Update app.py

app.py

@@ -519,7 +519,7 @@ Output Format:
 **Why Interesting:** [1 sentence hook]
 ---""")
         
-        user_msg = HumanMessage(content=f"Search for recent breakthroughs in {topic}. Check titles carefully to avoid duplicates.")
+        user_msg = HumanMessage(content=f"Search for recent breakthroughs in {topic}.")
         
         discovery_llm = llm_small.bind_tools([search_science_breakthroughs, get_all_previous_posts, check_topic_similarity])
         response = discovery_llm.invoke([system_msg, user_msg])
@@ -589,7 +589,12 @@ Then rank on:
 
 Output: RANKED CANDIDATES, then SELECTED STORY with title uniqueness check.""")
         
-        user_msg = HumanMessage(content=f"Rank and select the best story. CHECK TITLE SIMILARITY FIRST:\n{candidates_text}")
+        if retry_count > 0:
+            instruction = f"Refine the previous draft based on this feedback:\n{state.get('critic_feedback')}\n\nOriginal Story:\n{story_text}"
+        else:
+            instruction = f"Write Tuesday Trivia post based on:\n{story_text}"
+        
+        user_msg = HumanMessage(content=instruction)
         
         curator_llm = llm_medium.bind_tools([check_topic_similarity, get_all_previous_posts])
         response = curator_llm.invoke([system_msg, user_msg])
@@ -665,7 +670,7 @@ CONTENT:
 - keep the content formal as in the examples
 HASHTAGS: Always include #TuesdayTrivia #RnDCell #CCA + 2-4 topic hashtags""")
         
-        user_msg = HumanMessage(content=f"Write Tuesday Trivia post. VERIFY TITLE UNIQUENESS:\n{story_text}\n{retry_context}")
+        user_msg = HumanMessage(content=f"Write Tuesday Trivia post:\n{story_text}\n{retry_context}")
         
         writer_llm = llm_medium.bind_tools([get_example_posts_for_writer, check_topic_similarity, fetch_article_content, count_words])
         response = writer_llm.invoke([system_msg, user_msg])
@@ -752,7 +757,7 @@ ACTIONABLE FIXES:
 
 """)
         
-        user_msg = HumanMessage(content=f"Evaluate this post. CHECK TITLE UNIQUENESS FIRST:\n\n{draft}")
+        user_msg = HumanMessage(content=f"Evaluate this post:\n\n{draft}")
         
         critic_llm = llm_large.bind_tools([get_example_posts_for_critic, check_topic_similarity])
         response = critic_llm.invoke([system_msg, user_msg])