commit

.gitignore

@@ -155,3 +155,5 @@ cython_debug/
 
 *.pkl
 *.csv
+colleen.py
+assets/Images/colleen-logo.png

Quivr

@@ -1 +0,0 @@
-Subproject commit 3ee69683e0ae09c62e7b13d83f22bfc8606a8aa3

colleen.py

@@ -0,0 +1,140 @@
+# main.py
+import os
+import tempfile
+
+import streamlit as st
+from files import file_uploader, url_uploader
+from question import chat_with_doc
+from brain import brain
+from langchain.embeddings.openai import OpenAIEmbeddings
+from langchain.vectorstores import SupabaseVectorStore
+from supabase import Client, create_client
+from explorer import view_document
+from stats import get_usage_today
+
+supabase_url = 'https://ktexmliefragugupzmqw.supabase.co'
+st.secrets.supabase_url = supabase_url
+
+supabase_key = 'eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJzdXBhYmFzZSIsInJlZiI6Imt0ZXhtbGllZnJhZ3VndXB6bXF3Iiwicm9sZSI6ImFub24iLCJpYXQiOjE2ODUyNjg1MjcsImV4cCI6MjAwMDg0NDUyN30.7DBDCcqelS0GNojPqv0zuvCT5vs5x2Codxyr5cDPZvU'
+st.secrets.supabase_key = supabase_key
+
+openai_api_key_head = 'sk-9utMl6JfUfgm4lRIXmK'
+openai_api_key_tail = 'bT3BlbkFJBvNXhwDz9WJrzmi5G6FP'
+openai_api_key = openai_api_key_head+openai_api_key_tail
+st.secrets.opeanai_api_key = openai_api_key
+
+st.secrets.anthropic_api_key = ""
+st.secrets.usage_limit = 1000
+anthropic_api_key = ''
+supabase: Client = create_client(supabase_url, supabase_key)
+st.secrets.self_hosted = "true"
+self_hosted = "true"
+
+embeddings = OpenAIEmbeddings(openai_api_key=openai_api_key)
+vector_store = SupabaseVectorStore(
+    supabase, embeddings, table_name="documents")
+models = ["gpt-3.5-turbo", "gpt-4"]
+if anthropic_api_key:
+    models += ["claude-v1", "claude-v1.3",
+               "claude-instant-v1-100k", "claude-instant-v1.1-100k"]
+
+# Set the theme
+st.set_page_config(
+    page_title="ColleenGPT",
+    layout="wide",
+    initial_sidebar_state="expanded",
+)
+
+st.title("🧠 ColleenGPT")
+st.markdown("ask your ledger anything.")
+if self_hosted == "false":
+    st.markdown('**📢 Note: In the public demo, access to functionality is restricted. You can only use the GPT-3.5-turbo model and upload files up to 1Mb. To use more models and upload larger files, consider self-hosting Quivr.**')
+
+st.markdown("---\n\n")
+
+st.session_state["overused"] = False
+if self_hosted == "false":
+    usage = get_usage_today(supabase)
+    if usage > st.secrets.usage_limit:
+    # if usage > 1000:
+        st.markdown(
+            f"<span style='color:red'>You have used {usage} tokens today, which is more than your daily limit of {st.secrets.usage_limit} tokens. Please come back later or consider self-hosting.</span>", unsafe_allow_html=True)
+            # f"<span style='color:red'>You have used {usage} tokens today, which is more than your daily limit of {1000} tokens. Please come back later or consider self-hosting.</span>", unsafe_allow_html = True)
+
+        st.session_state["overused"] = True
+    else:
+        st.markdown(f"<span style='color:blue'>Usage today: {usage} tokens out of {st.secrets.usage_limit}</span>", unsafe_allow_html=True)
+        # st.markdown(f"<span style='color:blue'>Usage today: {usage} tokens out of {1000}</span>", unsafe_allow_html=True)
+
+    st.write("---")
+    
+
+
+
+# Initialize session state variables
+if 'model' not in st.session_state:
+    st.session_state['model'] = "gpt-3.5-turbo"
+if 'temperature' not in st.session_state:
+    st.session_state['temperature'] = 0.0
+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'] = 256
+
+# 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")
+# st.sidebar.image('assets/Images/Vanti - Main Logo@4x copy.png')
+st.sidebar.image('assets/Images/colleen-logo.png')
+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", 0.0, 1.0, st.session_state['temperature'], 0.1)
+    if st.secrets.self_hosted != "false":
+    # if "true" != "false":
+        st.session_state['max_tokens'] = st.sidebar.slider(
+            "Select Max Tokens", 256, 2048, st.session_state['max_tokens'], 2048)
+    else:
+        st.session_state['max_tokens'] = 256
+    
+    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")

question.py

@@ -16,13 +16,9 @@ memory = ConversationBufferMemory(
 
 openai_api_key_head = 'sk-9utMl6JfUfgm4lRIXmK'
 openai_api_key_tail = 'bT3BlbkFJBvNXhwDz9WJrzmi5G6FP'
-openai_api_key = openai_api_key_head+openai_api_key_tail
+openai_api_key = openai_api_key_head + openai_api_key_tail
 anthropic_api_key = ""
 logger = get_logger(__name__)
-print('niro','niro', openai_api_key)
-
-
-
 
 
 def count_tokens(question, model):
@@ -33,12 +29,9 @@ def count_tokens(question, model):
 
 
 def chat_with_doc(model, vector_store: SupabaseVectorStore, stats_db):
-    
     if 'chat_history' not in st.session_state:
         st.session_state['chat_history'] = []
-        
-    
-    
+
     question = st.text_area("## Ask a question")
     columns = st.columns(3)
     with columns[0]:
@@ -47,9 +40,7 @@ def chat_with_doc(model, vector_store: SupabaseVectorStore, stats_db):
         count_button = st.button("Count Tokens", type='secondary')
     with columns[2]:
         clear_history = st.button("Clear History", type='secondary')
-    
-    
-    
+
     if clear_history:
         # Clear memory in Langchain
         memory.clear()
@@ -59,19 +50,24 @@ def chat_with_doc(model, vector_store: SupabaseVectorStore, stats_db):
     if button:
         qa = None
         if not st.session_state["overused"]:
-            add_usage(stats_db, "chat", "prompt" + question, {"model": model, "temperature": st.session_state['temperature']})
+            add_usage(stats_db, "chat", "prompt" + question,
+                      {"model": model, "temperature": st.session_state['temperature']})
             if model.startswith("gpt"):
                 logger.info('Using OpenAI model %s', model)
                 qa = ConversationalRetrievalChain.from_llm(
                     OpenAI(
-                        model_name=st.session_state['model'], openai_api_key=openai_api_key, temperature=st.session_state['temperature'], max_tokens=st.session_state['max_tokens']), vector_store.as_retriever(), memory=memory, verbose=True)
+                        model_name=st.session_state['model'], openai_api_key=openai_api_key,
+                        temperature=st.session_state['temperature'], max_tokens=st.session_state['max_tokens']),
+                    vector_store.as_retriever(), memory=memory, verbose=True)
             elif anthropic_api_key and model.startswith("claude"):
                 logger.info('Using Anthropics model %s', model)
                 qa = ConversationalRetrievalChain.from_llm(
                     ChatAnthropic(
-                        model=st.session_state['model'], anthropic_api_key=anthropic_api_key, temperature=st.session_state['temperature'], max_tokens_to_sample=st.session_state['max_tokens']), vector_store.as_retriever(), memory=memory, verbose=True, max_tokens_limit=102400)
-            
-            
+                        model=st.session_state['model'], anthropic_api_key=anthropic_api_key,
+                        temperature=st.session_state['temperature'],
+                        max_tokens_to_sample=st.session_state['max_tokens']), vector_store.as_retriever(),
+                    memory=memory, verbose=True, max_tokens_limit=102400)
+
             st.session_state['chat_history'].append(("You", question))
 
             # Generate model's response and add it to chat history
@@ -86,6 +82,6 @@ def chat_with_doc(model, vector_store: SupabaseVectorStore, stats_db):
                 st.markdown(f"**{speaker}:** {text}")
         else:
             st.error("You have used all your free credits. Please try again later or self host.")
-        
+
     if count_button:
         st.write(count_tokens(question, model))