实现多工程数据存储支持

backend/app/engine/index.py

@@ -1,22 +1,23 @@
 import logging
 from llama_index.core.indices import VectorStoreIndex
 from app.engine.vectordb import get_vector_store
-
+from app.engine.generate import get_document_Types
 
 logger = logging.getLogger("uvicorn")
 
-index = None
+indexs = {}
 
 def get_index(params=None):
-    global index
-    if index is None:
+    global indexs
+    if len(index) <= 0:
         logger.info("Connecting vector store...")
-
-        store = get_vector_store()
-        # Load the index from the vector store
-        # If you are using a vector store that doesn't store text,
-        # you must load the index from both the vector store and the document store
-        index = VectorStoreIndex.from_vector_store(store)
-        logger.info("Finished load index from vector store.")
-
-    return index
+        docTypes = get_document_Types()
+        for docType in docTypes:
+            store = get_vector_store(docType)
+            # Load the index from the vector store
+            # If you are using a vector store that doesn't store text,
+            # you must load the index from both the vector store and the document store
+            index = VectorStoreIndex.from_vector_store(store)
+            logger.info("Finished load index from vector store.")
+            indexs[docType] = index
+    return indexs