Replace GPTSimpleVectorIndex import with GPTVectorStoreIndex

src/data_loader.py

@@ -4,7 +4,7 @@ import pandas as pd
 from pathlib import Path
 import glob
 
-from llama_index import GPTSimpleVectorIndex, download_loader, SimpleDirectoryReader, SimpleWebPageReader
+from llama_index import GPTVectorStoreIndex, download_loader, SimpleDirectoryReader, SimpleWebPageReader
 from langchain.document_loaders import PyPDFLoader, TextLoader
 from langchain.agents import initialize_agent, Tool
 from langchain.llms import OpenAI
@@ -170,7 +170,7 @@ class DATA_LOADER:
             # Load data from URLs
             documents = loader.load_data(urls=urls)
             # Build the Vector database
-            index = GPTSimpleVectorIndex(documents)
+            index = GPTVectorStoreIndex(documents)
             tools = [
                 Tool(
                     name="Website Index",

src/langchain_utils.py

@@ -13,7 +13,7 @@ import chromadb
 from langchain.chains.question_answering import load_qa_chain
 from langchain.chains.qa_with_sources import load_qa_with_sources_chain
 from langchain.prompts import PromptTemplate
-from llama_index import GPTSimpleVectorIndex, GPTListIndex
+from llama_index import GPTVectorStoreIndex, GPTListIndex
 from langchain.vectorstores import FAISS
 
 import pickle
@@ -365,8 +365,8 @@ class LANGCHAIN_UTILS:
             )
 
         # Vector store using GPT vector index
-        elif self.index_type == 'GPTSimpleVectorIndex':
-            self.index = GPTSimpleVectorIndex.from_documents(self.documents)
+        elif self.index_type == 'GPTVectorStoreIndex':
+            self.index = GPTVectorStoreIndex.from_documents(self.documents)
 
         logger.info(f'Index created successfully!')
         return self.index
@@ -522,7 +522,7 @@ class LANGCHAIN_UTILS:
         elif self.index_type == 'Chroma':
             index.persist()
 
-        elif self.index_type == 'GPTSimpleVectorIndex':
+        elif self.index_type == 'GPTVectorStoreIndex':
             index.save_to_disk(index_filepath)
 
         elif self.index_type == 'pickle':
@@ -550,8 +550,8 @@ class LANGCHAIN_UTILS:
                 embedding_function=self.embeddings
             )
 
-        elif self.index_type == 'GPTSimpleVectorIndex':
-            self.index = GPTSimpleVectorIndex.load_from_disk(self.index_filepath)
+        elif self.index_type == 'GPTVectorStoreIndex':
+            self.index = GPTVectorStoreIndex.load_from_disk(self.index_filepath)
 
         elif self.index_type == 'pickle':
             with open(self.index_filepath, "rb") as f:
@@ -579,9 +579,9 @@ class LANGCHAIN_UTILS:
         url_documents
     ):
         # Build the Vector store for docs
-        doc_index = GPTSimpleVectorIndex.from_documents(doc_documents)
+        doc_index = GPTVectorStoreIndex.from_documents(doc_documents)
         # Build the Vector store for URLs
-        url_index = GPTSimpleVectorIndex.from_documents(url_documents)
+        url_index = GPTVectorStoreIndex.from_documents(url_documents)
 
         # Set summary of each index
         doc_index.set_text("index_from_docs")
@@ -628,10 +628,10 @@ class LANGCHAIN_UTILS:
                     continue
                 raise NotImplementedError
 
-        elif self.index_type == 'GPTSimpleVectorIndex':
+        elif self.index_type == 'GPTVectorStoreIndex':
             for doc_type, index in doc_type_indices.items():
-                if not index or not isinstance(index, GPTSimpleVectorIndex):
-                    logger.warning(f'{doc_type} index to be merged is not an instance of type llama_index.GPTSimpleVectorIndex')
+                if not index or not isinstance(index, GPTVectorStoreIndex):
+                    logger.warning(f'{doc_type} index to be merged is not an instance of type llama_index.GPTVectorStoreIndex')
                     continue
                 raise NotImplementedError
 
@@ -715,7 +715,7 @@ class LANGCHAIN_UTILS:
                 k=similarity_top_k
             )
 
-        elif self.index_type == 'GPTSimpleVectorIndex':
+        elif self.index_type == 'GPTVectorStoreIndex':
             # Querying the index
             response = index.query(
                 question,