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AbdallaouiMed
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Delete ask-multiple-pdfs-main
Browse files- ask-multiple-pdfs-main/.DS_Store +0 -0
- ask-multiple-pdfs-main/.gitignore +0 -160
- ask-multiple-pdfs-main/Pipfile +0 -19
- ask-multiple-pdfs-main/Pipfile.lock +0 -0
- ask-multiple-pdfs-main/__pycache__/htmlTemplates.cpython-39.pyc +0 -0
- ask-multiple-pdfs-main/app.py +0 -105
- ask-multiple-pdfs-main/htmlTemplates.py +0 -44
ask-multiple-pdfs-main/.DS_Store
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ask-multiple-pdfs-main/.gitignore
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# Byte-compiled / optimized / DLL files
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__pycache__/
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#pdm.lock
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# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
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# https://pdm.fming.dev/#use-with-ide
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__pypackages__/
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ask-multiple-pdfs-main/Pipfile
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[[source]]
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url = "https://pypi.org/simple"
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verify_ssl = true
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name = "pypi"
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[packages]
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langchain = "*"
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pypdf2 = "==3.0.1"
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python-dotenv = "==1.0.0"
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streamlit = "==1.18.1"
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openai = "==0.27.6"
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faiss-cpu = "==1.7.4"
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altair = "==4"
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tiktoken = "==0.4.0"
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[dev-packages]
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python_version = "3.10"
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ask-multiple-pdfs-main/Pipfile.lock
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See raw diff
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ask-multiple-pdfs-main/__pycache__/htmlTemplates.cpython-39.pyc
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ask-multiple-pdfs-main/app.py
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import streamlit as st
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from dotenv import load_dotenv
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from PyPDF2 import PdfReader
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from langchain.text_splitter import CharacterTextSplitter
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from langchain.embeddings import OpenAIEmbeddings, HuggingFaceEmbeddings
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from langchain.vectorstores import FAISS
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from langchain.chat_models import ChatOpenAI
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from langchain.memory import ConversationBufferMemory
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from langchain.chains import ConversationalRetrievalChain
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from htmlTemplates import css, bot_template, user_template
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from langchain.llms import HuggingFaceHub
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def get_pdf_text(pdf_docs):
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text = ""
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for pdf in pdf_docs:
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pdf_reader = PdfReader(pdf)
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for page in pdf_reader.pages:
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text += page.extract_text()
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return text
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def get_text_chunks(text):
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text_splitter = CharacterTextSplitter(
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separator="\n",
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chunk_overlap=200,
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length_function=len
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chunks = text_splitter.split_text(text)
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return chunks
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def get_vectorstore(text_chunks):
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# embeddings = OpenAIEmbeddings()
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embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-mpnet-base-v2")
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vectorstore = FAISS.from_texts(texts=text_chunks, embedding=embeddings)
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return vectorstore
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def get_conversation_chain(vectorstore):
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# llm = ChatOpenAI()
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llm = HuggingFaceHub(repo_id="HuggingFaceH4/zephyr-7b-beta", model_kwargs={"temperature":0.5, "max_length":512})
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memory = ConversationBufferMemory(
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memory_key='chat_history', return_messages=True)
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conversation_chain = ConversationalRetrievalChain.from_llm(
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llm=llm,
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retriever=vectorstore.as_retriever(),
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memory=memory
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)
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return conversation_chain
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def handle_userinput(user_question):
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response = st.session_state.conversation({'question': user_question})
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for i, message in enumerate(st.session_state.chat_history):
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if i % 2 == 0:
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st.write(user_template.replace(
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"{{MSG}}", message.content), unsafe_allow_html=True)
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else:
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st.write(bot_template.replace(
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"{{MSG}}", message.content), unsafe_allow_html=True)
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def main():
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load_dotenv()
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st.set_page_config(page_title="Chat with multiple PDFs",
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page_icon=":books:")
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st.write(css, unsafe_allow_html=True)
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if "conversation" not in st.session_state:
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st.session_state.conversation = None
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if "chat_history" not in st.session_state:
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st.session_state.chat_history = None
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st.header("Chat with multiple PDFs :books:")
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user_question = st.text_input("Ask a question about your documents:")
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if user_question:
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handle_userinput(user_question)
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with st.sidebar:
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st.subheader("Your documents")
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pdf_docs = st.file_uploader(
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"Upload your PDFs here and click on 'Process'", accept_multiple_files=True)
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if st.button("Process"):
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with st.spinner("Processing"):
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# get pdf text
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raw_text = get_pdf_text(pdf_docs)
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# get the text chunks
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text_chunks = get_text_chunks(raw_text)
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# create vector store
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vectorstore = get_vectorstore(text_chunks)
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# create conversation chain
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st.session_state.conversation = get_conversation_chain(
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vectorstore)
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st.write("Processed Successfuly")
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if __name__ == '__main__':
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main()
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ask-multiple-pdfs-main/htmlTemplates.py
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css = '''
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<style>
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.chat-message {
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padding: 1.5rem; border-radius: 0.5rem; margin-bottom: 1rem; display: flex
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}
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.chat-message.user {
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background-color: #2b313e
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}
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.chat-message.bot {
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background-color: #475063
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}
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.chat-message .avatar {
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width: 20%;
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}
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.chat-message .avatar img {
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max-width: 78px;
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max-height: 78px;
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border-radius: 50%;
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object-fit: cover;
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}
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.chat-message .message {
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width: 80%;
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padding: 0 1.5rem;
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color: #fff;
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}
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'''
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bot_template = '''
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<div class="chat-message bot">
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<div class="avatar">
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<img src="/Users/mohamedabdallaoui/Desktop/ayoub_bot.png">
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</div>
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<div class="message">{{MSG}}</div>
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</div>
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'''
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user_template = '''
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<div class="chat-message user">
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<div class="avatar">
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<img src="/Users/mohamedabdallaoui/Desktop/mohamed_bot.png">
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</div>
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<div class="message">{{MSG}}</div>
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</div>
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'''
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