backend/app/engine/engine.py

@@ -2,17 +2,41 @@ import os
 
 from llama_index.core import SummaryIndex, SQLDatabase, VectorStoreIndex
 from llama_index.core.indices.struct_store import SQLTableRetrieverQueryEngine
-from llama_index.core.objects import SQLTableNodeMapping, ObjectIndex
+from llama_index.core.objects import SQLTableNodeMapping, ObjectIndex, SQLTableSchema
 from llama_index.core.query_engine import RetrieverQueryEngine
 from llama_index.core.response_synthesizers import ResponseMode
+from llama_index.readers.database import DatabaseReader
 from sqlalchemy import create_engine
 
-from app.engine import makeDescriptionByEngine
 from app.engine.prompt import text_qa_template, refine_template, summary_template, simple_template
 from app.engine.retriever.HybridRetriever import HybridRetriever
 from app.settings import get_node_postprocessors
 
+def makeDescriptionByEngine(sql_database:SQLDatabase):
+    reader = DatabaseReader(sql_database)
 
+    table_names = sql_database.get_usable_table_names()
+    table_schema_objs = []
+    for table_name in table_names:
+        columns = sql_database.get_table_columns(table_name)
+        if len(columns) > 150:
+            continue
+        stats_txt = ""
+
+        if table_name == 'gongchengshuxing':
+            stats_txt = '该表中有以下属性:'
+            documents = reader.load_data(query='select name from gongchengshuxing')
+            for index in range(len(documents) if len(documents) < 30 else 30):
+                if index == 0:
+                    continue
+                elif index > 1:
+                    stats_txt += ','
+                stats_txt += documents[index].text.split(':')[1]
+
+        tbSchema = (SQLTableSchema(table_name=table_name, context_str=stats_txt))
+        table_schema_objs.append(tbSchema)
+
+    return table_schema_objs
 
 def get_Retriever(index,**kwargs):
     bEnableHybrid = True if os.getenv("HYBRID_ENABLED",False).title() == 'True' else False

backend/app/engine/loaders/db.py

@@ -1,20 +1,14 @@
-import os
 import logging
-from typing import List
 from typing import Any, List, Optional
 
-from llama_index.core.readers.base import BaseReader
-from llama_index.core.schema import Document
-from llama_index.core.utilities.sql_wrapper import SQLDatabase
-from sqlalchemy import text
-from sqlalchemy.engine import Engine
 from llama_index.core import SQLDatabase, Document
-from llama_index.core.objects import SQLTableSchema, SQLTableNodeMapping
+from llama_index.core.objects import SQLTableSchema
 from llama_index.core.readers.base import BaseReader
 from llama_index.readers.database import DatabaseReader
-from pydantic import BaseModel, validator
-from llama_index.core.indices.vector_store import VectorStoreIndex
+from pydantic import BaseModel
 from sqlalchemy import create_engine
+from sqlalchemy import text
+from sqlalchemy.engine import Engine
 
 logger = logging.getLogger(__name__)
 
@@ -119,32 +113,6 @@ class DBLoaderConfig(BaseModel):
     uri: str
     queries: List[str]
 
-def makeDescriptionByEngine(sql_database:SQLDatabase):
-    reader = DatabaseReader(sql_database)
-
-    table_names = sql_database.get_usable_table_names()
-    table_schema_objs = []
-    for table_name in table_names:
-        columns = sql_database.get_table_columns(table_name)
-        if len(columns) > 150:
-            continue
-        stats_txt = ""
-
-        if table_name == 'gongchengshuxing':
-            stats_txt = '该表中有以下属性:'
-            documents = reader.load_data(query='select name from gongchengshuxing')
-            for index in range(len(documents) if len(documents) < 30 else 30):
-                if index == 0:
-                    continue
-                elif index > 1:
-                    stats_txt += ','
-                stats_txt += documents[index].text.split(':')[1]
-
-        tbSchema = (SQLTableSchema(table_name=table_name, context_str=stats_txt))
-        table_schema_objs.append(tbSchema)
-
-    return table_schema_objs
-
 def get_db_documents(configs: list[DBLoaderConfig]):
     docs = []