Update app.py

app.py

@@ -7,15 +7,15 @@ from PyPDF2 import PdfReader
 from langchain.text_splitter import CharacterTextSplitter, RecursiveCharacterTextSplitter
 from langchain.embeddings.openai import OpenAIEmbeddings
 from langchain import VectorDBQA
-from langchain.llms import AzureOpenAI
+from langchain.llms import ChatOpenAI
 from langchain.chains import RetrievalQA
 from langchain.chat_models import AzureChatOpenAI
 
 # from langchain.chat_models import AzureChatOpenAI
 
-os.environ["OPENAI_API_TYPE"] = openai.api_type = "azure"
-os.environ["OPENAI_API_VERSION"] = openai.api_version = "2023-03-15-preview"
-os.environ["OPENAI_API_BASE"] = openai.api_base = "https://cog-mnjbf5r4o6b3e.openai.azure.com/"
+# os.environ["OPENAI_API_TYPE"] = openai.api_type = "azure"
+# os.environ["OPENAI_API_VERSION"] = openai.api_version = "2023-03-15-preview"
+# os.environ["OPENAI_API_BASE"] = openai.api_base = "https://cog-mnjbf5r4o6b3e.openai.azure.com/"
 openai.api_key = os.environ["OPENAI_API_KEY"] 
 
 
@@ -59,8 +59,8 @@ def upload_pdf(file, pdf_text, embeddings, vectorstore, azure_embeddings, qa, pr
         documents=texts,
         embeddings=embeddings,
         metadatas=[{"source": "source"} for text in texts])
-    # qa = RetrievalQA.from_chain_type(llm= ChatOpenAI(model_name='gpt-3.5-turbo' ), chain_type="stuff", retriever=vectorstore.as_retriever())
-    qa = RetrievalQA.from_chain_type(llm= AzureChatOpenAI(deployment_name="chat", model_name="gpt-35-turbo"), chain_type="stuff", vectorstore=vectorstore.as_retriever())
+    qa = RetrievalQA.from_chain_type(llm= ChatOpenAI(model_name='gpt-3.5-turbo' ), chain_type="stuff", retriever=vectorstore.as_retriever())
+    # qa = RetrievalQA.from_chain_type(llm= AzureChatOpenAI(deployment_name="chat", model_name="gpt-35-turbo"), chain_type="stuff", vectorstore=vectorstore.as_retriever())
 
     return pdf_text, pdf_text, embeddings, vectorstore, azure_embeddings, qa, gr.update(visible=True), gr.update(visible=True), gr.update(visible=False)