Create app.py

app.py

@@ -0,0 +1,44 @@
+import os
+import openai
+import sys
+
+import gradio as gr
+from langchain import OpenAI, PromptTemplate
+from langchain.text_splitter import CharacterTextSplitter
+from langchain.chains.summarize import load_summarize_chain
+from langchain.document_loaders import PyPDFLoader
+from langchain.chains import RetrievalQA
+
+sys.path.append('../..')
+
+from dotenv import load_dotenv, find_dotenv
+_ = load_dotenv(find_dotenv()) # read local .env file
+
+openai.api_key  = os.environ['OPENAI_API_KEY']
+
+llm = OpenAI(temperature=0)
+text_splitter = CharacterTextSplitter()
+
+def summarize_pdf(pdf_file_path, custom_prompt=""):
+    pdf_file_path = pdf_file_path.name
+    loader = PyPDFLoader(pdf_file_path)
+    docs = loader.load_and_split()
+    chain = load_summarize_chain(llm, chain_type="map_reduce")
+    summary = chain.run(docs)
+    return summary
+
+def main():
+    output_summary = gr.Textbox(label="Summary")
+
+    iface = gr.Interface(
+        fn=summarize_pdf,
+        inputs=["file"],
+        outputs=[output_summary],
+        title="PDF Summarizer",
+        description="Langchain based summarization application that's given a PDF file or a text from a text box can then create a summary of the text content. <br> Enter the PDF file and get its summary.",
+    )
+
+    iface.launch()
+
+if __name__ == "__main__":
+    main()