Update app.py

app.py

@@ -1,33 +1,48 @@
 import gradio as gr
 from transformers import pipeline
 import os
+import pandas as pd
 
 # Load the text summarization pipeline
 summarizer = pipeline("summarization", model="astro21/bart-cls")
 
 chunk_counter = 0
 
+
 def summarize_text(input_text):
-    global chunk_counter  # Use a global variable to keep track of the chunk number
-    chunk_counter = 0  # Initialize the chunk counter
+    global chunk_counter
+    chunk_counter = 0
 
-    # Split the input text into chunks with a maximum size of 512
-    max_chunk_size = 512
-    chunks = [input_text[i:i+max_chunk_size] for i in range(0, len(input_text), max_chunk_size)]
+    max_chunk_size = 1024
+    chunks = [input_text[i:i + max_chunk_size] for i in range(0, len(input_text), max_chunk_size)]
 
     summarized_chunks = []
+    chunk_lengths = []
+    summarized_chunks_only = []
+
     for chunk in chunks:
         chunk_counter += 1
-        # Summarize each chunk
         summarized_chunk = summarizer(chunk, max_length=128, min_length=64, do_sample=False)[0]['summary_text']
         summarized_chunks.append(f"Chunk {chunk_counter}:\n{summarized_chunk}")
+        summarized_chunks_only.append(summarized_chunk)
+
+        chunk_lengths.append(len(chunk))
 
-    # Concatenate the summaries
     summarized_text = "\n".join(summarized_chunks)
-    return summarized_text
+    summarized_text_only = "\n".join(summarized_chunks_only)
+
+    # Save the merged summary to a file
+    with open("summarized.txt", "w") as output_file:
+        output_file.write(summarized_text_only)
+
+    chunk_df = pd.DataFrame({'Chunk Number': range(1, chunk_counter + 1), 'Chunk Length': chunk_lengths})
+
+    return summarized_text, chunk_df, "summarized.txt"
+
 
 def read_file(file):
-    with open(file.name, 'r') as file_:
+    print(file[0].name)
+    with open(file[0].name, 'r') as file_:
         content = file_.read()
     return content
 
@@ -37,8 +52,18 @@ def summarize_text_file(file):
         content = read_file(file)
         return summarize_text(content)
 
+
 input_type = gr.inputs.File("text")
 
-demo = gr.Interface(fn=summarize_text_file, inputs=input_type, outputs="text", live=True)
+# Name the outputs using the label parameter and provide a download option
+demo = gr.Interface(fn=summarize_text_file, inputs=input_type,
+                    outputs=[gr.Textbox(label="Summarized Text"),
+                             gr.Dataframe(label="Chunk Information", type="pandas"),
+                             gr.File(label="Download Summarized Text", type="file", live=False)],
+                    title = "Text Summarization",
+                    description = "Summarize text using BART",
+                    theme = "huggingface",
+                    allow_flagging="never",
+                    live=True)
 
 demo.launch()