Update app.py

app.py

@@ -1,3 +1,4 @@
+%%writefile app.py
 from langchain.chains import LLMChain
 from langchain.llms import HuggingFaceHub
 from langchain.prompts import PromptTemplate
@@ -26,42 +27,46 @@ existing_ideas = load_ideas()
 st.sidebar.header("Previous Ideas:")
 
 while(True):
-  if topic:
+    keys = list(set([key for idea in existing_ideas for key in idea.keys()]))
+    if keys:  
+        selected_idea = st.sidebar.selectbox("Select Idea", keys, key="selectbox")
+        selected_idea_from_list = next((idea for idea in existing_ideas if selected_idea in idea), None)
+        st.markdown(selected_idea_from_list[selected_idea])
     if button_clicked:
 
-      hub_llm = HuggingFaceHub(repo_id ="HuggingFaceH4/zephyr-7b-beta")
-      prompt = PromptTemplate(
-          input_variables = ['keyword'],
-          template = """
-          Write a comprehensive article about {keyword} covering the following aspects:
-          Introduction, History and Background, Key Concepts and Terminology, Use Cases and Applications, Benefits and Drawbacks, Future Outlook, Conclusion
-          Ensure that the article is well-structured, informative, and at least 1500 words long. Use SEO best practices for content optimization.
-          """)
-      hub_chain = LLMChain(prompt=prompt,llm = hub_llm,verbose=True)
+        hub_llm = HuggingFaceHub(repo_id ="HuggingFaceH4/zephyr-7b-beta")
+        prompt = PromptTemplate(
+            input_variables = ['keyword'],
+            template = """
+            Write a comprehensive article about {keyword} covering the following aspects:
+            Introduction, History and Background, Key Concepts and Terminology, Use Cases and Applications, Benefits and Drawbacks, Future Outlook, Conclusion
+            Ensure that the article is well-structured, informative, and at least 1500 words long. Use SEO best practices for content optimization.
+            """)
+        hub_chain = LLMChain(prompt=prompt,llm = hub_llm,verbose=True)
 
-      content = hub_chain.run(topic)
+        content = hub_chain.run(topic)
 
 
-      subheadings = [
-              "Introduction:",
-              "History and Background:",
-              "Key Concepts and Terminology:",
-              "Use Cases and Applications:",
-              "Benefits and Drawbacks:",
-              "Future Outlook:",
-              "Conclusion:",
-          ]
-      organized_content = ""
+        subheadings = [
+                "Introduction:",
+                "History and Background:",
+                "Key Concepts and Terminology:",
+                "Use Cases and Applications:",
+                "Benefits and Drawbacks:",
+                "Future Outlook:",
+                "Conclusion:",
+            ]
+        organized_content = ""
 
-      for subheading in subheadings:
-          if subheading in content:
-              content = content.replace(subheading,"## "+subheading+"\n")
+        for subheading in subheadings:
+            if subheading in content:
+                content = content.replace(subheading,"## "+subheading+"\n")
+
+        existing_ideas.append({topic:content})
+        keys = list(set([key for idea in existing_ideas for key in idea.keys()]))
+        save_ideas(existing_ideas)
+        selected_idea = st.sidebar.selectbox("Select Idea", keys, key="selectbox",index=keys.index(topic))
+        selected_idea_from_list = next((idea for idea in existing_ideas if selected_idea in idea), None)
+        st.markdown(selected_idea_from_list[selected_idea])
 
-      existing_ideas.append({topic:content})
-      keys = [key for idea in existing_ideas for key in idea.keys()]
-      save_ideas(existing_ideas)
-    keys = [key for idea in existing_ideas for key in idea.keys()]
-    selected_idea = st.sidebar.selectbox("Select Idea", keys, key="selectbox")
-    selected_idea_from_list = next((idea for idea in existing_ideas if selected_idea in idea), None)
-    st.markdown(selected_idea_from_list[selected_idea])