import warnings warnings.simplefilter(action='ignore', category=FutureWarning) import PyPDF2 import gradio as gr from langchain.prompts import PromptTemplate from pathlib import Path from langchain_huggingface import ChatHuggingFace, HuggingFaceEndpoint from langchain_core.output_parsers import JsonOutputParser 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): global llm # 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_detect = ''' Please carefully read the following document: {TEXT} identify the MOST used language in the document, return detected language in json format with key "language" and value is the detected language ''' prompt_detect = PromptTemplate( template=template_detect, input_variables=['TEXT'] ) language_detect = prompt_detect | llm | JsonOutputParser() formatted_prompt = prompt_detect.format(TEXT=text) language = language_detect.invoke(formatted_prompt) lang = language["language"] template_translate = ''' Please carefully read the following document: {TEXT} After reading through the document, pinpoint the key points and main ideas covered in the text. Organize these key points into a concise bulleted list that summarizes the essential information from the document. The summary should be in {LANG} language. ''' prompt_summarize = PromptTemplate( template=template_translate, input_variables=["TEXT", "LANG"] ) formatted_prompt = prompt_summarize.format(TEXT=text, LANG=lang) summary = llm.invoke(formatted_prompt) 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)