Update app.py

app.py

@@ -4,30 +4,30 @@ model_id = "knkarthick/MEETING_SUMMARY"
 
 generator = pipeline(task="text2text-generation", model=model_id)
 
-#def split_paragraph(paragraph, max_chunk_size=1024):
-#    words = paragraph.split()
-#    chunks = []
-#    current_chunk = []
-#    current_chunk_size = 0
+def split_paragraph(paragraph, max_chunk_size=1024):
+    words = paragraph.split()
+    chunks = []
+    current_chunk = []
+    current_chunk_size = 0
 
-#    for word in words:
-#        word_len = len(word) + 1  # Add 1 for the space
-#        if current_chunk_size + word_len <= max_chunk_size:
-#            current_chunk.append(word)
-#            current_chunk_size += word_len
-#        else:
-#            chunks.append(' '.join(current_chunk))
-#            current_chunk = [word]
-#            current_chunk_size = word_len
+    for word in words:
+        word_len = len(word) + 1  # Add 1 for the space
+        if current_chunk_size + word_len <= max_chunk_size:
+            current_chunk.append(word)
+            current_chunk_size += word_len
+        else:
+            chunks.append(' '.join(current_chunk))
+            current_chunk = [word]
+            current_chunk_size = word_len
 
-#    if current_chunk:
-#        chunks.append(' '.join(current_chunk))
+    if current_chunk:
+        chunks.append(' '.join(current_chunk))
 
-#    return chunks
+    return chunks
 
 def launch(input):
-#    if len(input) > 1024:
-#        return " ".join([res["generated_text"] for res in generator(split_paragraph(input))])
+    if len(input) > 1024:
+        return " ".join([res["generated_text"] for res in generator(split_paragraph(input))])
     return generator(input)[0]["generated_text"]
 
 iface = gr.Interface(launch, inputs="text", outputs="text")