Create app.py

app.py

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