195 lines
7.5 KiB
Python
195 lines
7.5 KiB
Python
import json
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import os
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import time
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from core import config, utils
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from ai import models as ai_models
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def get_style_guidelines():
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defaults = {
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"ai_isms": [
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'testament to', 'tapestry', 'shiver down spine', 'unspoken agreement',
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'palpable tension', 'a sense of', 'suddenly', 'in that moment',
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'symphony of', 'dance of', 'azure', 'cerulean',
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'delved', 'mined', 'neon-lit', 'bustling', 'weaved', 'intricately',
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'a reminder that', 'couldn\'t help but', 'it occurred to',
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'the air was thick with', 'etched in', 'a wave of', 'wash of emotion',
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'intertwined', 'navigate', 'realm', 'in the grand scheme',
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'at the end of the day', 'painting a picture', 'a dance between',
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'the weight of', 'visceral reminder', 'stark reminder',
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'a symphony', 'a mosaic', 'rich tapestry', 'whirlwind of',
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'his/her heart raced', 'time seemed to slow', 'the world fell away',
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'needless to say', 'it goes without saying', 'importantly',
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'it is worth noting', 'commendable', 'meticulous', 'pivotal',
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'in conclusion', 'overall', 'in summary', 'to summarize'
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],
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"filter_words": [
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'felt', 'saw', 'heard', 'realized', 'decided', 'noticed', 'knew', 'thought',
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'wondered', 'seemed', 'appeared', 'looked like', 'watched', 'observed', 'sensed'
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]
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}
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path = os.path.join(config.DATA_DIR, "style_guidelines.json")
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if os.path.exists(path):
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try:
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user_data = utils.load_json(path)
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if user_data:
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if 'ai_isms' in user_data: defaults['ai_isms'] = user_data['ai_isms']
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if 'filter_words' in user_data: defaults['filter_words'] = user_data['filter_words']
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except: pass
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else:
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try:
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with open(path, 'w') as f: json.dump(defaults, f, indent=2)
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except: pass
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return defaults
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def refresh_style_guidelines(model, folder=None):
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utils.log("SYSTEM", "Refreshing Style Guidelines via AI...")
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current = get_style_guidelines()
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prompt = f"""
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ROLE: Literary Editor
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TASK: Update 'Banned Words' lists for AI writing.
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INPUT_DATA:
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- CURRENT_AI_ISMS: {json.dumps(current.get('ai_isms', []))}
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- CURRENT_FILTER_WORDS: {json.dumps(current.get('filter_words', []))}
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INSTRUCTIONS:
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1. Review lists. Remove false positives.
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2. Add new common AI tropes (e.g. 'neon-lit', 'bustling', 'a sense of', 'mined', 'delved').
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3. Ensure robustness.
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OUTPUT_FORMAT (JSON): {{ "ai_isms": [strings], "filter_words": [strings] }}
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"""
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try:
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response = model.generate_content(prompt)
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model_name = getattr(model, 'name', ai_models.logic_model_name)
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if folder: utils.log_usage(folder, model_name, response.usage_metadata)
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new_data = json.loads(utils.clean_json(response.text))
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if 'ai_isms' in new_data and 'filter_words' in new_data:
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path = os.path.join(config.DATA_DIR, "style_guidelines.json")
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with open(path, 'w') as f: json.dump(new_data, f, indent=2)
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utils.log("SYSTEM", "Style Guidelines updated.")
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return new_data
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except Exception as e:
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utils.log("SYSTEM", f"Failed to refresh guidelines: {e}")
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return current
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def create_initial_persona(bp, folder):
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utils.log("SYSTEM", "Generating initial Author Persona based on genre/tone...")
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meta = bp.get('book_metadata', {})
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style = meta.get('style', {})
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prompt = f"""
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ROLE: Creative Director
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TASK: Create a fictional 'Author Persona'.
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METADATA:
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- TITLE: {meta.get('title')}
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- GENRE: {meta.get('genre')}
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- TONE: {style.get('tone')}
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- AUDIENCE: {meta.get('target_audience')}
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OUTPUT_FORMAT (JSON): {{ "name": "Pen Name", "bio": "Description of writing style (voice, sentence structure, vocabulary)...", "age": "...", "gender": "..." }}
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"""
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try:
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response = ai_models.model_logic.generate_content(prompt)
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utils.log_usage(folder, ai_models.model_logic.name, response.usage_metadata)
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return json.loads(utils.clean_json(response.text))
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except Exception as e:
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utils.log("SYSTEM", f"Persona generation failed: {e}")
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return {"name": "AI Author", "bio": "Standard, balanced writing style."}
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def refine_persona(bp, text, folder):
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utils.log("SYSTEM", "Refining Author Persona based on recent chapters...")
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ad = bp.get('book_metadata', {}).get('author_details', {})
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current_bio = ad.get('bio', 'Standard style.')
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prompt = f"""
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ROLE: Literary Stylist
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TASK: Refine Author Bio based on text sample.
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INPUT_DATA:
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- TEXT_SAMPLE: {text[:3000]}
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- CURRENT_BIO: {current_bio}
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GOAL: Ensure future chapters sound exactly like the sample. Highlight quirks, patterns, vocabulary.
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OUTPUT_FORMAT (JSON): {{ "bio": "Updated bio..." }}
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"""
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try:
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response = ai_models.model_logic.generate_content(prompt)
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utils.log_usage(folder, ai_models.model_logic.name, response.usage_metadata)
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new_bio = json.loads(utils.clean_json(response.text)).get('bio')
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if new_bio:
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ad['bio'] = new_bio
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utils.log("SYSTEM", " -> Persona bio updated.")
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return ad
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except: pass
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return ad
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def update_persona_sample(bp, folder):
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utils.log("SYSTEM", "Extracting author persona from manuscript...")
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ms_path = os.path.join(folder, "manuscript.json")
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if not os.path.exists(ms_path): return
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ms = utils.load_json(ms_path)
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if not ms: return
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full_text = "\n".join([c.get('content', '') for c in ms])
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if len(full_text) < 500: return
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if not os.path.exists(config.PERSONAS_DIR): os.makedirs(config.PERSONAS_DIR)
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meta = bp.get('book_metadata', {})
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safe_title = utils.sanitize_filename(meta.get('title', 'book'))[:20]
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timestamp = int(time.time())
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filename = f"sample_{safe_title}_{timestamp}.txt"
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filepath = os.path.join(config.PERSONAS_DIR, filename)
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sample_text = full_text[:3000]
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with open(filepath, 'w', encoding='utf-8') as f: f.write(sample_text)
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author_name = meta.get('author', 'Unknown Author')
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# Use a local file mirror for the engine context (runs outside Flask app context)
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_personas_file = os.path.join(config.PERSONAS_DIR, "personas.json")
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personas = {}
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if os.path.exists(_personas_file):
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try:
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with open(_personas_file, 'r') as f: personas = json.load(f)
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except: pass
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if author_name not in personas:
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utils.log("SYSTEM", f"Generating new persona profile for '{author_name}'...")
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prompt = f"""
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ROLE: Literary Analyst
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TASK: Analyze writing style (Tone, Voice, Vocabulary).
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TEXT: {sample_text[:1000]}
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OUTPUT: 1-sentence author bio.
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"""
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try:
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response = ai_models.model_logic.generate_content(prompt)
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utils.log_usage(folder, ai_models.model_logic.name, response.usage_metadata)
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bio = response.text.strip()
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except: bio = "Style analysis unavailable."
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personas[author_name] = {
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"name": author_name,
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"bio": bio,
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"sample_files": [filename],
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"sample_text": sample_text[:500]
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}
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else:
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utils.log("SYSTEM", f"Updating persona '{author_name}' with new sample.")
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if 'sample_files' not in personas[author_name]: personas[author_name]['sample_files'] = []
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if filename not in personas[author_name]['sample_files']:
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personas[author_name]['sample_files'].append(filename)
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with open(_personas_file, 'w') as f: json.dump(personas, f, indent=2)
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