Delete app1.py

app1.py

@@ -1,154 +0,0 @@
-import streamlit as st
-import os
-import requests
-from dotenv import load_dotenv  # Only needed if using a .env file
-
-# Langchain and HuggingFace
-from langchain.vectorstores import Chroma
-from langchain_community.embeddings import HuggingFaceEmbeddings
-from langchain_groq import ChatGroq
-from langchain.chains import RetrievalQA
-
-# Load the .env file (if using it)
-load_dotenv()
-groq_api_key = os.getenv("GROQ_API_KEY")
-
-# Load embeddings, model, and vector store
-@st.cache_resource  # Singleton, prevent multiple initializations
-def init_chain():
-    
-    model_kwargs = {'trust_remote_code': True}
-    embedding = HuggingFaceEmbeddings(model_name='nomic-ai/nomic-embed-text-v1.5', model_kwargs=model_kwargs)
-    llm = ChatGroq(groq_api_key=groq_api_key, model_name="llama3-70b-8192", temperature=0.2)
-    vectordb = Chroma(persist_directory='updated_CSPCDB2', embedding_function=embedding)
-
-    # Create chain
-    chain = RetrievalQA.from_chain_type(llm=llm,
-                                        chain_type="stuff",
-                                        retriever=vectordb.as_retriever(k=5),
-                                        return_source_documents=True)
-    return chain
-
-# Streamlit app layout
-st.set_page_config(
-    page_title="CSPC Citizens Charter Conversational Agent",
-    page_icon="cspclogo.png"
-)
-
-with st.sidebar:
-    st.title('CSPCean Conversational Agent')
-    st.subheader('Ask anything CSPC Related here!')
-
-    st.markdown('''**About CSPC:**
-        History, Core Values, Mission and Vision''')
-
-    st.markdown('''**Admission & Graduation:**
-        Apply, Requirements, Process, Graduation''')
-
-    st.markdown('''**Student Services:**
-         Scholarships, Orgs, Facilities''')
-
-    st.markdown('''**Academics:**
-         Degrees, Courses, Faculty''')
-
-    st.markdown('''**Officials:**
-         President, VPs, Deans, Admin''')
-
-    st.markdown('''
-        Access the resources here:
-
-        - [CSPC Citizen’s Charter](https://cspc.edu.ph/governance/citizens-charter/)
-        - [About CSPC](https://cspc.edu.ph/about/)
-        - [College Officials](https://cspc.edu.ph/college-officials/)
-    ''')
-    st.markdown('Team XceptionNet')
-
-# Store LLM generated responses
-if "messages" not in st.session_state:
-    st.session_state.chain = init_chain()
-    st.session_state.messages = [{"role": "assistant", "content": "How may I help you today?"}]
-
-# Function for generating response using the last three conversations
-def generate_response(prompt_input):
-    # Initialize result
-    result = ''
-    
-    # Prepare conversation history: get the last 3 user and assistant messages
-    conversation_history = ""
-    recent_messages = st.session_state.messages[-3:]  # Last 3 user and assistant exchanges (each exchange is 2 messages)
-
-    for message in recent_messages:
-        conversation_history += f"{message['role']}: {message['content']}\n"
-    
-    # Append the current user prompt to the conversation history
-    conversation_history += f"user: {prompt_input}\n"
-
-    # Invoke chain with the truncated conversation history
-    res = st.session_state.chain.invoke(conversation_history)
-    
-    # Process response (as in the original code)
-    if res['result'].startswith('According to the provided context, '):
-        res['result'] = res['result'][35:]
-        res['result'] = res['result'][0].upper() + res['result'][1:]
-    elif res['result'].startswith('Based on the provided context, '):
-        res['result'] = res['result'][31:]
-        res['result'] = res['result'][0].upper() + res['result'][1:]
-    elif res['result'].startswith('According to the provided text, '):
-        res['result'] = res['result'][34:]
-        res['result'] = res['result'][0].upper() + res['result'][1:]
-    elif res['result'].startswith('According to the context, '):
-        res['result'] = res['result'][26:]
-        res['result'] = res['result'][0].upper() + res['result'][1:]
-        
-    
-    # result += res['result']
-    
-    # # Process sources
-    # result += '\n\nSources: '
-    # sources = []
-    # for source in res["source_documents"]:
-    #     sources.append(source.metadata['source'][122:-4])  # Adjust as per your source format
-
-    # sources = list(set(sources))  # Remove duplicates
-    # source_list = ", ".join(sources)
-    
-    # result += source_list
-
-    # return result, res['result'], source_list
-    # return result, res['result']
-    return res['result']
-
-# Display chat messages
-for message in st.session_state.messages:
-    with st.chat_message(message["role"]):
-        st.write(message["content"])
-
-# User-provided prompt for input box
-if prompt := st.chat_input(placeholder="Ask a question..."):
-    # Append user query to session state
-    st.session_state.messages.append({"role": "user", "content": prompt})
-    with st.chat_message("user"):
-        st.write(prompt)
-
-    # Generate and display placeholder for assistant response
-    with st.chat_message("assistant"):
-        message_placeholder = st.empty()  # Placeholder for response while it's being generated
-        with st.spinner("Generating response..."):
-            # Use conversation history when generating response
-            response = generate_response(prompt)
-        message_placeholder.markdown(response)  # Replace placeholder with actual response
-        st.session_state.messages.append({"role": "assistant", "content": response})
-
-# Clear chat history function
-def clear_chat_history():
-    # Clear chat messages (reset the assistant greeting)
-    st.session_state.messages = [{"role": "assistant", "content": "How may I help you today?"}]
-    
-    # Reinitialize the chain to clear any stored history (ensures it forgets previous user inputs)
-    st.session_state.chain = init_chain()
-
-    # Clear any additional session state that might be remembering user inquiries
-    if "recent_user_messages" in st.session_state:
-        del st.session_state["recent_user_messages"]  # Clear remembered user inputs
-
-st.sidebar.button('Clear Chat History', on_click=clear_chat_history)