core/prompt_engineering.py

# core/prompt_engineering.py

def create_story_breakdown_prompt(user_idea, genre="sci-fi", mood="suspenseful", num_scenes=3):
    return f"""
    You are an expert screenwriter and visual storyteller.
    Based on the user's idea: "{user_idea}"
    And considering the genre: "{genre}" and mood: "{mood}"

    Generate a {num_scenes}-scene story breakdown. For each scene, provide:
    1. scene_number (int)
    2. setting_description (str): Vivid description of the location and atmosphere.
    3. characters_involved (list of str): Names of characters in the scene.
    4. key_action (str): The main event or action happening.
    5. dialogue_snippet (str): A brief, impactful line of dialogue if applicable.
    6. visual_style_suggestion (str): e.g., "Dark and gritty, high contrast, Blade Runner-esque neon"
    7. camera_angle_suggestion (str): e.g., "Low-angle shot to emphasize power"
    8. emotional_beat (str): The core emotion or turning point in the scene.

    Output ONLY the JSON object for the list of scenes.
    Example for one scene:
    {{
      "scene_number": 1,
      "setting_description": "A dimly lit, cluttered spaceship cockpit. Warning lights flash intermittently.",
      "characters_involved": ["Captain Eva Rostova"],
      "key_action": "Eva notices an unusual energy signature on the main console.",
      "dialogue_snippet": "Eva: 'What in the void is that?'",
      "visual_style_suggestion": "Claustrophobic, practical lighting, lens flares.",
      "camera_angle_suggestion": "Close-up on Eva's face, then a point-of-view shot of the console.",
      "emotional_beat": "Curiosity mixed with apprehension."
    }}

    Provide the full JSON structure for {num_scenes} scenes in a list:
    [
        {{scene1_details...}},
        {{scene2_details...}},
        ...
    ]
    """

def create_image_prompt_from_scene_data(scene_data, character_details=None, style_reference_desc=None):
    """
    Generates an image prompt from structured scene data.
    scene_data: dictionary for a single scene.
    character_details: dict {char_name: description} for consistency (future use).
    style_reference_desc: textual description of a desired style (future use).
    """
    base_desc = f"Scene {scene_data.get('scene_number', '')}: {scene_data.get('key_action', '')}. Setting: {scene_data.get('setting_description', '')}."
    visual_style = scene_data.get('visual_style_suggestion', 'cinematic')
    camera_angle = scene_data.get('camera_angle_suggestion', '')

    char_info = ""
    if character_details and scene_data.get('characters_involved'):
        for char_name in scene_data.get('characters_involved'):
            if char_name in character_details:
                char_info += f" {char_name} ({character_details[char_name]})."

    style_mod = ""
    if style_reference_desc:
        style_mod = f" Artistic style inspired by: {style_reference_desc}."

    full_prompt = f"""
    Generate a highly detailed, photorealistic image generation prompt.
    The image should depict: {base_desc}{char_info}
    Visual Style: {visual_style}{style_mod}.
    Camera Perspective: {camera_angle}.
    Emphasize mood: {scene_data.get('emotional_beat', '')}.
    Focus on cinematic composition, lighting. Suitable for DALL-E 3 or Midjourney.
    Output only the prompt string.
    """
    return full_prompt.strip()


def create_scene_regeneration_prompt(original_scene_data, user_feedback, full_story_context=None):
    """
    Creates a prompt for Gemini to regenerate a specific scene's script details.
    original_scene_data: The JSON object of the scene to be modified.
    user_feedback: Text from the user describing desired changes.
    full_story_context: (Optional) JSON of all scenes for better consistency.
    """
    context_str = f"Original scene details:\n{json.dumps(original_scene_data, indent=2)}\n\n"
    if full_story_context:
        context_str += f"Full story context (this scene is number {original_scene_data.get('scene_number')}):\n{json.dumps(full_story_context, indent=2)}\n\n"

    return f"""
    You are an expert script doctor.
    {context_str}
    The user wants to modify this scene based on the following feedback: "{user_feedback}"

    Please regenerate ONLY the JSON object for this single scene, incorporating the feedback.
    Maintain the same JSON structure as the original scene:
    (scene_number, setting_description, characters_involved, key_action, dialogue_snippet, visual_style_suggestion, camera_angle_suggestion, emotional_beat).
    Ensure the scene_number remains the same.
    Focus on making the changes impactful while keeping the scene coherent.
    If the feedback is about visual style or camera, update those fields accordingly.
    If the feedback is about action or dialogue, update those.
    """

def create_visual_regeneration_prompt(original_image_prompt, user_feedback_on_visuals, scene_data):
    """
    Creates a prompt for Gemini to regenerate an image prompt based on feedback.
    """
    return f"""
    The previous image prompt for a scene was: "{original_image_prompt}"
    The scene details are:
    Setting: {scene_data.get('setting_description')}
    Action: {scene_data.get('key_action')}
    Mood/Emotion: {scene_data.get('emotional_beat')}
    Visual Style: {scene_data.get('visual_style_suggestion')}
    Camera: {scene_data.get('camera_angle_suggestion')}

    The user provided this feedback on the visuals: "{user_feedback_on_visuals}"

    Generate a new, refined image generation prompt that incorporates this feedback.
    The new prompt should aim to correct or enhance the visuals as per the user's request.
    Output only the new prompt string.
    """

# (Keep other prompt functions if needed)
import json # Add this at the top of prompt_engineering.py if not already there