Rename prompts/prompt_templates.py to prompts/narrative_prompts.py

prompts/narrative_prompts.py

@@ -0,0 +1,30 @@
+# storyverse_weaver/prompts/narrative_prompts.py
+
+NARRATIVE_SYSTEM_PROMPT_DEFAULT = (
+    "You are a master storyteller and descriptive writer. Your task is to take a user's scene idea "
+    "and expand it into a vivid and engaging narrative segment. Focus on imagery, atmosphere, and character actions "
+    "or emotions if mentioned. Keep the tone consistent with the user's prompt. Aim for about 1-3 paragraphs."
+)
+
+NARRATIVE_SYSTEM_PROMPT_COMIC = (
+    "You are a concise and impactful comic book writer. Given a scene description, write a brief but evocative narrative "
+    "caption or description suitable for a comic panel. Focus on key actions, settings, and dialogue cues. "
+    "Be punchy and visually oriented. Output 1-2 short paragraphs or a few descriptive sentences."
+)
+
+
+def get_narrative_system_prompt(story_type: str = "default") -> str:
+    if story_type == "comic":
+        return NARRATIVE_SYSTEM_PROMPT_COMIC
+    return NARRATIVE_SYSTEM_PROMPT_DEFAULT
+
+def format_narrative_user_prompt(scene_idea: str, previous_narrative: str = None, character_context: str = None) -> str:
+    prompt = f"The user wants to create a scene based on this idea: \"{scene_idea}\"\n\n"
+    if previous_narrative:
+        prompt += f"For context, the previous scene's narrative ended with:\n\"\"\"\n{previous_narrative[:500]}...\n\"\"\"\n\n" # Limit context
+    if character_context:
+        prompt += f"Relevant character context to consider: \"{character_context}\"\n\n"
+    prompt += "Please write the narrative for the current scene based on the user's idea and any provided context."
+    return prompt
+
+print("DEBUG: prompts.narrative_prompts (for StoryVerseWeaver) - Module defined.")

prompts/prompt_templates.py

@@ -1,70 +0,0 @@
-# algoforge_prime/prompts/prompt_templates.py
-
-# These functions help construct the user-facing part of the prompts,
-# ensuring consistency and making it easier to manage complex prompt structures.
-
-def format_genesis_user_prompt(
-    problem_description: str,
-    initial_hints: str,
-    attempt_num: int,
-    total_attempts: int
-) -> str:
-    """Formats the user prompt for the Genesis (initial solution generation) stage."""
-    hints_section = f"Initial Thoughts/Constraints to consider: \"{initial_hints}\"" if initial_hints else "No specific initial hints provided."
-    return (
-        f"User Problem Description: \"{problem_description}\"\n\n"
-        f"{hints_section}\n\n"
-        f"Task: Please provide one distinct and complete algorithmic solution or well-commented code (as appropriate for the problem type) to address the problem description. "
-        f"This is solution attempt #{attempt_num} of {total_attempts}. "
-        f"If possible, try to offer a different approach or perspective compared to what might be a very obvious first attempt."
-    )
-
-def format_critique_user_prompt(
-    problem_description_context: str, # A snippet for context
-    solution_text_to_evaluate: str
-) -> str:
-    """Formats the user prompt for the Critique (evaluation) stage."""
-    return (
-        f"Context: The overall problem being solved is related to: \"{problem_description_context[:200]}...\"\n\n"
-        f"Solution to Evaluate:\n"
-        f"```\n{solution_text_to_evaluate}\n```\n\n"
-        f"Task: Critically evaluate this solution according to the system instructions (correctness, efficiency, clarity, etc.). "
-        f"Remember to provide your overall assessment and conclude with the mandatory 'Score: X/10' line."
-    )
-
-def format_evolution_user_prompt(
-    problem_description_context: str,
-    original_solution_text: str,
-    comprehensive_critique_text: str, # Includes LLM critique and test summary
-    original_score: int
-) -> str:
-    """Formats the user prompt for the Evolution (refinement) stage."""
-    return (
-        f"Context: The original problem is: \"{problem_description_context}\"\n\n"
-        f"Solution to Evolve (Original Score: {original_score}/10):\n"
-        f"```\n{original_solution_text}\n```\n\n"
-        f"Comprehensive Evaluation Received for the Above Solution:\n"
-        f"'''\n{comprehensive_critique_text}\n'''\n\n"
-        f"Task: Based on the provided solution and its comprehensive evaluation, your goal is to evolve it into a significantly improved version. "
-        f"Address all identified weaknesses, enhance its strengths, and ensure it is more robust, efficient, or clear. "
-        f"Output the *complete evolved solution*. "
-        f"Follow this with a brief explanation of the key changes and improvements you implemented."
-    )
-
-def format_code_test_analysis_user_prompt(
-    generated_code: str,
-    unit_tests_code: str,
-    test_execution_summary: str # e.g., "Simulated: 2/3 tests passed. Some tests likely failed."
-) -> str:
-    """Formats the user prompt for asking an LLM to analyze code test results."""
-    return (
-        f"Generated Python Code:\n"
-        f"```python\n{generated_code}\n```\n\n"
-        f"Unit Tests Applied:\n"
-        f"```python\n{unit_tests_code}\n```\n\n"
-        f"Test Execution Summary:\n"
-        f"'''\n{test_execution_summary}\n'''\n\n"
-        f"Task: Please analyze these test results in relation to the generated Python code. "
-        f"Provide a concise explanation of what the test outcomes (passes, failures, errors) indicate about the code's correctness or potential issues. "
-        f"If tests failed, suggest likely reasons or areas in the code to inspect."
-    )