Update app.py

app.py

@@ -1,125 +1,29 @@
-import streamlit as st
-import pandas as pd
-import numpy as np
-from wordcloud import WordCloud, STOPWORDS
-import matplotlib.pyplot as plt
+from flask import Flask, request, jsonify
+from io import BytesIO
+from PIL import Image
 import PyPDF2
 from docx import Document
-import plotly.express as px
-import base64
-from io import BytesIO
-
-# Functions for file reading
-def read_txt(file):
-    return file.getvalue().decode("utf-8")
-
-def read_docx(file):
-    doc = Document(file)
-    return " ".join([para.text for para in doc.paragraphs])
-
-def read_pdf(file):
-    pdf = PyPDF2.PdfReader(file)
-    return " ".join([page.extract_text() for page in pdf.pages])
-
-# Function to filter out stopwords
-def filter_stopwords(text, additional_stopwords=[]):
-    words = text.split()
-    all_stopwords = STOPWORDS.union(set(additional_stopwords))
-    filtered_words = [word for word in words if word.lower() not in all_stopwords]
-    return " ".join(filtered_words)
-
-# Function to create download link for plot
-def get_image_download_link(buffered, format_):
-    image_base64 = base64.b64encode(buffered.getvalue()).decode()
-    return f'<a href="data:image/{format_};base64,{image_base64}" download="wordcloud.{format_}">Download Plot as {format_}</a>'
-
-# Function to generate a download link for a DataFrame
-def get_table_download_link(df, filename, file_label):
-    csv = df.to_csv(index=False)
-    b64 = base64.b64encode(csv.encode()).decode()
-    return f'<a href="data:file/csv;base64,{b64}" download="{filename}">{file_label}</a>'
-
-# Streamlit code
-st.title("Word Cloud Generator")
-st.subheader("📁 Upload a pdf, docx or text file to generate a word cloud")
-
-uploaded_file = st.file_uploader("Choose a file", type=["txt", "pdf", "docx"])
-st.set_option('deprecation.showPyplotGlobalUse', False)
-
-if uploaded_file:
-    file_details = {"FileName": uploaded_file.name, "FileType": uploaded_file.type, "FileSize": uploaded_file.size}
-    st.write(file_details)
-
-    # Check the file type and read the file
-    if uploaded_file.type == "text/plain":
-        text = read_txt(uploaded_file)
-    elif uploaded_file.type == "application/pdf":
-        text = read_pdf(uploaded_file)
-    elif uploaded_file.type == "application/vnd.openxmlformats-officedocument.wordprocessingml.document":
-        text = read_docx(uploaded_file)
-    else:
-        st.error("File type not supported. Please upload a txt, pdf or docx file.")
-        st.stop()
-
-    # Generate word count table
-    words = text.split()
-    word_count = pd.DataFrame({'Word': words}).groupby('Word').size().reset_index(name='Count').sort_values('Count', ascending=False)
-
-    # Sidebar: Checkbox and Multiselect box for stopwords
-    use_standard_stopwords = st.sidebar.checkbox("Use standard stopwords?", True)
-    top_words = word_count['Word'].head(50).tolist()
-    additional_stopwords = st.sidebar.multiselect("Additional stopwords:", sorted(top_words))
-
-    if use_standard_stopwords:
-        all_stopwords = STOPWORDS.union(set(additional_stopwords))
-    else:
-        all_stopwords = set(additional_stopwords)
-
-    text = filter_stopwords(text, all_stopwords)
-
-    if text:
-        # Word Cloud dimensions
-        width = st.sidebar.slider("Select Word Cloud Width", 400, 2000, 1200, 50)
-        height = st.sidebar.slider("Select Word Cloud Height", 200, 2000, 800, 50)
-
-        # Generate wordcloud
-        st.subheader("Generated Word Cloud")
-        fig, ax = plt.subplots(figsize=(width/100, height/100))  # Convert pixels to inches for figsize
-        wordcloud_img = WordCloud(width=width, height=height, background_color='white', max_words=200, contour_width=3, contour_color='steelblue').generate(text)
-        ax.imshow(wordcloud_img, interpolation='bilinear')
-        ax.axis('off')
-
-        # Save plot functionality
-        format_ = st.selectbox("Select file format to save the plot", ["png", "jpeg", "svg", "pdf"])
-        resolution = st.slider("Select Resolution", 100, 500, 300, 50)
-        # Generate word count table
-        st.subheader("Word Count Table")
-        words = text.split()
-        word_count = pd.DataFrame({'Word': words}).groupby('Word').size().reset_index(name='Count').sort_values('Count', ascending=False)
-        st.write(word_count)
-    st.pyplot(fig)
-    if st.button(f"Save as {format_}"):
-        buffered = BytesIO()
-        plt.savefig(buffered, format=format_, dpi=resolution)
-        st.markdown(get_image_download_link(buffered, format_), unsafe_allow_html=True)
-
+from wordcloud import WordCloud, STOPWORDS
 
-    # Word count table at the end
-    st.sidebar.markdown("---")
-    st.sidebar.subheader("Learn Advanced AI| Hope to Skill with Irfan Malik")
-    # add a youtube video
-    st.sidebar.video("https://www.youtube.com/watch?v=vCKF1vYVNTs&list=PLxf3-FrL8GzRALeq_9BtdQclN6SF4bTCG")
-    st.sidebar.markdown("---")
-    # add author name and info
-    st.sidebar.markdown("Created by: [Virtual Student](https://github.com/dashboard)")
-    st.sidebar.markdown("website:(https://xevenskills.com)")
+app = Flask(__name__)
 
+ALLOWED_EXTENSIONS = {'txt', 'pdf', 'docx'}
 
+def allowed_file(filename):
+  return '.' in filename and \
+         filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS
 
+@app.route('/api/generate-wordcloud', methods=['POST'])
+def generate_wordcloud():
+  if 'file' not in request.files:
+    return jsonify({'error': 'Missing file upload'}), 400
 
-    st.subheader("Word Count Table")
-    st.write(word_count)
-    # Provide download link for table
-    if st.button('Download Word Count Table as CSV'):
-        st.markdown(get_table_download_link(word_count, "word_count.csv", "Click Here to Download"), unsafe_allow_html=True)
+  file = request.files['file']
+  if file.filename == '':
+    return jsonify({'error': 'No selected file'}), 400
 
+  if file and allowed_file(file.filename):
+    text = ''
+    if file.filename.endswith('.txt'):
+      text = file.read().decode('utf-8')
+    elif file.filename.