Update memory paths for Docker volume persistence

Backup code/app_V18.py

@@ -0,0 +1,1040 @@
+# -*- coding:utf-8 -*-
+
+import os
+import sys
+import json
+import time
+import copy
+import shutil
+import signal
+import logging
+import platform
+import re
+
+import gradio as gr
+import nltk
+import torch
+import tiktoken
+
+from openai import OpenAI as OpenAIClient
+from llama_index.embeddings.openai import OpenAIEmbedding
+
+# from langchain_openai import ChatOpenAI, OpenAI as LangChainOpenAI # (If not used, can be commented out)
+from llama_index.llms.openai import OpenAI as LlamaIndexOpenAI
+from llama_index.core import Settings
+from llama_index.core.indices.prompt_helper import PromptHelper
+
+prompt_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), '../')
+sys.path.append(prompt_path)
+
+# Assuming these imports exist in your local environment
+from utils.sys_args import data_args, model_args
+from utils.app_modules.utils import *
+from utils.app_modules.presets import *
+from utils.app_modules.overwrites import *
+from utils.prompt_utils import *
+from utils.memory_utils import (
+    enter_name_llamaindex,
+    summarize_memory_event_personality,
+    save_local_memory,
+    extract_session_summary,
+    extract_semantic_memory,
+)
+
+# Ensure NLTK data path
+nltk.data.path = [os.path.join(os.path.dirname(__file__), "nltk_data")] + nltk.data.path
+
+tokenizer = tiktoken.get_encoding("cl100k_base")
+
+GAPGPT_BASE_URL = os.getenv("GAPGPT_BASE_URL", "https://api.gapgpt.app/v1")
+openai_client_cache = {}
+
+import torch
+import torch.nn.functional as F
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+
+
+LOCAL_MODEL_PATH = os.path.join(os.path.dirname(os.path.abspath(__file__)), "Classification_Model", "final_xlm_r_model_router")
+
+print(f"Loading model from: {LOCAL_MODEL_PATH}")
+
+try:
+    _tokenizer = AutoTokenizer.from_pretrained(LOCAL_MODEL_PATH)
+    _classifier_model = AutoModelForSequenceClassification.from_pretrained(LOCAL_MODEL_PATH)
+    _classifier_model.eval()
+    print("Local classifier loaded successfully.")
+except Exception as e:
+    print(f"Error loading local classifier: {e}")
+
+
+def get_gapgpt_client(api_key: str) -> OpenAIClient:
+    if not api_key:
+        raise ValueError("API key is missing while attempting to create a GapGPT client.")
+    if api_key not in openai_client_cache:
+        openai_client_cache[api_key] = OpenAIClient(api_key=api_key, base_url=GAPGPT_BASE_URL)
+    return openai_client_cache[api_key]
+
+
+os_name = platform.system()
+clear_command = 'cls' if os_name == 'Windows' else 'clear'
+stop_stream = False
+
+
+def signal_handler(signal_number, frame):
+    global stop_stream
+    stop_stream = True
+
+
+VECTOR_SEARCH_TOP_K = 2
+
+# Update this path to your actual file location
+api_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "data", "api_key_list.txt")
+
+
+def read_apis(path):
+    api_keys_local = []
+    if os.path.exists(path):
+        with open(path, 'r', encoding='utf8') as f:
+            for line in f:
+                line = line.strip()
+                if line:
+                    api_keys_local.append(line)
+    return api_keys_local
+
+
+memory_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), "data", "memories", "update_memory_0512_eng.json")
+
+# Ensure directory exists
+os.makedirs(os.path.dirname(memory_dir), exist_ok=True)
+
+if not os.path.exists(memory_dir):
+    json.dump({}, open(memory_dir, "w", encoding="utf-8"))
+
+global memory
+memory = json.load(open(memory_dir, "r", encoding="utf-8"))
+language = 'en'
+user_keyword = generate_user_keyword()[language]
+ai_keyword = generate_ai_keyword()[language]
+boot_name = boot_name_dict[language]
+boot_actual_name = boot_actual_name_dict[language]
+meta_prompt = generate_meta_prompt_dict_chatgpt()[language]
+meta_prompt_semantic = generate_meta_prompt_dict_semantic_chatgpt()[language]
+meta_prompt_semantic_episodic = generate_meta_prompt_dict_semantic_episodic_chatgpt()[language]
+new_user_meta_prompt = generate_new_user_meta_prompt_dict_chatgpt()[language]
+
+api_keys = read_apis(api_path)
+# Fallback if file is empty or missing for testing purposes
+if not api_keys:
+    print(f"Warning: No API keys found in {api_path}.")
+
+new_conversation = False
+chatgpt_config = {
+    "model": "gpt-4o",
+    "temperature": 1,
+    "max_tokens": 1024,
+    "top_p": 0.95,
+    "frequency_penalty": 0.4,
+    "presence_penalty": 0.2,
+    "n": 1,
+}
+
+deactivated_keys = []
+logging.basicConfig(
+    level=logging.DEBUG,
+    format="%(asctime)s [%(levelname)s] [%(filename)s:%(lineno)d] %(message)s",
+)
+
+
+def chatgpt_chat(prompt, system, history, gpt_config, api_index=0):
+    """
+    Handles the chat request to OpenAI.
+    History is expected to be a list of dictionaries: [{'role': 'user', 'content': '...'}, ...]
+    """
+    retry_times, count = 5, 0
+    response = None
+
+    while response is None and count < retry_times:
+        try:
+            request = copy.deepcopy(gpt_config)
+            
+            # Initial system and greeting messages
+            if data_args.language == 'en':
+                message = [
+                    {"role": "system", "content": system.strip()},
+                    {"role": "user", "content": "Hi!"},
+                    {"role": "assistant",
+                     "content": f"Hi! I'm {boot_actual_name}! I will give you warm companion!"},
+                ]
+            else:
+                message = [
+                    {"role": "system", "content": system.strip()},
+                    {"role": "user", "content": "Hi"},
+                    {"role": "assistant",
+                     "content": f"Hi! I'm {boot_actual_name}! I will give you warm companion!"},
+                ]
+
+            # --- FIX: Handle History as List of Dicts ---
+            if history:
+                # Verify if history is old format (list of lists) or new (list of dicts)
+                if isinstance(history[0], list):
+                     # Convert old format temporarily if encountered
+                     for q, a in history:
+                         message.append({"role": "user", "content": str(q)})
+                         message.append({"role": "assistant", "content": str(a)})
+                elif isinstance(history[0], dict):
+                    # New format
+                    for msg in history:
+                        if msg.get('role') in ['user', 'assistant']:
+                            message.append(msg)
+
+            # Add the current prompt
+            message.append({"role": "user", "content": f"{prompt}"})
+
+            if not api_keys:
+                return "Error: No API Keys available."
+                
+            client = get_gapgpt_client(api_keys[api_index])
+            
+            # New OpenAI 1.x Syntax
+            response = client.chat.completions.create(messages=message, **request)
+
+        except Exception as e:
+            print(f"Chat Error: {e}")
+            if 'This key is associated with a deactivated account' in str(e):
+                deactivated_keys.append(api_keys[api_index])
+
+            if api_keys:
+                api_index = api_index + 1 if api_index < len(api_keys) - 1 else 0
+                loop_check = 0
+                while api_keys[api_index] in deactivated_keys and loop_check < len(api_keys):
+                    api_index = api_index + 1 if api_index < len(api_keys) - 1 else 0
+                    loop_check += 1
+            count += 1
+
+    if response:
+        response = response.choices[0].message.content
+    else:
+        response = ''
+    return response
+
+
+def classify_query_local(text):
+  
+    
+    # 0: episodic, 1: semantic, 2: semantic_episodic, 3: unrelated
+    id2label_map = {
+        0: "episodic_memory",
+        1: "semantic_memory",
+        2: "semantic-episodic",  
+        3: "unknown"             
+    }
+
+    try:
+       
+        inputs = _tokenizer(
+            text, 
+            return_tensors="pt", 
+            truncation=True, 
+            padding=True, 
+            max_length=512
+        )
+        
+        
+       
+        with torch.no_grad():
+            outputs = _classifier_model(**inputs)
+        
+        
+        logits = outputs.logits
+        probabilities = F.softmax(logits, dim=-1)
+        predicted_class_id = torch.argmax(probabilities, dim=-1).item()
+        
+        
+        category = id2label_map.get(predicted_class_id, "unknown")
+        
+        print(f"Local Classifier: '{text}' -> {category} (Class ID: {predicted_class_id})")
+        return category
+
+    except Exception as e:
+        print(f"Error in local classification: {e}")
+        return "unknown"
+
+
+
+def classify_query_openai(text, gpt_config, api_index=0, retry_times=5):
+    response = None
+    count = 0
+    local_deactivated = []
+    print("text********:", text)
+
+    system_prompt = """
+You are an AI that classifies user queries into one of the following memory types:
+- 'episodic_memory': Queries about past personal events, daily life logs, or specific experiences the user has shared (e.g., "What did I eat yesterday?", "Tell me about my trip").
+- 'semantic_memory': Queries about facts, preferences, general knowledge the user has taught you, or summaries of their personality (e.g., "What is my favorite color?", "Do I like sci-fi movies?").
+- 'semantic-episodic': Complex queries requiring both specific past events and general facts/preferences (e.g., "Based on my food preferences, did I enjoy the dinner last night?").
+
+Output ONLY one of these three strings: 'episodic_memory', 'semantic_memory', or 'semantic-episodic'. If unsure, output 'episodic_memory'.
+    """.strip()
+    
+    if not api_keys:
+        return "unknown"
+
+    while response is None and count < retry_times:
+        try:
+            client = get_gapgpt_client(api_keys[api_index])
+            
+            # New OpenAI 1.x Syntax
+            response = client.chat.completions.create(
+                messages=[
+                    {"role": "system", "content": system_prompt},
+                    {"role": "user", "content": text.strip()},
+                ],
+                **copy.deepcopy(gpt_config),
+            )
+        except Exception as e:
+            print(f"Classify Error: {e}")
+            if "This key is associated with a deactivated account" in str(e):
+                local_deactivated.append(api_keys[api_index])
+
+            api_index = api_index + 1 if api_index < len(api_keys) - 1 else 0
+            while api_keys[api_index] in local_deactivated:
+                api_index = api_index + 1 if api_index < len(api_keys) - 1 else 0
+            count += 1
+
+    if response:
+        category = response.choices[0].message.content.strip().lower()
+        # Basic cleanup
+        if "semantic_memory" in category: category = "semantic_memory"
+        elif "semantic-episodic" in category: category = "semantic-episodic"
+        elif "episodic_memory" in category: category = "episodic_memory"
+        else: category = "unknown"
+    else:
+        category = "unknown"
+
+    return category
+
+
+def predict_new(
+    text,
+    history,
+    top_p,
+    temperature,
+    max_length_tokens,
+    max_context_length_tokens,
+    user_name,
+    user_memory,
+    user_memory_index,
+    service_context,
+    api_index,
+    semantic_memory_text,
+    query_category,
+    user_profile=None
+     
+
+):
+    chatgpt_cfg = {
+        "model": "gpt-4o",
+        "temperature": temperature,
+        "max_tokens": max_length_tokens,
+        "top_p": top_p,
+        "frequency_penalty": 0.4,
+        "presence_penalty": 0.2,
+        "n": 1,
+    }
+
+    if text == "":
+        # Return same history if empty input
+        return history, history, "Empty context."
+        
+    # Ensure history is initialized
+    if history is None:
+        history = []
+
+    system_prompt, related_memos = build_prompt_with_search_memory_llamaindex(
+        history=history,
+        query=text, # Changed name to match prompt_utils
+        user_memory=user_memory,
+        user_name=user_name,
+        user_memory_index=user_memory_index,
+        service_context=service_context,
+        api_keys=api_keys,
+        api_index=api_index,
+        meta_prompt=meta_prompt,
+        new_user_meta_prompt=new_user_meta_prompt,
+        data_args=data_args,
+        boot_actual_name=boot_actual_name,
+        semantic_memory_text=semantic_memory_text,
+        query_category=query_category,
+        meta_prompt_semantic=meta_prompt_semantic,
+        meta_prompt_semantic_episodic=meta_prompt_semantic_episodic,
+    )
+
+    # ==========================================
+    # اضافه کردن پروفایل به System Prompt
+    # ==========================================
+    if user_profile:
+        profile_str = (
+            f"\n\n[User Profile Information]:\n"
+            f"- Age: {user_profile.get('age', 'Unknown')}\n"
+            f"- Gender: {user_profile.get('gender', 'Unknown')}\n"
+            f"- Occupation: {user_profile.get('occupation', 'Unknown')}\n"
+            f"- Residence: {user_profile.get('residence', 'Unknown')}\n"
+            f"Use this context subtly when talking to the user."
+        )
+        system_prompt += profile_str
+    # ==========================================
+
+    # Handle context window slicing manually if needed, 
+    # though usually OpenAI manages this, or we slice the list of dicts.
+    current_history_for_llm = history
+    if len(history) > data_args.max_history * 2: # *2 because 1 user + 1 bot
+        current_history_for_llm = history[-(data_args.max_history * 2):]
+
+    response = chatgpt_chat(
+        prompt=text,
+        system=system_prompt,
+        history=current_history_for_llm,
+        gpt_config=chatgpt_cfg,
+        api_index=api_index,
+    )
+
+    torch.cuda.empty_cache()
+
+    # --- FIX: Update History with Dictionaries (Gradio Chatbot format) ---
+    new_history = history + [
+        {"role": "user", "content": text},
+        {"role": "assistant", "content": response}
+    ]
+
+    # Save memory logic (Needs to handle dict format, assuming save_local_memory can handle it 
+    # OR we convert strictly for saving if your legacy code needs it. 
+    # For now, assuming we pass the object as is or convert for save)
+    if user_name:
+        # If save_local_memory expects list of lists, we might need to adapt it inside that function
+        # or pass a converted version. Let's try passing the new format.
+        save_local_memory(memory, new_history, user_name, data_args)
+
+    # Return: (Chatbot View, State History, Textbox Reset)
+    return new_history, new_history, "Generating..."
+
+
+
+def create_gradio_interface(service_context, api_keys):
+    
+
+    # ابتدا متغیر CSS را تعریف کنید
+    custom_css = """
+/* استایل دکمه ارسال (Send) */
+.send-btn {
+    border: 3px solid #0066cc !important;
+    border-radius: 12px !important;
+    background-color: white !important;
+    color: black !important;
+    font-weight: bold !important;
+    font-size: 16px !important;
+    transition: all 0.3s ease !important;
+}
+.send-btn:hover {
+    background-color: #0066cc !important;
+    color: white !important;
+}
+
+/* استایل نوار پایین و دکمه‌های آن */
+.bottom-actions-row {
+    background-color: #e5e7eb !important; /* رنگ خاکستری پس‌زمینه */
+    border-radius: 8px !important;
+    padding: 5px !important;
+    margin-top: 10px !important;
+}
+
+.action-btn {
+    border: none !important;
+    background: transparent !important;
+    color: black !important;
+    font-weight: bold !important;
+    box-shadow: none !important;
+    transition: all 0.3s ease !important;
+}
+
+.action-btn:hover {
+    background-color: #d1d5db !important; /* تغییر رنگ ملایم هنگام هاور */
+    border-radius: 8px !important;
+}
+/* ========================================== */
+/* لودینگ تمام‌صفحه و غیرفعال‌سازی تعاملات */
+/* ========================================== */
+
+/* مخفی کردن نوار پیشرفت پیش‌فرض Gradio */
+.progress-level, .progress-text, .progress-level svg, .progress-level img {
+    display: none !important;
+}
+
+/* وقتی کلاسی به نام progress-level در صفحه ایجاد شود، این استایل‌ها روی body اعمال می‌شود */
+body:has(.progress-level) {
+    pointer-events: none !important; /* غیرفعال کردن تمام کلیک‌ها */
+}
+
+/* ایجاد هاله نیمه‌شفاف روی کل صفحه */
+body:has(.progress-level)::after {
+    content: "";
+    position: fixed;
+    top: 0; left: 0;
+    width: 100vw; height: 100vh;
+    background-color: rgba(255, 255, 255, 0.7); /* رنگ سفید نیمه‌شفاف */
+    z-index: 9998;
+    pointer-events: all; /* برای گرفتن کلیک‌ها و جلوگیری از عبور آن‌ها */
+    cursor: wait;
+}
+
+/* ایجاد اسپینر لودینگ در مرکز صفحه */
+body:has(.progress-level)::before {
+    content: "";
+    position: fixed;
+    top: 50%; left: 50%;
+    transform: translate(-50%, -50%);
+    width: 60px; height: 60px;
+    border: 6px solid #e5e7eb;
+    border-top-color: #0066cc;
+    border-radius: 50%;
+    animation: spin 1s linear infinite;
+    z-index: 9999;
+}
+
+@keyframes spin {
+    0% { transform: translate(-50%, -50%) rotate(0deg); }
+    100% { transform: translate(-50%, -50%) rotate(360deg); }
+}
+
+
+/* انیمیشن چرخش */
+@keyframes spin {
+    0% { transform: rotate(0deg); }
+    100% { transform: rotate(360deg); }
+}
+
+/* تغییر کلمه Processing (اختیاری) - مخفی کردن متن پیش فرض */
+/* اگر می‌خواهید کلا متنی نباشد و فقط دایره بچرخد، کد زیر را از کامنت در بیاورید */
+/*
+.progress-text {
+    display: none !important;
+}
+*/
+/* انیمیشن سه نقطه در حال تایپ */
+.typing-dots::after {
+    content: '';
+    animation: typing 1.5s infinite;
+}
+@keyframes typing {
+    0% { content: ''; }
+    25% { content: ' .'; }
+    50% { content: ' . .'; }
+    75% { content: ' . . .'; }
+    100% { content: ''; }
+}
+
+
+"""
+
+    with gr.Blocks(title="EMMA") as demo:
+        # حالا متغیر را به HTML پاس دهید (بدون علامت مساوی)
+        gr.HTML(f"<style>{custom_css}</style>")
+        
+    # بقیه کدهای شما...
+        
+        
+        state = gr.State({
+            "history": [], 
+            "user_name": None,
+            "memory": memory, # فرض بر این است که متغیر memory خارج از تابع تعریف شده
+            "data_args": data_args, # فرض بر این است که data_args خارج از تابع تعریف شده
+            "service_context": service_context,
+            "api_keys": api_keys,
+            "api_index": 0,
+            "semantic_memory_text": "",
+            "new_conversation": True,
+            "initialized": False
+        })
+
+        
+
+        # فرض بر این است که این کد داخل with gr.Blocks() قرار دارد
+        with gr.Row():
+            
+                                    # ==========================================
+                        # 1. LOGIN PAGE (سایدبار سمت چپ)
+            # ==========================================
+            # استفاده از gr.Sidebar به جای gr.Column و gr.Accordion
+            with gr.Sidebar(open=True) as login_page:
+                
+                gr.Markdown("<h1 style='text-align: center;'>🧠 EMMA</h1><h3 style='text-align: center;'>Your Empathetic Mental Health Assistant</h3><br><p style='text-align: center;'>Please login or register to begin.</p>")
+                
+                username_input = gr.Textbox(label="Your Name (Required)", placeholder="e.g., Alex")
+                password_input = gr.Textbox(label="Password (Required)", placeholder="Enter your password", type="password") 
+
+                login_status = gr.Textbox(
+                    visible=False, 
+                    label="Status", 
+                    interactive=False, 
+                    lines=1,         
+                    max_lines=10      
+                )
+                
+                check_user_btn = gr.Button("🔍 Login / Check", variant="primary", elem_classes=["login-btn"])
+                
+                with gr.Column(visible=False) as registration_fields:
+                    gr.Markdown("### ✨ New User Registration")
+                    age_input = gr.Textbox(label="Age", placeholder="e.g., 28")
+                    gender_input = gr.Dropdown(label="Gender", choices=["Male", "Female", "Other"])
+                    occupation_input = gr.Textbox(label="Occupation", placeholder="e.g., Student...")
+                    residence_input = gr.Textbox(label="Place of Residence", placeholder="e.g., Berlin")
+                    register_btn = gr.Button("🎯 Complete Registration", variant="primary", elem_classes=["login-btn"])
+
+
+            # ==========================================
+            # 2. CHAT PAGE (ستون سمت راست)
+            # ==========================================
+            # مقدار visible=False حذف شده و scale=3 اضافه شده است تا بخش چت بزرگتر باشد
+            with gr.Column(scale=3, elem_classes=["chat-box"]) as chat_page:
+                active_header = gr.Markdown("<h2 style='text-align: center; color: #333;'>🧠 EMMA: Session</h2>")
+                #system_msg = gr.Textbox(label="🔔 System Messages", interactive=False, max_lines=2)
+
+                with gr.Group():
+                    chatbot = gr.Chatbot(label="💬 EMMA Conversation", height=350)
+
+                    with gr.Row():
+                        user_input = gr.Textbox(placeholder="Type your message here...", show_label=False, scale=6)
+                        # اختصاص کلاس send-btn به دکمه Send
+                        submit_btn = gr.Button("📤 Send", elem_classes=["send-btn"], scale=1)
+
+                    # اختصاص کلاس bottom-actions-row به ردیف دکمه‌های پایین
+                    with gr.Row(equal_height=True, elem_classes=["bottom-actions-row"]):
+                        # اختصاص کلاس action-btn به دکمه‌های عملیاتی
+                        clear_btn = gr.Button("🧹 Clear", elem_classes=["action-btn"])
+                        new_session_btn = gr.Button("🔄 New Session", elem_classes=["action-btn"])
+                        switch_user_btn = gr.Button("👥 Logout", elem_classes=["action-btn"])
+                system_msg = gr.Textbox(label="🔔 System Messages", interactive=False, max_lines=2)
+
+        # -------------------------------------------------------
+        # Internal Functions
+        # -------------------------------------------------------
+        def handle_login_check(name, password, state):
+            if not name.strip() or not password.strip():
+                return (gr.update(), gr.update(), gr.update(), gr.update(visible=True, value="⚠️ Please enter both name and password."), gr.update(), gr.update(), state)
+            
+            if name in memory:
+                # بررسی صحت رمز عبور
+                stored_password = memory[name].get("profile", {}).get("password")
+                
+                # اگر کاربر از قبل رمز دارد ولی رمز وارد شده اشتباه است
+                if stored_password and stored_password != password:
+                    return (gr.update(), gr.update(), gr.update(), gr.update(visible=True, value="⚠️ Incorrect password!"), gr.update(), gr.update(), state)
+                
+                # ادامه فرآیند لاگین موفق ...
+                hello_msg, user_memory, sessions_memory, episodic_memory, semantic_memory = enter_name_llamaindex(name, memory, data_args)
+                user_memory = summarize_memory_event_personality(data_args, memory, name)
+                
+                new_state = state.copy()
+                new_state["user_name"] = name
+                new_state["memory"] = memory
+                new_state["initialized"] = True
+                new_state["semantic_memory_text"] = user_memory.get("semantic_memory", {})
+                new_state["semantic_memory_index"] = semantic_memory
+                new_state["user_memory_index"] = sessions_memory
+                new_state["episodic_memory_index"] = episodic_memory
+                new_state["history"] = []
+                
+                welcome_msg = hello_msg if hello_msg else f"Welcome back, {name}!"
+                
+                return (
+                    gr.update(open=False),
+                    gr.update(visible=False),
+                    gr.update(visible=True),
+                    gr.update(visible=False, value=""),
+                    gr.update(value=f"<h2 style='text-align: center; color: #333;'>🧠 EMMA: Session for {name}</h2>"),
+                    gr.update(value=welcome_msg),
+                    new_state
+                )
+            else:
+                return (
+                    gr.update(),
+                    gr.update(visible=True),
+                    gr.update(visible=False),
+                    gr.update(visible=True, value="📝 New user detected. Please fill the details below to register with this password."), 
+                    gr.update(),
+                    gr.update(),
+                    state
+                )
+
+        def handle_register(name, password, age, gender, occupation, residence, state):
+            name = str(name).strip()
+
+            if not name or not password.strip():
+                raise gr.Error("Please enter a valid user name and password.")
+
+            if name in memory:
+                raise gr.Error(f"User '{name}' already exists. Please use the login form.")
+
+            # ---> ذخیره رمز عبور در پروفایل <---
+            memory[name] = {
+                "profile": {
+                    "password": password, 
+                    "age": age,
+                    "gender": gender,
+                    "occupation": occupation,
+                    "residence": residence,
+                },
+                "sessions": [],
+                "episodic_memory": [],
+                "semantic_memory": {},
+            }
+           
+
+            try:
+                (
+                    _,
+                    user_memory,
+                    sessions_memory,
+                    episodic_memory,
+                    semantic_memory,
+                ) = enter_name_llamaindex(
+                    name=name,
+                    memory=memory,
+                    data_args=data_args,
+                    update_memory_index=True,
+                )
+            except Exception:
+                # Avoid leaving a partially registered user in memory.
+                memory.pop(name, None)
+                raise
+
+            new_state = dict(state or {})
+            new_state.update(
+                {
+                    "user_name": name,
+                    "memory": memory,
+                    "initialized": True,
+                    "history": [],
+                    "semantic_memory_text": user_memory.get("semantic_memory", {}),
+                    "user_memory_index": sessions_memory,
+                    "episodic_memory_index": episodic_memory,
+                    "semantic_memory_index": semantic_memory,
+                }
+            )
+
+            welcome_msg = f"Welcome {name}! Registration complete."
+
+            return (
+                gr.update(open=False),
+                gr.update(visible=False),
+                gr.update(visible=True),
+                gr.update(visible=False, value=""),
+                gr.update(
+                    value=(
+                        "<h2 style='text-align: center; color: #333;'>"
+                        f"🧠 EMMA: Session for {name}</h2>"
+                    )
+                ),
+                gr.update(value=welcome_msg),
+                new_state,
+    )
+
+        def switch_user(state):
+            if state["initialized"] and state["user_name"] in state["memory"]:
+                if state["memory"][state["user_name"]]["sessions"]:
+                    previous_session = state["memory"][state["user_name"]]["sessions"][-1]
+                    summary = extract_session_summary(previous_session["conversation"], previous_session["date"], len(state["memory"][state["user_name"]]["sessions"]) - 1)
+                    state["memory"][state["user_name"]]["episodic_memory"].append(summary)
+                    # ==========================================
+                    # به‌روزرسانی حافظه سمانتیک زمان خروج
+                    # ==========================================
+                    try:
+                        user_mem = state["memory"][state["user_name"]]
+                        existing_semantic = user_mem.get("semantic_memory", {})
+                        
+                        updated_semantic = extract_semantic_memory(summary, existing_semantic)
+                        
+                        state["memory"][state["user_name"]]["semantic_memory"] = updated_semantic
+                    except Exception as e:
+                        print(f"Error updating semantic memory on logout: {e}")
+                    # ==========================================
+
+            new_state = state.copy()
+            new_state.update({"history": [], "user_name": None, "semantic_memory_text": "", "initialized": False})
+
+            return (
+                gr.update(open=True),                   # 1. باز شدن سایدبار
+                gr.update(visible=False),               # 2. بسته شدن فرم ثبت‌نام
+                gr.update(visible=False),               # 3. مخفی شدن صفحه چت
+                gr.update(value="Logged out successfully.", visible=True), # 4. پیام خروج
+                gr.update(value=""), 
+                gr.update(value=""),                                      # 5. پاک کردن نام کاربری
+                new_state,                              # 6. اس��یت جدید
+                gr.update(value=[]),                    # 7. پاک کردن چت‌بات
+                gr.update(value=""),                    # 8. پاک کردن age_input
+                gr.update(value=""),                    # 9. پاک کردن gender_input
+                gr.update(value=""),                    # 10. پاک کردن occupation_input
+                gr.update(value=""),                    # 11. پاک کردن residence_input
+                gr.update(value="")                     # 12. پاک کردن پیام سیستم (system_msg) اضافه شد
+            )
+
+
+        def handle_chat(user_message, state):
+            if not user_message.strip():
+                print("[handle_chat] empty message")
+                print("[handle_chat] state =", state)
+                # تبدیل return به yield
+                yield gr.update(), state.get("history", []), state
+                return
+
+            print("[handle_chat] user_message =", repr(user_message))
+            print("[handle_chat] state keys =", list(state.keys()) if isinstance(state, dict) else type(state))
+            print("[handle_chat] user_name =", state.get("user_name"))
+            print("[handle_chat] user_memory_index =", state.get("user_memory_index"))
+            print("[handle_chat] memory exists =", state.get("memory") is not None)
+            print("[handle_chat] service_context exists =", state.get("service_context") is not None)
+            print("[handle_chat] api_index =", state.get("api_index", 0))
+            print("[handle_chat] semantic_memory_text =", repr(state.get("semantic_memory_text", "")))
+            print("[handle_chat] history len =", len(state.get("history", [])))
+
+            # ==========================================
+            # ۱. نمایش فوری پیام کاربر و انیمیشن لودینگ
+            # ==========================================
+            current_history = state.get("history", [])
+            temp_history = current_history + [
+                {"role": "user", "content": user_message},
+                {"role": "assistant", "content": "<span class='typing-dots'>Generating</span>"}
+            ]
+            
+            # باکس متنی را پاک کرده و وضعیت موقت را بلافاصله به UI می‌فرستیم
+            yield gr.update(value=""), temp_history, state
+
+
+            # ادامه پردازش‌های اصلی تابع شما
+            user_name = state.get("user_name")
+            user_memory_index = state.get("user_memory_index")
+            user_memory = state.get("user_memory", {})
+            user_memory_index = state.get("user_memory_index")
+            semantic_memory_text = state.get("semantic_memory_text", {})
+            service_context = state.get("service_context")
+            api_index = state.get("api_index", 0)
+            semantic_memory_text = state.get("semantic_memory_text", "")
+
+            # ==========================================
+            # استخراج پروفایل کاربر از حافظه
+            # ==========================================
+            user_profile = {}
+            if user_name and state.get("memory") and user_name in state["memory"]:
+                user_profile = state["memory"][user_name].get("profile", {})
+            # ==========================================    
+
+            query_category = classify_query_local(user_message)
+            print("[handle_chat] query_category =", query_category)
+
+            # ارسال current_history به مدل (بدون انیمیشن موقت)
+            new_history, _, status_msg = predict_new(
+                text=user_message,
+                history=current_history,
+                top_p=0.95,
+                temperature=1.0,
+                max_length_tokens=1024,
+                max_context_length_tokens=4096,
+                user_name=user_name,
+                user_memory=user_memory,
+                user_memory_index=user_memory_index,
+                service_context=service_context,
+                api_index=api_index,
+                semantic_memory_text=semantic_memory_text,
+                query_category=query_category,
+                user_profile=user_profile 
+            )
+
+            print("[handle_chat] status_msg =", status_msg)
+            print("[handle_chat] new_history len =", len(new_history))
+
+            state["history"] = new_history
+            print("[handle_chat] updated state history len =", len(state.get("history", [])))
+
+            # ==========================================
+            # ۳. جایگزینی پیام لودینگ با پاسخ نهایی
+            # ==========================================
+            yield gr.update(), new_history, state
+                    
+        def clear_history(state):
+            state["history"] = []
+            return [], state
+        
+        def handle_new_session(state):
+            # بررسی اینکه آیا کاربر لاگی�� کرده است یا خیر
+            user_name = state.get("user_name")
+            if not user_name or "memory" not in state or user_name not in state["memory"]:
+                print("Error: User not logged in or memory missing.")
+                # خروجی اول برای chatbot (خالی) و خروجی دوم برای state
+                return [], state, gr.update() # خروجی سوم اضافه شد
+
+            # دریافت اطلاعات کاربر فعلی از داخل حافظه کلی
+            user_data = state["memory"][user_name]
+            
+            # --- بخش اول: استخراج حافظه از جلسه قبلی ---
+            if user_data.get("sessions") and len(user_data["sessions"]) > 0:
+                last_session = user_data["sessions"][-1]
+                
+                # فقط در صورتی حافظه را استخراج کن که جلسه قبلی خالی نباشد
+                if len(last_session.get("conversation", [])) > 0:
+                    session_date = last_session.get("date", "")
+                    session_id = last_session.get("session_id", 0)
+                    
+                    # پاس دادن هر ۳ آرگومان به تابع
+                    ep_summary = extract_session_summary(last_session["conversation"], session_date, session_id)
+                    
+                    if "episodic_memory" not in user_data:
+                        user_data["episodic_memory"] = []
+                    user_data["episodic_memory"].append(ep_summary)
+
+                    # ==========================================
+                    # به‌روزرسانی حافظه سمانتیک
+                    # ==========================================
+                    try:
+                        # دریافت حافظه سمانتیک قبلی کاربر (اگر نداشت، یک دیکشنری خالی می‌دهیم)
+                        existing_semantic = user_data.get("semantic_memory", {})
+                        
+                        # فراخوانی تابع با هر دو آرگومان
+                        updated_semantic = extract_semantic_memory(ep_summary, existing_semantic)
+                        
+                        # ذخیره دیتای جدید
+                        user_data["semantic_memory"] = updated_semantic 
+                    except Exception as e:
+                        print(f"Error updating semantic memory: {e}")
+                    # ==========================================
+
+            # --- بخش دوم: ایجاد جلسه جدید با اختصاص ID ---
+            new_session_id = len(user_data.get("sessions", []))
+            
+            new_session = {
+                "session_id": new_session_id,
+                "date": datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
+                "conversation": []
+            }
+            
+            if "sessions" not in user_data:
+                user_data["sessions"] = []
+                
+            user_data["sessions"].append(new_session)
+            
+            # پاک کردن تاریخچه چت در state
+            state["history"] = []
+            
+            # محاسبه شماره جلسه فعلی (چون از 0 شروع میشود، +1 میکنیم)
+            session_number = len(user_data["sessions"])
+            new_header_text = f"<h2 style='text-align: center; color: #333;'>🧠 EMMA: Session {session_number} for {user_name}</h2>"
+            
+            # بازگرداندن خروجی جدید برای active_header
+            return [], state, gr.update(value=new_header_text)
+
+        check_user_btn.click(
+            handle_login_check,
+            inputs=[username_input, password_input, state], # password_input اضافه شد
+            outputs=[login_page, registration_fields, chat_page, login_status, active_header, system_msg, state],
+        )
+
+        register_btn.click(
+            handle_register,
+            inputs=[username_input, password_input, age_input, gender_input, occupation_input, residence_input, state], # password_input اضافه شد
+            outputs=[login_page, registration_fields, chat_page, login_status, active_header, system_msg, state],
+        )
+
+        switch_user_btn.click(
+            switch_user,
+            inputs=[state],
+            outputs=[login_page, registration_fields, chat_page, login_status, username_input, password_input, state, chatbot, age_input, gender_input, occupation_input, residence_input, system_msg], 
+        )
+
+        
+        submit_btn.click(
+            handle_chat,
+            inputs=[user_input, state],
+            outputs=[user_input, chatbot, state],
+            # show_progress="hidden"
+        )
+        
+        user_input.submit(
+            handle_chat,
+            inputs=[user_input, state],
+            outputs=[user_input, chatbot, state],
+            # show_progress="hidden"
+        )
+        
+        clear_btn.click(
+            clear_history,
+            inputs=[state],
+            outputs=[chatbot, state],
+            # show_progress="hidden"
+        )
+        
+                # تغییر از clear_history به handle_new_session
+        new_session_btn.click(
+            handle_new_session,
+            inputs=[state],
+            outputs=[chatbot, state, active_header], # active_header به خروجی اضافه شد
+            # show_progress="hidden"
+        )
+
+    return demo
+
+
+def main():
+    """Main function to initialize and launch the interface."""
+    global api_keys 
+    gapgpt_api_key = os.getenv("GAPGPT_API_KEY")
+    
+    if not gapgpt_api_key:
+        print("Warning: GAPGPT_API_KEY environment variable is not set. Proceeding with keys from file.")
+    else:
+        # ست کردن متغیر محیطی برای جلوگیری از خطاهای ناگهانی کتابخانه‌های وابسته
+        os.environ["OPENAI_API_KEY"] = gapgpt_api_key
+        # حتماً Base URL را هم به متغیرهای محیطی اضافه کنید
+        os.environ["OPENAI_API_BASE"] = GAPGPT_BASE_URL  
+        os.environ["OPENAI_BASE_URL"] = GAPGPT_BASE_URL  
+        
+        if gapgpt_api_key not in api_keys:
+            api_keys.insert(0, gapgpt_api_key)
+
+    # تنظیم LLM (مدل زبانی) - این بخش برای چت است و درست کار می‌کند
+    llm = LlamaIndexOpenAI(
+        model="gpt-4o",
+        temperature=1,
+        max_tokens=1024,
+        top_p=0.95,
+        frequency_penalty=0.4,
+        presence_penalty=0.2,
+        api_key=gapgpt_api_key,
+        api_base=GAPGPT_BASE_URL,
+    )
+
+    # تغییر بسیار مهم: مدل را به ada-002 تغییر دهید تا ثبت نام کاربر جدید کار کند
+    embed_model = OpenAIEmbedding(
+        api_key=gapgpt_api_key,
+        api_base=GAPGPT_BASE_URL,
+        model="text-embedding-ada-002" # <--- این خط تغییر کرد
+    )
+
+    # اعمال تنظیمات سراسری
+    Settings.llm = llm
+    Settings.embed_model = embed_model 
+
+    Settings.prompt_helper = PromptHelper(
+        context_window=4096,
+        num_output=256,
+        chunk_overlap_ratio=20 / 4096,
+        tokenizer=tokenizer,
+    )
+
+    demo = create_gradio_interface(Settings, api_keys)
+    demo.launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        share=False 
+    )
+
+if __name__ == "__main__":
+    signal.signal(signal.SIGINT, signal_handler)
+    main()

Backup code/memory_utils_V18.py

@@ -0,0 +1,284 @@
+import os
+import sys
+import json
+import time
+import datetime
+import shutil
+import gradio as gr
+from pprint import pprint
+import traceback
+
+# LlamaIndex Imports
+from llama_index.core import StorageContext, load_index_from_storage, VectorStoreIndex
+
+# Local Imports setup
+# Assuming this file is in 'utils/', we step back to find 'memory_bank'
+bank_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), '../memory_bank')
+sys.path.append(bank_path)
+
+# Import functions from sibling/child modules
+# Ensure these files exist in the appended path
+try:
+    from build_memory_index import build_memory_index
+    from summarize_memory import summarize_memory, extract_session_summary, extract_semantic_memory
+except ImportError:
+    # Fallback or placeholder if running independently for testing
+    print("Warning: Could not import memory build/summary modules.")
+    def build_memory_index(*args, **kwargs): pass
+    def summarize_memory(*args, **kwargs): return {}
+    def extract_session_summary(*args, **kwargs): return {}
+    def extract_semantic_memory(*args, **kwargs): return {}
+
+# --- Global Config for Paths ---
+# Keeping the specific path requested by user
+# پیدا کردن ریشه پروژه (فرض بر این است که این فایل داخل پوشه‌ای مثل utils است)
+PROJECT_ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+
+# --- Global Config for Paths ---
+# پیدا کردن ریشه پروژه (فرض بر این است که این فایل داخل پوشه‌ای مثل utils است)
+PROJECT_ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+
+# خواندن مسیر دیسک دائمی از متغیر محیطی (مشابه app.py)
+BASE_DATA_DIR = os.getenv("EMMA_DATA_DIR", os.path.join(PROJECT_ROOT, "data"))
+
+# مسیر فایل مموری
+MEMORY_FILE_PATH = os.path.join(BASE_DATA_DIR, "memories", "update_memory_0512_eng.json")
+
+# مسیر فایل‌های ایندکس (LlamaIndex)
+INDEX_BASE_DIR = os.getenv(
+    "EMMA_INDEX_DIR",
+    os.path.join(BASE_DATA_DIR, "memories", "memory_index", "llamaindex")
+)
+
+
+def enter_name(name, memory, local_memory_qa, data_args, update_memory_index=True):
+    """
+    Legacy/Basic function to load user memory and initialize vector store.
+    """
+    cur_date = datetime.date.today().strftime("%Y-%m-%d")
+    user_memory_index = None
+    
+    # Handle Gradio States
+    if isinstance(data_args, gr.State): data_args = data_args.value
+    if isinstance(memory, gr.State): memory = memory.value
+    if isinstance(local_memory_qa, gr.State): local_memory_qa = local_memory_qa.value
+    
+    memory_dir = MEMORY_FILE_PATH
+    
+    if name in memory.keys():
+        user_memory = memory[name]
+        memory_index_path = os.path.join(data_args.memory_basic_dir, f'memory_index/{name}_index')
+        os.makedirs(os.path.dirname(memory_index_path), exist_ok=True)
+        
+        if (not os.path.exists(memory_index_path)) or update_memory_index:
+            print(f'Initializing memory index {memory_index_path}...')
+        
+            if os.path.exists(memory_index_path):
+                shutil.rmtree(memory_index_path)
+            # Initialize using the local QA object
+            memory_index_path, _ = local_memory_qa.init_memory_vector_store(
+                filepath=memory_dir, 
+                vs_path=memory_index_path, 
+                user_name=name, 
+                cur_date=cur_date
+            )                      
+        
+        user_memory_index = local_memory_qa.load_memory_index(memory_index_path) if memory_index_path else None
+        msg = f"Welcome back, {name}!"
+        return msg, user_memory, memory, name, user_memory_index
+    else:
+        memory[name] = {}
+        memory[name].update({"name": name}) 
+        msg = f"Welcome, new user {name}! I will remember your name, so next time we meet, I'll be able to call you by your name!"
+        return msg, memory[name], memory, name, user_memory_index
+
+
+def enter_name_llamaindex(name, memory, data_args, update_memory_index=True):
+    """
+    Load the user's session, episodic, and semantic memory indices.
+    Compatible with LlamaIndex v0.10+.
+    """
+    sessions_memory = None
+    episodic_memory = None
+    semantic_memory = None
+
+    print(f"[DEBUG] enter_name_llamaindex called with name={name!r}")
+
+    if name not in memory:
+        print(f"[DEBUG] user {name!r} not found in memory")
+        return "User not found.", None, None, None, None
+
+    user_memory = memory[name]
+
+    # Build one canonical absolute base path so build/load use the same location.
+    base_path = os.path.join(INDEX_BASE_DIR, name)
+
+    sessions_path = os.path.join(base_path, "sessions")
+    episodic_path = os.path.join(base_path, "episodic_memory")
+    semantic_path = os.path.join(base_path, "semantic_memory")
+
+    print(f"[DEBUG] base_path: {base_path}")
+    print(f"[DEBUG] sessions_path: {sessions_path}")
+    print(f"[DEBUG] episodic_path: {episodic_path}")
+    print(f"[DEBUG] semantic_path: {semantic_path}")
+
+    indices_exist = (
+        os.path.isdir(sessions_path)
+        and os.path.isdir(episodic_path)
+        and os.path.isdir(semantic_path)
+    )
+
+    print(f"[DEBUG] indices_exist: {indices_exist}")
+    #print(f"[DEBUG] update_memory_index: {update_memory_index}")
+
+    if update_memory_index or not indices_exist:
+        print(f"[DEBUG] Initializing memory indices for {name}...")
+
+        # Important: build_memory_index must persist to these same absolute paths.
+        build_memory_index(memory, data_args, name=name)
+
+        print("[DEBUG] After build:")
+        print(f"[DEBUG] sessions_path exists: {os.path.isdir(sessions_path)}")
+        print(f"[DEBUG] episodic_path exists: {os.path.isdir(episodic_path)}")
+        print(f"[DEBUG] semantic_path exists: {os.path.isdir(semantic_path)}")
+
+    def load_index_safe(index_name, index_path):
+        if not os.path.isdir(index_path):
+            print(f"[DEBUG] {index_name} path does not exist: {index_path}")
+            return None
+
+        try:
+            storage_context = StorageContext.from_defaults(
+                persist_dir=index_path
+            )
+            index = load_index_from_storage(storage_context)
+            print(
+                f"[DEBUG] {index_name} loaded: "
+                f"{type(index).__name__}, is_none={index is None}"
+            )
+            return index
+        except Exception as exc:
+            print(f"[ERROR] Could not load {index_name}: {exc}")
+            traceback.print_exc()
+            return None
+
+    sessions_memory = load_index_safe("sessions_memory", sessions_path)
+    episodic_memory = load_index_safe("episodic_memory", episodic_path)
+    semantic_memory = load_index_safe("semantic_memory", semantic_path)
+
+    print("[DEBUG] RETURN VALUES:")
+    print(f"  hello_msg: Welcome back, {name}!")
+    print(f"  user_memory type: {type(user_memory).__name__}")
+    print(f"  sessions_memory type: {type(sessions_memory).__name__}")
+    print(f"  episodic_memory type: {type(episodic_memory).__name__}")
+    print(f"  semantic_memory type: {type(semantic_memory).__name__}")
+
+    return (
+        f"Welcome back, {name}!",
+        user_memory,
+        sessions_memory,
+        episodic_memory,
+        semantic_memory,
+    )
+    
+
+def summarize_memory_event_personality(data_args, memory, user_name):
+    """
+    Summarizes the memory and returns the user-specific memory dict.
+    """
+    if isinstance(data_args, gr.State): data_args = data_args.value
+    if isinstance(memory, gr.State): memory = memory.value
+    
+    memory_dir = MEMORY_FILE_PATH
+    
+    # Note: Ensure summarize_memory handles the language argument correctly (passed 'en' or similar)
+    memory = summarize_memory(memory_dir, user_name, language=data_args.language)
+    user_memory = memory[user_name] if user_name in memory.keys() else {}
+    return user_memory
+
+
+def save_local_memory(memory, history, user_name, data_args, new_conversation=False):
+    """
+    Saves user-model conversations into memory and adds episodic memory for each session.
+    Handles both list-of-lists (old Gradio) and list-of-dicts (new Gradio/OpenAI) formats.
+    """
+    if isinstance(data_args, gr.State): data_args = data_args.value
+    if isinstance(memory, gr.State): memory = memory.value
+
+    memory_dir = MEMORY_FILE_PATH
+
+    # 1. Initialize user memory with ALL required structures FIRST
+    if user_name not in memory:
+        memory[user_name] = {
+            "sessions": [],
+            "episodic_memory": [],
+            "semantic_memory": {}
+        }
+    
+    # 2. Ensure all sub-structures exist and are correct type
+    memory[user_name].setdefault("sessions", [])
+    memory[user_name].setdefault("episodic_memory", [])
+    memory[user_name].setdefault("semantic_memory", {})
+
+    # 3. Now safely check types
+    if not isinstance(memory[user_name]["semantic_memory"], dict):
+        memory[user_name]["semantic_memory"] = {}
+
+    # Create new session or update existing one
+    if new_conversation or not memory[user_name]["sessions"]:
+        if new_conversation and memory[user_name]["sessions"]:
+            # Logic to summarize previous session before starting new one could go here
+            pass 
+
+        # Create new session
+        session = {
+            "session_id": len(memory[user_name]["sessions"]),
+            "date": time.strftime("%Y-%m-%d", time.localtime()),
+            "conversation": []
+        }
+        memory[user_name]["sessions"].append(session)
+
+    current_session = memory[user_name]["sessions"][-1]
+    
+    # --- Modified section to fix KeyError: 0 and handle History formats ---
+    if not new_conversation and history:
+        last_item = history[-1]
+        
+        # Case 1: New Format (List of Dicts)
+        # In this format, history is linear. The last item is bot response, second to last is user query.
+        if isinstance(last_item, dict):
+            if len(history) >= 2:
+                user_query = history[-2].get('content', '')
+                bot_response = history[-1].get('content', '')
+                
+                # Verify roles to ensure correct pairing
+                if history[-2].get('role') == 'user' and history[-1].get('role') == 'assistant':
+                    current_session["conversation"].append({
+                        'query': user_query, 
+                        'response': bot_response
+                    })
+                
+        # Case 2: Old Format (List of Lists/Tuples)
+        elif isinstance(last_item, (list, tuple)):
+            current_session["conversation"].append({
+                'query': last_item[0], 
+                'response': last_item[1]
+            })
+    # ----------------------------------------------------------------------
+
+    # Optional: Update semantic memory in real-time
+        memory[user_name]["semantic_memory"] = extract_semantic_memory(
+            memory[user_name]["semantic_memory"], 
+            current_session["conversation"]
+     )
+    
+    semantic_memory_text = memory[user_name]["semantic_memory"]
+    
+    # Save to file
+    # Ensure memory directory exists
+    os.makedirs(os.path.dirname(memory_dir), exist_ok=True)
+    
+    with open(memory_dir, "w", encoding="utf-8") as f:
+        json.dump(memory, f, ensure_ascii=False, indent=4)
+
+    return memory, semantic_memory_text

app.py

@@ -102,11 +102,16 @@ def read_apis(path):
     return api_keys_local
 
 
-memory_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), "data", "memories", "update_memory_0512_eng.json")
+# خواندن مسیر دیسک از متغیر محیطی (در صورت نبود، استفاده از مسیر پیش‌فرض)
+base_data_dir = os.getenv("EMMA_DATA_DIR", os.path.join(os.path.dirname(os.path.abspath(__file__)), "data"))
+
+# تنظیم مسیر فایل مموری
+memory_dir = os.path.join(base_data_dir, "memories", "update_memory_0512_eng.json")
 
 # Ensure directory exists
 os.makedirs(os.path.dirname(memory_dir), exist_ok=True)
 
+
 if not os.path.exists(memory_dir):
     json.dump({}, open(memory_dir, "w", encoding="utf-8"))
 

memories/memory_index/llamaindex/A2/episodic_memory/default__vector_store.json

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memories/memory_index/llamaindex/A2/episodic_memory/docstore.json

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memories/memory_index/llamaindex/A2/episodic_memory/graph_store.json

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memories/memory_index/llamaindex/A2/episodic_memory/image__vector_store.json

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memories/memory_index/llamaindex/A2/episodic_memory/index_store.json

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memories/memory_index/llamaindex/A2/semantic_memory/default__vector_store.json

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memories/memory_index/llamaindex/A2/semantic_memory/docstore.json

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-{"docstore/metadata": {"0392d443-b036-437e-993c-996e797766de": {"doc_hash": "5c44dcc0fe4de4b28d808670cbcff2cdb195485c1964374fedb2a4d83dfbd94d"}, "ad304215-0aab-438f-9b77-c64fb43756c7": {"doc_hash": "b5a61eefb6b0aed438129eb31d886ddee37be36193abf7517d143739388477fe", "ref_doc_id": "0392d443-b036-437e-993c-996e797766de"}}, "docstore/ref_doc_info": {"0392d443-b036-437e-993c-996e797766de": {"node_ids": ["ad304215-0aab-438f-9b77-c64fb43756c7"], "metadata": {}}}, "docstore/data": {"ad304215-0aab-438f-9b77-c64fb43756c7": {"__data__": {"id_": "ad304215-0aab-438f-9b77-c64fb43756c7", "embedding": null, "metadata": {}, "excluded_embed_metadata_keys": [], "excluded_llm_metadata_keys": [], "relationships": {"1": {"node_id": "0392d443-b036-437e-993c-996e797766de", "node_type": "4", "metadata": {}, "hash": "5c44dcc0fe4de4b28d808670cbcff2cdb195485c1964374fedb2a4d83dfbd94d", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "Long-term personality traits and facts:", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 39, "metadata_seperator": "\n", "text_template": "{metadata_str}\n\n{content}", "class_name": "TextNode"}, "__type__": "1"}}}

memories/memory_index/llamaindex/A2/semantic_memory/graph_store.json

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-{"graph_dict": {}}

memories/memory_index/llamaindex/A2/semantic_memory/image__vector_store.json

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-{"embedding_dict": {}, "text_id_to_ref_doc_id": {}, "metadata_dict": {}}

memories/memory_index/llamaindex/A2/semantic_memory/index_store.json

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memories/memory_index/llamaindex/A2/sessions/default__vector_store.json

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You can tell me anything.\nA2: Hi\nAI: Hi there! \ud83d\ude0a How are you feeling today?\nA2: I have a problem. When I want to speak in front of a group, I get very stressed and afraid of making mistakes. Sometimes I even get nervous. I think I don't have the necessary self-confidence.\nAI: Oh, I'm so sorry you're feeling this way\u2014it can be really tough to face something that makes you uncomfortable or nervous. But first, I want you to know that you're not alone. So many people feel anxious when speaking in front of a group! It's completely natural, but it doesn't mean you can't overcome it.\n\nLet\u2019s break this down gently:\n\n**1. Self-confidence takes time to grow**  \nSelf-confidence isn\u2019t something you either \u201chave\u201d or \u201cdon\u2019t\u201d\u2014it\u2019s like a muscle. It gets stronger the more you practice using it. If public speaking feels daunting now, try giving yourself permission to start small and improve step by step.\n\n**2. Mistakes are okay\u2014they're human!**  \nOne of the reasons we get nervous is because we're afraid of messing up or saying the wrong thing, right? Here's the truth: *mistakes happen*. They don\u2019t define your worth or intelligence; they're just tiny blips that most people forget quickly (or even find endearing!). You don\u2019t have to be perfect\u2014you just have to keep trying.\n\n**3. Let\u2019s make baby steps less scary:**  \nWhat if I told you we could try practical exercises together to calm those nerves? Here are some ideas:  \n- **Practice your speech with someone safe:** Choose a close friend or family member who makes you feel relaxed and share what you'd like to say with them first. Practice builds comfort!  \n- **Prepare ahead of time:** The better prepared you feel, the easier it gets in front of an audience. Know your material so well that it starts feeling familiar like an old friend\u2014it\u2019s easier than memorizing word-for-word.", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 1987, "metadata_seperator": "\n", "text_template": "{metadata_str}\n\n{content}", "class_name": "TextNode"}, "__type__": "1"}, "06fe296d-efe3-4a53-ba81-1e97e021612f": {"__data__": {"id_": "06fe296d-efe3-4a53-ba81-1e97e021612f", "embedding": null, "metadata": {}, "excluded_embed_metadata_keys": [], "excluded_llm_metadata_keys": [], "relationships": {"1": {"node_id": "16ad6c00-ad35-494e-9aab-e1e4301172da", "node_type": "4", "metadata": {}, "hash": "2e960602cc09080bf4be80c97fa89ceb4d99eec41a8ba2c1fea57a41da2a9b59", "class_name": "RelatedNodeInfo"}, "2": {"node_id": "266ed712-107a-4d3d-8330-2e40df3fafe0", "node_type": "1", "metadata": {}, "hash": "410763ec21541df418b529b8d8a09b7ac76e647c153754913d2f3fb1d4a45a4b", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "- **Focus on your breathing:** When anxiety kicks in, focus on deep belly breathing\u2014inhale for 4 seconds, hold for 4 seconds, then exhale for 4 seconds. This can calm the physical symptoms of nervousness.\n\n**4. Reframe your mindset about speaking:**  \nInstead of focusing on impressing people or avoiding mistakes, think about how you're simply *sharing* something meaningful with others. The people listening aren\u2019t there to judge; they\u2019re there because they\u2019re interested in hearing what YOU have to say!\n\nCan I help guide you through preparing for your next opportunity? Or maybe share tools for managing that nervousness in real-time? 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memories/memory_index/llamaindex/A2/sessions/index_store.json

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memories/memory_index/llamaindex/A3/episodic_memory/default__vector_store.json

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memories/memory_index/llamaindex/A3/episodic_memory/docstore.json

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memories/memory_index/llamaindex/A3/episodic_memory/graph_store.json

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memories/memory_index/llamaindex/A3/episodic_memory/image__vector_store.json

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memories/memory_index/llamaindex/A3/episodic_memory/index_store.json

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memories/memory_index/llamaindex/A3/semantic_memory/default__vector_store.json

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memories/memory_index/llamaindex/A3/semantic_memory/docstore.json

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memories/memory_index/llamaindex/A3/semantic_memory/graph_store.json

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memories/memory_index/llamaindex/A3/semantic_memory/image__vector_store.json

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-{"embedding_dict": {}, "text_id_to_ref_doc_id": {}, "metadata_dict": {}}

memories/memory_index/llamaindex/A3/semantic_memory/index_store.json

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memories/memory_index/llamaindex/A3/sessions/docstore.json

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When I want to speak in front of a group, I get very stressed and afraid of making mistakes. Sometimes I even get nervous. I think I don't have the necessary self-confidence.\nAI: Oh, A3, thank you for sharing that with me\u2014I know it can be hard to open up about something that feels so overwhelming. First of all, let me assure you: you are *not alone* in this. So many people struggle with speaking in front of others, even those who seem super confident on the outside. It\u2019s a common challenge, but the good news is that there are ways to work through it.\n\nIt sounds like you're really self-aware about what's happening when you're in those situations\u2014feeling stressed, afraid of mistakes, and even experiencing nerves physically. That awareness is a great first step because it means we can work together to address what\u2019s going on!\n\nHere are a few suggestions I think might help:\n\n1. **Shift Your Focus** \u2013 When we speak in front of others, it's easy to focus on ourselves\u2014\u201cWhat if I mess up?\u201d or \u201cWhat will they think of me?\u201d Instead, try shifting your mindset from *performing* to *connecting*. Remember that your audience (big or small) is made up of humans just like you\u2014they're not perfect either! Picture yourself having a conversation with them instead of \"presenting.\"\n\n2. **Prepare Without Overloading** \u2013 Preparing ahead of time can build confidence! But avoid over-preparing until you feel overwhelmed or trapped by perfectionism. Focus on knowing your key points really well so you can communicate naturally without needing to remember every single word.\n\n3. **Practice Makes Progress** \u2013 Speaking confidence doesn\u2019t happen overnight\u2014it takes practice! Start small: rehearse out loud at home or in front of someone who makes you feel comfortable and safe (even practicing in front of a mirror works). With each small success, your confidence will grow.\n\n4. **Breathe Through the Nerves** \u2013 Deep breathing is like magic when it comes to calming nerves. When you feel anxiety creeping in, take slow breaths in through your nose for four counts, hold for four counts, then exhale gently through your mouth for four counts. This helps regulate your body and sends a signal to your brain that it's okay\u2014you\u2019ve got this.", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 2275, "metadata_seperator": "\n", "text_template": "{metadata_str}\n\n{content}", "class_name": "TextNode"}, "__type__": "1"}, "0ebe9a9b-fe2b-4304-9508-d2ad75beb672": {"__data__": {"id_": "0ebe9a9b-fe2b-4304-9508-d2ad75beb672", "embedding": null, "metadata": {}, "excluded_embed_metadata_keys": [], "excluded_llm_metadata_keys": [], "relationships": {"1": {"node_id": "3af7666f-394d-40e4-bb2d-fdd3f5e1de3e", "node_type": "4", "metadata": {}, "hash": "8f200f5ebb8126581d186441a378e5fdb0abe0819e3eb49d2283243453a3c7f1", "class_name": "RelatedNodeInfo"}, "2": {"node_id": "dbb98324-2858-4cf3-82f8-e74ca0e33c1a", "node_type": "1", "metadata": {}, "hash": "c6302110d74e6e3ee3b7126a54d89d8deb6f262fc3740f5f8a239b5335d8ad8c", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "5. **Challenge Negative Thoughts** \u2013 You mentioned self-confidence\u2014it sounds like part of what\u2019s holding you back may be some unhelpful thoughts about yourself or what could go wrong (\"What if I make mistakes?\"). Let\u2019s challenge those: Is making a mistake truly the end of the world? Likely not! In fact, even if something doesn\u2019t go perfectly, people are usually much kinder and more forgiving than we expect.\n\n6. **Celebrate Small Wins** \u2013 Each time you speak up\u2014even if it feels scary\u2014celebrate that as progress! It doesn\u2019t have to be perfect; what matters is that you're taking steps forward.\n\nLastly\u2014and maybe most importantly\u2014be kind to yourself along the way. Growth takes time and patience. Imagine how you'd encourage a close friend if they were feeling nervous; try giving yourself that same encouragement.\n\nIf you'd like more specific tips or just want to talk through things further, I\u2019m right here for you every step of the way! You\u2019ve already taken such a big first step by opening up\u2014and honestly? That takes bravery too! \ud83d\ude0a", "mimetype": "text/plain", "start_char_idx": 2277, "end_char_idx": 3315, "metadata_seperator": "\n", "text_template": "{metadata_str}\n\n{content}", "class_name": "TextNode"}, "__type__": "1"}, "10d686cb-b50b-43ac-b56a-05a4a0e472af": {"__data__": {"id_": "10d686cb-b50b-43ac-b56a-05a4a0e472af", "embedding": null, "metadata": {}, "excluded_embed_metadata_keys": [], "excluded_llm_metadata_keys": [], "relationships": {"1": {"node_id": "50ed7743-8518-44b3-a666-86b2dc69e4a0", "node_type": "4", "metadata": {}, "hash": "25e5c699e18b604196f5e859f3eb872396b92aeb7b5662c5871b1e7550a11316", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "Session on 2026-07-13 18:03:46:\n\nA3: hi\nAI: Hi there! \ud83d\ude0a It's so nice to hear from you. How are you feeling today?\nA3: My friend's name is Cyrus. He likes the color red.\nAI: That's such a nice detail to share about your friend Cyrus! Red is such a bold and vibrant color\u2014it\u2019s often associated with energy, passion, and strength. It\u2019s great that you know this little thing about him; it shows you really care and pay attention to the things he likes. Is there something special about Cyrus you'd like to talk about?", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 513, "metadata_seperator": "\n", "text_template": "{metadata_str}\n\n{content}", "class_name": "TextNode"}, "__type__": "1"}, "5fa8535c-8e93-41c8-a242-057c4ffe5412": {"__data__": {"id_": "5fa8535c-8e93-41c8-a242-057c4ffe5412", "embedding": null, "metadata": {}, "excluded_embed_metadata_keys": [], "excluded_llm_metadata_keys": [], "relationships": {"1": {"node_id": "a1e688e1-cd03-4651-91e8-944129e8e696", "node_type": "4", "metadata": {}, "hash": "88a527e2bf824d8be4bec214878b59c58ce08c80e607824920c649e55029d82d", "class_name": "RelatedNodeInfo"}, "3": {"node_id": "5e37aa2e-cb88-4856-a41e-60d6580cc604", "node_type": "1", "metadata": {}, "hash": "59a8f281c81edf2231ec56e263ac9237d74c6652a033deff2287db6ac9431c07", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "Session on 2026-07-13 18:46:19:\n\nA3: Can you tell me the name of my friend I told you about a few sessions ago?\nAI: Oh no, I don\u2019t have memory of past sessions. But I\u2019d love for you to tell me again about your friend! What's their name, and what makes them special to you? \ud83d\ude0a\nA3: What job is right for me based on my personality traits?\nAI: Great question! Discovering the right job for you starts with knowing yourself and finding ways to align your personality traits, values, and interests with a career that feels fulfilling. Why don't you tell me a bit about yourself? \ud83d\ude0a For example:\n\n- What are your strengths? Are you creative, analytical, empathetic, detail-oriented, or maybe great at leading others?\n- What do you enjoy doing or feel passionate about? Do you thrive working alone or in teams?\n- How do you usually solve problems\u2014logically, creatively, or by relying on intuition?\n- What\u2019s most important to you in a job\u2014money, work-life balance, helping people, opportunities to grow?\n\nIf you'd like, I can help explore some possibilities that match who *you* are! \ud83d\udc9b\nA3: What job is right for me based on my personality traits?\nAI: That's a great question and an important one! Deciding on a career that aligns with your personality traits can lead to greater job satisfaction, personal fulfillment, and success. If you're comfortable sharing some details about your personality\u2014such as whether you're more introverted or extroverted, detail-oriented or big-picture focused, creative or analytical\u2014it could help guide the discussion. For now, here are some general ideas based on common personality traits:\n\n### 1. **If You're Analytical and Detail-Oriented**\n   - **Potential Careers:** Data analyst, accountant, scientist, engineer\n   - These fields often require precision and problem-solving skills.\n\n### 2. **If You're Creative and Imaginative**\n   - **Potential Careers:** Graphic designer, writer, artist, advertising professional\n   - Creative fields allow you to express ideas in unique ways.\n\n### 3. **If You Enjoy Helping Others**\n   - **Potential Careers:** Teacher, therapist, social worker, healthcare provider\n   - These roles focus on making a difference in people's lives.\n\n### 4.", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 2206, "metadata_seperator": "\n", "text_template": "{metadata_str}\n\n{content}", "class_name": "TextNode"}, "__type__": "1"}, "5e37aa2e-cb88-4856-a41e-60d6580cc604": {"__data__": {"id_": "5e37aa2e-cb88-4856-a41e-60d6580cc604", "embedding": null, "metadata": {}, "excluded_embed_metadata_keys": [], "excluded_llm_metadata_keys": [], "relationships": {"1": {"node_id": "a1e688e1-cd03-4651-91e8-944129e8e696", "node_type": "4", "metadata": {}, "hash": "88a527e2bf824d8be4bec214878b59c58ce08c80e607824920c649e55029d82d", "class_name": "RelatedNodeInfo"}, "2": {"node_id": "5fa8535c-8e93-41c8-a242-057c4ffe5412", "node_type": "1", "metadata": {}, "hash": "0b216677a78ea2fad032c2d8c8e8fb53077547b414a00792411d3b928c14fa91", "class_name": "RelatedNodeInfo"}, "3": {"node_id": "899d5e26-14b9-49a0-b82e-56f7f62d007e", "node_type": "1", "metadata": {}, "hash": "66bbf6498616ef6de2315fc7bba82641968ab56ed6d4fce8cc9fe42d4a055fca", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "### 4. **If You're Extroverted and Thrive Around People**\n   - **Potential Careers:** Salesperson, event planner, public relations specialist\n   - Extroverts often enjoy careers that involve networking and interpersonal communication.\n\n### 5. **If You're Introverted and Prefer Independent Work**\n   - **Potential Careers:** Software developer, researcher, writer\n   - Introverts may excel in fields that involve deep concentration.\n\nUnderstanding yourself is key to finding a meaningful path. If you'd like to explore further or take a specific personality test (like Myers-Briggs or Holland Codes), I\u2019d be happy to guide you! What's something you're passionate about or enjoy doing? \ud83d\ude0a\nA3: What job is right for me based on my personality traits?\nAI: Choosing the right career based on your personality traits can be such an exciting journey! While I don\u2019t know much about you yet, I\u2019m happy to help you explore your options by focusing on what might align with your strengths, values, and preferences. Let\u2019s dig in together!\n\n### Step 1: Self-Reflection  \nHere are a few questions to reflect on:  \n- **What excites you?** Are you drawn to creative projects, helping people, solving problems, organizing details, or working with your hands?  \n- **How do you prefer working?** Do you thrive in team settings or do you enjoy solo work? Do you crave structure or freedom in how tasks are approached?  \n- **What stresses or energizes you?** Knowing how you respond to challenges can help avoid mismatches.  \n\n---\n\n### Personality Trait & Career Match Guide\nHere\u2019s how certain personality traits often relate to career paths:  \n\n#### 1\ufe0f\u20e3 **If you're analytical and detail-oriented:**  \n   - Careers like data analysis, accounting, engineering, or software development may fit because they require precision and problem-solving.  \n\n#### 2\ufe0f\u20e3 **If you're creative and imaginative:**  \n   - Consider fields such as graphic design, marketing, writing, art therapy, architecture, or filmmaking where your innovation thrives.\n\n#### 3\ufe0f\u20e3 **If you're empathetic and people-focused:**  \n   - Teaching, psychology/counseling (yay for psychology!), nursing, social work, human resources (HR), or roles that involve advocacy could be deeply fulfilling.", "mimetype": "text/plain", "start_char_idx": 2200, "end_char_idx": 4434, "metadata_seperator": "\n", "text_template": "{metadata_str}\n\n{content}", "class_name": "TextNode"}, "__type__": "1"}, "899d5e26-14b9-49a0-b82e-56f7f62d007e": {"__data__": {"id_": "899d5e26-14b9-49a0-b82e-56f7f62d007e", "embedding": null, "metadata": {}, "excluded_embed_metadata_keys": [], "excluded_llm_metadata_keys": [], "relationships": {"1": {"node_id": "a1e688e1-cd03-4651-91e8-944129e8e696", "node_type": "4", "metadata": {}, "hash": "88a527e2bf824d8be4bec214878b59c58ce08c80e607824920c649e55029d82d", "class_name": "RelatedNodeInfo"}, "2": {"node_id": "5e37aa2e-cb88-4856-a41e-60d6580cc604", "node_type": "1", "metadata": {}, "hash": "59a8f281c81edf2231ec56e263ac9237d74c6652a033deff2287db6ac9431c07", "class_name": "RelatedNodeInfo"}, "3": {"node_id": "9828df2d-ecab-4985-8647-91af64d1aaff", "node_type": "1", "metadata": {}, "hash": "c1bf2082163a7cafe35f2a17625cf2709758718dc7fe8a78a18945a136f60aaf", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "#### 4\ufe0f\u20e3 **If you're adventurous and thrive under pressure:**  \n   - You might enjoy entrepreneurship, event planning, emergency response roles (like EMTs or firefighters), travel-based jobs (flight attendant/tour guide), or careers in media.\n\n#### 5\ufe0f\u20e3 **If you're methodical and organized:**  \n   - Administrative roles (e.g., project manager), library sciences, law/legal studies (paralegal/lawyer), urban planning\u2014and even logistics\u2014might appeal.\n\n---\n\n### Personality Tests for More Clarity  \nPsychological tools like the Myers-Briggs Type Indicator (MBTI) or Holland Codes can help narrow down possibilities by connecting personality traits to job categories:  \n- MBTI Types (e.g., INFPs love meaningful work; ESTJs excel at structured leadership roles).  \n- Holland Codes focus on interests like Artistic (\"A\"), Investigative (\"I\"), Social (\"S\"), etc.  \n\nWould you like me to dive into a specific test or trait with you? Or share anything about yourself so we can brainstorm further\u2014I\u2019m here for it! \ud83d\ude0a\nA3: What job is right for me based on my personality traits?\nAI: That's such a great question! Choosing the right career often comes down to understanding your strengths, values, and personality traits. While I don't know much about your specific characteristics yet, I can help guide you through some reflective questions to uncover what might suit you best.\n\n### 1. **Discover Your Personality Traits**\nConsider your preferences and tendencies. Are you:\n   - **Social** (do you thrive in team settings and enjoy interacting with others)?\n   - **Creative** (do you love solving problems or expressing ideas in unique ways)?\n   - **Logical** (do you enjoy structure, data, and critical thinking)?\n   - **Compassionate** (are you motivated by helping people or making a difference)?\n   - **Detail-oriented** (do you have a knack for organization and precision)?\n\nYou could also look into tools like the Myers-Briggs Type Indicator (MBTI) or Big Five Personality traits for deeper insights.\n\n---\n\n### 2. **Evaluate Your Interests**\nWhat kinds of activities light you up? Are there hobbies or topics you're naturally drawn toward? For example:\n   - If you're energized by helping people, roles like counseling, healthcare, or teaching could be great.", "mimetype": "text/plain", "start_char_idx": 4436, "end_char_idx": 6691, "metadata_seperator": "\n", "text_template": "{metadata_str}\n\n{content}", "class_name": "TextNode"}, "__type__": "1"}, "9828df2d-ecab-4985-8647-91af64d1aaff": {"__data__": {"id_": "9828df2d-ecab-4985-8647-91af64d1aaff", "embedding": null, "metadata": {}, "excluded_embed_metadata_keys": [], "excluded_llm_metadata_keys": [], "relationships": {"1": {"node_id": "a1e688e1-cd03-4651-91e8-944129e8e696", "node_type": "4", "metadata": {}, "hash": "88a527e2bf824d8be4bec214878b59c58ce08c80e607824920c649e55029d82d", "class_name": "RelatedNodeInfo"}, "2": {"node_id": "899d5e26-14b9-49a0-b82e-56f7f62d007e", "node_type": "1", "metadata": {}, "hash": "66bbf6498616ef6de2315fc7bba82641968ab56ed6d4fce8cc9fe42d4a055fca", "class_name": "RelatedNodeInfo"}, "3": {"node_id": "500c89b8-dd6c-46eb-9942-47b36d68941a", "node_type": "1", "metadata": {}, "hash": "820296d22b4a5580e3be7c8a52678cb87195658844208e6d3be4fac8b29a0e8e", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "- If problem-solving excites you, consider careers in engineering, science, or strategy-focused fields.\n   - If creativity is your forte, explore jobs in design, marketing, writing, or arts-based industries.\n\n---\n\n### 3. **Use Career Assessments**\nTools like Holland\u2019s Career Theory divide jobs into six interest areas: Realistic (hands-on work), Investigative (research-oriented), Artistic (creative), Social (helping others), Enterprising (leadership/sales), and Conventional (organized office work). These assessments pair personality types with occupations that might suit them best.\n\n---\n\n### 4. **Align with Core Values**\nThink about what matters most to you in life: Stability? Freedom? Collaboration? Work-life balance? Choosing a job aligned with your values can bring long-term satisfaction.\n\nWould it help if I walked through some of these points more deeply with examples? Or tell me more about yourself\u2014I\u2019d love to assist further!\nA3: What job is right for me based on my personality traits?\nAI: Great question! Figuring out a career path that matches your personality can help you find fulfillment and happiness in your work. To start, let\u2019s take a closer look at how your personality traits align with potential jobs. If you'd like to share more about yourself\u2014such as strengths, hobbies, values, or even how you recharge (e.g., alone time or social activities)\u2014it would help me give you more tailored suggestions!\n\nThat said, here are some general suggestions based on common personality dimensions:\n\n---\n\n### 1. **Are you outgoing and energized by people?**\n   - **Consider:** Careers that involve communication, teamwork, or public-facing roles.\n     - Examples: Sales, marketing, teaching, event planning, counseling, or customer relations.\n\n---\n\n### 2. **Do you enjoy details and structured tasks?**\n   - **Consider:** Roles that involve organization and precision.\n     - Examples: Project management, data analysis, accounting, administrative work.\n\n---\n\n### 3. **Are you creative and imaginative?**\n   - **Consider:** Careers where innovation and originality shine.\n     - Examples: Graphic design, writing/journalism, advertising/branding, architecture.\n\n---\n\n### 4. **Do you love helping others?**\n   - **Consider:** Jobs that focus on empathy and service.\n     - Examples: Social work, psychology/counseling, healthcare (like nursing), non-profit roles.", "mimetype": "text/plain", "start_char_idx": 6695, "end_char_idx": 9074, "metadata_seperator": "\n", "text_template": "{metadata_str}\n\n{content}", "class_name": "TextNode"}, "__type__": "1"}, "500c89b8-dd6c-46eb-9942-47b36d68941a": {"__data__": {"id_": "500c89b8-dd6c-46eb-9942-47b36d68941a", "embedding": null, "metadata": {}, "excluded_embed_metadata_keys": [], "excluded_llm_metadata_keys": [], "relationships": {"1": {"node_id": "a1e688e1-cd03-4651-91e8-944129e8e696", "node_type": "4", "metadata": {}, "hash": "88a527e2bf824d8be4bec214878b59c58ce08c80e607824920c649e55029d82d", "class_name": "RelatedNodeInfo"}, "2": {"node_id": "9828df2d-ecab-4985-8647-91af64d1aaff", "node_type": "1", "metadata": {}, "hash": "c1bf2082163a7cafe35f2a17625cf2709758718dc7fe8a78a18945a136f60aaf", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "- Examples: Social work, psychology/counseling, healthcare (like nursing), non-profit roles.\n\n---\n\n### 5. **Do you have an investigative mind or enjoy solving complex problems?**\n   - **Consider:** Analytical fields where your curiosity is valued.\n     - Examples: Science (biology/physics), engineering, IT/software development.\n\n---\n\nIf you'd like to dive deeper into this topic together\u2014or take a quick personality quiz to pinpoint things\u2014I\u2019m here for it! Let me know what resonates with you most about these options!\nA3: Hi\nAI: Hey there! \ud83d\ude0a How\u2019s your day going so far?", "mimetype": "text/plain", "start_char_idx": 8982, "end_char_idx": 9555, "metadata_seperator": "\n", "text_template": "{metadata_str}\n\n{content}", "class_name": "TextNode"}, "__type__": "1"}}}

memories/memory_index/llamaindex/A3/sessions/graph_store.json

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-{"graph_dict": {}}

memories/memory_index/llamaindex/A3/sessions/image__vector_store.json

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-{"embedding_dict": {}, "text_id_to_ref_doc_id": {}, "metadata_dict": {}}

memories/memory_index/llamaindex/A3/sessions/index_store.json

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memories/memory_index/llamaindex/A4/episodic_memory/default__vector_store.json

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memories/memory_index/llamaindex/A4/episodic_memory/docstore.json

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memories/memory_index/llamaindex/A4/episodic_memory/graph_store.json

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memories/memory_index/llamaindex/A4/episodic_memory/image__vector_store.json

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memories/memory_index/llamaindex/A4/episodic_memory/index_store.json

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memories/memory_index/llamaindex/A4/semantic_memory/default__vector_store.json

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memories/memory_index/llamaindex/A4/semantic_memory/docstore.json

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memories/memory_index/llamaindex/A4/semantic_memory/graph_store.json

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memories/memory_index/llamaindex/A4/semantic_memory/image__vector_store.json

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-{"embedding_dict": {}, "text_id_to_ref_doc_id": {}, "metadata_dict": {}}

memories/memory_index/llamaindex/A4/semantic_memory/index_store.json

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memories/memory_index/llamaindex/A4/sessions/docstore.json

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memories/memory_index/llamaindex/A4/sessions/graph_store.json

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memories/memory_index/llamaindex/A4/sessions/image__vector_store.json

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memories/memory_index/llamaindex/A4/sessions/index_store.json

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memories/memory_index/llamaindex/Ali/episodic_memory/default__vector_store.json

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memories/memory_index/llamaindex/Ali/episodic_memory/docstore.json

@@ -1 +0,0 @@
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