Adding files

app.py

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+import streamlit as st
+from langchain.agents import initialize_agent, AgentType, Tool
+from langchain.chains import LLMMathChain, RetrievalQA
+from langchain.chat_models import ChatOpenAI
+from langchain.embeddings import OpenAIEmbeddings
+from langchain.text_splitter import CharacterTextSplitter
+from langchain.utilities import SQLDatabase
+from langchain.vectorstores import FAISS
+from langchain_experimental.sql import SQLDatabaseChain
+from langchain.document_loaders import PyPDFLoader
+from langchain.schema import ChatMessage
+from langchain.callbacks.manager import CallbackManager
+from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
+
+
+# Dummy users and passwords
+USERS = {
+    "johndoe": {"password": "Streamlit@12", "username": "John Doe"},
+    "janesmith": {"password": "Streamlit@12", "username": "Jane Smith"}
+}
+
+# Initialize the system
+llm = ChatOpenAI(temperature=0, model="gpt-3.5-turbo-0613")
+llm_math_chain = LLMMathChain.from_llm(llm=llm, verbose=True)
+db = SQLDatabase.from_uri("sqlite:///utilities_monthly.db")
+db_chain = SQLDatabaseChain.from_llm(llm, db, verbose=True)
+pdf_loader = PyPDFLoader("sewa.pdf")
+pages = pdf_loader.load_and_split()
+text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
+docs = text_splitter.split_documents(pages)
+embeddings = OpenAIEmbeddings()
+retriever = FAISS.from_documents(docs, embeddings).as_retriever()
+
+tools = [
+    Tool(
+        name="FAQ",
+        func=RetrievalQA.from_chain_type(llm=llm, retriever=retriever),
+        description="Useful for answering generic questions related to SEWA, bill, usage, etc."
+    ),
+    Tool(
+        name="Electricity-DB",
+        func=db_chain.run,
+        description="Useful for answering questions about Customer Energy Usage.Plase use this username given in the prompt Input should be in the form of a question containing full context"
+    )
+]
+callback_manager = CallbackManager([StreamingStdOutCallbackHandler()])
+agent_executor = initialize_agent(tools, llm, agent=AgentType.OPENAI_FUNCTIONS, verbose=True,
+                                  callback_manager=callback_manager)
+# Styling for sidebar
+# Set the secondary text color
+st.markdown("""
+    <style>
+        .stApp > div > div > div > div:first-child {
+            background-color: blue;
+        }
+    </style>
+    """, unsafe_allow_html=True)
+
+
+
+with st.sidebar:
+    if "logged_in_user" not in st.session_state:
+        st.session_state["logged_in_user"] = None
+
+    if st.session_state["logged_in_user"]:
+        user_data = st.session_state["logged_in_user"]
+        st.title(f"Welcome {user_data['username']}!")
+
+        st.write("You can ask about energy usage, bill, due date, etc..")
+        # col1, col2, col3 = st.columns([1,18,1])
+
+        if st.button("Log Out"):
+            st.session_state["logged_in_user"] = None
+            st.session_state["messages"] = [ChatMessage(role="assistant", content="How can I help you?")]  # Reset chat history
+            st.experimental_rerun()  # Refresh the page to show the login options again
+    else:
+        st.title("SEWA - At your service")
+        user_id = st.text_input("User ID")
+        password = st.text_input("Password", type="password")
+        if st.button("Login"):
+            if user_id in USERS and USERS[user_id]['password'] == password:
+                st.session_state["logged_in_user"] = USERS[user_id]
+                st.success(f"Logged in as {USERS[user_id]['username']}!")
+                st.experimental_rerun()  # Refresh the page immediately after a successful login
+            else:
+                st.error("Invalid user ID or password")
+# Chat Interface
+if "messages" not in st.session_state:
+    st.session_state["messages"] = [ChatMessage(role="assistant", content="How can I help you?")]
+
+for msg in st.session_state.messages:
+    st.chat_message(msg.role).write(msg.content)
+
+if prompt := st.chat_input():
+    # If the user is logged in, replace "my" with the user's name.
+
+
+    st.session_state.messages.append(ChatMessage(role="user", content=prompt))
+    st.chat_message("user").write(prompt)
+    if st.session_state["logged_in_user"]:
+        user_name = st.session_state["logged_in_user"]["username"]
+        prompt = prompt.replace("my", user_name)
+    response = agent_executor.invoke({"input": prompt})
+    st.session_state.messages.append(ChatMessage(role="assistant", content=response['output']))
+    st.chat_message("assistant").write(response['output'])

requirements.txt

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+streamlit
+langchain
+langchain_experimental