Update app.py

app.py

@@ -267,29 +267,19 @@ with st.form("my_form"):
         list_save_path.append(save_path)
     
     print('uploaded_files ', uploaded_files)
-    if uploaded_files is not None:
+    single_example_passage = st.text_area('Enter Query Here',"What is Governing Law ")
+    submitted = st.form_submit_button("Index and Calculate")
+    if submitted and (uploaded_files is not None):
         #list_docs, list_save_path = util_upload_file_and_return_list_docs(uploaded_files)
         print('list_docs ' ,list_docs)
         print('list_save_path ' , list_save_path)
-        
-        #page_documents , passage_documents = util_get_list_page_and_passage(docs)
-        #print('len(page_documents) len(passage_documents ', len(page_documents), len(passage_documents))
-    single_example_passage = st.text_area('Enter Query Here',"What is Governing Law ")
-    #hyde_passage = util_openai_hyde(single_example_passage)
-    #print("HYDE :: ", hyde_passage)
-    
-    submitted = st.form_submit_button("Index and Calculate")
-    if submitted and (uploaded_file is not None):
         bm25_retriever = BM25Retriever.from_documents(passage_documents)
         bm25_retriever.k = 2
         chroma_vectorstore = Chroma.from_documents(passage_documents, embedding)
         chroma_retriever = chroma_vectorstore.as_retriever(search_kwargs={"k": 2})
-        #initialize the ensemble retriever
         ensemble_retriever = EnsembleRetriever(retrievers=[bm25_retriever, chroma_retriever],weights=[0.25, 0.75])
         passage_nodes = ensemble_retriever.get_relevant_documents(single_example_passage)
         print('len(passage_nodes):', len(passage_nodes))
-        ### From Passage to PAGE
-
         found_passage, page_list_retrieve = util_get_list_pageno_and_contents(single_example_passage, page_documents,passage_documents,passage_nodes)
         print('len(page_list_retrieve):', len(page_list_retrieve))
         if(len(page_list_retrieve)>0):
@@ -299,11 +289,8 @@ with st.form("my_form"):
                 page_content = iindex[1]
                 annotated_text("  ",annotation("RELEVANT PAGENO : ", str(page_no), font_family="Comic Sans MS", border="2px dashed red"),)
                 util_openai_format(single_example_passage, page_content)
-                #st.write('Modified Prompt :: ')
                 annotated_text("  ",annotation("RELEVANT PASSAGE : ", "", font_family="Comic Sans MS", border="2px dashed red"),)
                 st.write(found_passage)
-            # util_del_file(save_path)
-            # chroma_client.delete_collection(name=collection_name)
         pchroma_client = chromadb.Client()
         for citem in pchroma_client.list_collections():
             print(citem.name)