add user authentication

brain.py

@@ -4,7 +4,7 @@ import streamlit as st
 
 def brain(supabase):
     ## List all documents
-    response = supabase.table("documents").select("name:metadata->>file_name, size:metadata->>file_size", count="exact").execute()
+    response = supabase.table("documents").select("name:metadata->>file_name, size:metadata->>file_size", count="exact").filter('metadata->>user', 'eq', st.session_state["username"]).execute()
     
     documents = response.data  # Access the data from the response
 

explorer.py

@@ -3,7 +3,7 @@ import streamlit as st
 
 def view_document(supabase):
     # Get the document from the database
-    response = supabase.table("documents").select("content").execute()
+    response = supabase.table("documents").select("content").filter('metadata->>user', 'eq', st.session_state["username"]).execute()
     # st.write("**This feature is in active development**")
     # Display a list of elements from the documents
     # If the user clicks on an element, display the content of the document

loaders/common.py

@@ -35,8 +35,12 @@ def process_file(vector_store, file, loader_class, file_suffix, stats_db=None):
     documents = text_splitter.split_documents(documents)
 
     # Add the document sha1 as metadata to each document
-    docs_with_metadata = [Document(page_content=doc.page_content, metadata={"file_sha1": file_sha1,"file_size":file_size ,"file_name": file_name, "chunk_size": chunk_size, "chunk_overlap": chunk_overlap, "date": dateshort}) for doc in documents]
+    docs_with_metadata = [Document(page_content=doc.page_content, metadata={"file_sha1": file_sha1,"file_size":file_size ,"file_name": file_name, 
+                                                                            "chunk_size": chunk_size, "chunk_overlap": chunk_overlap, "date": dateshort,
+                                                                            "user" : st.session_state["username"]}) 
+                          for doc in documents]
     
     vector_store.add_documents(docs_with_metadata)
     if stats_db:
-        add_usage(stats_db, "embedding", "file", metadata={"file_name": file_name,"file_type": file_suffix, "chunk_size": chunk_size, "chunk_overlap": chunk_overlap})
+        add_usage(stats_db, "embedding", "file", metadata={"file_name": file_name,"file_type": file_suffix, 
+                                                           "chunk_size": chunk_size, "chunk_overlap": chunk_overlap})

main.py

@@ -11,9 +11,10 @@ from langchain.vectorstores import SupabaseVectorStore
 from supabase import Client, create_client
 from explorer import view_document
 from stats import get_usage_today
+from st_login_form import login_form
 
-supabase_url = st.secrets.supabase_url
-supabase_key = st.secrets.supabase_service_key
+supabase_url = st.secrets.SUPABASE_URL
+supabase_key = st.secrets.SUPABASE_KEY
 openai_api_key = st.secrets.openai_api_key
 anthropic_api_key = st.secrets.anthropic_api_key
 hf_api_key = st.secrets.hf_api_key
@@ -64,72 +65,79 @@ if self_hosted == "false":
     else:
         st.markdown(f"<span style='color:blue'>Usage today: {usage} tokens out of {st.secrets.usage_limit}</span>", unsafe_allow_html=True)
     st.write("---")
-    
 
+client = login_form()
 
-
-# Initialize session state variables
-if 'model' not in st.session_state:
-    st.session_state['model'] = "llama-2"
-if 'temperature' not in st.session_state:
-    st.session_state['temperature'] = 0.1
-if 'chunk_size' not in st.session_state:
-    st.session_state['chunk_size'] = 500
-if 'chunk_overlap' not in st.session_state:
-    st.session_state['chunk_overlap'] = 0
-if 'max_tokens' not in st.session_state:
-    st.session_state['max_tokens'] = 500
-
-# Create a radio button for user to choose between adding knowledge or asking a question
-user_choice = st.radio(
-    "Choose an action", ('Add Knowledge', 'Chat with your Brain', 'Forget', "Explore"))
-
-st.markdown("---\n\n")
-
-if user_choice == 'Add Knowledge':
-    # Display chunk size and overlap selection only when adding knowledge
-    st.sidebar.title("Configuration")
-    st.sidebar.markdown(
-        "Choose your chunk size and overlap for adding knowledge.")
-    st.session_state['chunk_size'] = st.sidebar.slider(
-        "Select Chunk Size", 100, 1000, st.session_state['chunk_size'], 50)
-    st.session_state['chunk_overlap'] = st.sidebar.slider(
-        "Select Chunk Overlap", 0, 100, st.session_state['chunk_overlap'], 10)
-    
-    # Create two columns for the file uploader and URL uploader
-    col1, col2 = st.columns(2)
-    
-    with col1:
-        file_uploader(supabase, vector_store)
-    with col2:
-        url_uploader(supabase, vector_store)
-elif user_choice == 'Chat with your Brain':
-    # Display model and temperature selection only when asking questions
-    st.sidebar.title("Configuration")
-    st.sidebar.markdown(
-        "Choose your model and temperature for asking questions.")
-    if self_hosted != "false":
-        st.session_state['model'] = st.sidebar.selectbox(
-        "Select Model", models, index=(models).index(st.session_state['model']))
-    else:
-        st.sidebar.write("**Model**: gpt-3.5-turbo")
-        st.sidebar.write("**Self Host to unlock more models such as claude-v1 and GPT4**")
-        st.session_state['model'] = "gpt-3.5-turbo"
-    st.session_state['temperature'] = st.sidebar.slider(
-        "Select Temperature", 0.1, 1.0, st.session_state['temperature'], 0.1)
-    if st.secrets.self_hosted != "false":
-        st.session_state['max_tokens'] = st.sidebar.slider(
-            "Select Max Tokens", 500, 4000, st.session_state['max_tokens'], 500)
+if st.session_state["authenticated"]:
+    if st.session_state["username"]:
+        st.success(f"Welcome {st.session_state['username']}")
     else:
+        st.success("Welcome guest")
+
+    # Initialize session state variables
+    if 'model' not in st.session_state:
+        st.session_state['model'] = "llama-2"
+    if 'temperature' not in st.session_state:
+        st.session_state['temperature'] = 0.1
+    if 'chunk_size' not in st.session_state:
+        st.session_state['chunk_size'] = 500
+    if 'chunk_overlap' not in st.session_state:
+        st.session_state['chunk_overlap'] = 0
+    if 'max_tokens' not in st.session_state:
         st.session_state['max_tokens'] = 500
-    
-    chat_with_doc(st.session_state['model'], vector_store, stats_db=supabase)
-elif user_choice == 'Forget':
-    st.sidebar.title("Configuration")
-
-    brain(supabase)
-elif user_choice == 'Explore':
-    st.sidebar.title("Configuration")
-    view_document(supabase)
 
-st.markdown("---\n\n")
+    # Create a radio button for user to choose between adding knowledge or asking a question
+    user_choice = st.radio(
+        "Choose an action", ('Add Knowledge', 'Chat with your Brain', 'Forget', "Explore"))
+
+    st.markdown("---\n\n")
+
+    if user_choice == 'Add Knowledge':
+        # Display chunk size and overlap selection only when adding knowledge
+        st.sidebar.title("Configuration")
+        st.sidebar.markdown(
+            "Choose your chunk size and overlap for adding knowledge.")
+        st.session_state['chunk_size'] = st.sidebar.slider(
+            "Select Chunk Size", 100, 1000, st.session_state['chunk_size'], 50)
+        st.session_state['chunk_overlap'] = st.sidebar.slider(
+            "Select Chunk Overlap", 0, 100, st.session_state['chunk_overlap'], 10)
+        
+        # Create two columns for the file uploader and URL uploader
+        col1, col2 = st.columns(2)
+        
+        with col1:
+            file_uploader(supabase, vector_store)
+        with col2:
+            url_uploader(supabase, vector_store)
+    elif user_choice == 'Chat with your Brain':
+        # Display model and temperature selection only when asking questions
+        st.sidebar.title("Configuration")
+        st.sidebar.markdown(
+            "Choose your model and temperature for asking questions.")
+        if self_hosted != "false":
+            st.session_state['model'] = st.sidebar.selectbox(
+            "Select Model", models, index=(models).index(st.session_state['model']))
+        else:
+            st.sidebar.write("**Model**: gpt-3.5-turbo")
+            st.sidebar.write("**Self Host to unlock more models such as claude-v1 and GPT4**")
+            st.session_state['model'] = "gpt-3.5-turbo"
+        st.session_state['temperature'] = st.sidebar.slider(
+            "Select Temperature", 0.1, 1.0, st.session_state['temperature'], 0.1)
+        if st.secrets.self_hosted != "false":
+            st.session_state['max_tokens'] = st.sidebar.slider(
+                "Select Max Tokens", 500, 4000, st.session_state['max_tokens'], 500)
+        else:
+            st.session_state['max_tokens'] = 500
+        
+        chat_with_doc(st.session_state['model'], vector_store, stats_db=supabase)
+    elif user_choice == 'Forget':
+        st.sidebar.title("Configuration")
+
+        brain(supabase)
+    elif user_choice == 'Explore':
+        st.sidebar.title("Configuration")
+        view_document(supabase)
+
+    st.markdown("---\n\n")
+else:
+    st.error("Not authenticated")

requirements.txt

@@ -12,4 +12,5 @@ anthropic==0.2.8
 fastapi==0.95.2
 python-multipart==0.0.6
 uvicorn==0.22.0
-docx2txt
+docx2txt
+st-login-form