Create app.py

app.py

@@ -0,0 +1,96 @@
+import streamlit as st
+from dotenv import load_dotenv
+from PyPDF2 import PdfReader
+import langchain
+from htmlTemplates import css,bot_template,user_template,url,aiLogoUrl
+
+
+def get_pdf_text(pdf_docs):
+    text = ""
+    for pdf in pdf_docs:
+        pdfReader = PdfReader(pdf)
+        for Page in pdfReader.pages:
+            text += Page.extract_text()
+    return text
+
+def get_text_chunks(text):
+    text_splitter = langchain.text_splitter.CharacterTextSplitter(
+        separator="\n",
+        chunk_size=1000,
+        chunk_overlap=200,
+        length_function=len
+    )
+    chunks = text_splitter.split_text(text)
+    return chunks
+
+def get_vectorstore(text_chunks):
+    embeddings = langchain.embeddings.CohereEmbeddings()
+    vectorstore = langchain.vectorstores.FAISS.from_texts(texts=text_chunks,embedding=embeddings)
+    return vectorstore
+
+
+def get_conversation_chain(vectorstore):
+    llm = langchain.llms.Cohere()
+    memory = langchain.memory.ConversationBufferMemory(memory_key = 'chat_history',return_messages=True)
+    conversation_chain = langchain.chains.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.session_state.chat_history = response['chat_history']
+
+    for i,message in enumerate(st.session_state.chat_history):
+        if i % 2 == 0:
+            st.write(user_template.replace("{{MSG}}",message.content), unsafe_allow_html=True)
+        else:
+            st.write(bot_template.replace("{{MSG}}", message.content), unsafe_allow_html=True)
+
+def main():
+    load_dotenv()
+    st.set_page_config(page_title="Chat with multiple pdfs", page_icon=":books:")
+    st.write(css,unsafe_allow_html=True)
+    st.markdown(
+        '<div class="logo-container"><img class="logo" src="' + url + '" /><img class="logo" src="' + aiLogoUrl + '" /></div>',
+        unsafe_allow_html=True)
+
+
+    if "conversation" not in st.session_state:
+        st.session_state.conversation = None
+
+    if "chat_history" not in st.session_state:
+        st.session_state.chat_history = None
+
+
+
+    st.header("Chat with multiple pdfs :books:")
+    user_question = st.text_input("Ask a question about your documents:")
+
+    if user_question:
+        handle_userinput(user_question)
+
+
+    with st.sidebar:
+        st.subheader("Your documents")
+        pdf_docs=st.file_uploader("Upload your files here and click process",accept_multiple_files=True)
+        if st.button("Process"):
+            with st.spinner("Processing"):
+                # get pdf text
+                raw_text = get_pdf_text(pdf_docs)
+
+                # get the text chunks
+                text_chunks = get_text_chunks(raw_text)
+
+                # create vector store
+                vectorstore = get_vectorstore(text_chunks)
+
+                # create conversation chai
+
+                st.session_state.conversation = get_conversation_chain(vectorstore)
+
+if __name__=='__main__':
+    main()