Rename core/evolution_engine.py to core/story_engine.py

core/evolution_engine.py

@@ -1,57 +0,0 @@
-# algoforge_prime/core/evolution_engine.py
-print("DEBUG: Importing core.evolution_engine")
-
-from core.llm_clients import call_huggingface_api, call_gemini_api, LLMResponse
-from prompts.system_prompts import get_system_prompt
-# from core.evaluation_engine import EvaluationResultOutput # For type hinting if needed
-
-print("DEBUG: core.evolution_engine - Imports successful")
-
-def evolve_solution(
-    original_solution_text: str,
-    evaluation_output_obj, # This is an EvaluationResultOutput object
-    problem_description: str,
-    problem_type: str,
-    llm_client_config: dict
-) -> str:
-    print(f"DEBUG: evolution_engine.py - Evolving solution. Problem type: {problem_type}")
-    system_p_evolve = get_system_prompt("evolution_general")
-    
-    try:
-        # Use the method from EvaluationResultOutput to get formatted critique and test results
-        critique_and_test_feedback = evaluation_output_obj.get_display_critique() 
-        original_score = evaluation_output_obj.combined_score
-    except AttributeError: # Fallback if evaluation_output_obj is not as expected
-        critique_and_test_feedback = "Detailed evaluation feedback was not available or malformed."
-        original_score = 0 # Or try to get it from evaluation_output_obj if it's just a simple dict
-        if hasattr(evaluation_output_obj, 'score'): original_score = evaluation_output_obj.score
-        elif isinstance(evaluation_output_obj, dict) and 'score' in evaluation_output_obj: original_score = evaluation_output_obj['score']
-
-    user_p_evolve = (
-        f"Original Problem Context: \"{problem_description}\"\n\n"
-        f"The solution to be evolved achieved a combined score of {original_score}/10.\n"
-        f"Here is the original solution text:\n```python\n{original_solution_text}\n```\n\n"
-        f"Here is the comprehensive evaluation it received (including LLM critique AND automated test feedback/errors if run):\n'''\n{critique_and_test_feedback}\n'''\n\n"
-        f"Your Task: Based on ALL the information above (solution, LLM critique, and crucially any test execution results/errors mentioned in the evaluation), "
-        f"evolve the provided solution to make it demonstrably superior. "
-        f"**Your HIGHEST PRIORITY is to fix any reported execution errors or failed tests.** "
-        f"Then, address other critique points like efficiency, clarity, or completeness. "
-        f"Output ONLY the *complete, raw, evolved Python code block*. Do not include explanations outside the code block unless explicitly part of the solution's comments."
-    )
-
-    llm_response_obj = None
-    if llm_client_config["type"] == "hf":
-        llm_response_obj = call_huggingface_api(user_p_evolve, llm_client_config["model_id"], llm_client_config["temp"], llm_client_config["max_tokens"], system_p_evolve)
-    elif llm_client_config["type"] == "google_gemini":
-        llm_response_obj = call_gemini_api(user_p_evolve, llm_client_config["model_id"], llm_client_config["temp"], llm_client_config["max_tokens"], system_p_evolve)
-    else:
-        return f"ERROR (Evolution): Unknown LLM client type '{llm_client_config['type']}'"
-
-    if llm_response_obj.success:
-        # Optional: basic cleanup of the LLM output if it tends to add markdown
-        from core.utils import basic_text_cleanup # Assuming you have this
-        return basic_text_cleanup(llm_response_obj.text)
-    else:
-        return f"ERROR (Evolution with {llm_response_obj.model_id_used}): {llm_response_obj.error}"
-
-print("DEBUG: core.evolution_engine - Module fully defined.")

core/story_engine.py

@@ -0,0 +1,117 @@
+# storyverse_weaver/core/story_engine.py
+from PIL import Image # Make sure Pillow is in requirements.txt
+
+class Scene:
+    def __init__(self, scene_number: int, user_prompt: str, narrative_text: str = None, 
+                 image: Image.Image = None, image_style_prompt: str = None, 
+                 image_provider: str = None, error_message: str = None): # Added error_message here
+        self.scene_number = scene_number
+        self.user_prompt = user_prompt 
+        self.narrative_text = narrative_text 
+        self.image_style_prompt = image_style_prompt 
+        self.image = image 
+        self.image_provider = image_provider 
+        self.error_message = error_message # Store errors specific to this scene
+
+    def __str__(self):
+        img_status = "Yes" if self.image else ("Error" if self.error_message and not self.image else "No")
+        narr_status = str(self.narrative_text)[:50] if self.narrative_text and "Error" not in self.narrative_text else ("Error" if "Error" in str(self.narrative_text) else "N/A")
+        return f"Scene {self.scene_number}: {self.user_prompt[:50]}... Narrative: {narr_status}... Image: {img_status}"
+
+class Story:
+    def __init__(self, title: str = "Untitled StoryVerse"):
+        self.title = title
+        self.scenes: list[Scene] = []
+        self.current_scene_number = 0
+        self.global_style_prompt: str = None 
+        self.global_negative_prompt: str = None 
+
+    def add_scene_from_elements(self, user_prompt: str, narrative_text: str, 
+                                image: Image.Image, image_style_prompt: str, 
+                                image_provider: str, error_message: str = None) -> Scene: # Added error_message
+        self.current_scene_number += 1
+        scene = Scene(
+            scene_number=self.current_scene_number,
+            user_prompt=user_prompt,
+            narrative_text=narrative_text,
+            image=image,
+            image_style_prompt=image_style_prompt,
+            image_provider=image_provider,
+            error_message=error_message # Store any error that occurred during this scene's generation
+        )
+        self.scenes.append(scene)
+        print(f"DEBUG: story_engine.py - Added scene {self.current_scene_number}: {scene.user_prompt[:30]}")
+        return scene
+    
+    # This method might be redundant if add_scene_from_elements can handle errors
+    # def add_scene_with_error(self, user_prompt: str, error_message: str) -> Scene:
+    #     self.current_scene_number += 1
+    #     scene = Scene(scene_number=self.current_scene_number, user_prompt=user_prompt, error_message=error_message)
+    #     self.scenes.append(scene)
+    #     print(f"DEBUG: story_engine.py - Added scene {self.current_scene_number} WITH ERROR: {error_message}")
+    #     return scene
+
+    def get_last_scene_narrative(self) -> str:
+        if self.scenes and self.scenes[-1].narrative_text and "Error" not in self.scenes[-1].narrative_text:
+            return self.scenes[-1].narrative_text
+        return "" # Return empty if last scene had error or no narrative
+
+    def get_all_scenes_for_gallery_display(self) -> list[tuple[Image.Image, str]]:
+        """Prepares scenes for Gradio Gallery: list of (image, caption)"""
+        gallery_items = []
+        if not self.scenes:
+            # Return a placeholder if no scenes, so gallery doesn't error out
+            placeholder_img = Image.new('RGB', (100,100), color='lightgrey')
+            gallery_items.append((placeholder_img, "No scenes yet. Weave your story!"))
+            return gallery_items
+
+        for scene in self.scenes:
+            caption = f"S{scene.scene_number}: {scene.user_prompt[:40]}..."
+            if scene.image_style_prompt: caption += f"\nStyle: {scene.image_style_prompt}"
+            
+            if scene.error_message:
+                # Create a placeholder image for errors
+                # error_img = Image.new('RGB', (100,100), color='#FFCCCB') # Light red for error
+                # For gallery, might be better to use None for image if error occurred, or a default "error" image
+                # Gradio gallery might handle None gracefully, or you might need a placeholder PIL image.
+                # Let's try None and see how Gradio handles it. If it errors, use a placeholder image.
+                gallery_items.append((None, f"{caption}\n⚠️ Error: {scene.error_message[:100]}..."))
+            elif scene.image:
+                gallery_items.append((scene.image, caption))
+            else: # No image, but no specific error reported for the image part of this scene
+                placeholder_img = Image.new('RGB', (100,100), color='whitesmoke')
+                gallery_items.append((placeholder_img, f"{caption}\n(No image generated for this scene)"))
+        return gallery_items
+
+    def get_latest_scene_details_for_display(self) -> tuple[Image.Image, str]:
+        """Returns (PIL.Image or None, markdown_string_for_narrative) for the latest scene."""
+        if not self.scenes:
+            return None, "No scenes yet. Describe your first scene idea above!"
+
+        ls = self.scenes[-1]
+        latest_image = ls.image if ls.image else None # Will be None if error or no image
+        
+        narrative_display = f"## Scene {ls.scene_number}: {ls.user_prompt}\n\n"
+        if ls.error_message:
+            narrative_display += f"<p style='color:red;'><strong>Generation Error for this scene:</strong><br>{ls.error_message}</p>\n"
+        
+        if ls.image and not ls.error_message : # Only show style if image was successful
+             narrative_display += f"**Style:** {ls.image_style_prompt}\n\n"
+        
+        if ls.narrative_text:
+            if "Error" in ls.narrative_text: # Check if narrative itself is an error message
+                narrative_display += f"<p style='color:orange;'>{ls.narrative_text}</p>"
+            else:
+                narrative_display += ls.narrative_text
+        elif not ls.error_message: # No narrative but no major scene error
+            narrative_display += "(No narrative generated for this scene)."
+            
+        return latest_image, narrative_display
+
+
+    def clear_story(self):
+        self.scenes = []
+        self.current_scene_number = 0
+        print("DEBUG: story_engine.py - Story cleared.")
+
+print("DEBUG: core.story_engine (for StoryVerseWeaver) - Module defined.")