Simplified prompts

app.py

@@ -47,23 +47,19 @@ format_map = {
     "Ballad": "The poem MUST tell a narrative story using four-line stanzas (quatrains) and a simple rhyme scheme like A-B-C-B. It should be 4-6 stanzas long."
 }
 
-# --- Prompt Construction Helper Function (Robust, Delimited Prompt) ---
+# --- Prompt Construction Helper Function (Simplified) ---
 def build_poem_prompt(voice_instruction, constraint_instruction, format_type, topic):
-    """Constructs a robust, delimited prompt for initial poem generation."""
+    """Constructs a simple, direct prompt for initial poem generation."""
     
-    system_context = (
-        f"SYSTEM: You are a highly disciplined creative writer. You ABSOLUTELY MUST follow all constraints "
-        f"on line count, structure, and persona. Your entire response MUST contain ONLY the poem and NOTHING else. "
-        f"Do NOT include any titles, headers, or extra text.\n"
-        f"PERSONA: {voice_instruction}\n"
-        f"FORMAT RULES: {constraint_instruction}\n"
+    # Combined, prioritized instruction block for maximum clarity
+    full_instruction = (
+        f"You are a highly disciplined creative writer. {voice_instruction} "
+        f"You must write a {format_type} about '{topic}'.\n"
+        f"STRICT FORMAT RULE: {constraint_instruction}\n"
+        f"Your output must contain ONLY the poem, nothing else. Do NOT include a title.\n\n"
+        f"BEGIN POEM: " # Simple, clear marker for generation start
     )
-
-    user_task = (
-        f"USER: Write a {format_type} about the topic: '{topic}'. The poem MUST strictly adhere to all FORMAT RULES.\n"
-    )
-        
-    return f"### Instruction:\n{system_context}\n{user_task}\n\n"
+    return full_instruction
 
 # --- LLM Functions ---
 def generate_poem(format_type, persona, topic, progress=gr.Progress()):
@@ -86,41 +82,53 @@ def generate_poem(format_type, persona, topic, progress=gr.Progress()):
         prompt=full_poem_prompt,
         max_tokens=MAX_NEW_TOKENS,
         temperature=TEMPERATURE,
-        stop=["### Instruction:", "USER:", "SYSTEM:", "### Human:"],
+        # Simplified stop list for the generation call
+        stop=["STRICT FORMAT RULE:", "BEGIN POEM:"],
         echo=False
     )
+    # Remove potential preamble text markers from output
     poem_text = output['choices'][0]['text'].strip()
+    if poem_text.startswith("BEGIN POEM:"):
+        poem_text = poem_text[len("BEGIN POEM:"):].strip()
     
-    # --- 2. POET SUGGESTION (ANALYSIS) ---
+    # --- 2. POET SUGGESTION (ANALYSIS - Simplified Prompt) ---
     progress(0.5, desc="Analyzing style for literary match...")
 
-    # Secondary prompt for the analysis task - HARDENED CONSTRAINT ADDED HERE
+    # Secondary prompt for the analysis task - Simplified Question
     poet_prompt = (
-        f"### Instruction:\n"
-        f"SYSTEM: You are a literary analyst specializing in poetry. Your task is to find the single most appropriate historical poet "
-        f"whose style and themes match the provided poem. The poet MUST be a REAL, historical figure. "
-        f"Do NOT suggest any fictional characters, places, or entities mentioned in the poem. "
-        f"Output ONLY the POET'S NAME, followed by a COLON, and then a brief, single-sentence justification. Begin immediately with the poet's name. \n"
-        f"Do NOT output any other text or headers. You MUST adhere to the requested persona's style.\n"
-        f"PERSONA: {selected_voice}\n"
-        f"USER: Analyze the poem below and suggest the best matching poet:\n\n"
+        f"You are a literary analyst. Analyze the poem below. Your analysis should reflect the persona of {selected_voice}. \n"
+        f"Identify the single most appropriate REAL, historical poet whose style and themes match the poem. Do NOT suggest fictional characters.\n"
+        f"Format your answer as: Poet Name: [Name] - Justification: [Reason].\n\n"
         f"POEM:\n{poem_text}\n\n"
-        f"BEGIN ANALYSIS HERE: " # Added a strong generation marker to prevent echoing the input poem
+        f"ANALYSIS: " # Simple marker for generation start
     )
     
     output_poet = llm(
         prompt=poet_prompt,
-        max_tokens=150, # Keep this response short
+        max_tokens=80, # Keep this response short
         temperature=0.4, # Lower temperature for analysis/retrieval
-        # Added "POEM:" and "BEGIN ANALYSIS HERE:" to the stop list for safety
-        stop=["### Instruction:", "USER:", "SYSTEM:", "### Human:", "\n\n", "POEM:", "BEGIN ANALYSIS HERE:"], 
+        # Simple stop list focused on stopping after the answer
+        stop=["POEM:", "ANALYSIS:", "\n\n", "\n"], 
         echo=False
     )
     
-    # Remove the generation marker from the start of the output if it was successful
+    # Clean up the output using simple string manipulation
     poet_suggestion = output_poet['choices'][0]['text'].strip()
-    if poet_suggestion.startswith("BEGIN ANALYSIS HERE:"):
-        poet_suggestion = poet_suggestion[len("BEGIN ANALYSIS HERE:"):].strip()
+    
+    # 1. Find and remove the "ANALYSIS:" marker if it appeared in the output
+    if poet_suggestion.startswith("ANALYSIS:"):
+        poet_suggestion = poet_suggestion[len("ANALYSIS:"):].strip()
+    
+    # 2. Re-format the output cleanly (removing the template names)
+    if "Poet Name:" in poet_suggestion:
+        poet_suggestion = poet_suggestion.replace("Poet Name:", "").replace(" - Justification:", ":").strip()
+    # Handle the case where the LLM just gives the answer directly
+    elif ":" in poet_suggestion:
+        # Keep the output as is, assuming it's in the Poet: Justification format
+        pass
+    else:
+        # Simple fallback for totally non-compliant output
+        poet_suggestion = f"Analysis failed: {poet_suggestion[:50]}..."
 
 
     progress(0.9, desc="Poem and analysis complete!")