Update app.py

app.py

@@ -1,1028 +1,30 @@
 import pandas as pd
+import yfinance as yf
 from datasets import load_dataset
 from transformers import pipeline
 import plotly.express as px
-import yfinance as yf
+import plotly.graph_objects as go
 import gradio as gr
 
-# --- CONFIG ---
-companies =['Nvidia',
- 'Microsoft',
- 'Apple Inc.',
- 'Amazon',
- 'Meta Platforms',
- 'Broadcom',
- 'Alphabet Inc. (Class A)',
- 'Alphabet Inc. (Class C)',
- 'Tesla, Inc.',
- 'Berkshire Hathaway',
- 'Oracle Corporation',
- 'JPMorgan Chase',
- 'Walmart',
- 'Lilly (Eli)',
- 'Visa Inc.',
- 'Mastercard',
- 'Netflix',
- 'ExxonMobil',
- 'Palantir Technologies',
- 'Johnson & Johnson',
- 'Costco',
- 'Home Depot (The)',
- 'AbbVie',
- 'Bank of America',
- 'Procter & Gamble',
- 'GE Aerospace',
- 'Chevron Corporation',
- 'UnitedHealth Group',
- 'Coca-Cola Company (The)',
- 'Wells Fargo',
- 'Cisco',
- 'T-Mobile US',
- 'Morgan Stanley',
- 'Advanced Micro Devices',
- 'Philip Morris International',
- 'IBM',
- 'Goldman Sachs',
- 'American Express',
- 'Abbott Laboratories',
- 'Salesforce',
- 'Linde plc',
- 'Caterpillar Inc.',
- "McDonald's",
- 'RTX Corporation',
- 'AT&T',
- 'Merck & Co.',
- 'Uber',
- 'Walt Disney Company (The)',
- 'ServiceNow',
- 'PepsiCo',
- 'Intuit',
- 'Citigroup',
- 'Arista Networks',
- 'Verizon',
- 'Micron Technology',
- 'Thermo Fisher Scientific',
- 'Qualcomm',
- 'Booking Holdings',
- 'BlackRock',
- 'Charles Schwab Corporation',
- 'GE Vernova',
- 'Boeing',
- 'Lam Research',
- 'Texas Instruments',
- 'Intuitive Surgical',
- 'S&P Global',
- 'TJX Companies',
- 'Adobe Inc.',
- 'Applied Materials',
- 'Amgen',
- 'Amphenol',
- 'Accenture',
- "Lowe's",
- 'Blackstone Inc.',
- 'NextEra Energy',
- 'Capital One',
- 'Boston Scientific',
- 'Eaton Corporation',
- 'Stryker Corporation',
- 'Progressive Corporation',
- 'Gilead Sciences',
- 'Palo Alto Networks',
- 'Pfizer',
- 'Danaher Corporation',
- 'Intel',
- 'KLA Corporation',
- 'KKR',
- 'Honeywell',
- 'Union Pacific Corporation',
- 'Deere & Company',
- 'CrowdStrike',
- 'Medtronic',
- 'Analog Devices',
- 'Automatic Data Processing',
- 'Comcast',
- 'ConocoPhillips',
- 'DoorDash',
- 'Welltower',
- 'Lockheed Martin',
- 'Altria',
- 'Chubb Limited',
- 'Prologis',
- 'Nike, Inc.',
- 'Constellation Energy',
- 'Cadence Design Systems',
- 'Southern Company',
- 'Vertex Pharmaceuticals',
- 'Marsh McLennan',
- 'Intercontinental Exchange',
- 'Starbucks',
- 'Parker Hannifin',
- 'CVS Health',
- 'CME Group',
- 'Duke Energy',
- 'HCA Healthcare',
- 'Newmont',
- 'Bristol Myers Squibb',
- 'Trane Technologies',
- 'Synopsys',
- 'American Tower',
- 'Royal Caribbean Group',
- 'Dell Technologies',
- "O'Reilly Auto Parts",
- 'Waste Management',
- "Moody's Corporation",
- 'General Dynamics',
- 'Sherwin-Williams',
- 'McKesson Corporation',
- 'Coinbase Global',
- '3M',
- 'Mondelez International',
- 'Northrop Grumman',
- 'Apollo Global Management',
- 'PNC Financial Services',
- 'Cintas',
- 'Motorola Solutions',
- 'U.S. Bancorp',
- 'Cigna',
- 'Airbnb',
- 'Equinix',
- 'Arthur J. Gallagher & Co.',
- 'BNY Mellon',
- 'Howmet Aerospace',
- 'Illinois Tool Works',
- 'Aon',
- 'Ecolab',
- 'Emerson Electric',
- 'Williams Companies',
- 'Marriott International',
- 'TransDigm Group',
- 'Fiserv',
- 'Vistra Corp.',
- 'United Parcel Service',
- 'Republic Services',
- 'Johnson Controls',
- 'Elevance Health',
- 'AutoZone',
- 'Autodesk',
- 'Corning Inc.',
- 'Colgate-Palmolive',
- 'PayPal',
- 'Zoetis',
- 'Freeport-McMoRan',
- 'Fortinet',
- 'Air Products',
- 'TE Connectivity',
- 'Norfolk Southern Railway',
- 'EOG Resources',
- 'Hilton Worldwide',
- 'Regeneron Pharmaceuticals',
- 'Monster Beverage',
- 'Travelers Companies (The)',
- 'Workday, Inc.',
- 'CSX Corporation',
- 'Kinder Morgan',
- 'Axon Enterprise',
- 'United Rentals',
- 'Digital Realty',
- 'Truist Financial',
- 'Simon Property Group',
- 'Cummins',
- 'Quanta Services',
- 'Aflac',
- 'American Electric Power',
- 'Marathon Petroleum',
- 'NXP Semiconductors',
- 'Cencora',
- 'General Motors',
- 'FedEx',
- 'Fastenal',
- 'Roper Technologies',
- 'Allstate',
- 'Sempra',
- 'Realty Income',
- 'Becton Dickinson',
- 'L3Harris',
- 'Chipotle Mexican Grill',
- 'Idexx Laboratories',
- 'Phillips 66',
- 'MetLife',
- 'Paccar',
- 'Schlumberger',
- 'Carrier Global',
- 'Nasdaq, Inc.',
- 'Dominion Energy',
- 'Valero Energy',
- 'D. R. Horton',
- 'Public Storage',
- 'CBRE Group',
- 'Datadog',
- 'Warner Bros. Discovery',
- 'Corteva',
- 'Ross Stores',
- 'W. W. Grainger',
- 'Seagate Technology',
- 'Paychex',
- 'Block, Inc.',
- 'Baker Hughes',
- 'Take-Two Interactive',
- 'Ford Motor Company',
- 'Ameriprise Financial',
- 'Garmin',
- 'Occidental Petroleum',
- 'ONEOK',
- 'Copart',
- 'Exelon',
- 'Monolithic Power Systems',
- 'Edwards Lifesciences',
- 'Ametek',
- 'Kroger',
- 'Electronic Arts',
- 'MSCI',
- 'Xcel Energy',
- 'American International Group',
- 'eBay',
- 'Carnival',
- 'Crown Castle',
- 'Kimberly-Clark',
- 'Yum! Brands',
- 'Public Service Enterprise Group',
- 'Diamondback Energy',
- 'ResMed',
- 'Target Corporation',
- 'Entergy',
- 'Sysco',
- 'Vulcan Materials Company',
- 'Rockwell Automation',
- 'Delta Air Lines',
- 'Hershey Company (The)',
- 'Live Nation Entertainment',
- 'Martin Marietta Materials',
- 'Western Digital',
- 'CoStar Group',
- 'Las Vegas Sands',
- 'Hartford (The)',
- 'Keurig Dr Pepper',
- 'Prudential Financial',
- 'Charter Communications',
- 'Cardinal Health',
- 'Fair Isaac',
- 'WEC Energy Group',
- 'Targa Resources',
- 'Agilent Technologies',
- 'Otis Worldwide',
- 'Microchip Technology',
- 'Consolidated Edison',
- 'Raymond James Financial',
- 'Xylem Inc.',
- 'Verisk Analytics',
- 'United Airlines Holdings',
- 'Fidelity National Information Services',
- 'GE HealthCare',
- 'Vici Properties',
- 'Kenvue',
- 'Arch Capital Group',
- 'Willis Towers Watson',
- 'Hewlett Packard Enterprise',
- 'PG&E Corporation',
- 'DuPont',
- 'Lennar',
- 'Cognizant',
- 'Wabtec',
- 'State Street Corporation',
- 'Ingersoll Rand',
- 'Equifax',
- 'IQVIA',
- 'NRG Energy',
- 'M&T Bank',
- 'Tractor Supply',
- 'Estée Lauder Companies (The)',
- 'Kraft Heinz',
- 'Nucor',
- 'EQT Corporation',
- 'Fifth Third Bancorp',
- 'Ventas',
- 'Brown & Brown',
- 'Humana',
- 'Keysight Technologies',
- 'Extra Space Storage',
- 'Old Dominion',
- 'Iron Mountain',
- 'Archer Daniels Midland',
- 'Interactive Brokers Group',
- 'Synchrony Financial',
- 'Broadridge Financial Solutions',
- 'DTE Energy',
- 'W. R. Berkley Corporation',
- 'Expedia Group',
- 'AvalonBay Communities',
- 'Rollins, Inc.',
- 'Supermicro',
- 'General Mills',
- 'Kellanova',
- 'Ameren',
- 'Dexcom',
- 'Teledyne Technologies',
- 'American Water Works',
- 'PPL Corporation',
- 'Verisign',
- 'HP Inc.',
- 'PulteGroup',
- 'Atmos Energy',
- 'Huntington Bancshares',
- 'Veralto',
- 'Mettler Toledo',
- 'Northern Trust',
- 'Equity Residential',
- 'FirstEnergy',
- 'CenterPoint Energy',
- 'NetApp',
- 'Eversource Energy',
- 'PPG Industries',
- 'PTC Inc.',
- 'Steris',
- 'International Paper',
- 'Cboe Global Markets',
- 'Regions Financial Corporation',
- 'Jabil',
- 'Williams-Sonoma',
- 'Leidos',
- 'Tapestry, Inc.',
- 'Cincinnati Financial',
- 'Expand Energy',
- 'Constellation Brands',
- 'Dover Corporation',
- 'Hubbell Incorporated',
- 'Ulta Beauty',
- 'T. Rowe Price',
- 'Insulet Corporation',
- 'LabCorp',
- 'Tyler Technologies',
- 'Citizens Financial Group',
- 'First Solar',
- 'Smurfit WestRock',
- 'Dollar General',
- 'NVR, Inc.',
- 'Church & Dwight',
- 'Edison International',
- 'Darden Restaurants',
- 'The Trade Desk, Inc.',
- 'Devon Energy',
- 'CDW',
- 'SBA Communications',
- 'Corpay',
- 'CMS Energy',
- 'Global Payments',
- 'Biogen',
- 'KeyCorp',
- 'ON Semiconductor',
- 'Paramount Skydance Corp',
- 'Steel Dynamics',
- 'Quest Diagnostics',
- 'Lululemon Athletica',
- 'Loews Corporation',
- 'Texas Pacific Land Corporation',
- 'Zimmer Biomet',
- 'Trimble Inc.',
- 'GoDaddy',
- 'NiSource',
- 'Dollar Tree',
- 'Gartner',
- 'Teradyne',
- 'Genuine Parts Company',
- 'Halliburton',
- 'Tyson Foods',
- 'Amcor',
- 'Packaging Corporation of America',
- 'Lennox International',
- 'Ralph Lauren Corporation',
- 'F5, Inc.',
- 'Aptiv',
- 'Invitation Homes',
- 'Principal Financial Group',
- 'West Pharmaceutical Services',
- 'Pentair',
- 'Waters Corporation',
- 'Gen Digital',
- 'Coterra',
- 'Jacobs Solutions',
- 'Snap-on',
- 'McCormick & Company',
- 'Weyerhaeuser',
- 'Essex Property Trust',
- 'Southwest Airlines',
- 'Incyte',
- 'Deckers Brands',
- 'LyondellBasell',
- 'Evergy',
- 'Erie Indemnity',
- 'Dow Inc.',
- 'TKO Group Holdings',
- 'Alliant Energy',
- 'Mid-America Apartment Communities',
- 'Fortive',
- 'International Flavors & Fragrances',
- 'Expeditors International',
- 'Zebra Technologies',
- 'C.H. Robinson',
- 'Bunge Global',
- 'Centene Corporation',
- 'Masco',
- 'Best Buy',
- 'Clorox',
- 'Textron',
- 'Kimco Realty',
- 'Allegion',
- 'Hologic',
- 'Alexandria Real Estate Equities',
- "Domino's",
- 'Omnicom Group',
- 'Everest Group',
- 'CF Industries',
- 'Hormel Foods',
- 'Builders FirstSource',
- 'Cooper Companies (The)',
- 'Fox Corporation (Class B)',
- 'Wynn Resorts',
- 'Brown–Forman',
- 'Ball Corporation',
- 'Fox Corporation (Class A)',
- 'Healthpeak Properties',
- 'Avery Dennison',
- 'J.B. Hunt',
- 'Regency Centers',
- 'Solventum',
- 'Franklin Resources',
- 'Nordson Corporation',
- 'UDR, Inc.',
- 'Paycom',
- 'BXP, Inc.',
- 'IDEX Corporation',
- 'Host Hotels & Resorts',
- 'Universal Health Services',
- 'Stanley Black & Decker',
- 'Baxter International',
- 'Pool Corporation',
- 'Skyworks Solutions',
- 'Globe Life',
- 'News Corp (Class A)',
- 'J.M. Smucker Company (The)',
- 'Camden Property Trust',
- 'Viatris',
- 'Norwegian Cruise Line Holdings',
- 'Jack Henry & Associates',
- 'FactSet',
- 'Akamai Technologies',
- 'Dayforce',
- 'Huntington Ingalls Industries',
- 'Mosaic Company (The)',
- 'Generac',
- 'Assurant',
- 'Hasbro',
- 'Pinnacle West',
- 'A. O. Smith',
- 'Revvity',
- 'Invesco',
- 'Campbell Soup Company',
- 'Moderna',
- 'MGM Resorts',
- 'Albemarle Corporation',
- 'Align Technology',
- 'Molina Healthcare',
- 'Interpublic Group of Companies (The)',
- 'DaVita',
- 'AES Corporation',
- 'Match Group',
- 'Molson Coors Beverage Company',
- 'Conagra Brands',
- 'CarMax',
- 'EPAM Systems',
- 'Federal Realty Investment Trust',
- 'APA Corporation',
- 'Bio-Techne',
- 'Henry Schein',
- 'Mohawk Industries',
- 'LKQ Corporation',
- 'Lamb Weston',
- 'Charles River Laboratories',
- 'Eastman Chemical Company',
- 'MarketAxess',
- 'News Corp (Class B)',
- 'Caesars Entertainment',
- 'Enphase Energy']
-
-TICKERS ={'Nvidia': 'NVDA',
- 'Microsoft': 'MSFT',
- 'Apple Inc.': 'AAPL',
- 'Amazon': 'AMZN',
- 'Meta Platforms': 'META',
- 'Broadcom': 'AVGO',
- 'Alphabet Inc. (Class A)': 'GOOGL',
- 'Alphabet Inc. (Class C)': 'GOOG',
- 'Tesla, Inc.': 'TSLA',
- 'Berkshire Hathaway': 'BRK.B',
- 'Oracle Corporation': 'ORCL',
- 'JPMorgan Chase': 'JPM',
- 'Walmart': 'WMT',
- 'Lilly (Eli)': 'LLY',
- 'Visa Inc.': 'V',
- 'Mastercard': 'MA',
- 'Netflix': 'NFLX',
- 'ExxonMobil': 'XOM',
- 'Palantir Technologies': 'PLTR',
- 'Johnson & Johnson': 'JNJ',
- 'Costco': 'COST',
- 'Home Depot (The)': 'HD',
- 'AbbVie': 'ABBV',
- 'Bank of America': 'BAC',
- 'Procter & Gamble': 'PG',
- 'GE Aerospace': 'GE',
- 'Chevron Corporation': 'CVX',
- 'UnitedHealth Group': 'UNH',
- 'Coca-Cola Company (The)': 'KO',
- 'Wells Fargo': 'WFC',
- 'Cisco': 'CSCO',
- 'T-Mobile US': 'TMUS',
- 'Morgan Stanley': 'MS',
- 'Advanced Micro Devices': 'AMD',
- 'Philip Morris International': 'PM',
- 'IBM': 'IBM',
- 'Goldman Sachs': 'GS',
- 'American Express': 'AXP',
- 'Abbott Laboratories': 'ABT',
- 'Salesforce': 'CRM',
- 'Linde plc': 'LIN',
- 'Caterpillar Inc.': 'CAT',
- "McDonald's": 'MCD',
- 'RTX Corporation': 'RTX',
- 'AT&T': 'T',
- 'Merck & Co.': 'MRK',
- 'Uber': 'UBER',
- 'Walt Disney Company (The)': 'DIS',
- 'ServiceNow': 'NOW',
- 'PepsiCo': 'PEP',
- 'Intuit': 'INTU',
- 'Citigroup': 'C',
- 'Arista Networks': 'ANET',
- 'Verizon': 'VZ',
- 'Micron Technology': 'MU',
- 'Thermo Fisher Scientific': 'TMO',
- 'Qualcomm': 'QCOM',
- 'Booking Holdings': 'BKNG',
- 'BlackRock': 'BLK',
- 'Charles Schwab Corporation': 'SCHW',
- 'GE Vernova': 'GEV',
- 'Boeing': 'BA',
- 'Lam Research': 'LRCX',
- 'Texas Instruments': 'TXN',
- 'Intuitive Surgical': 'ISRG',
- 'S&P Global': 'SPGI',
- 'TJX Companies': 'TJX',
- 'Adobe Inc.': 'ADBE',
- 'Applied Materials': 'AMAT',
- 'Amgen': 'AMGN',
- 'Amphenol': 'APH',
- 'Accenture': 'ACN',
- "Lowe's": 'LOW',
- 'Blackstone Inc.': 'BX',
- 'NextEra Energy': 'NEE',
- 'Capital One': 'COF',
- 'Boston Scientific': 'BSX',
- 'Eaton Corporation': 'ETN',
- 'Stryker Corporation': 'SYK',
- 'Progressive Corporation': 'PGR',
- 'Gilead Sciences': 'GILD',
- 'Palo Alto Networks': 'PANW',
- 'Pfizer': 'PFE',
- 'Danaher Corporation': 'DHR',
- 'Intel': 'INTC',
- 'KLA Corporation': 'KLAC',
- 'KKR': 'KKR',
- 'Honeywell': 'HON',
- 'Union Pacific Corporation': 'UNP',
- 'Deere & Company': 'DE',
- 'CrowdStrike': 'CRWD',
- 'Medtronic': 'MDT',
- 'Analog Devices': 'ADI',
- 'Automatic Data Processing': 'ADP',
- 'Comcast': 'CMCSA',
- 'ConocoPhillips': 'COP',
- 'DoorDash': 'DASH',
- 'Welltower': 'WELL',
- 'Lockheed Martin': 'LMT',
- 'Altria': 'MO',
- 'Chubb Limited': 'CB',
- 'Prologis': 'PLD',
- 'Nike, Inc.': 'NKE',
- 'Constellation Energy': 'CEG',
- 'Cadence Design Systems': 'CDNS',
- 'Southern Company': 'SO',
- 'Vertex Pharmaceuticals': 'VRTX',
- 'Marsh McLennan': 'MMC',
- 'Intercontinental Exchange': 'ICE',
- 'Starbucks': 'SBUX',
- 'Parker Hannifin': 'PH',
- 'CVS Health': 'CVS',
- 'CME Group': 'CME',
- 'Duke Energy': 'DUK',
- 'HCA Healthcare': 'HCA',
- 'Newmont': 'NEM',
- 'Bristol Myers Squibb': 'BMY',
- 'Trane Technologies': 'TT',
- 'Synopsys': 'SNPS',
- 'American Tower': 'AMT',
- 'Royal Caribbean Group': 'RCL',
- 'Dell Technologies': 'DELL',
- "O'Reilly Auto Parts": 'ORLY',
- 'Waste Management': 'WM',
- "Moody's Corporation": 'MCO',
- 'General Dynamics': 'GD',
- 'Sherwin-Williams': 'SHW',
- 'McKesson Corporation': 'MCK',
- 'Coinbase Global': 'COIN',
- '3M': 'MMM',
- 'Mondelez International': 'MDLZ',
- 'Northrop Grumman': 'NOC',
- 'Apollo Global Management': 'APO',
- 'PNC Financial Services': 'PNC',
- 'Cintas': 'CTAS',
- 'Motorola Solutions': 'MSI',
- 'U.S. Bancorp': 'USB',
- 'Cigna': 'CI',
- 'Airbnb': 'ABNB',
- 'Equinix': 'EQIX',
- 'Arthur J. Gallagher & Co.': 'AJG',
- 'BNY Mellon': 'BK',
- 'Howmet Aerospace': 'HWM',
- 'Illinois Tool Works': 'ITW',
- 'Aon': 'AON',
- 'Ecolab': 'ECL',
- 'Emerson Electric': 'EMR',
- 'Williams Companies': 'WMB',
- 'Marriott International': 'MAR',
- 'TransDigm Group': 'TDG',
- 'Fiserv': 'FI',
- 'Vistra Corp.': 'VST',
- 'United Parcel Service': 'UPS',
- 'Republic Services': 'RSG',
- 'Johnson Controls': 'JCI',
- 'Elevance Health': 'ELV',
- 'AutoZone': 'AZO',
- 'Autodesk': 'ADSK',
- 'Corning Inc.': 'GLW',
- 'Colgate-Palmolive': 'CL',
- 'PayPal': 'PYPL',
- 'Zoetis': 'ZTS',
- 'Freeport-McMoRan': 'FCX',
- 'Fortinet': 'FTNT',
- 'Air Products': 'APD',
- 'TE Connectivity': 'TEL',
- 'Norfolk Southern Railway': 'NSC',
- 'EOG Resources': 'EOG',
- 'Hilton Worldwide': 'HLT',
- 'Regeneron Pharmaceuticals': 'REGN',
- 'Monster Beverage': 'MNST',
- 'Travelers Companies (The)': 'TRV',
- 'Workday, Inc.': 'WDAY',
- 'CSX Corporation': 'CSX',
- 'Kinder Morgan': 'KMI',
- 'Axon Enterprise': 'AXON',
- 'United Rentals': 'URI',
- 'Digital Realty': 'DLR',
- 'Truist Financial': 'TFC',
- 'Simon Property Group': 'SPG',
- 'Cummins': 'CMI',
- 'Quanta Services': 'PWR',
- 'Aflac': 'AFL',
- 'American Electric Power': 'AEP',
- 'Marathon Petroleum': 'MPC',
- 'NXP Semiconductors': 'NXPI',
- 'Cencora': 'COR',
- 'General Motors': 'GM',
- 'FedEx': 'FDX',
- 'Fastenal': 'FAST',
- 'Roper Technologies': 'ROP',
- 'Allstate': 'ALL',
- 'Sempra': 'SRE',
- 'Realty Income': 'O',
- 'Becton Dickinson': 'BDX',
- 'L3Harris': 'LHX',
- 'Chipotle Mexican Grill': 'CMG',
- 'Idexx Laboratories': 'IDXX',
- 'Phillips 66': 'PSX',
- 'MetLife': 'MET',
- 'Paccar': 'PCAR',
- 'Schlumberger': 'SLB',
- 'Carrier Global': 'CARR',
- 'Nasdaq, Inc.': 'NDAQ',
- 'Dominion Energy': 'D',
- 'Valero Energy': 'VLO',
- 'D. R. Horton': 'DHI',
- 'Public Storage': 'PSA',
- 'CBRE Group': 'CBRE',
- 'Datadog': 'DDOG',
- 'Warner Bros. Discovery': 'WBD',
- 'Corteva': 'CTVA',
- 'Ross Stores': 'ROST',
- 'W. W. Grainger': 'GWW',
- 'Seagate Technology': 'STX',
- 'Paychex': 'PAYX',
- 'Block, Inc.': 'XYZ',
- 'Baker Hughes': 'BKR',
- 'Take-Two Interactive': 'TTWO',
- 'Ford Motor Company': 'F',
- 'Ameriprise Financial': 'AMP',
- 'Garmin': 'GRMN',
- 'Occidental Petroleum': 'OXY',
- 'ONEOK': 'OKE',
- 'Copart': 'CPRT',
- 'Exelon': 'EXC',
- 'Monolithic Power Systems': 'MPWR',
- 'Edwards Lifesciences': 'EW',
- 'Ametek': 'AME',
- 'Kroger': 'KR',
- 'Electronic Arts': 'EA',
- 'MSCI': 'MSCI',
- 'Xcel Energy': 'XEL',
- 'American International Group': 'AIG',
- 'eBay': 'EBAY',
- 'Carnival': 'CCL',
- 'Crown Castle': 'CCI',
- 'Kimberly-Clark': 'KMB',
- 'Yum! Brands': 'YUM',
- 'Public Service Enterprise Group': 'PEG',
- 'Diamondback Energy': 'FANG',
- 'ResMed': 'RMD',
- 'Target Corporation': 'TGT',
- 'Entergy': 'ETR',
- 'Sysco': 'SYY',
- 'Vulcan Materials Company': 'VMC',
- 'Rockwell Automation': 'ROK',
- 'Delta Air Lines': 'DAL',
- 'Hershey Company (The)': 'HSY',
- 'Live Nation Entertainment': 'LYV',
- 'Martin Marietta Materials': 'MLM',
- 'Western Digital': 'WDC',
- 'CoStar Group': 'CSGP',
- 'Las Vegas Sands': 'LVS',
- 'Hartford (The)': 'HIG',
- 'Keurig Dr Pepper': 'KDP',
- 'Prudential Financial': 'PRU',
- 'Charter Communications': 'CHTR',
- 'Cardinal Health': 'CAH',
- 'Fair Isaac': 'FICO',
- 'WEC Energy Group': 'WEC',
- 'Targa Resources': 'TRGP',
- 'Agilent Technologies': 'A',
- 'Otis Worldwide': 'OTIS',
- 'Microchip Technology': 'MCHP',
- 'Consolidated Edison': 'ED',
- 'Raymond James Financial': 'RJF',
- 'Xylem Inc.': 'XYL',
- 'Verisk Analytics': 'VRSK',
- 'United Airlines Holdings': 'UAL',
- 'Fidelity National Information Services': 'FIS',
- 'GE HealthCare': 'GEHC',
- 'Vici Properties': 'VICI',
- 'Kenvue': 'KVUE',
- 'Arch Capital Group': 'ACGL',
- 'Willis Towers Watson': 'WTW',
- 'Hewlett Packard Enterprise': 'HPE',
- 'PG&E Corporation': 'PCG',
- 'DuPont': 'DD',
- 'Lennar': 'LEN',
- 'Cognizant': 'CTSH',
- 'Wabtec': 'WAB',
- 'State Street Corporation': 'STT',
- 'Ingersoll Rand': 'IR',
- 'Equifax': 'EFX',
- 'IQVIA': 'IQV',
- 'NRG Energy': 'NRG',
- 'M&T Bank': 'MTB',
- 'Tractor Supply': 'TSCO',
- 'Estée Lauder Companies (The)': 'EL',
- 'Kraft Heinz': 'KHC',
- 'Nucor': 'NUE',
- 'EQT Corporation': 'EQT',
- 'Fifth Third Bancorp': 'FITB',
- 'Ventas': 'VTR',
- 'Brown & Brown': 'BRO',
- 'Humana': 'HUM',
- 'Keysight Technologies': 'KEYS',
- 'Extra Space Storage': 'EXR',
- 'Old Dominion': 'ODFL',
- 'Iron Mountain': 'IRM',
- 'Archer Daniels Midland': 'ADM',
- 'Interactive Brokers Group': 'IBKR',
- 'Synchrony Financial': 'SYF',
- 'Broadridge Financial Solutions': 'BR',
- 'DTE Energy': 'DTE',
- 'W. R. Berkley Corporation': 'WRB',
- 'Expedia Group': 'EXPE',
- 'AvalonBay Communities': 'AVB',
- 'Rollins, Inc.': 'ROL',
- 'Supermicro': 'SMCI',
- 'General Mills': 'GIS',
- 'Kellanova': 'K',
- 'Ameren': 'AEE',
- 'Dexcom': 'DXCM',
- 'Teledyne Technologies': 'TDY',
- 'American Water Works': 'AWK',
- 'PPL Corporation': 'PPL',
- 'Verisign': 'VRSN',
- 'HP Inc.': 'HPQ',
- 'PulteGroup': 'PHM',
- 'Atmos Energy': 'ATO',
- 'Huntington Bancshares': 'HBAN',
- 'Veralto': 'VLTO',
- 'Mettler Toledo': 'MTD',
- 'Northern Trust': 'NTRS',
- 'Equity Residential': 'EQR',
- 'FirstEnergy': 'FE',
- 'CenterPoint Energy': 'CNP',
- 'NetApp': 'NTAP',
- 'Eversource Energy': 'ES',
- 'PPG Industries': 'PPG',
- 'PTC Inc.': 'PTC',
- 'Steris': 'STE',
- 'International Paper': 'IP',
- 'Cboe Global Markets': 'CBOE',
- 'Regions Financial Corporation': 'RF',
- 'Jabil': 'JBL',
- 'Williams-Sonoma': 'WSM',
- 'Leidos': 'LDOS',
- 'Tapestry, Inc.': 'TPR',
- 'Cincinnati Financial': 'CINF',
- 'Expand Energy': 'EXE',
- 'Constellation Brands': 'STZ',
- 'Dover Corporation': 'DOV',
- 'Hubbell Incorporated': 'HUBB',
- 'Ulta Beauty': 'ULTA',
- 'T. Rowe Price': 'TROW',
- 'Insulet Corporation': 'PODD',
- 'LabCorp': 'LH',
- 'Tyler Technologies': 'TYL',
- 'Citizens Financial Group': 'CFG',
- 'First Solar': 'FSLR',
- 'Smurfit WestRock': 'SW',
- 'Dollar General': 'DG',
- 'NVR, Inc.': 'NVR',
- 'Church & Dwight': 'CHD',
- 'Edison International': 'EIX',
- 'Darden Restaurants': 'DRI',
- 'The Trade Desk, Inc.': 'TTD',
- 'Devon Energy': 'DVN',
- 'CDW': 'CDW',
- 'SBA Communications': 'SBAC',
- 'Corpay': 'CPAY',
- 'CMS Energy': 'CMS',
- 'Global Payments': 'GPN',
- 'Biogen': 'BIIB',
- 'KeyCorp': 'KEY',
- 'ON Semiconductor': 'ON',
- 'Paramount Skydance Corp': 'PSKY',
- 'Steel Dynamics': 'STLD',
- 'Quest Diagnostics': 'DGX',
- 'Lululemon Athletica': 'LULU',
- 'Loews Corporation': 'L',
- 'Texas Pacific Land Corporation': 'TPL',
- 'Zimmer Biomet': 'ZBH',
- 'Trimble Inc.': 'TRMB',
- 'GoDaddy': 'GDDY',
- 'NiSource': 'NI',
- 'Dollar Tree': 'DLTR',
- 'Gartner': 'IT',
- 'Teradyne': 'TER',
- 'Genuine Parts Company': 'GPC',
- 'Halliburton': 'HAL',
- 'Tyson Foods': 'TSN',
- 'Amcor': 'AMCR',
- 'Packaging Corporation of America': 'PKG',
- 'Lennox International': 'LII',
- 'Ralph Lauren Corporation': 'RL',
- 'F5, Inc.': 'FFIV',
- 'Aptiv': 'APTV',
- 'Invitation Homes': 'INVH',
- 'Principal Financial Group': 'PFG',
- 'West Pharmaceutical Services': 'WST',
- 'Pentair': 'PNR',
- 'Waters Corporation': 'WAT',
- 'Gen Digital': 'GEN',
- 'Coterra': 'CTRA',
- 'Jacobs Solutions': 'J',
- 'Snap-on': 'SNA',
- 'McCormick & Company': 'MKC',
- 'Weyerhaeuser': 'WY',
- 'Essex Property Trust': 'ESS',
- 'Southwest Airlines': 'LUV',
- 'Incyte': 'INCY',
- 'Deckers Brands': 'DECK',
- 'LyondellBasell': 'LYB',
- 'Evergy': 'EVRG',
- 'Erie Indemnity': 'ERIE',
- 'Dow Inc.': 'DOW',
- 'TKO Group Holdings': 'TKO',
- 'Alliant Energy': 'LNT',
- 'Mid-America Apartment Communities': 'MAA',
- 'Fortive': 'FTV',
- 'International Flavors & Fragrances': 'IFF',
- 'Expeditors International': 'EXPD',
- 'Zebra Technologies': 'ZBRA',
- 'C.H. Robinson': 'CHRW',
- 'Bunge Global': 'BG',
- 'Centene Corporation': 'CNC',
- 'Masco': 'MAS',
- 'Best Buy': 'BBY',
- 'Clorox': 'CLX',
- 'Textron': 'TXT',
- 'Kimco Realty': 'KIM',
- 'Allegion': 'ALLE',
- 'Hologic': 'HOLX',
- 'Alexandria Real Estate Equities': 'ARE',
- "Domino's": 'DPZ',
- 'Omnicom Group': 'OMC',
- 'Everest Group': 'EG',
- 'CF Industries': 'CF',
- 'Hormel Foods': 'HRL',
- 'Builders FirstSource': 'BLDR',
- 'Cooper Companies (The)': 'COO',
- 'Fox Corporation (Class B)': 'FOX',
- 'Wynn Resorts': 'WYNN',
- 'Brown–Forman': 'BF.B',
- 'Ball Corporation': 'BALL',
- 'Fox Corporation (Class A)': 'FOXA',
- 'Healthpeak Properties': 'DOC',
- 'Avery Dennison': 'AVY',
- 'J.B. Hunt': 'JBHT',
- 'Regency Centers': 'REG',
- 'Solventum': 'SOLV',
- 'Franklin Resources': 'BEN',
- 'Nordson Corporation': 'NDSN',
- 'UDR, Inc.': 'UDR',
- 'Paycom': 'PAYC',
- 'BXP, Inc.': 'BXP',
- 'IDEX Corporation': 'IEX',
- 'Host Hotels & Resorts': 'HST',
- 'Universal Health Services': 'UHS',
- 'Stanley Black & Decker': 'SWK',
- 'Baxter International': 'BAX',
- 'Pool Corporation': 'POOL',
- 'Skyworks Solutions': 'SWKS',
- 'Globe Life': 'GL',
- 'News Corp (Class A)': 'NWSA',
- 'J.M. Smucker Company (The)': 'SJM',
- 'Camden Property Trust': 'CPT',
- 'Viatris': 'VTRS',
- 'Norwegian Cruise Line Holdings': 'NCLH',
- 'Jack Henry & Associates': 'JKHY',
- 'FactSet': 'FDS',
- 'Akamai Technologies': 'AKAM',
- 'Dayforce': 'DAY',
- 'Huntington Ingalls Industries': 'HII',
- 'Mosaic Company (The)': 'MOS',
- 'Generac': 'GNRC',
- 'Assurant': 'AIZ',
- 'Hasbro': 'HAS',
- 'Pinnacle West': 'PNW',
- 'A. O. Smith': 'AOS',
- 'Revvity': 'RVTY',
- 'Invesco': 'IVZ',
- 'Campbell Soup Company': 'CPB',
- 'Moderna': 'MRNA',
- 'MGM Resorts': 'MGM',
- 'Albemarle Corporation': 'ALB',
- 'Align Technology': 'ALGN',
- 'Molina Healthcare': 'MOH',
- 'Interpublic Group of Companies (The)': 'IPG',
- 'DaVita': 'DVA',
- 'AES Corporation': 'AES',
- 'Match Group': 'MTCH',
- 'Molson Coors Beverage Company': 'TAP',
- 'Conagra Brands': 'CAG',
- 'CarMax': 'KMX',
- 'EPAM Systems': 'EPAM',
- 'Federal Realty Investment Trust': 'FRT',
- 'APA Corporation': 'APA',
- 'Bio-Techne': 'TECH',
- 'Henry Schein': 'HSIC',
- 'Mohawk Industries': 'MHK',
- 'LKQ Corporation': 'LKQ',
- 'Lamb Weston': 'LW',
- 'Charles River Laboratories': 'CRL',
- 'Eastman Chemical Company': 'EMN',
- 'MarketAxess': 'MKTX',
- 'News Corp (Class B)': 'NWS',
- 'Caesars Entertainment': 'CZR',
- 'Enphase Energy': 'ENPH'}
-
+# --- PARAMETRI ---
 HF_DATASET = "SelmaNajih001/FT_MultiCompany"
 MODEL_SENTIMENT = "SelmaNajih001/SentimentBasedOnPriceVariation"
-#MODEL_PRICE_TESLA = "SelmaNajih001/PricePredictionForTesla"
-#MODEL_PRICE_MICROSOFT = "SelmaNajih001/PricePredictionForMicrosoft"
+MODEL_PRICE_TESLA = "SelmaNajih001/PricePredictionForTesla"
+MODEL_PRICE_MICROSOFT = "SelmaNajih001/PricePredictionForMicrosoft"
+MODEL_FINBERT = "ProsusAI/finbert"
+
+TICKERS = {
+    "Tesla": "TSLA",
+    "Microsoft": "MSFT",
+    #"Nvidia": "NVDA"
+}
+companies = list(TICKERS.keys())
 
 # --- PIPELINES ---
 sentiment_pipeline = pipeline("sentiment-analysis", model=MODEL_SENTIMENT)
-#price_pipeline_tesla = pipeline("text-classification", model=MODEL_PRICE_TESLA)
-#price_pipeline_msft = pipeline("text-classification", model=MODEL_PRICE_MICROSOFT)
+price_pipeline_tesla = pipeline("text-classification", model=MODEL_PRICE_TESLA)
+price_pipeline_msft = pipeline("text-classification", model=MODEL_PRICE_MICROSOFT)
+finbert_pipeline = pipeline("sentiment-analysis", model=MODEL_FINBERT)
 
 # --- LOAD DATASET ---
 df_multi = pd.DataFrame(load_dataset(HF_DATASET)["train"])
@@ -1033,12 +35,14 @@ df_multi.sort_values('date', inplace=True)
 # --- SENTIMENT & PREDICTION ---
 df_multi['Sentiment'] = ""
 df_multi['Confidence'] = 0.0
-#df_multi['Predicted'] = 0.0
+df_multi['Predicted'] = 0.0
+df_multi['FinBERT_Sentiment'] = ""
+df_multi['FinBERT_Confidence'] = 0.0
 
 for i, row in df_multi.iterrows():
     company = row['Company']
 
-    # Sentiment for all companies
+    # --- Sentiment con modello custom ---
     try:
         res = sentiment_pipeline(row['Summary'])[0]
         df_multi.at[i,'Sentiment'] = res['label'].upper().strip()
@@ -1047,21 +51,25 @@ for i, row in df_multi.iterrows():
         df_multi.at[i,'Sentiment'] = 'ERROR'
         df_multi.at[i,'Confidence'] = 0.0
 
+    # --- FinBERT ---
+    try:
+        res_f = finbert_pipeline(row['Summary'])[0]
+        df_multi.at[i,'FinBERT_Sentiment'] = res_f['label'].upper().strip()
+        df_multi.at[i,'FinBERT_Confidence'] = res_f['score']
+    except:
+        df_multi.at[i,'FinBERT_Sentiment'] = 'ERROR'
+        df_multi.at[i,'FinBERT_Confidence'] = 0.0
 
-### Regression only for Tesla & Microsoft
-#    if company == "Tesla":
-#        try:
-#            val = price_pipeline_tesla(row['Riassunto'])[0]['score']
-#            df_multi.at[i,'Predicted'] = min(val, 1.0)
-#        except:
-#            df_multi.at[i,'Predicted'] = 0.0
-#    elif company == "Microsoft":
-#        try:
-#            val = price_pipeline_msft(row['Riassunto'])[0]['score']
-#            df_multi.at[i,'Predicted'] = min(val, 1.0)
-#       except:
-#            df_multi.at[i,'Predicted'] = 0.0
-
+    # --- Regression solo per Tesla & Microsoft ---
+    try:
+        if company == "Tesla":
+            val = price_pipeline_tesla(row['Summary'])[0]['score']
+            df_multi.at[i,'Predicted'] = min(val, 1.0)
+        elif company == "Microsoft":
+            val = price_pipeline_msft(row['Summary'])[0]['score']
+            df_multi.at[i,'Predicted'] = min(val, 1.0)
+    except:
+        df_multi.at[i,'Predicted'] = 0.0
 
 # --- FETCH STOCK PRICES ---
 prices = {}
@@ -1069,150 +77,71 @@ for company, ticker in TICKERS.items():
     start_date = df_multi[df_multi['Company']==company]['date'].min()
     end_date = pd.Timestamp.today()
     df_prices = yf.download(ticker, start=start_date, end=end_date)[['Close']].reset_index()
-    # Flatten the columns to a single level
-    df_prices.columns = ['_'.join(col).strip() if isinstance(col, tuple) else col for col in df_prices.columns]
+    df_prices.columns = ['Date_', f'Close_{ticker}']
     df_prices['date_merge'] = pd.to_datetime(df_prices['Date_']).dt.normalize()
     df_prices['PctChangeDaily'] = df_prices[f'Close_{ticker}'].pct_change().shift(-1)
     prices[company] = df_prices
 
-# --- MERGE & CALCOLA STRATEGIE ---
+# --- MERGE & STRATEGIE ---
 dfs_final = {}
-
 for company in companies:
     df_c = df_multi[df_multi['Company'] == company].copy()
-    
-    # Merge con i prezzi
+
     if company in prices:
         df_c = pd.merge(df_c, prices[company], on='date_merge', how='inner')
-    
-    # --- Aggiungi colonne di aggregazione prima di eliminare date ---
+
     df_c['Day'] = df_c['date'].dt.date
     df_c['Month'] = df_c['date'].dt.to_period('M').dt.to_timestamp()
     df_c['Year'] = df_c['date'].dt.year
 
-    # --- Strategy A: Sentiment ---
-    df_c['StrategyA_Daily'] = 0.0
+    # --- Strategy A: Sentiment custom ---
     df_c['StrategyA_Cumulative'] = 0.0
     for i in range(1, len(df_c)):
-        score = df_c.loc[i, 'Confidence']
-        pct = df_c.loc[i, 'PctChangeDaily'] if pd.notnull(df_c.loc[i, 'PctChangeDaily']) else 0
-        if df_c.loc[i, 'Sentiment'] == "UP" and score > 0.8:
-            df_c.loc[i, 'StrategyA_Daily'] = df_c.loc[i, f'Close_{TICKERS[company]}'] * pct
-        elif df_c.loc[i, 'Sentiment'] == "DOWN" and score > 0.8:
-            df_c.loc[i, 'StrategyA_Daily'] = df_c.loc[i, f'Close_{TICKERS[company]}'] * pct * -1
-        df_c.loc[i, 'StrategyA_Cumulative'] = df_c.loc[i-1, 'StrategyA_Cumulative'] + df_c.loc[i, 'StrategyA_Daily']
-
-    # Strategy B (opzionale, commentata)
-    # df_c['StrategyB_Daily'] = df_c['Predicted'] * df_c['PctChangeDaily'] * df_c[f'Close_{TICKERS[company]}']
-    # df_c['StrategyB_Cumulative'] = df_c['StrategyB_Daily'].cumsum()
-
-    # Rimuovi solo colonne non necessarie, non quelle di aggregazione
-    df_c = df_c.drop(columns=["date", "date_merge"], errors="ignore")
-
-    # Salva nel dizionario finale
-    dfs_final[company] = df_c
-
-# --- PLOT STRATEGIES ---
-df_plot_A = pd.concat([df[['Date','StrategyA_Cumulative']].assign(Company=company) for company, df in dfs_final.items()], ignore_index=True)
-#df_plot_B = pd.concat([df[['Data','StrategyB_Cumulative']].assign(Company=company) for company, df in dfs_final.items()], ignore_index=True)
-
-fig_strategy_A = px.line(df_plot_A, x='Date', y='StrategyA_Cumulative', color='Company',
-                         title="Portfolio Evolution Following Strategy A (Sentiment)",
-                         labels={'StrategyA_Cumulative':'Cumulative Value','Date':'Date'})
-#fig_strategy_B = px.line(df_plot_B, x='Data', y='StrategyB_Cumulative', color='Company',
-#                         title="Portfolio Evolution Following Strategy B (Regression)",
-#                         labels={'StrategyB_Cumulative':'Cumulative Value','Data':'Date'})
-
-# --- FUNCTION FOR GRADIO ---
-import pandas as pd
-import plotly.graph_objects as go
-import gradio as gr
-
-# --- PREPARA COLONNE AGGREGAZIONE ---
-df_multi['Day'] = df_multi['date'].dt.date
-df_multi['Month'] = df_multi['date'].dt.to_period('M').dt.to_timestamp()  # Period -> datetime
-df_multi['Year'] = df_multi['date'].dt.year
-
-# --- FUNZIONE PER GRADIO ---
-def show_company_data(selected_companies, aggregation="Day"):
-    if not selected_companies:
-        return "Select at least one company to visualize.", None
-
-    # --- CONCAT DATAFRAMES TOP 10 ---
-    tables = pd.concat(
-        [dfs_final[c].head(10).assign(Company=c) for c in selected_companies if c in dfs_final],
-        ignore_index=True
-    )
-
-    # --- CREA FIGURA ---
-    fig = go.Figure()
-    agg_col = {"Day": "Day", "Month": "Month", "Year": "Year"}.get(aggregation, "Day")
-
-    for c in selected_companies:
-        if c not in dfs_final:
-            continue
-        df_c = dfs_final[c]
-
-        # --- AGGREGAZIONE ---
-        df_grouped = df_c.groupby(agg_col).agg({
-            'StrategyA_Cumulative': 'last',
-            **({f'Close_{TICKERS[c]}': 'last'} if f'Close_{TICKERS[c]}' in df_c.columns else {})
-        }).reset_index()
-
-        # --- CONVERSIONE DATETIME PER PLOTLY ---
-        if agg_col in ['Day', 'Month'] and not pd.api.types.is_datetime64_any_dtype(df_grouped[agg_col]):
-            df_grouped[agg_col] = pd.to_datetime(df_grouped[agg_col])
-
-        # --- LINEA STRATEGY A ---
-        fig.add_trace(go.Scatter(
-            x=df_grouped[agg_col],
-            y=df_grouped['StrategyA_Cumulative'],
-            mode='lines',
-            name=f"{c} Strategy A",
-            line=dict(width=2)
-        ))
-
-        # --- LINEA PREZZO SECONDARY Y ---
-        if f'Close_{TICKERS[c]}' in df_grouped.columns:
-            fig.add_trace(go.Scatter(
-                x=df_grouped[agg_col],
-                y=df_grouped[f'Close_{TICKERS[c]}'],
-                mode='lines',
-                name=f"{c} Price",
-                yaxis="y2",
-                line=dict(width=2, dash='dot')
-            ))
-
-    # --- LAYOUT FIGURA ---
-    fig.update_layout(
-        title="Portfolio Evolution vs Stock Price",
-        xaxis_title=aggregation,
-        yaxis_title="Strategy A Cumulative Value",
-        yaxis2=dict(
-            title="Stock Price",
-            overlaying="y",
-            side="right"
-        ),
-        legend=dict(orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1),
-        template="plotly_dark",
-        hovermode="x unified"
-    )
+        pct = df_c.loc[i, 'PctChangeDaily'] if pd.notnull(df_c.loc[i,'PctChangeDaily']) else 0
+        if df_c.loc[i, 'Sentiment'] == "UP" and df_c.loc[i,'Confidence'] > 0.8:
+            df_c.loc[i,'StrategyA_Cumulative'] = df_c.loc[i-1,'StrategyA_Cumulative'] + pct
+        elif df_c.loc[i, 'Sentiment'] == "DOWN" and df_c.loc[i,'Confidence'] > 0.8:
+            df_c.loc[i,'StrategyA_Cumulative'] = df_c.loc[i-1,'StrategyA_Cumulative'] - pct
+        else:
+            df_c.loc[i,'StrategyA_Cumulative'] = df_c.loc[i-1,'StrategyA_Cumulative']
+
+    # --- Strategy B: Regression ---
+    df_c['StrategyB_Cumulative'] = (df_c['Predicted'] * df_c['PctChangeDaily']).cumsum()
+
+    # --- Strategy C: FinBERT ---
+    df_c['StrategyC_Cumulative'] = 0.0
+    for i in range(1, len(df_c)):
+        pct = df_c.loc[i, 'PctChangeDaily'] if pd.notnull(df_c.loc[i,'PctChangeDaily']) else 0
+        if df_c.loc[i, 'FinBERT_Sentiment'] == "POSITIVE" and df_c.loc[i,'FinBERT_Confidence'] > 0.8:
+            df_c.loc[i,'StrategyC_Cumulative'] = df_c.loc[i-1,'StrategyC_Cumulative'] + pct
+        elif df_c.loc[i, 'FinBERT_Sentiment'] == "NEGATIVE" and df_c.loc[i,'FinBERT_Confidence'] > 0.8:
+            df_c.loc[i,'StrategyC_Cumulative'] = df_c.loc[i-1,'StrategyC_Cumulative'] - pct
+        else:
+            df_c.loc[i,'StrategyC_Cumulative'] = df_c.loc[i-1,'StrategyC_Cumulative']
+
+    dfs_final[company] = df_c.drop(columns=["date", "date_merge"], errors="ignore")
+
+# --- PLOT: CONFRONTO STRATEGIE ---
+df_plot = pd.concat([
+    df[['Date','StrategyA_Cumulative','StrategyB_Cumulative','StrategyC_Cumulative']].assign(Company=company)
+    for company, df in dfs_final.items()
+], ignore_index=True)
+
+fig_strategies = px.line(
+    df_plot, x='Date', y=['StrategyA_Cumulative','StrategyB_Cumulative','StrategyC_Cumulative'], 
+    color='Company',
+    title="Confronto Strategie (Custom Sentiment vs Regression vs FinBERT)"
+)
 
-    return tables, fig
+# --- PLOT: PREZZI ---
+df_prices_plot = pd.concat([
+    df[[f'Close_{TICKERS[company]}','Date']].assign(Company=company) for company, df in dfs_final.items()
+], ignore_index=True)
 
-# --- GRADIO INTERFACE ---
-demo = gr.Interface(
-    fn=show_company_data,
-    inputs=[
-        gr.Dropdown(choices=companies, value=["Microsoft", "Nvidia"], label="Select Companies", multiselect=True),
-        gr.Radio(choices=["Day", "Month", "Year"], value="Day", label="Aggregation Level")
-    ],
-    outputs=[
-        gr.Dataframe(label="Top 10 Rows per Company", type="pandas"),
-        gr.Plot(label="Strategy A: Sentiment"),
-    ],
-    title="Interactive Portfolio Evolution",
-    description="Select one or more companies to visualize portfolio evolution based on the sentiment of the news."
+fig_prices = px.line(
+    df_prices_plot, x='Date', y=df_prices_plot.columns[0], color='Company',
+    title="Andamento Prezzi"
 )
 
-demo.launch()
+fig_strategies.show()
+fig_prices.show()