- core/utils.py: Added estimate_tokens(), truncate_to_tokens(), get_ai_cache(), set_ai_cache(), make_cache_key() utilities - story/writer.py: Applied truncate_to_tokens() to prev_content (2000 tokens) and prev_sum (600 tokens) context injections - story/editor.py: Applied truncate_to_tokens() to summary (1000t), last_chapter_text (800t), eval text (7500t), propagation contexts (2500t/3000t) - web/routes/persona.py: Added MD5-keyed in-memory cache for persona analyze endpoint; truncated sample_text to 750 tokens - ai/models.py: Added pre-dispatch payload size estimation with 30k-token warning threshold Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
151 lines
4.7 KiB
Python
151 lines
4.7 KiB
Python
import os
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import json
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from flask import Blueprint, render_template, request, redirect, url_for, flash
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from flask_login import login_required
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from core import config, utils
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from ai import models as ai_models
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from ai import setup as ai_setup
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persona_bp = Blueprint('persona', __name__)
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@persona_bp.route('/personas')
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@login_required
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def list_personas():
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personas = {}
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if os.path.exists(config.PERSONAS_FILE):
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try:
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with open(config.PERSONAS_FILE, 'r') as f: personas = json.load(f)
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except: pass
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return render_template('personas.html', personas=personas)
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@persona_bp.route('/persona/new')
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@login_required
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def new_persona():
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return render_template('persona_edit.html', persona={}, name="")
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@persona_bp.route('/persona/<string:name>')
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@login_required
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def edit_persona(name):
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personas = {}
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if os.path.exists(config.PERSONAS_FILE):
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try:
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with open(config.PERSONAS_FILE, 'r') as f: personas = json.load(f)
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except: pass
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persona = personas.get(name)
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if not persona:
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flash(f"Persona '{name}' not found.")
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return redirect(url_for('persona.list_personas'))
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return render_template('persona_edit.html', persona=persona, name=name)
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@persona_bp.route('/persona/save', methods=['POST'])
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@login_required
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def save_persona():
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old_name = request.form.get('old_name')
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name = request.form.get('name')
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if not name:
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flash("Persona name is required.")
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return redirect(url_for('persona.list_personas'))
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personas = {}
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if os.path.exists(config.PERSONAS_FILE):
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try:
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with open(config.PERSONAS_FILE, 'r') as f: personas = json.load(f)
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except: pass
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if old_name and old_name != name and old_name in personas:
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del personas[old_name]
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persona = {
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"name": name,
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"bio": request.form.get('bio'),
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"age": request.form.get('age'),
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"gender": request.form.get('gender'),
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"race": request.form.get('race'),
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"nationality": request.form.get('nationality'),
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"language": request.form.get('language'),
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"sample_text": request.form.get('sample_text'),
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"voice_keywords": request.form.get('voice_keywords'),
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"style_inspirations": request.form.get('style_inspirations')
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}
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personas[name] = persona
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with open(config.PERSONAS_FILE, 'w') as f: json.dump(personas, f, indent=2)
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flash(f"Persona '{name}' saved.")
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return redirect(url_for('persona.list_personas'))
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@persona_bp.route('/persona/delete/<string:name>', methods=['POST'])
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@login_required
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def delete_persona(name):
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personas = {}
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if os.path.exists(config.PERSONAS_FILE):
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try:
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with open(config.PERSONAS_FILE, 'r') as f: personas = json.load(f)
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except: pass
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if name in personas:
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del personas[name]
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with open(config.PERSONAS_FILE, 'w') as f: json.dump(personas, f, indent=2)
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flash(f"Persona '{name}' deleted.")
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return redirect(url_for('persona.list_personas'))
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@persona_bp.route('/persona/analyze', methods=['POST'])
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@login_required
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def analyze_persona():
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try: ai_setup.init_models()
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except: pass
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if not ai_models.model_logic:
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return {"error": "AI models not initialized."}, 500
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data = request.json
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sample = data.get('sample_text', '')
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# Cache by a hash of the inputs to avoid redundant API calls for unchanged data
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cache_key = utils.make_cache_key(
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"persona_analyze",
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data.get('name', ''),
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data.get('age', ''),
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data.get('gender', ''),
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data.get('nationality', ''),
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sample[:500]
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)
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cached = utils.get_ai_cache(cache_key)
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if cached:
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return cached
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prompt = f"""
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ROLE: Literary Analyst
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TASK: Create or analyze an Author Persona profile.
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INPUT_DATA:
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- NAME: {data.get('name')}
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- DEMOGRAPHICS: Age: {data.get('age')} | Gender: {data.get('gender')} | Nationality: {data.get('nationality')}
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- SAMPLE_TEXT: {utils.truncate_to_tokens(sample, 750)}
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INSTRUCTIONS:
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1. BIO: Write a 2-3 sentence description of the writing style. If sample is provided, analyze it. If not, invent a style that fits the demographics/name.
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2. KEYWORDS: Comma-separated list of 3-5 adjectives describing the voice (e.g. Gritty, Whimsical, Sarcastic).
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3. INSPIRATIONS: Comma-separated list of 1-3 famous authors or genres that this style resembles.
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OUTPUT_FORMAT (JSON): {{ "bio": "String", "voice_keywords": "String", "style_inspirations": "String" }}
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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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result = json.loads(utils.clean_json(response.text))
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utils.set_ai_cache(cache_key, result)
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return result
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except Exception as e:
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return {"error": str(e)}, 500
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