Update app.py

app.py

@@ -1,46 +1,37 @@
 # Import the required libraries
 import openai
+# import os
 import streamlit as st
 
 # Set the GPT-3 API key
-# In this case, st.secrets["pass"] is accessing the value of the "pass" secret.
+openai.api_key = st.secrets["pass"]
 
-openai.api_key = st.secrets["pass"] 
-# Create Text Area Widget to enable user to enter texts
+# Read the text of the article from a file
+# with open("article.txt", "r") as f:
+#     article_text = f.read()
 article_text = st.text_area("Enter your scientific texts to summarize")
-# Create Radio Buttons
-output_size = st.radio( label = "What kind of output do you want?", 
-                        options= ["To-The-Point", "Concise", "Detailed"]
-                     )
-# First, we'll use an if statement to determine the desired output size 
-# and set the out_token variable accordingly:
+output_size = st.radio(label = "What kind of output do you want?", 
+                    options= ["To-The-Point", "Concise", "Detailed"])
 
 if output_size == "To-The-Point":
- out_token = 50
+    out_token = 50
 elif output_size == "Concise":
- out_token = 128
+    out_token = 128
 else:
- out_token = 516
-
-# Next, we'll add a check to make sure that the input text is long enough 
-# to summarize, and display a warning if it is not:
+    out_token = 516
 
 if len(article_text)>100:
- # Generate the summary
- # .......
+    if st.button("Generate Summary",type='primary'):
+    # Use GPT-3 to generate a summary of the article
+        response = openai.Completion.create(
+            engine="text-davinci-002",
+            prompt="Please summarize this scientific article for me in a few sentences: " + article_text,
+            max_tokens = out_token,
+            temperature = 0.5,
+        )
+        # Print the generated summary
+        res = response["choices"][0]["text"]
+        st.success(res)
+        st.download_button('Download result', res)
 else:
- st.warning("Not enough words to summarize!")
-if st.button("Generate Summary",type='primary'):
- 
-# Use GPT-3 to generate a summary of the article
- response = openai.Completion.create(
-                    engine = "text-davinci-002",
-                    prompt = "Please summarize this scientific article for me in a few sentences: "+ article_text,
-                    max_tokens = out_token,
-                    temperature = 0.5)
- 
-# Print the generated summary
- res = response["choices"][0]["text"]
- st.success(res)
-# Give user the option to download result
-st.download_button('Download result', res)
+    st.warning("Not enough words to summarize!")