app.py

import warnings
warnings.simplefilter(action='ignore', category=FutureWarning)

import PyPDF2
import gradio as gr
from langchain.prompts import PromptTemplate
from langchain.chains.summarize import load_summarize_chain
from langchain_core.documents import Document
from pathlib import Path
from langchain_huggingface import ChatHuggingFace, HuggingFaceEndpoint

llm = HuggingFaceEndpoint(
    repo_id="mistralai/Mistral-7B-Instruct-v0.3",
    task="text-generation",
    max_new_tokens=4096,
    temperature=0.5,
    do_sample=False,
)
llm_engine_hf = ChatHuggingFace(llm=llm)

def read_pdf(file_path):
    pdf_reader = PyPDF2.PdfReader(file_path)
    text = ""
    for page in range(len(pdf_reader.pages)):
        text += pdf_reader.pages[page].extract_text()
    return text
    
def summarize(file, n_words):
    # Read the content of the uploaded file
    file_path = file.name
    if file_path.endswith('.pdf'):
        text = read_pdf(file_path)
    else:
        with open(file_path, 'r', encoding='utf-8') as f:
            text = f.read()
            
    template = '''
    You are a commentator. Your task is to write a report on an essay.
When presented with the essay, come up with interesting questions to ask, and answer each question.
Afterward, combine all the information and write a report in the markdown format.

# Essay:
{TEXT}

# Instructions:
## Summarize:
In clear and concise language, summarize the key points and themes presented in the essay.

## Interesting Questions:
Generate three distinct and thought-provoking questions that can be asked about the content of the essay. For each question:
- After "Q: ", describe the problem
- After "A: ", provide a detailed explanation of the problem addressed in the question.
- Enclose the ultimate answer in <>.

## Write a report
Using the essay summary and the answers to the interesting questions, create a comprehensive report in Markdown format.
    '''
    
    prompt = PromptTemplate(
        template=template,
        input_variables=['TEXT']    
    )
    
    summary = ""
    while len(summary.split()) < 100:
        formatted_prompt = prompt.format(TEXT=text)
        output_summary = llm_engine_hf.invoke(formatted_prompt)
        summary = output_summary.content
    return summary

def download_summary(output_text):
    if output_text:
        file_path = Path('summary.txt')
        with open(file_path, 'w', encoding='utf-8') as f:
            f.write(output_text)
        return file_path
    else:
        return None
def create_download_file(summary_text):
    file_path = download_summary(summary_text)
    return str(file_path) if file_path else None

# Create the Gradio interface
with gr.Blocks() as demo:
    gr.Markdown("## Document Summarizer")

    with gr.Row():
        with gr.Column():
            file = gr.File(label="Submit a file")
        
        with gr.Column():
            output_text = gr.Textbox(label="Summary", lines=20)

    submit_button = gr.Button("Summarize")
    submit_button.click(summarize, inputs=[file], outputs=output_text)

    def generate_file():
        summary_text = output_text
        file_path = download_summary(summary_text)
        return file_path

    download_button = gr.Button("Download Summary")
    download_button.click(
        fn=create_download_file,
        inputs=[output_text],
        outputs=gr.File()
    )
# Run the Gradio app
demo.launch(share=True)