataDictionary_table_structure.json
-2026-04-16 16:22:10 INFO [main] main.py:128 setup_environment() | - LLM: openai
-2026-04-16 16:22:10 INFO [main] main.py:154 load_schema() | 加载Schema: ./data/schemas/G3SB_MCDataDictionary_table_structure.json
-2026-04-16 16:22:10 INFO [main] main.py:156 load_schema() | 表注释(meta): ./data/schemas/G3SB_MCDataDictionary_table_meta.json
-2026-04-16 16:22:10 INFO [schema.loader] loader.py:107 load_from_json() | [OK] 加载Schema完成(G3SB schemas): G3SB_MCDataDictionary_table_structure, 共2516张表
-2026-04-16 16:22:10 INFO [main] main.py:163 load_schema() | [OK] Schema加载完成: G3SB_MCDataDictionary_table_structure, 共2516张表, 59196个字段
-2026-04-16 16:22:14 INFO [llm.openai_client] openai_client.py:55 __init__() | [OK] OpenAIClient初始化: model=gpt-4o-mini, base_url=http://113.192.49.54:9080/v1
-2026-04-16 16:22:17 INFO [utils.embedding] embedding.py:144 __init__() | 使用 OpenAI Embedding API：model=text-embedding-ada-002，base_url=http://113.192.49.54:9080/v1，max_batch=100
-2026-04-16 16:22:19 INFO [utils.fewshot_chroma_store] fewshot_chroma_store.py:86 __init__() | [OK] FewShotChromaStore: 磁盘 data\embeddings\chroma_fewshot collection=fewshot_samples count=50
-2026-04-16 16:22:19 INFO [utils.fewshot_selector] fewshot_selector.py:128 _init_chroma_mode() | [Few-shot] 已从向量库加载（Chroma 50 条，data\embeddings\chroma_fewshot）
-2026-04-16 16:22:19 INFO [utils.fewshot_selector] fewshot_selector.py:159 _init_chroma_mode() | [OK] Few-shot 使用 Chroma（50 条）
-2026-04-16 16:22:19 INFO [agents.orchestrator] orchestrator.py:116 __init__() | Few-shot已启用: top_k=3, min_rating=7
-2026-04-16 16:22:19 INFO [agents.orchestrator] orchestrator.py:127 __init__() | [OK] Text2SQLOrchestrator初始化完成: max_retry=2, use_vector_search=True, fewshot=on, nl→zh_norm=on
-2026-04-16 16:22:19 INFO [__main__] api_server.py:132 get_orchestrator() | [OK] Orchestrator 初始化完成
-2026-04-16 16:22:19 INFO [__main__] api_server.py:805 lifespan() | [OK] 服务已就绪
-2026-04-16 16:22:19 INFO [uvicorn.error] on.py:62 startup() | Application startup complete.
-2026-04-16 16:22:19 INFO [uvicorn.error] server.py:224 _log_started_message() | Uvicorn running on http://0.0.0.0:8041 (Press CTRL+C to quit)
-2026-04-16 16:22:20 INFO [uvicorn.access] httptools_impl.py:483 send() | 127.0.0.1:14651 - "POST /g3sb/api/nl/chat/stream HTTP/1.1" 200
-2026-04-16 16:22:20 INFO [__main__] api_server.py:669 _chat_stream_events() | [API/stream] 开始: user_id='anonymous' visitor_biz_id=None session_id=None service_code=None model='gpt-4o-mini' lang_code='auto' msg_chars=15 preview='所有客户账户之间的股票转移记录' dialog_context_chars=0 last_turn_was_data_query=False
-2026-04-16 16:22:23 INFO [llm.openai_client] openai_client.py:55 __init__() | [OK] OpenAIClient初始化: model=gpt-4o-mini, base_url=http://113.192.49.54:9080/v1
-2026-04-16 16:22:23 INFO [utils.dialog_classifier] dialog_classifier.py:261 classify_dialog() | [dialog] intent=text2sql (hybrid fast: query hint) preview='所有客户账户之间的股票转移记录'
-2026-04-16 16:22:23 INFO [__main__] api_server.py:712 _chat_stream_events() | [GEN/API/stream] dialect=tsql top_k=20 dialog_context_chars=0 question_len=15 preview='所有客户账户之间的股票转移记录'
-2026-04-16 16:22:26 INFO [llm.openai_client] openai_client.py:55 __init__() | [OK] OpenAIClient初始化: model=gpt-4o-mini, base_url=http://113.192.49.54:9080/v1
-2026-04-16 16:22:29 INFO [agents.orchestrator] orchestrator.py:803 generate() | [GEN] 问句已归一中文：所有客户账户的股票转移记录
-2026-04-16 16:22:29 INFO [agents.orchestrator] orchestrator.py:816 generate() | [GEN] 开始生成SQL: question_chars=13 preview='所有客户账户的股票转移记录' dialog_context_chars=0
-2026-04-16 16:22:29 INFO [agents.orchestrator] orchestrator.py:831 generate() | 尝试 #1
-2026-04-16 16:22:29 INFO [schema.indexer] indexer.py:82 __init__() | [OK] 初始化SchemaIndexer(Chroma磁盘 path=data\embeddings\chroma): collection=schema_tables, count=2516
-2026-04-16 16:22:29 INFO [schema.indexer] indexer.py:106 ensure_index_for_schema() | Schema 向量索引已就绪（2516 张表），跳过向量化
-2026-04-16 16:22:29 INFO [agents.orchestrator] orchestrator.py:188 _coarse_filter() | [Orchestrator] 开始向量检索: query_chars=13 query_preview='所有客户账户的股票转移记录'
-2026-04-16 16:22:30 INFO [utils.embedding] embedding.py:163 _set_dim_from_vector() | [OK] Embedding 向量维度：1536
-2026-04-16 16:22:31 INFO [schema.indexer] indexer.py:244 search() | Schema 向量检索: query_chars=13 命中=20（阈值=0.1）top=[('VSBHKRpt0430', 0.8264), ('VSBHKRpt0431', 0.8188), ('TSBTransferInstruction', 0.8147), ('VSBTransferInstruction', 0.8134), ('VSBHKRpt0397', 0.8126), ('VSBHKRpt0672', 0.8117), ('VSBHKRpt0090C', 0.81), ('VSBHKRpt0570', 0.8084), ('VSBHKRpt1030A', 0.8077), ('VSBRpt0999E', 0.8065), ('VSBRpt0999C', 0.8064), ('TSBAccountEntitlementRelease', 0.8063), ('VSBRpt0999A', 0.8059), ('TSBAccountInstrumentMovement', 0.8038), ('VSBTransferInstructionGenerationByAccountContract', 0.8033)]
-2026-04-16 16:22:31 INFO [agents.orchestrator] orchestrator.py:204 _coarse_filter() | [Orchestrator] 向量粗筛: 命中=20 张（阈值内），表名+分: [('VSBHKRpt0430', 0.8264), ('VSBHKRpt0431', 0.8188), ('TSBTransferInstruction', 0.8147), ('VSBTransferInstruction', 0.8134), ('VSBHKRpt0397', 0.8126), ('VSBHKRpt0672', 0.8117), ('VSBHKRpt0090C', 0.81), ('VSBHKRpt0570', 0.8084), ('VSBHKRpt1030A', 0.8077), ('VSBRpt0999E', 0.8065), ('VSBRpt0999C', 0.8064), ('TSBAccountEntitlementRelease', 0.8063), ('VSBRpt0999A', 0.8059), ('TSBAccountInstrumentMovement', 0.8038), ('VSBTransferInstructionGenerationByAccountContract', 0.8033), ('VSBRpt0060', 0.8021), ('XCGatewayStockReconciliationReport', 0.802), ('TSBAccountEntitlementHold', 0.8013), ('WSBBatchLocationTransferDetail', 0.8012), ('VCAccountCashMovement', 0.8012)]
-2026-04-16 16:22:35 INFO [agents.orchestrator] orchestrator.py:258 _llm_select_tables() | LLM精筛选中表：['VSBHKRpt0430', 'VSBHKRpt0431', 'TSBTransferInstruction', 'VSBTransferInstruction', 'TSBAccountInstrumentMovement'] | reasoning_chars=192 reasoning_preview='问题涉及客户账户的股票转移记录，VSBHKRpt0430和VSBHKRpt0431提供了客户股票的日常转移报告和账户工具移动报告，TSBTransferInstruction和VSBTransferInstruction包含账户转移指令的详细信息，TSBAccountInstrumentMovement记录账户工具的移动交易。这些表共同涵盖了股票转移的各个方面，确保了信息的完整性。'
-2026-04-16 16:22:35 INFO [agents.orchestrator] orchestrator.py:859 generate() | 选中表：['VSBHKRpt0430', 'VSBHKRpt0431', 'TSBTransferInstruction', 'VSBTransferInstruction', 'TSBAccountInstrumentMovement']，扩展后：['TSBAccountInstrumentMovement', 'TSBTransferInstruction', 'VSBHKRpt0431', 'VSBHKRpt0430', 'VSBTransferInstruction']
-2026-04-16 16:22:37 INFO [utils.fewshot_selector] fewshot_selector.py:209 select_best_with_score() | [Few-shot] best_with_score: qid=Q2 score=0.9575 preview='列出今日所有客户账户之间的股票转移记录。'
-2026-04-16 16:22:37 INFO [agents.orchestrator] orchestrator.py:432 _generate_sql_golden_adapt() | [GEN] 黄金 few-shot 条件适配: qid=Q2 score=0.9575
-2026-04-16 16:22:41 INFO [agents.orchestrator] orchestrator.py:450 _generate_sql_golden_adapt() | 生成的SQL（黄金适配，chars=494）:
--- 查询所有客户账户间股票转移记录
--- 使用 TSBAccountInstrumentMovement，MovementType='T' 表示账户间转移
-SELECT
- m.MovementID,
- m.AccountID AS FromAccountID,
- m.TransferToAccountID,
- m.InstrumentID,
- i.Name AS InstrumentSymbol,
- m.MovementType,
- m.Quantity AS TransferQuantity,
- m.ValueDate AS TransferDate
-FROM TSBAccountInstrumentMovement m
-LEFT JOIN MCInstrument i ON m.InstrumentID = i.InstrumentID
-WHERE m.MovementType = 'T'
- AND m.ValueDate = CAST(GETDATE() AS DATE)
-ORDER BY m.ValueDate;
-2026-04-16 16:22:41 INFO [db.engine] engine.py:45 get_engine() | SQLAlchemy engine initialized from database_url
-2026-04-16 16:22:41 INFO [db.dbhub_tools] dbhub_tools.py:627 _execute_sql() | _execute_sql 执行语句数=1 readonly=True max_rows=1
-2026-04-16 16:22:44 INFO [agents.orchestrator] orchestrator.py:754 _validate_sql() | [validate] 程序+探针+LLM 汇总: valid=True err_count=0 warn_count=0 db_execution_status=0 sql_chars=494
-2026-04-16 16:22:44 INFO [agents.orchestrator] orchestrator.py:921 generate() | [OK] SQL生成与验证通过（1次尝试）
-2026-04-16 16:22:44 INFO [__main__] api_server.py:765 _chat_stream_events() | [API/stream] Text2SQL 完成: valid=True attempts=1 tables_used=['TSBAccountInstrumentMovement', 'TSBTransferInstruction', 'VSBHKRpt0431', 'VSBHKRpt0430', 'VSBTransferInstruction'] sql_chars=494 sql_head="-- 查询所有客户账户间股票转移记录\n-- 使用 TSBAccountInstrumentMovement，MovementType='T' 表示账户间转移\nSELECT \n m.MovementID,\n m.AccountID AS FromAccountID,\n m.TransferToAccountID,\n m.InstrumentID,\n i.Name AS InstrumentSymbol,\n m.MovementType,\n m.Quantity AS TransferQuantity,\n m.ValueDate AS TransferDate\nFROM TSBAccountInstrumentMovement m\nLEFT JOIN MCInstrument i ON m.InstrumentID = i.InstrumentID\nWHERE m.MovementType = 'T'\n AND m.ValueDate = CAST(GETDATE() AS DATE)\nORDER BY m.ValueDate;"
+2026-04-17 10:48:50 INFO [utils.repo_logging] repo_logging.py:79 configure_text2sql_api_logging() | 日志文件: C:\Users\24019\Desktop\backman-camel\logs\text2sql_api.log
+2026-04-17 10:48:55 INFO [__main__] api_server.py:86 () | [OK] 已加载配置文件: C:\Users\24019\Desktop\backman-camel\.env
+2026-04-17 10:48:55 INFO [__main__] api_server.py:1299