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Create app.py
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app.py
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import os
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import gradio as gr
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from langchain.document_loaders import PyPDFLoader
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from langchain.llms import OpenAI
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from langchain.chains import load_qa_chain
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from langchain.chains.combine_documents import create_stuff_documents_chain
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from langchain_core.prompts import ChatPromptTemplate
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from langchain.text_splitter import RecursiveCharacterTextSplitter
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# Setup OpenAI API key (replace with your OpenAI API key)
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openai.api_key = os.getenv("OPENAI_API_KEY")
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# Initialize GPT-4o-mini model
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llm = OpenAI(model_name="gpt-4o-mini")
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# Function to load PDF document
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def load_pdf(file):
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loader = PyPDFLoader(file.name)
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documents = loader.load()
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return documents
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# Summarization using the "stuff" method
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def summarize_pdf(file):
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docs = load_pdf(file)
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# Define a prompt for summarization
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prompt = ChatPromptTemplate.from_messages([("system", "Write a concise summary of the following:\n\n{context}")])
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# Create summarization chain
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chain = create_stuff_documents_chain(llm, prompt)
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summary = chain.invoke({"context": docs})
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return summary['result']
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# Question Answering on PDF
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def qa_on_pdf(file, question):
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docs = load_pdf(file)
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# Create QA chain
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qa_chain = load_qa_chain(llm)
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response = qa_chain.run({"input_documents": docs, "question": question})
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return response
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# Gradio interface
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def create_interface():
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# Define the interface components
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with gr.Blocks() as interface:
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gr.Markdown("# Research Paper Summarization and QA")
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with gr.Row():
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with gr.Column():
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pdf_file = gr.File(label="Upload Research Paper PDF")
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summarize_btn = gr.Button("Summarize PDF")
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summary_output = gr.Textbox(label="Summary", lines=10)
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summarize_btn.click(summarize_pdf, inputs=[pdf_file], outputs=[summary_output])
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with gr.Column():
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qa_question = gr.Textbox(label="Ask a Question about the PDF", placeholder="Type your question here...")
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qa_btn = gr.Button("Submit Question")
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qa_output = gr.Textbox(label="Answer", lines=10)
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qa_btn.click(qa_on_pdf, inputs=[pdf_file, qa_question], outputs=[qa_output])
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return interface
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# Launch Gradio app
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interface = create_interface()
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interface.launch()
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