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app1.py

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+from dotenv import load_dotenv
+import streamlit as st
+from langchain.chains import RetrievalQA
+from langchain.llms import HuggingFaceHub
+from langchain.vectorstores import Qdrant
+from langchain.embeddings import HuggingFaceInstructEmbeddings
+import qdrant_client
+import os
+from langchain.memory import ConversationBufferMemory
+from langchain.chains import ConversationalRetrievalChain
+from htmlTemplates import css, user_template, bot_template
+
+def get_vector_store():
+    
+    client = qdrant_client.QdrantClient(
+        os.getenv("QDRANT_HOST"),
+        api_key=os.getenv("QDRANT_API_KEY")
+    )
+    
+    embeddings =HuggingFaceInstructEmbeddings(model_name = "hkunlp/instructor-xl")
+
+    vector_store = Qdrant(
+        client=client, 
+        collection_name="penalCode", 
+        embeddings=embeddings,
+    )
+    
+    return vector_store
+
+def get_conversation_chain(vectorstore):
+    #llm = ChatOpenAI()
+    llm = HuggingFaceHub( repo_id="google/flan-t5-xxl", model_kwargs={"temperature":0.5, "max_length":512})
+    memory = ConversationBufferMemory(memory_key='chat_history', return_messages=True)
+    conversation_chain = ConversationalRetrievalChain.from_llm(
+            llm =llm,
+            retriever=vectorstore.as_retriever(),
+            memory=memory
+    )
+    return conversation_chain
+
+def handle_userinput(user_question):
+    response = st.session_state.conversation({'question':user_question})
+    st.write(response)
+
+
+def main():
+    load_dotenv()
+    
+    st.set_page_config(page_title="PDF Assistant", page_icon=":books:")
+    st.write(css, unsafe_allow_html=True)
+    st.header("Is that legal?")
+    
+    if "conversation" not in st.session_state:
+        st.session_state.conversation = None
+    # create vector store
+    vector_store = get_vector_store()
+    
+    if st.button("Start!"):
+        with st.spinner("Processing"):
+            st.session_state.conversation = get_conversation_chain(vector_store)
+        user_question = st.text_input("Ask your questions here:")
+        
+        if user_question:
+            handle_userinput(user_question)
+    
+        st.write(user_template.replace("{{MSG}}","Hello Bot"), unsafe_allow_html=True)
+        st.write(bot_template.replace("{{MSG}}","Hello Bot"), unsafe_allow_html=True)
+    
+    
+        
+if __name__ == '__main__':
+    main()

htmlTemplates.py

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+css = '''
+<style>
+.chat-message {
+    padding: 1.5rem; border-radius: 0.5rem; margin-bottom: 1rem; display: flex
+}
+.chat-message.user {
+    background-color: #2b313e
+}
+.chat-message.bot {
+    background-color: #475063
+}
+.chat-message .avatar {
+  width: 20%;
+}
+.chat-message .avatar img {
+  max-width: 78px;
+  max-height: 78px;
+  border-radius: 50%;
+  object-fit: cover;
+}
+.chat-message .message {
+  width: 80%;
+  padding: 0 1.5rem;
+  color: #fff;
+}
+'''
+
+bot_template = '''
+<div class="chat-message bot">
+    <div class="avatar">
+        <img src="https://i.ibb.co/cN0nmSj/Screenshot-2023-05-28-at-02-37-21.png" style="max-height: 78px; max-width: 78px; border-radius: 50%; object-fit: cover;">
+    </div>
+    <div class="message">{{MSG}}</div>
+</div>
+'''
+
+user_template = '''
+<div class="chat-message user">
+    <div class="avatar">
+        <img src="https://i.ibb.co/rdZC7LZ/Photo-logo-1.png">
+    </div>    
+    <div class="message">{{MSG}}</div>
+</div>
+'''