add collumns

app_V2.py

@@ -1,5 +1,4 @@
 import tempfile
-import time
 import streamlit as st
 from PyPDF2 import PdfReader
 from langchain.text_splitter import CharacterTextSplitter
@@ -11,9 +10,9 @@ from langchain.chains import ConversationalRetrievalChain
 import os
 import pickle
 from datetime import datetime
-from backend.generate_metadata import generate_metadata, ingest, MODEL_NAME
-
+from backend.generate_metadata import generate_metadata, ingest
 
+MODEL_NAME = "mixtral"
 css = '''
 <style>
 .chat-message {
@@ -58,46 +57,6 @@ user_template = '''
 </div>
 '''
 
-def main():
-
-    st.set_page_config(page_title="Doc Verify RAG", page_icon=":mag:")
-    st.write('Anomaly detection for document metadata', unsafe_allow_html=True)
-    st.header("Doc Verify RAG :mag:")
-
-    if "openai_api_key" not in st.session_state:
-        st.session_state.openai_api_key = False
-    if "openai_org" not in st.session_state:
-        st.session_state.openai_org = False
-    if "classify" not in st.session_state:
-        st.session_state.classify = False
-
-    col1, col2 = st.columns(2)
-    with col1:
-        uploaded_file = st.file_uploader("Choose a PDF file", type=["pdf", "txt"])
-
-        if uploaded_file is not None:
-            try:
-                with tempfile.NamedTemporaryFile(delete=False, suffix=os.path.splitext(uploaded_file.name)[1]) as tmp:
-                    tmp.write(uploaded_file.read())
-                    file_path = tmp.name
-                    st.write(f'Created temporary file {file_path}')
-
-                docs = ingest(file_path)
-                st.write('## Querying Together.ai API')
-                metadata = generate_metadata(docs)
-                st.write(f'## Metadata Generated by {MODEL_NAME}')
-                st.write(metadata)
-
-                # Clean up the temporary file
-                os.remove(file_path)
-
-            except Exception as e:
-                st.error(f'Error: {e}')
-    with col2:
-        if st.button("Abbruch MFH Holzweg 13"):
-            st.session_state.user_space = "deconstruction"
-
-
 
 def get_pdf_text(pdf_docs):
     text = ""
@@ -166,13 +125,11 @@ def safe_vec_store():
         pickle.dump(vector_store, f)
 
 
+"""
 def main():
 
 
 
-    def set_pw():
-        st.session_state.openai_api_key = True
-
     st.subheader("Your documents")
 
     if st.session_state.classify:
@@ -239,6 +196,51 @@ def main():
 
         if st.button("Load Embeddings"):
             st.warning("this function is not in use, just upload the vectorstore")
+"""
+
+
+def main():
+
+    st.set_page_config(page_title="Doc Verify RAG", page_icon=":mag:")
+    st.write('Anomaly detection for document metadata', unsafe_allow_html=True)
+    st.header("Doc Verify RAG :mag:")
+
+    def set_pw():
+        st.session_state.openai_api_key = True
+
+    if "openai_api_key" not in st.session_state:
+        st.session_state.openai_api_key = False
+    if "openai_org" not in st.session_state:
+        st.session_state.openai_org = False
+    if "classify" not in st.session_state:
+        st.session_state.classify = False
+
+    col1, col2 = st.columns(2)
+    with col1:
+        uploaded_file = st.file_uploader("Choose a PDF file", type=["pdf", "txt"])
+
+        if uploaded_file is not None:
+            try:
+                with tempfile.NamedTemporaryFile(delete=False, suffix=os.path.splitext(uploaded_file.name)[1]) as tmp:
+                    tmp.write(uploaded_file.read())
+                    file_path = tmp.name
+                    st.write(f'Created temporary file {file_path}')
+
+                docs = ingest(file_path)
+                st.write('## Querying Together.ai API')
+                metadata = generate_metadata(docs)
+                st.write(f'## Metadata Generated by {MODEL_NAME}')
+                st.write(metadata)
+
+                # Clean up the temporary file
+                os.remove(file_path)
+
+            except Exception as e:
+                st.error(f'Error: {e}')
+    with col2:
+        OPENAI_API_KEY = st.text_input("OPENAI API KEY:", type="password",
+                                       disabled=st.session_state.openai_api_key, on_change=set_pw)
+        classification = st.file_uploader("upload the metadata", type=["csv", "txt"])
 
 
 if __name__ == '__main__':