Commit Test SRT

app.py

@@ -1,31 +1,31 @@
 import streamlit as st
 from transformers import pipeline
 
-# Function to extract text from SRT file
-# Function to extract text from SRT file
-def extract_text_from_srt(srt_text):
+# Function to extract text from SRT-formatted text
+def extract_text_from_srt_text(srt_text):
     lines = srt_text.strip().split("\n")
-    # Extract text content from SRT
-    texts = [line.split("\n")[2] for line in lines if len(line.split("\n")) > 2 and not line.startswith("0")]
+    texts = [line.split("\n")[2] for line in lines if not line.startswith("0")]
     return " ".join(texts)
 
-
 # Load summarization pipeline
 summarizer = pipeline("summarization")
 
 # Streamlit app
 st.title("SRT Summarization")
 
-# Text area for user to upload SRT file
-srt_file = st.file_uploader("Upload SRT file", type=["srt"])
+# Text area for user to input SRT-formatted text
+srt_text_input = st.text_area("Paste SRT-formatted text here:")
 
-if srt_file is not None:
-    # Read uploaded SRT file
-    srt_text = srt_file.read().decode("utf-8")
-    # Extract text from SRT
-    text_to_summarize = extract_text_from_srt(srt_text)
-    # Summarize text
-    summary = summarizer(text_to_summarize, max_length=150, min_length=30, do_sample=False)
-    # Display summary
-    st.subheader("Summary:")
-    st.write(summary[0]["summary_text"])
+# Button to trigger summarization
+if st.button("Summarize"):
+    # Check if text area is not empty
+    if srt_text_input.strip():
+        # Extract text from SRT-formatted text
+        text_to_summarize = extract_text_from_srt_text(srt_text_input)
+        # Summarize text
+        summary = summarizer(text_to_summarize, max_length=1500, min_length=10, do_sample=False)
+        # Display summary
+        st.subheader("Summary:")
+        st.write(summary[0]["summary_text"])
+    else:
+        st.warning("Please enter some SRT-formatted text.")