Update app.py

app.py

@@ -14,6 +14,28 @@ import streamlit as st
 from PIL import Image
 import time
 
+def findanswer(Nand_url, Nand_question):
+    if True:
+      if Nand_url:
+          index = None
+          loader1 = PyPDFLoader(Nand_url)
+          langchainembeddings = OpenAIEmbeddings(deployment="textembedding", chunk_size=1)
+
+          index = VectorstoreIndexCreator(
+                  # split the documents into chunks
+                  text_splitter=CharacterTextSplitter(chunk_size=1000, chunk_overlap=0),
+                  # select which embeddings we want to use
+                  embedding=langchainembeddings,
+                  # use Chroma as the vectorestore to index and search embeddings
+                  vectorstore_cls=Chroma
+              ).from_loaders([loader1])             
+#          st.write("indexed PDF...AI finding answer....please wait")
+      if Nand_question:
+        answer = index.query(llm=llmgpt3, question=yourquestion, chain_type="map_reduce")
+        return answer
+
+
+          
 image = Image.open('Wipro logo.png')
 st.image(image)
 
@@ -40,26 +62,8 @@ with st.form("my_form"):
    submitted = st.form_submit_button("Ask question")
    if submitted:
       st.write("AI is looking for the answer...It will take atleast 2 mintutes... Answers will appear below....")
+      Nandanswer = findanswer(myurl, yourquestion )
+      st.write(Nandanswer)
 
-      if myurl:
-          index = None
-          loader1 = PyPDFLoader(myurl)
-          langchainembeddings = OpenAIEmbeddings(deployment="textembedding", chunk_size=1)
 
-          index = VectorstoreIndexCreator(
-                  # split the documents into chunks
-                  text_splitter=CharacterTextSplitter(chunk_size=1000, chunk_overlap=0),
-                  # select which embeddings we want to use
-                  embedding=langchainembeddings,
-                  # use Chroma as the vectorestore to index and search embeddings
-                  vectorstore_cls=Chroma
-              ).from_loaders([loader1])
-              
-          st.write("indexed PDF...AI finding answer....please wait")
-
-
-
-      if yourquestion:
-        answer = index.query(llm=llmgpt3, question=yourquestion, chain_type="map_reduce")
-        st.subheader(answer)