non-building checkpoint 1
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416
backend/app/services/prompt_service.py
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416
backend/app/services/prompt_service.py
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"""
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Main prompt service that orchestrates prompt generation and management.
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"""
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from typing import List, Dict, Any, Optional
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from datetime import datetime
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from app.core.config import settings
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from app.core.logging import setup_logging
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from app.services.data_service import DataService
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from app.services.ai_service import AIService
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from app.models.prompt import (
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PromptResponse,
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PoolStatsResponse,
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HistoryStatsResponse,
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FeedbackWord,
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FeedbackHistoryItem
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)
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logger = setup_logging()
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class PromptService:
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"""Main service for prompt generation and management."""
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def __init__(self):
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"""Initialize prompt service with dependencies."""
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self.data_service = DataService()
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self.ai_service = AIService()
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# Load settings from config file
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self.settings_config = {}
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# Cache for loaded data
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self._prompts_historic_cache = None
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self._prompts_pool_cache = None
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self._feedback_words_cache = None
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self._feedback_historic_cache = None
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self._prompt_template_cache = None
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self._feedback_template_cache = None
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async def _load_settings_config(self):
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"""Load settings from config file if not already loaded."""
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if not self.settings_config:
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self.settings_config = await self.data_service.load_settings_config()
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async def _get_setting(self, key: str, default: Any) -> Any:
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"""Get setting value, preferring config file over environment."""
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await self._load_settings_config()
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return self.settings_config.get(key, default)
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# Data loading methods with caching
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async def get_prompts_historic(self) -> List[Dict[str, str]]:
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"""Get historic prompts with caching."""
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if self._prompts_historic_cache is None:
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self._prompts_historic_cache = await self.data_service.load_prompts_historic()
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return self._prompts_historic_cache
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async def get_prompts_pool(self) -> List[str]:
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"""Get prompt pool with caching."""
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if self._prompts_pool_cache is None:
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self._prompts_pool_cache = await self.data_service.load_prompts_pool()
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return self._prompts_pool_cache
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async def get_feedback_words(self) -> List[Dict[str, Any]]:
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"""Get feedback words with caching."""
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if self._feedback_words_cache is None:
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self._feedback_words_cache = await self.data_service.load_feedback_words()
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return self._feedback_words_cache
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async def get_feedback_historic(self) -> List[Dict[str, str]]:
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"""Get historic feedback words with caching."""
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if self._feedback_historic_cache is None:
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self._feedback_historic_cache = await self.data_service.load_feedback_historic()
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return self._feedback_historic_cache
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async def get_prompt_template(self) -> str:
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"""Get prompt template with caching."""
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if self._prompt_template_cache is None:
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self._prompt_template_cache = await self.data_service.load_prompt_template()
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return self._prompt_template_cache
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async def get_feedback_template(self) -> str:
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"""Get feedback template with caching."""
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if self._feedback_template_cache is None:
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self._feedback_template_cache = await self.data_service.load_feedback_template()
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return self._feedback_template_cache
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# Core prompt operations
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async def draw_prompts_from_pool(self, count: Optional[int] = None) -> List[str]:
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"""
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Draw prompts from the pool.
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Args:
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count: Number of prompts to draw
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Returns:
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List of drawn prompts
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"""
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if count is None:
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count = await self._get_setting('num_prompts', settings.NUM_PROMPTS_PER_SESSION)
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pool = await self.get_prompts_pool()
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if len(pool) < count:
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raise ValueError(
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f"Pool only has {len(pool)} prompts, requested {count}. "
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f"Use fill-pool endpoint to add more prompts."
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)
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# Draw prompts from the beginning of the pool
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drawn_prompts = pool[:count]
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remaining_pool = pool[count:]
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# Update cache and save
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self._prompts_pool_cache = remaining_pool
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await self.data_service.save_prompts_pool(remaining_pool)
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logger.info(f"Drew {len(drawn_prompts)} prompts from pool, {len(remaining_pool)} remaining")
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return drawn_prompts
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async def fill_pool_to_target(self) -> int:
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"""
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Fill the prompt pool to target volume.
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Returns:
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Number of prompts added
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"""
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target_volume = await self._get_setting('cached_pool_volume', settings.CACHED_POOL_VOLUME)
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current_pool = await self.get_prompts_pool()
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current_size = len(current_pool)
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if current_size >= target_volume:
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logger.info(f"Pool already at target volume: {current_size}/{target_volume}")
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return 0
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prompts_needed = target_volume - current_size
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logger.info(f"Generating {prompts_needed} prompts to fill pool")
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# Generate prompts
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new_prompts = await self.generate_prompts(
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count=prompts_needed,
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use_history=True,
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use_feedback=True
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)
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if not new_prompts:
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logger.error("Failed to generate prompts for pool")
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return 0
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# Add to pool
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updated_pool = current_pool + new_prompts
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self._prompts_pool_cache = updated_pool
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await self.data_service.save_prompts_pool(updated_pool)
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added_count = len(new_prompts)
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logger.info(f"Added {added_count} prompts to pool, new size: {len(updated_pool)}")
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return added_count
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async def generate_prompts(
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self,
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count: Optional[int] = None,
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use_history: bool = True,
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use_feedback: bool = True
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) -> List[str]:
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"""
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Generate new prompts using AI.
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Args:
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count: Number of prompts to generate
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use_history: Whether to use historic prompts as context
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use_feedback: Whether to use feedback words as context
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Returns:
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List of generated prompts
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"""
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if count is None:
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count = await self._get_setting('num_prompts', settings.NUM_PROMPTS_PER_SESSION)
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min_length = await self._get_setting('min_length', settings.MIN_PROMPT_LENGTH)
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max_length = await self._get_setting('max_length', settings.MAX_PROMPT_LENGTH)
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# Load templates and data
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prompt_template = await self.get_prompt_template()
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if not prompt_template:
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raise ValueError("Prompt template not found")
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historic_prompts = await self.get_prompts_historic() if use_history else []
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feedback_words = await self.get_feedback_words() if use_feedback else None
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# Generate prompts using AI
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new_prompts = await self.ai_service.generate_prompts(
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prompt_template=prompt_template,
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historic_prompts=historic_prompts,
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feedback_words=feedback_words,
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count=count,
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min_length=min_length,
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max_length=max_length
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)
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return new_prompts
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async def add_prompt_to_history(self, prompt_text: str) -> str:
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"""
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Add a prompt to the historic prompts cyclic buffer.
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Args:
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prompt_text: Prompt text to add
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Returns:
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Position key of the added prompt (e.g., "prompt00")
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"""
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historic_prompts = await self.get_prompts_historic()
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# Create the new prompt object
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new_prompt = {"prompt00": prompt_text}
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# Shift all existing prompts down by one position
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updated_prompts = [new_prompt]
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# Add all existing prompts, shifting their numbers down by one
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for i, prompt_dict in enumerate(historic_prompts):
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if i >= settings.HISTORY_BUFFER_SIZE - 1: # Keep only HISTORY_BUFFER_SIZE prompts
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break
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# Get the prompt text
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prompt_key = list(prompt_dict.keys())[0]
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prompt_text = prompt_dict[prompt_key]
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# Create prompt with new number (shifted down by one)
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new_prompt_key = f"prompt{i+1:02d}"
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updated_prompts.append({new_prompt_key: prompt_text})
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# Update cache and save
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self._prompts_historic_cache = updated_prompts
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await self.data_service.save_prompts_historic(updated_prompts)
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logger.info(f"Added prompt to history as prompt00, history size: {len(updated_prompts)}")
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return "prompt00"
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# Statistics methods
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async def get_pool_stats(self) -> PoolStatsResponse:
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"""Get statistics about the prompt pool."""
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pool = await self.get_prompts_pool()
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total_prompts = len(pool)
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prompts_per_session = await self._get_setting('num_prompts', settings.NUM_PROMPTS_PER_SESSION)
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target_pool_size = await self._get_setting('cached_pool_volume', settings.CACHED_POOL_VOLUME)
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available_sessions = total_prompts // prompts_per_session if prompts_per_session > 0 else 0
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needs_refill = total_prompts < target_pool_size
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return PoolStatsResponse(
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total_prompts=total_prompts,
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prompts_per_session=prompts_per_session,
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target_pool_size=target_pool_size,
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available_sessions=available_sessions,
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needs_refill=needs_refill
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)
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async def get_history_stats(self) -> HistoryStatsResponse:
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"""Get statistics about prompt history."""
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historic_prompts = await self.get_prompts_historic()
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total_prompts = len(historic_prompts)
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history_capacity = settings.HISTORY_BUFFER_SIZE
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available_slots = max(0, history_capacity - total_prompts)
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is_full = total_prompts >= history_capacity
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return HistoryStatsResponse(
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total_prompts=total_prompts,
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history_capacity=history_capacity,
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available_slots=available_slots,
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is_full=is_full
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)
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async def get_prompt_history(self, limit: Optional[int] = None) -> List[PromptResponse]:
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"""
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Get prompt history.
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Args:
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limit: Maximum number of history items to return
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Returns:
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List of historical prompts
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"""
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historic_prompts = await self.get_prompts_historic()
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if limit is not None:
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historic_prompts = historic_prompts[:limit]
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prompts = []
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for i, prompt_dict in enumerate(historic_prompts):
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prompt_key = list(prompt_dict.keys())[0]
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prompt_text = prompt_dict[prompt_key]
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prompts.append(PromptResponse(
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key=prompt_key,
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text=prompt_text,
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position=i
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))
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return prompts
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# Feedback operations
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async def generate_theme_feedback_words(self) -> List[str]:
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"""Generate 6 theme feedback words using AI."""
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feedback_template = await self.get_feedback_template()
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if not feedback_template:
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raise ValueError("Feedback template not found")
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historic_prompts = await self.get_prompts_historic()
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if not historic_prompts:
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raise ValueError("No historic prompts available for feedback analysis")
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current_feedback_words = await self.get_feedback_words()
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historic_feedback_words = await self.get_feedback_historic()
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theme_words = await self.ai_service.generate_theme_feedback_words(
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feedback_template=feedback_template,
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historic_prompts=historic_prompts,
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current_feedback_words=current_feedback_words,
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historic_feedback_words=historic_feedback_words
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)
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return theme_words
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async def update_feedback_words(self, ratings: Dict[str, int]) -> List[FeedbackWord]:
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"""
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Update feedback words with new ratings.
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Args:
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ratings: Dictionary of word to rating (0-6)
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Returns:
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Updated feedback words
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"""
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if len(ratings) != 6:
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raise ValueError(f"Expected 6 ratings, got {len(ratings)}")
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feedback_items = []
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for i, (word, rating) in enumerate(ratings.items()):
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if not 0 <= rating <= 6:
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raise ValueError(f"Rating for '{word}' must be between 0 and 6, got {rating}")
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feedback_key = f"feedback{i:02d}"
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feedback_items.append({
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feedback_key: word,
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"weight": rating
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})
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# Update cache and save
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self._feedback_words_cache = feedback_items
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await self.data_service.save_feedback_words(feedback_items)
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# Also add to historic feedback
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await self._add_feedback_words_to_history(feedback_items)
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# Convert to FeedbackWord models
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feedback_words = []
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for item in feedback_items:
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key = list(item.keys())[0]
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word = item[key]
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weight = item["weight"]
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feedback_words.append(FeedbackWord(key=key, word=word, weight=weight))
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logger.info(f"Updated feedback words with {len(feedback_words)} items")
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return feedback_words
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async def _add_feedback_words_to_history(self, feedback_items: List[Dict[str, Any]]) -> None:
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"""Add feedback words to historic buffer."""
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historic_feedback = await self.get_feedback_historic()
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# Extract just the words from current feedback
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new_feedback_words = []
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for i, item in enumerate(feedback_items):
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feedback_key = f"feedback{i:02d}"
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if feedback_key in item:
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word = item[feedback_key]
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new_feedback_words.append({feedback_key: word})
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if len(new_feedback_words) != 6:
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logger.warning(f"Expected 6 feedback words, got {len(new_feedback_words)}. Not adding to history.")
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return
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# Shift all existing feedback words down by 6 positions
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updated_feedback_historic = new_feedback_words
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# Add all existing feedback words, shifting their numbers down by 6
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for i, feedback_dict in enumerate(historic_feedback):
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if i >= settings.FEEDBACK_HISTORY_SIZE - 6: # Keep only FEEDBACK_HISTORY_SIZE items
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break
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feedback_key = list(feedback_dict.keys())[0]
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word = feedback_dict[feedback_key]
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new_feedback_key = f"feedback{i+6:02d}"
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updated_feedback_historic.append({new_feedback_key: word})
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# Update cache and save
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self._feedback_historic_cache = updated_feedback_historic
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await self.data_service.save_feedback_historic(updated_feedback_historic)
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logger.info(f"Added 6 feedback words to history, history size: {len(updated_feedback_historic)}")
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# Utility methods for API endpoints
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def get_pool_size(self) -> int:
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"""Get current pool size (synchronous for API endpoints)."""
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if self._prompts_pool_cache is None:
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raise RuntimeError("Pool cache not initialized")
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return len(self._prompts_pool_cache)
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def get_target_volume(self) -> int:
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"""Get target pool volume (synchronous for API endpoints)."""
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return settings.CACHED_POOL_VOLUME
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