Update app.py

app.py

@@ -23,9 +23,9 @@ def preprocess_text(element):
     else:
         return ""
 
-def get_openai_response(text, max_length=100, model="t5-small"):
+def get_openai_response(text, min_length=100, model="t5-small"):
     summarizer = pipeline("summarization", model=model)
-    return summarizer(text, min_length=max_length)
+    return summarizer(text, min_length=min_length)
 
 ## Streamlit app
 
@@ -34,8 +34,8 @@ st.header("PDF Summarizer")
 
 # User options
 st.subheader("Settings")
-# min_summary_length = st.slider("Minimum Summary Length", min_value=50, max_value=500, value=100)
-max_summary_length = st.slider("Maximum Summary Length", min_value=50, max_value=500, value=100)
+min_summary_length = st.slider("Minimum Summary Length", min_value=50, max_value=500, value=100)
+# max_summary_length = st.slider("Maximum Summary Length", min_value=50, max_value=500, value=100)
 summarization_model = st.selectbox("Summarization Model", ["t5-small", "facebook/bart-large-cnn"])
 
 # File upload and processing
@@ -50,7 +50,7 @@ if uploaded_file is not None:
             submit = st.button("Generate Summary")
             if submit:
                 with st.spinner("Summarizing..."):
-                    response = get_openai_response(text, max_length=max_summary_length, model=summarization_model)
+                    response = get_openai_response(text, min_length=min_summary_length, model=summarization_model)
                     st.subheader("Summary")
                     st.write(response[0]["summary_text"])
         else: