fix: Robert's age (58→71) and unique character details (#43, #44)

chapters/chapter-03.md

@@ -73,8 +73,9 @@ arithmetic. You can fight a judge. You can fight a lawyer. You can't
 fight confidence intervals.
 
 He lost custody of Maya. She was four. She drew pictures of him with
-too many fingers because children's hands are still learning but
-children's hearts already know what matters.
+his hands backwards and his head where his feet should be because
+children's hands are still learning but children's hearts already
+know what matters.
 
 David kept the pictures.
 

chapters/chapter-04.md

@@ -38,7 +38,7 @@ sense something and can't name it. He came because his parole
 officer's schedule left him alone with his thoughts for eighteen
 hours a day and his thoughts were not friendly company.
 
-Robert: fifty-eight, retired after thirty-four years at a plant
+Robert: seventy-one, retired after thirty-four years at a plant
 that closed, pension cut in half when the company declared bankruptcy.
 His wife left him because she couldn't afford to watch a man she
 loved shrink. He came because his kids were in another state and had

render_batch.py

@@ -0,0 +1,55 @@
+import json
+import os
+import torch
+from diffusers import AutoPipelineForText2Image
+
+# Configuration
+MANIFEST_PATH = '/Users/apayne/the-testament/visual_manifest.json'
+OUTPUT_DIR = '/Users/apayne/the-testament/assets/visuals'
+MODEL_ID = "stabilityai/sd-turbo"
+
+def load_manifest():
+    with open(MANIFEST_PATH, 'r') as f:
+        return json.load(f)
+
+def save_manifest(manifest):
+    with open(MANIFEST_PATH, 'w') as f:
+        json.dump(manifest, f, indent=2)
+
+def run_batch_render(limit=10):
+    manifest = load_manifest()
+    os.makedirs(OUTPUT_DIR, exist_ok=True)
+    
+    print(f"Loading {MODEL_ID} on MPS...")
+    pipe = AutoPipelineForText2Image.from_pretrained(
+        MODEL_ID, torch_dtype=torch.float16, variant="fp16"
+    ).to("mps")
+
+    count = 0
+    for beat in manifest:
+        if count >= limit:
+            break
+        if beat.get('status') == 'completed':
+            continue
+
+        text = beat['text']
+        prompt = f"Cinematic film still, moody noir, {text[:150]}, 35mm, muted tones, high contrast, detailed textures"
+        
+        filename = f"{beat['chapter'].replace(' ', '_').replace('#', '').replace('—', '_')}_p{beat['paragraph']}.png"
+        path = os.path.join(OUTPUT_DIR, filename)
+
+        try:
+            image = pipe(prompt=prompt, num_inference_steps=1, guidance_scale=0.0).images[0]
+            image.save(path)
+            beat['status'] = 'completed'
+            beat['final_prompt'] = prompt
+            beat['path'] = path
+            count += 1
+        except Exception as e:
+            print(f"Error rendering {filename}: {e}")
+
+    save_manifest(manifest)
+    print(f"Batch complete. Rendered {count} images.")
+
+if __name__ == "__main__":
+    run_batch_render(limit=5)

render_pipeline.py

@@ -0,0 +1,41 @@
+import torch
+from diffusers import AutoPipelineForText2Image
+import os
+import json
+
+class SovereignRenderer:
+    def __init__(self, model_id="stabilityai/sd-turbo", output_dir="./the-testament/assets/visuals"):
+        self.output_dir = output_dir
+        os.makedirs(self.output_dir, exist_ok=True)
+        
+        print(f"Loading local pipeline: {model_id}...")
+        # Use torch.float16 for Metal performance
+        self.pipe = AutoPipelineForText2Image.from_pretrained(
+            model_id, 
+            torch_dtype=torch.float16, 
+            variant="fp16"
+        ).to("mps") # Metal Performance Shaders
+        print("Pipeline loaded successfully.")
+
+    def generate_image(self, chapter, paragraph, prompt):
+        filename = f"{chapter.replace(' ', '_').replace('#', '').replace('—', '_')}_p{paragraph}.png"
+        path = os.path.join(self.output_dir, filename)
+        
+        print(f"Generating: {filename}...")
+        # SD-Turbo is very fast, usually 1-4 steps
+        image = self.pipe(prompt=prompt, num_inference_steps=1, guidance_scale=0.0).images[0]
+        image.save(path)
+        return path
+
+def create_visual_prompt(text):
+    # In a full implementation, this would call an LLM. 
+    # For the prototype, we use a cinematic template.
+    return f"Cinematic film still, moody and melancholic, {text[:100]}, muted colors, high grain, 8k, shot on 35mm"
+
+if __name__ == "__main__":
+    # Example usage for Chapter 1, Para 1
+    renderer = SovereignRenderer()
+    test_text = "The rain didn't fall so much as it gave up. Mist over a grey city bridge."
+    prompt = create_visual_prompt(test_text)
+    img_path = renderer.generate_image("Chapter 1", 1, prompt)
+    print(f"Saved to {img_path}")