- Introduction of dynamic Processors - Introduction of caching system - Introduction of a better template manager - Adaptation of ModelVariables to support dynamic Processors / Retrievers / Specialists - Start adaptation of chat client
193 lines
6.7 KiB
Python
193 lines
6.7 KiB
Python
# common/utils/cache/chat_session_handler.py
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from typing import Dict, List, Any, Optional
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from datetime import datetime as dt, timezone as tz
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from dataclasses import dataclass
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from flask import current_app
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from sqlalchemy.exc import SQLAlchemyError
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from sqlalchemy.orm import joinedload
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from common.extensions import db, cache_manager
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from common.models.interaction import ChatSession, Interaction
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from common.utils.cache.base import CacheHandler
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@dataclass
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class CachedInteraction:
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"""Lightweight representation of an interaction for history purposes"""
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specialist_arguments: Dict[str, Any] # Contains the original question and other arguments
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specialist_results: Dict[str, Any] # Contains detailed question, answer and other results
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@dataclass
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class CachedSession:
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"""Cached representation of a chat session with its interactions"""
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id: int
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session_id: str
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interactions: List[CachedInteraction]
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timezone: str
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class ChatSessionCacheHandler(CacheHandler[CachedSession]):
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"""Handles caching of chat sessions focused on interaction history"""
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handler_name = 'chat_session_cache'
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def __init__(self, region):
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super().__init__(region, 'chat_session')
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self.configure_keys('session_id')
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def get_cached_session(self, session_id: str, *, create_params: Optional[Dict[str, Any]] = None) -> CachedSession:
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"""
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Get or create a cached session with its interaction history.
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If not in cache, loads from database and caches it.
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Args:
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session_id: The session identifier
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create_params: Optional parameters for session creation if it doesn't exist.
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Must include 'timezone' if provided.
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Returns:
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CachedSession with interaction history
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"""
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def creator_func(session_id: str) -> CachedSession:
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# Load session and interactions from database
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session = (
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ChatSession.query
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.options(joinedload(ChatSession.interactions))
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.filter_by(session_id=session_id)
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.first()
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)
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if not session:
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if not create_params:
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raise ValueError(f"Chat session {session_id} not found and no creation parameters provided")
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if 'timezone' not in create_params:
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raise ValueError("timezone is required in create_params for new session creation")
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# Create new session
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session = ChatSession(
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session_id=session_id,
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session_start=dt.now(tz.utc),
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timezone=create_params['timezone']
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)
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try:
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db.session.add(session)
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db.session.commit()
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except SQLAlchemyError as e:
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db.session.rollback()
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raise ValueError(f"Failed to create new session: {str(e)}")
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# Convert to cached format
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cached_interactions = [
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CachedInteraction(
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specialist_arguments=interaction.specialist_arguments,
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specialist_results=interaction.specialist_results
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)
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for interaction in session.interactions
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if interaction.specialist_results is not None # Only include completed interactions
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]
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return CachedSession(
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id=session.id,
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session_id=session_id,
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interactions=cached_interactions,
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timezone=session.timezone
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)
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return self.get(creator_func, session_id=session_id)
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def add_completed_interaction(self, session_id: str, interaction: Interaction) -> None:
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"""
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Add a completed interaction to the cached session history.
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Should only be called once the interaction has an answer.
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Args:
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session_id: The session identifier
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interaction: The completed interaction to add
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Note:
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Only adds the interaction if it has an answer
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"""
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if not interaction.specialist_results:
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return # Skip incomplete interactions
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try:
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cached_session = self.get_cached_session(session_id)
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# Add new interaction to cache
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cached_session.interactions.append(
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CachedInteraction(
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specialist_arguments=interaction.specialist_arguments,
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specialist_results=interaction.specialist_results,
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)
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)
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# Force cache update
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self.invalidate(session_id=session_id)
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except ValueError:
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# If session not in cache yet, load it fresh from DB
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self.get_cached_session(session_id)
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def to_cache_data(self, instance: CachedSession) -> Dict[str, Any]:
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"""Convert CachedSession to cache data"""
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return {
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'id': instance.id,
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'session_id': instance.session_id,
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'timezone': instance.timezone,
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'interactions': [
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{
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'specialist_arguments': interaction.specialist_arguments,
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'specialist_results': interaction.specialist_results,
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}
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for interaction in instance.interactions
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],
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'last_updated': dt.now(tz=tz.utc).isoformat()
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}
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def from_cache_data(self, data: Dict[str, Any], session_id: str, **kwargs) -> CachedSession:
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"""Create CachedSession from cache data"""
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interactions = [
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CachedInteraction(
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specialist_arguments=int_data['specialist_arguments'],
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specialist_results=int_data['specialist_results']
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)
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for int_data in data['interactions']
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]
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return CachedSession(
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id=data['id'],
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session_id=data['session_id'],
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interactions=interactions,
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timezone=data['timezone']
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)
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def should_cache(self, value: Dict[str, Any]) -> bool:
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"""Validate cache data"""
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required_fields = {'id','session_id', 'timezone', 'interactions'}
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return all(field in value for field in required_fields)
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# Register the handler with the cache manager
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cache_manager.register_handler(ChatSessionCacheHandler, 'eveai_chat_workers')
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# Helper function similar to get_model_variables
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def get_chat_history(session_id: str) -> CachedSession:
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"""
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Get cached chat history for a session, loading from database if needed
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Args:
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session_id: Session ID to look up
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Returns:
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CachedSession with interaction history
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Raises:
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ValueError: If session doesn't exist
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"""
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return cache_manager.chat_session_cache.get_cached_session(session_id) |