Update app.py

app.py

@@ -181,28 +181,36 @@ st.write("# GPT3 and Langchain Demo")
 # )
 
 # Sidebar
-st.sidebar.header("Options")
-st.sidebar.write("## File Upload:")
-data_files = st.sidebar.file_uploader(
-    "upload", type=["pdf", "txt", "docx"], accept_multiple_files=True, label_visibility="hidden"
-)
+# st.sidebar.header("Options")
+# st.sidebar.write("## File Upload:")
+# data_files = st.sidebar.file_uploader(
+#     "upload", type=["pdf", "txt", "docx"], accept_multiple_files=True, label_visibility="hidden"
+# )
 ALL_FILES = []
 META_DATA = []
-for data_file in data_files:
-    # Upload file
-    if data_file:
-        file_path = Path(FILE_UPLOAD_PATH) / f"{uuid.uuid4().hex}_{data_file.name}"
-        with open(file_path, "wb") as f:
-            f.write(data_file.getbuffer())
-        ALL_FILES.append(file_path)
-        st.sidebar.write(str(data_file.name) + "    ✅ ")
-        META_DATA.append({"filename": data_file.name})
+# for data_file in data_files:
+#     # Upload file
+#     if data_file:
+#         file_path = Path(FILE_UPLOAD_PATH) / f"{uuid.uuid4().hex}_{data_file.name}"
+#         with open(file_path, "wb") as f:
+#             f.write(data_file.getbuffer())
+#         ALL_FILES.append(file_path)
+#         st.sidebar.write(str(data_file.name) + "    ✅ ")
+#         META_DATA.append({"filename": data_file.name})
 # ALL_FILES = ["./wellous_products.txt"]
 # "wellous_products.txt"
-# META_DATA.append({"filename": data_file.name})
-
-print(ALL_FILES)
-print(META_DATA)
+text_file = 'wellous_products.txt'
+file_path = "./" f"{text_file}"
+print("file_path",file_path)
+
+with open(file_path, "wb") as f:
+    f.write(file_path.getbuffer())
+    
+ALL_FILES.append(file_path)
+META_DATA.append({"filename": text_file})
+    
+print("ALL_FILES",ALL_FILES)
+print("META_DATA",META_DATA)
 
 if len(ALL_FILES) > 0:
     # document_store.update_embeddings(retriever, update_existing_embeddings=False)