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import streamlit as st
import time
import joblib
import google.generativeai as genai
class SessionState:
"""
Clase para gestionar el estado de la sesión de Streamlit de manera centralizada.
Encapsula todas las operaciones relacionadas con st.session_state.
"""
def __init__(self):
# Inicializar valores por defecto si no existen
if 'chat_id' not in st.session_state:
st.session_state.chat_id = None
if 'chat_title' not in st.session_state:
st.session_state.chat_title = None
if 'messages' not in st.session_state:
st.session_state.messages = []
if 'gemini_history' not in st.session_state:
st.session_state.gemini_history = []
if 'model' not in st.session_state:
st.session_state.model = None
if 'chat' not in st.session_state:
st.session_state.chat = None
if 'prompt' not in st.session_state:
st.session_state.prompt = None
self.avatar_analysis = AvatarAnalysis()
# Getters y setters para cada propiedad
@property
def chat_id(self):
return st.session_state.chat_id
@chat_id.setter
def chat_id(self, value):
st.session_state.chat_id = value
@property
def chat_title(self):
return st.session_state.chat_title
@chat_title.setter
def chat_title(self, value):
st.session_state.chat_title = value
@property
def messages(self):
return st.session_state.messages
@messages.setter
def messages(self, value):
st.session_state.messages = value
@property
def gemini_history(self):
return st.session_state.gemini_history
@gemini_history.setter
def gemini_history(self, value):
st.session_state.gemini_history = value
@property
def model(self):
return st.session_state.model
@model.setter
def model(self, value):
st.session_state.model = value
@property
def chat(self):
return st.session_state.chat
@chat.setter
def chat(self, value):
st.session_state.chat = value
@property
def prompt(self):
return st.session_state.prompt
@prompt.setter
def prompt(self, value):
st.session_state.prompt = value
# Métodos de utilidad
def add_message(self, role, content, avatar=None):
"""Añade un mensaje al historial"""
message = {
'role': role,
'content': content,
}
if avatar:
message['avatar'] = avatar
self.messages.append(message)
def clear_prompt(self):
"""Limpia el prompt del estado de la sesión"""
self.prompt = None
def initialize_model(self, model_name='gemini-2.0-flash'):
"""Inicializa el modelo de IA"""
self.model = genai.GenerativeModel(model_name)
def initialize_chat(self, history=None):
"""Inicializa el chat con el modelo"""
if history is None:
history = self.gemini_history
self.chat = self.model.start_chat(history=history)
def generate_chat_title(self, prompt, model_name='gemini-2.0-flash'):
"""Genera un título para el chat basado en el primer mensaje"""
try:
title_generator = genai.GenerativeModel(model_name)
title_response = title_generator.generate_content(
f"Genera un título corto (máximo 5 palabras) que describa de qué trata esta consulta, sin usar comillas ni puntuación: '{prompt}'")
return title_response.text.strip()
except Exception as e:
print(f"Error al generar título: {e}")
return None
def save_chat_history(self, chat_id=None):
"""Guarda el historial del chat"""
if chat_id is None:
chat_id = self.chat_id
joblib.dump(self.messages, f'data/{chat_id}-st_messages')
joblib.dump(self.gemini_history, f'data/{chat_id}-gemini_messages')
def load_chat_history(self, chat_id=None):
"""Carga el historial del chat"""
if chat_id is None:
chat_id = self.chat_id
try:
self.messages = joblib.load(f'data/{chat_id}-st_messages')
self.gemini_history = joblib.load(f'data/{chat_id}-gemini_messages')
return True
except:
self.messages = []
self.gemini_history = []
return False
def has_messages(self):
"""Verifica si hay mensajes en el historial"""
return len(self.messages) > 0
def has_prompt(self):
"""Verifica si hay un prompt en el estado de la sesión"""
return self.prompt is not None and self.prompt.strip() != ""
class AvatarAnalysis:
def __init__(self):
self.basic_profile = {
"who": None,
"what": None,
"age": None
}
self.main_pain = None
self.main_desire = None
self.obstacles = None
self.motivations = None
def update_profile(self, key, value):
if key in self.basic_profile:
self.basic_profile[key] = value
def save_avatar_analysis(self):
"""Guarda el análisis del avatar en el historial"""
analysis_data = {
'avatar_analysis': self.avatar_analysis.__dict__
}
# Guardar junto con el historial del chat
def load_avatar_analysis(self):
"""Carga el análisis del avatar del historial"""
# Cargar junto con el historial del chat |