from abc import ABC, abstractmethod
from typing import Dict, Any, Optional
import logging
from typing import Dict, Any, Optional
from core.data_access.base_data_source import BaseDataSource
import json
import logging
from pathlib import Path
from typing import Dict, Any, Optional
from core.data_access.base_data_source import BaseDataSource
from core.system.error_handler import FileReadError, InvalidInputError
import requests
import pandas as pd
import logging # Added import
from core.utils.secrets_utils import get_api_key # Added import
import tweepy
from textblob import TextBlob
from facebook_scraper import get_posts
import logging # Added import
from core.utils.secrets_utils import get_api_key # Added import
import requests
import pandas as pd
import logging # Added import
from core.utils.secrets_utils import get_api_key # Added import
import logging
import requests
from textblob import TextBlob
import logging # Added import
from core.utils.secrets_utils import get_api_key # Added import
import requests
from textblob import TextBlob
import tweepy
import logging # Added import
from core.utils.secrets_utils import get_api_key # Added import
from core.data_sources.financial_news_api import FinancialNewsAPI
from core.data_sources.market_data_api import MarketDataAPI
import logging
from typing import List, Optional
import os
from core.embeddings.base_embedding_model import BaseEmbeddingModel
import logging
from typing import List
from core.embeddings.base_embedding_model import BaseEmbeddingModel
from abc import ABC, abstractmethod
import numpy as np
from scipy.stats import norm
import pandas as pd  # For data manipulation
from typing import Dict, Any, Tuple, List  # For type hinting
from datetime import datetime
import pandas as pd
import numpy as np
from sklearn.ensemble import RandomForestClassifier
from ta.trend import SMAIndicator, MACD, ADXIndicator
from ta.momentum import RSIIndicator, StochasticOscillator
from ta.volatility import BollingerBands
from ta.volume import OnBalanceVolumeIndicator
from typing import Dict, Any, Tuple
import pandas as pd
import numpy as np
from langchain.agents import Tool
from langchain.tools.python.tool import PythonAstREPLTool
import logging
import yaml
import os
import importlib
from pathlib import Path
from collections import deque
from typing import Dict, Optional, List, Any
import asyncio  # expand asynchronous communication
import json
from core.agents.agent_base import AgentBase
from core.llm_plugin import LLMPlugin
from core.agents.query_understanding_agent import QueryUnderstandingAgent
from core.agents.data_retrieval_agent import DataRetrievalAgent
from core.agents.market_sentiment_agent import MarketSentimentAgent
from core.agents.macroeconomic_analysis_agent import MacroeconomicAnalysisAgent
from core.agents.geopolitical_risk_agent import GeopoliticalRiskAgent
from core.agents.industry_specialist_agent import IndustrySpecialistAgent
from core.agents.fundamental_analyst_agent import FundamentalAnalystAgent
from core.agents.technical_analyst_agent import TechnicalAnalystAgent
from core.agents.risk_assessment_agent import RiskAssessmentAgent
from core.agents.newsletter_layout_specialist_agent import NewsletterLayoutSpecialistAgent
from core.agents.data_verification_agent import DataVerificationAgent
from core.agents.lexica_agent import LexicaAgent
from core.agents.archive_manager_agent import ArchiveManagerAgent
from core.agents.agent_forge import AgentForge
from core.agents.prompt_tuner import PromptTuner
from core.agents.code_alchemist import CodeAlchemist
from core.agents.lingua_maestro import LinguaMaestro
from core.agents.sense_weaver import SenseWeaver
from core.agents.snc_analyst_agent import SNCAnalystAgent # Added import
from core.agents.behavioral_economics_agent import BehavioralEconomicsAgent
from core.agents.meta_cognitive_agent import MetaCognitiveAgent
from core.utils.config_utils import load_config
from core.utils.secrets_utils import get_api_key # Added import
from semantic_kernel import Kernel
from semantic_kernel.connectors.ai.open_ai import OpenAIChatCompletion
from financial_digital_twin.nexus_agent import NexusAgent
import pandas as pd
from core.utils.data_utils import validate_data
import importlib
import os
from core.utils.config_utils import load_config
import json
import logging
from typing import Optional
from pathlib import Path
import time
from core.utils.data_utils import send_alert
import psutil
import time
from core.utils.config_utils import load_error_codes # Import the function
from core.system.agent_orchestrator import AgentOrchestrator
from core.system.echo import Echo  # Assuming Echo is used for final output
from core.utils.config_utils import load_config  # For loading configurations
from core.utils.token_utils import check_token_limit, count_tokens  # Import token utilities
import logging  # Import the logging module
import schedule
import time
from plugin_manager import PluginManager
from agents import * # Import all agents
from core.utils.config_utils import load_app_config # Added import
import json
import pandas as pd
from typing import List, Dict
import random
import numpy as np
from mesa import Agent, Model
from mesa.time import RandomActivation
from mesa.datacollection import DataCollector
import json
from typing import Dict, Any
from core.llm.base_llm_engine import BaseLLMEngine
from core.world_simulation.config import WorldSimulationConfig
import yaml
from dataclasses import dataclass, field
from typing import List, Dict
import random
import numpy as np
from mesa import Agent, Model
from mesa.time import RandomActivation
from mesa.datacollection import DataCollector
from abc import ABC, abstractmethod
from typing import Any
import logging
from typing import Any
from core.tools.base_tool import BaseTool
from J鏟J_sandbox_tools import view_text_website
from semantic_kernel.functions.kernel_function_decorator import kernel_function
import os
import logging
from typing import Optional
import pika
import json
from core.utils.data_utils import send_message, receive_messages
import re
import json
import pandas as pd
import numpy as np
from datetime import datetime
import pika
import csv
import logging
import yaml #if needed
from pathlib import Path
from typing import Dict, Any, Optional, Union, List
from core.system.error_handler import FileReadError, InvalidInputError, DataNotFoundError
from flask import jsonify
import yaml
import os # Import the 'os' module
import logging
from typing import Dict, Any, Optional
import tiktoken  # Use tiktoken for accurate token counting
import logging
import json
from flask import Flask, request, jsonify
from core.system.agent_orchestrator import AgentOrchestrator
from core.system.echo import Echo
from core.utils.api_utils import (
import json
from datetime import datetime
from utils.api_communication import APICommunication
from agents.Fundamental_Analysis_Agent import FundamentalAnalystAgent
from agents.Technical_Analysis_Agent import TechnicalAnalystAgent
from agents.Risk_Assessment_Agent import RiskAssessmentAgent
from agents.Prediction_Market_Agent import PredictionMarketAgent
from agents.Alternative_Data_Agent import AlternativeDataAgent
from agents.Crypto_Agent import CryptoAgent
from agents.discussion_chair_agent import DiscussionChairAgent  # Import the Discussion Chair Agent
import json
from utils.api_communication import APICommunication
from agents.Risk_Assessment_Agent import RiskAssessmentAgent
from agents.Macroeconomic_Analysis_Agent import MacroeconomicAnalysisAgent
from agents.Geopolitical_Risk_Agent import GeopoliticalRiskAgent
from agents.Industry_Specialist_Agent import IndustrySpecialistAgent
import json
from utils.api_communication import APICommunication
from agents.SNC_Analyst_Agent import SNCAnalystAgent
from agents.Regulatory_Compliance_Agent import RegulatoryComplianceAgent
from agents.Legal_Agent import LegalAgent
import json
from utils.api_communication import APICommunication
from agents.Fundamental_Analysis_Agent import FundamentalAnalystAgent
from agents.Industry_Specialist_Agent import IndustrySpecialistAgent
from agents.Risk_Assessment_Agent import RiskAssessmentAgent
from agents.Legal_Agent import LegalAgent
import json
from utils.api_communication import APICommunication
from agents.Anomaly_Detection_Agent import AnomalyDetectionAgent
from agents.Machine_Learning_Model_Training_Agent import MachineLearningModelTrainingAgent
from agents.Alternative_Data_Agent import AlternativeDataAgent
import json
from agents.SNC_Analyst_Agent import SNCAnalystAgent
from agents.Fundamental_Analysis_Agent import FundamentalAnalystAgent
from agents.Industry_Specialist_Agent import IndustrySpecialistAgent
from agents.discussion_chair_agent import DiscussionChairAgent  # Import the Discussion Chair Agent
import json
from utils.api_communication import APICommunication
from agents.Risk_Assessment_Agent import RiskAssessmentAgent
from agents.Fundamental_Analysis_Agent import FundamentalAnalystAgent
from agents.Technical_Analysis_Agent import TechnicalAnalystAgent
from agents.Market_Sentiment_Agent import MarketSentimentAgent
from agents.Prediction_Market_Agent import PredictionMarketAgent
from agents.Alternative_Data_Agent import AlternativeDataAgent
import logging
from typing import List, Optional
from abc import ABC, abstractmethod
import logging
from typing import List
from core.llm.base_llm_engine import BaseLLMEngine
import logging
from typing import List, Optional
import os # For API key handling
from core.llm.base_llm_engine import BaseLLMEngine
import json
import numpy as np
import pandas as pd
from sklearn.linear_model import LinearRegression
from web3 import Web3
import statsmodels.api as sm
from core.agents.agent_base import AgentBase  # Assuming you have a base class for agents
from core.utils.config_utils import load_config
from core.utils.token_utils import count_tokens, check_token_limit
import logging
from core.agents.agent_base import AgentBase  # Assuming you have a base class for agents
from core.utils.config_utils import load_config
from core.utils.token_utils import count_tokens, check_token_limit
import logging
from typing import Any, Dict, List, Optional
import asyncio
from langchain.utilities import GoogleSearchAPIWrapper
from transformers import pipeline
from core.agents.agent_base import AgentBase
from typing import Any, Dict, List, Optional
import logging
from transformers import pipeline
import pandas as pd
import numpy as np
from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import train_test_split
import datetime
import requests
import json
from typing import List, Dict
from .base_agent import BaseAgent
from utils.data_validation import validate_event_data
from utils.visualization_tools import generate_event_impact_chart
from core.utils.data_utils import send_message
import json
import datetime
import requests
import numpy as np
from web3 import Web3
from web3.middleware import geth_poa_middleware
from sklearn.linear_model import LinearRegression
import nltk
from nltk.sentiment import SentimentIntensityAnalyzer
import talib
import ccxt
from pycoingecko import CoinGeckoAPI
import time
import os
from collections import deque
import json
import requests
from datetime import datetime
import logging
import os
import json
import logging
from core.utils.data_utils import send_message, receive_messages
from core.utils.api_utils import get_knowledge_graph_data
import sys
import os
import logging
import json 
import os # For os.path.exists and os.remove
import asyncio
from enum import Enum
from typing import Dict, Any, Optional, Tuple
from unittest.mock import patch 
from core.agents.agent_base import AgentBase
from semantic_kernel import Kernel 
from transformers import pipeline
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import random
import os
import ast
from langchain.utilities import GoogleSearchAPIWrapper
from typing import Dict, List, Union
import re
from io import StringIO
import sys
import contextlib
import logging
import os
import ast
from typing import Any, Dict, List, Optional, Union
import re
from io import StringIO
import sys
import contextlib
import logging
import asyncio
import aiohttp
import json
from core.agents.agent_base import AgentBase
from core.utils.config_utils import load_config
from core.llm_plugin import LLMPlugin
import logging
from typing import Any, Dict, Optional
from core.agents.agent_base import AgentBase
from typing import Any, Dict
from core.agents.agent_base import AgentBase
import requests
from core.agents.agent_base import AgentBase
from typing import Any, Dict
from core.agents.agent_base import AgentBase
from typing import Any, Dict
from core.agents.agent_base import AgentBase
import requests
from core.agents.agent_base import AgentBase
import csv
import os
import logging
import pandas as pd
import numpy as np
from scipy import stats  # For statistical calculations (e.g., for DCF)
from typing import Dict, Any, Optional, Union 
from core.agents.agent_base import AgentBase
from semantic_kernel import Kernel # Added for type hinting
import asyncio # Added import
import yaml # Added for example usage block
from unittest.mock import patch # Added for example usage
from typing import Any, Dict
from core.agents.agent_base import AgentBase
from typing import Any, Dict
from core.agents.agent_base import AgentBase
from typing import Any, Dict
from core.agents.agent_base import AgentBase
from typing import Any, Dict
from core.agents.agent_base import AgentBase
from typing import Any, Dict
from core.agents.agent_base import AgentBase
from core.agents.agent_base import AgentBase
from textblob import TextBlob
from core.agents.agent_base import AgentBase
from textblob import TextBlob
import requests
from bs4 import BeautifulSoup
from abc import ABC, abstractmethod
from typing import Any, Dict, List, Optional # Optional was already here, ensure Dict and Any are used consistently
import logging
import json
import asyncio
from semantic_kernel import Kernel
from core.llm.base_llm_engine import BaseLLMEngine
from core.embeddings.base_embedding_model import BaseEmbeddingModel
from core.vectorstore.base_vector_store import BaseVectorStore
import logging
import json
import os
import asyncio
from typing import Optional, Union, List, Dict, Any
from core.agents.agent_base import AgentBase
from core.utils.data_utils import load_data # Assuming load_data is suitable
from core.system.knowledge_base import KnowledgeBase
from core.system.error_handler import DataNotFoundError, FileReadError 
from semantic_kernel import Kernel # For AgentBase type hinting
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression
import requests
import logging
from bs4 import BeautifulSoup
import folium
from geopy.geocoders import Nominatim
import requests
import nltk
from nltk.sentiment import SentimentIntensityAnalyzer
from collections import defaultdict
import time
from pycoingecko import CoinGeckoAPI
import json
import numpy as np
from sklearn.cluster import KMeans
from datetime import datetime
import random
from sklearn.metrics import pairwise_distances_argmin_min
from typing import Dict, Any, Optional, List
import feedparser # Added import
import time # For parsing published_at if needed
from datetime import timezone # For timezone aware datetime objects
from semantic_kernel import Kernel
from core.agents.agent_base import AgentBase
import torch # Added import
from transformers import AutoTokenizer, AutoModelForSequenceClassification # Added import
import nltk # Added import for sentence tokenization in summarizer fallback
from transformers import AutoModelForSeq2SeqLM # Added import for summarization model
import json
import nltk
from nltk.sentiment import SentimentIntensityAnalyzer
from textblob import TextBlob
from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer as VaderSentiment
import yfinance as yf
import googlemaps
import importlib
from core.utils.data_utils import send_message
import json
import numpy as np
from scipy.stats import norm
import json
import datetime
from core.data_sources.financial_news_api import SimulatedFinancialNewsAPI
from core.data_sources.prediction_market_api import SimulatedPredictionMarketAPI
from core.data_sources.social_media_api import SimulatedSocialMediaAPI
from core.data_sources.web_traffic_api import SimulatedWebTrafficAPI
from core.utils.data_utils import send_message
import numpy as np
import pandas as pd
from scipy import stats
from sklearn.ensemble import IsolationForest
from sklearn.neighbors import LocalOutlierFactor
from sklearn.svm import OneClassSVM
from sklearn.cluster import KMeans
from statsmodels.tsa.seasonal import seasonal_decompose
from statsmodels.tsa.arima.model import ARIMA
from sklearn.preprocessing import StandardScaler
from typing import Dict, List
import os
import json
import datetime
import pandas as pd
from textblob import TextBlob
import pandas as pd
from textblob import TextBlob
import pandas as pd
from textblob import TextBlob
import pandas as pd
from textblob import TextBlob
import pandas as pd
from textblob import TextBlob
import pandas as pd
from textblob import TextBlob
import pandas as pd
from textblob import TextBlob
import pandas as pd
from textblob import TextBlob
import pandas as pd
from textblob import TextBlob
import pandas as pd
from textblob import TextBlob
import pandas as pd
from textblob import TextBlob
import json
import json
import logging
import json
from core.utils.data_utils import send_message
import logging
import os
from typing import Any, Dict, List, Optional
from pathlib import Path
import importlib
import yaml
from core.agents.agent_base import AgentBase
from core.utils.config_utils import load_config, save_config
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy import stats
import logging
from typing import Dict, Any, Tuple, List
import openpyxl
from langchain.prompts import PromptTemplate
from core.utils.data_utils import send_message, receive_messages
from typing import List, Dict
import re
from textblob import TextBlob  # Example NLP library
import spacy  # Another example NLP library
import json #knowledge base
from typing import Any, Dict
from core.agents.agent_base import AgentBase
from core.agents.agent_base import AgentBase
from core.agents.agent_base import AgentBase
import re
from typing import Dict, List, Tuple
import nltk  # Natural Language Processing
import requests  # API interaction
from bs4 import BeautifulSoup  # Web scraping
from neo4j import GraphDatabase  # Knowledge graph interaction
import matplotlib.pyplot as plt
import seaborn as sns
import plotly.express as px
import logging
from core.agents.agent_base import AgentBase
from core.utils.config_utils import load_config
import numpy as np
import pandas as pd
import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, LSTM, Dropout
from typing import List, Dict
from .base_agent import BaseAgent
from utils.data_validation import validate_portfolio_data
from utils.visualization_tools import generate_portfolio_visualization
from langchain.utilities import GoogleSearchAPIWrapper
from transformers import pipeline
from nltk.sentiment import SentimentIntensityAnalyzer
import pandas as pd
import numpy as np
from core.agents.agent_base import AgentBase
from typing import Any, Dict, List, Optional
import logging
import re
from core.agents.agent_base import Agent
from core.agents.agent_base import Agent
from core.llm.engines.dummy_llm_engine import DummyLLMEngine
from core.embeddings.models.dummy_embedding_model import DummyEmbeddingModel
from core.rag.document_handling import Document
from semantic_kernel import Kernel
import logging
from typing import List, Tuple
import numpy as np
from core.vectorstore.base_vector_store import BaseVectorStore
from abc import ABC, abstractmethod
from typing import List, Tuple
import os
import logging
from abc import ABC, abstractmethod
from typing import Dict, Any, Optional, Tuple, List
from dotenv import load_dotenv
import yaml
from pathlib import Path
import json
import time
import hashlib