Update app.py
Browse files
app.py
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if __name__ == "__main__":
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import streamlit as st
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from PyPDF2 import PdfReader
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from langchain.text_splitter import RecursiveCharacterTextSplitter
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import os
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from langchain_google_genai import GoogleGenerativeAIEmbeddings
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import google.generativeai as genai
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from langchain.vectorstores import FAISS
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from langchain_google_genai import ChatGoogleGenerativeAI
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from langchain.chains.question_answering import load_qa_chain
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from langchain.prompts import PromptTemplate
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from dotenv import load_dotenv
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load_dotenv()
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os.getenv("GOOGLE_API_KEY")
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genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
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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 = RecursiveCharacterTextSplitter(chunk_size=10000, chunk_overlap=1000)
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chunks = text_splitter.split_text(text)
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return chunks
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def get_vector_store(text_chunks):
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embeddings = GoogleGenerativeAIEmbeddings(model = "models/embedding-001")
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vector_store = FAISS.from_texts(text_chunks, embedding=embeddings)
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vector_store.save_local("faiss_index")
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def get_conversational_chain():
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prompt_template = """
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Answer the question as detailed as possible from the provided context, make sure to provide all the details, if the answer is not in
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provided context just say, "answer is not available in the context", don't provide the wrong answer\n\n
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Context:\n {context}?\n
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Question: \n{question}\n
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Answer:
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"""
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model = ChatGoogleGenerativeAI(model="gemini-pro",
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temperature=0.3)
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prompt = PromptTemplate(template = prompt_template, input_variables = ["context", "question"])
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chain = load_qa_chain(model, chain_type="stuff", prompt=prompt)
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return chain
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def user_input(user_question):
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embeddings = GoogleGenerativeAIEmbeddings(model = "models/embedding-001")
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new_db = FAISS.load_local("faiss_index", embeddings)
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docs = new_db.similarity_search(user_question)
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chain = get_conversational_chain()
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response = chain(
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{"input_documents":docs, "question": user_question}
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, return_only_outputs=True)
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print(response)
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st.write("Reply: ", response["output_text"])
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def main():
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st.set_page_config("Chat PDF")
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st.header("Gemini-Powered-MultiPDF-Chatbot")
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user_question = st.text_input("Ask a Question from the PDF Files")
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if user_question:
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user_input(user_question)
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with st.sidebar:
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st.title("Menu:")
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pdf_docs = st.file_uploader("Upload your PDF Files and Click on the Submit & Process Button", accept_multiple_files=True)
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if st.button("Submit & Process"):
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with st.spinner("Processing..."):
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raw_text = get_pdf_text(pdf_docs)
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text_chunks = get_text_chunks(raw_text)
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get_vector_store(text_chunks)
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st.success("Done")
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if __name__ == "__main__":
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main()
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def set_bg_from_url(url, opacity=1):
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footer = """
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<link href="https://cdn.jsdelivr.net/npm/bootstrap@5.2.0/dist/css/bootstrap.min.css" rel="stylesheet" integrity="sha384-gH2yIJqKdNHPEq0n4Mqa/HGKIhSkIHeL5AyhkYV8i59U5AR6csBvApHHNl/vI1Bx" crossorigin="anonymous">
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<footer>
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<div style='visibility: visible;margin-top:7rem;justify-content:center;display:flex;'>
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<p style="font-size:1.1rem;">
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Made by Mohamed Shaad
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<a href="https://www.linkedin.com/in/mohamedshaad">
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<svg xmlns="http://www.w3.org/2000/svg" width="23" height="23" fill="white" class="bi bi-linkedin" viewBox="0 0 16 16">
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<path d="M0 1.146C0 .513.526 0 1.175 0h13.65C15.474 0 16 .513 16 1.146v13.708c0 .633-.526 1.146-1.175 1.146H1.175C.526 16 0 15.487 0 14.854V1.146zm4.943 12.248V6.169H2.542v7.225h2.401zm-1.2-8.212c.837 0 1.358-.554 1.358-1.248-.015-.709-.52-1.248-1.342-1.248-.822 0-1.359.54-1.359 1.248 0 .694.521 1.248 1.327 1.248h.016zm4.908 8.212V9.359c0-.216.016-.432.08-.586.173-.431.568-.878 1.232-.878.869 0 1.216.662 1.216 1.634v3.865h2.401V9.25c0-2.22-1.184-3.252-2.764-3.252-1.274 0-1.845.7-2.165 1.193v.025h-.016a5.54 5.54 0 0 1 .016-.025V6.169h-2.4c.03.678 0 7.225 0 7.225h2.4z"/>
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</svg>
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</a>
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<a href="https://github.com/shaadclt">
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<svg xmlns="http://www.w3.org/2000/svg" width="23" height="23" fill="white" class="bi bi-github" viewBox="0 0 16 16">
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<path d="M8 0C3.58 0 0 3.58 0 8c0 3.54 2.29 6.53 5.47 7.59.4.07.55-.17.55-.38 0-.19-.01-.82-.01-1.49-2.01.37-2.53-.49-2.69-.94-.09-.23-.48-.94-.82-1.13-.28-.15-.68-.52-.01-.53.63-.01 1.08.58 1.23.82.72 1.21 1.87.87 2.33.66.07-.52.28-.87.51-1.07-1.78-.2-3.64-.89-3.64-3.95 0-.87.31-1.59.82-2.15-.08-.2-.36-1.02.08-2.12 0 0 .67-.21 2.2.82.64-.18 1.32-.27 2-.27.68 0 1.36.09 2 .27 1.53-1.04 2.2-.82 2.2-.82.44 1.1.16 1.92.08 2.12.51.56.82 1.27.82 2.15 0 3.07-1.87 3.75-3.65 3.95.29.25.54.73.54 1.48 0 1.07-.01 1.93-.01 2.2 0 .21.15.46.55.38A8.012 8.012 0 0 0 16 8c0-4.42-3.58-8-8-8z"/>
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</svg>
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</a>
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</p>
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</div>
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</footer>
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"""
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st.markdown(footer, unsafe_allow_html=True)
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# Set background image using HTML and CSS
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st.markdown(
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f"""
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<style>
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body {{
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background: url('{url}') no-repeat center center fixed;
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background-size: cover;
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opacity: {opacity};
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}}
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</style>
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""",
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unsafe_allow_html=True
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)
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# Set background image from URL
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set_bg_from_url("https://images.crunchbase.com/image/upload/c_pad,f_auto,q_auto:eco,dpr_1/awj1xai1s7tvk7zprgvh", opacity=0.875)
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