Update app.py

app.py

@@ -14,19 +14,25 @@ from langchain.schema import Document
 from langchain.vectorstores import Chroma
 from langchain.embeddings import HuggingFaceEmbeddings
 embedding = HuggingFaceEmbeddings(model_name='BAAI/bge-base-en-v1.5')
-
+from FlagEmbedding import FlagReranker
+reranker = FlagReranker('BAAI/bge-reranker-base')
 import spacy
 # Load the English model from SpaCy
 nlp = spacy.load("en_core_web_md")
 
-def util_upload_file_and_return_list_docs(uploaded_file):
+def util_upload_file_and_return_list_docs(uploaded_files):
     #util_del_cwd()
-    save_path = Path(os.getcwd(), uploaded_file.name)
-    with open(save_path, mode='wb') as w:
-        w.write(uploaded_file.getvalue())
-    print('save_path:', save_path)
-    docs = fitz.open(save_path)   
-    return(docs, save_path)
+    list_docs = []
+    list_save_path = []
+    for uploaded_file in uploaded_files:
+        save_path = Path(os.getcwd(), uploaded_file.name)
+        with open(save_path, mode='wb') as w:
+            w.write(uploaded_file.getvalue())
+        print('save_path:', save_path)
+        docs = fitz.open(save_path) 
+        list_docs.append(docs)
+        list_save_path.append(save_path)
+    return(list_docs, list_save_path)
 #### Helper Functions to Split using Rolling Window (recomm : use smaller rolling window )
 def split_txt_file_synthetic_sentence_rolling(ctxt, sentence_size_in_chars, sliding_size_in_chars,debug=False):
     sliding_size_in_chars = sentence_size_in_chars - sliding_size_in_chars
@@ -246,9 +252,13 @@ with st.form("my_form"):
     ** Attempt is made for appropriate page and passage retrieval ** \n
     '''
     st.markdown(multi)
-    uploaded_file = st.file_uploader("Choose a file")    
-    if uploaded_file is not None:
-        docs, save_path = util_upload_file_and_return_list_docs(uploaded_file)
+    #uploaded_file = st.file_uploader("Choose a file")  
+    uploaded_files = st.file_uploader('Upload Multiple files',accept_multiple_files=True)
+    if 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 ")