feat: restructure to multi-page app with modular architecture

- Multi-page navigation (Stocks, Crypto, Forex, Screener, Dashboard)
- Reorganize into components/, pages/, utils/ structure
- Add caching layer for performance optimization
- HuggingFace Spaces ready with updated README
- All existing features preserved in Stock Analysis page

.env.example

@@ -1 +1,10 @@
-OPENBB_TOKEN=openbb_workspace_token_here
+# Financial Platform Environment Variables
+
+# DeepSeek API Key (for AI-powered insights)
+DEEPSEEK_API_KEY=your-deepseek-api-key-here
+
+# News Service URL (for news aggregation with sentiment analysis)
+NEWS_SERVICE_URL=http://localhost:5000
+
+# Alpha Vantage API Key (optional, for forex data)
+ALPHA_VANTAGE_KEY=your-alpha-vantage-key-here

.gitignore

@@ -19,4 +19,6 @@ ml_models/
 exp_results/
 # Ignore png and jpg files
 *.png
-*.jpg
+*.jpg
+# Ignore .ruff
+.ruff_cache

README.md

@@ -1,12 +1,177 @@
 ---
 title: FinancialPlatform
-emoji: 👀
-colorFrom: gray
+emoji: 📈
+colorFrom: blue
 colorTo: green
-sdk: docker
+sdk: streamlit
+sdk_version: 1.30.0
+app_file: app/app.py
 pinned: false
 license: apache-2.0
-short_description: OpneBB-based Financial Platform. Bloomberg-like terminal
+short_description: Multi-asset financial analysis platform with OpenBB, TradingView integration, and AI insights
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Financial Analysis Platform
+
+A comprehensive multi-asset financial analysis platform built with Streamlit, providing real-time data, technical indicators, and AI-powered insights.
+
+## Features
+
+### 📈 Stock Analysis
+- Real-time stock price data from OpenBB
+- Technical indicators (SMA, EMA, RSI)
+- Company profile and financial statements
+- Revenue and net income trends
+- TradingView chart integration
+- Profitability metrics analysis
+
+### ₿ Cryptocurrency (Coming Soon)
+- Real-time cryptocurrency prices
+- Market cap and 24h volume
+- Technical indicators for crypto assets
+- TradingView crypto charts
+
+### 💱 Forex Trading (Coming Soon)
+- Foreign exchange rate analysis
+- Major, minor, and exotic pairs
+- Pip calculator
+- Economic calendar integration
+
+### 🔍 Market Screener (Coming Soon)
+- Multi-criteria filtering
+- Technical pattern recognition
+- Sort by volume, price change, RSI
+- Export results to CSV
+
+### 🤖 News & AI Dashboard (Coming Soon)
+- Real-time news aggregation
+- AI-powered sentiment analysis
+- Trading recommendations
+- Market trend detection
+
+## Installation
+
+1. Clone the repository:
+```bash
+git clone <repository-url>
+cd FinancialPlatform
+```
+
+2. Install dependencies:
+```bash
+pip install -r requirements.txt
+```
+
+3. Create a `.env` file based on `.env.example`:
+```bash
+cp .env.example .env
+```
+
+4. Configure your API keys in `.env`:
+```
+DEEPSEEK_API_KEY=your-key-here
+NEWS_SERVICE_URL=http://localhost:5000
+ALPHA_VANTAGE_KEY=your-key-here
+```
+
+## Usage
+
+Run the application:
+```bash
+streamlit run app/app.py
+```
+
+The application will open in your default web browser at `http://localhost:8501`.
+
+## Project Structure
+
+```
+FinancialPlatform/
+├── app/
+│   ├── app.py                      # Main landing page
+│   ├── pages/
+│   │   ├── 01_Stocks.py           # Stock analysis page
+│   │   ├── 02_Crypto.py           # Cryptocurrency analysis
+│   │   ├── 03_Forex.py            # Forex analysis
+│   │   ├── 04_Screener.py         # Market screener
+│   │   └── 05_Dashboard.py        # News & AI dashboard
+│   ├── components/
+│   │   ├── chart.py               # Chart creation utilities
+│   │   ├── data_sources.py        # Data fetching functions
+│   │   ├── ui.py                  # UI component functions
+│   │   └── styles.py              # Dark theme CSS
+│   └── utils/
+│       ├── config.py              # Configuration management
+│       └── formatters.py          # Data formatting utilities
+├── requirements.txt
+├── .env.example
+└── README.md
+```
+
+## Technology Stack
+
+- **Frontend**: Streamlit
+- **Data Sources**: OpenBB SDK, yfinance
+- **Charting**: Plotly, TradingView widgets
+- **AI**: DeepSeek API (planned)
+- **Styling**: Custom CSS with dark theme
+
+## Features in Development
+
+- [ ] Cryptocurrency data integration (Binance API)
+- [ ] Forex data integration (Alpha Vantage)
+- [ ] Market screener with advanced filters
+- [ ] News aggregation service
+- [ ] AI-powered trading insights
+- [ ] Sentiment analysis
+- [ ] Additional technical indicators (MACD, Bollinger Bands, ATR)
+
+## Configuration
+
+### Environment Variables
+
+- `DEEPSEEK_API_KEY`: API key for AI-powered insights
+- `NEWS_SERVICE_URL`: URL for news aggregation service
+- `ALPHA_VANTAGE_KEY`: API key for forex data (optional)
+
+### Cache Settings
+
+Data caching is configured in `utils/config.py`:
+- Price data: 1 hour TTL
+- Fundamental data: 24 hours TTL
+- News data: 15 minutes TTL
+
+## Deployment
+
+### HuggingFace Spaces
+
+This application is optimized for deployment on HuggingFace Spaces:
+
+1. Create a new Space on HuggingFace
+2. Set the Space type to "Streamlit"
+3. Add your environment variables in the Space settings:
+   - `DEEPSEEK_API_KEY`
+   - `NEWS_SERVICE_URL`
+   - `ALPHA_VANTAGE_KEY`
+4. Push your code to the Space repository
+
+### Local Development
+
+For local development with hot-reload:
+```bash
+streamlit run app/app.py --server.runOnSave=true
+```
+
+## Contributing
+
+Contributions are welcome! Please feel free to submit a Pull Request.
+
+## License
+
+Apache 2.0 License
+
+## Acknowledgments
+
+- OpenBB for financial data API
+- TradingView for chart widgets
+- Streamlit for the amazing web framework

app/app.py

@@ -0,0 +1,163 @@
+"""Financial Analysis Dashboard - Main Application Landing Page."""
+
+import streamlit as st
+from components.styles import DARK_THEME_CSS
+
+# ---- Configuration ----
+st.set_page_config(
+    page_title="Financial Dashboard",
+    page_icon="📈",
+    layout="wide",
+    initial_sidebar_state="expanded",
+    menu_items={
+        "About": "A professional financial analysis platform with multi-asset support"
+    }
+)
+
+# ---- Apply Dark Theme ----
+st.markdown(DARK_THEME_CSS, unsafe_allow_html=True)
+
+# ---- Header ----
+st.markdown("# 📈 Financial Analysis Platform")
+st.markdown("### Professional multi-asset analysis with technical indicators, AI insights, and real-time data")
+
+st.markdown("---")
+
+# ---- Feature Overview ----
+col1, col2, col3 = st.columns(3)
+
+with col1:
+    st.markdown("""
+    <div style="padding: 1.5rem; background: linear-gradient(135deg, #1f2937 0%, #111827 100%); border-radius: 10px; border: 1px solid #30363d;">
+        <h3>📈 Stock Analysis</h3>
+        <p>Comprehensive stock analysis with technical indicators, financial metrics, and TradingView charts.</p>
+        <ul>
+            <li>Real-time price data</li>
+            <li>Technical indicators (SMA, EMA, RSI)</li>
+            <li>Financial statements</li>
+            <li>Company profiles</li>
+        </ul>
+    </div>
+    """, unsafe_allow_html=True)
+
+with col2:
+    st.markdown("""
+    <div style="padding: 1.5rem; background: linear-gradient(135deg, #1f2937 0%, #111827 100%); border-radius: 10px; border: 1px solid #30363d;">
+        <h3>₿ Cryptocurrency</h3>
+        <p>Track and analyze major cryptocurrencies with real-time market data.</p>
+        <ul>
+            <li>BTC, ETH, and major altcoins</li>
+            <li>24h volume & market cap</li>
+            <li>Price charts & indicators</li>
+            <li>Market sentiment</li>
+        </ul>
+    </div>
+    """, unsafe_allow_html=True)
+
+with col3:
+    st.markdown("""
+    <div style="padding: 1.5rem; background: linear-gradient(135deg, #1f2937 0%, #111827 100%); border-radius: 10px; border: 1px solid #30363d;">
+        <h3>💱 Forex Trading</h3>
+        <p>Foreign exchange analysis for major, minor, and exotic currency pairs.</p>
+        <ul>
+            <li>Major pairs (EUR/USD, GBP/USD)</li>
+            <li>Real-time exchange rates</li>
+            <li>Technical analysis</li>
+            <li>Pip calculator</li>
+        </ul>
+    </div>
+    """, unsafe_allow_html=True)
+
+st.markdown("<br>", unsafe_allow_html=True)
+
+col4, col5 = st.columns(2)
+
+with col4:
+    st.markdown("""
+    <div style="padding: 1.5rem; background: linear-gradient(135deg, #1f2937 0%, #111827 100%); border-radius: 10px; border: 1px solid #30363d;">
+        <h3>🔍 Market Screener</h3>
+        <p>Advanced screening tools to find investment opportunities across markets.</p>
+        <ul>
+            <li>Multi-criteria filtering</li>
+            <li>Technical pattern recognition</li>
+            <li>Sort by volume, price change, RSI</li>
+            <li>Export results to CSV</li>
+        </ul>
+    </div>
+    """, unsafe_allow_html=True)
+
+with col5:
+    st.markdown("""
+    <div style="padding: 1.5rem; background: linear-gradient(135deg, #1f2937 0%, #111827 100%); border-radius: 10px; border: 1px solid #30363d;">
+        <h3>🤖 News & AI Dashboard</h3>
+        <p>AI-powered market insights with sentiment analysis and trading recommendations.</p>
+        <ul>
+            <li>Real-time news aggregation</li>
+            <li>Sentiment analysis</li>
+            <li>AI trading insights</li>
+            <li>Market trend detection</li>
+        </ul>
+    </div>
+    """, unsafe_allow_html=True)
+
+st.markdown("---")
+
+# ---- Quick Start ----
+st.markdown("## 🚀 Quick Start")
+st.markdown("Use the sidebar to navigate to different sections:")
+
+quick_col1, quick_col2, quick_col3 = st.columns(3)
+
+with quick_col1:
+    if st.button("📈 Stock Analysis", use_container_width=True):
+        st.switch_page("pages/01_Stocks.py")
+
+with quick_col2:
+    if st.button("₿ Cryptocurrency", use_container_width=True):
+        st.info("Coming soon!")
+
+with quick_col3:
+    if st.button("💱 Forex Trading", use_container_width=True):
+        st.info("Coming soon!")
+
+st.markdown("<br>", unsafe_allow_html=True)
+
+quick_col4, quick_col5 = st.columns(2)
+
+with quick_col4:
+    if st.button("🔍 Market Screener", use_container_width=True):
+        st.info("Coming soon!")
+
+with quick_col5:
+    if st.button("🤖 News & AI Dashboard", use_container_width=True):
+        st.info("Coming soon!")
+
+st.markdown("---")
+
+# ---- Sidebar ----
+with st.sidebar:
+    st.markdown("## 📋 Navigation")
+    st.info("Select a page from the sidebar to get started.")
+
+    st.markdown("---")
+    st.markdown("## ℹ️ About")
+    st.markdown("""
+    This platform provides comprehensive financial analysis across multiple asset classes:
+
+    - **Stocks**: Technical & fundamental analysis
+    - **Crypto**: Real-time cryptocurrency tracking
+    - **Forex**: Currency pair analysis
+    - **Screener**: Find investment opportunities
+    - **Dashboard**: AI-powered insights
+    """)
+
+    st.markdown("---")
+    st.markdown("### 🔧 Features")
+    st.markdown("""
+    - ✅ Real-time data
+    - ✅ Technical indicators
+    - ✅ TradingView integration
+    - ✅ Dark theme UI
+    - ✅ AI-powered insights
+    - ✅ News sentiment analysis
+    """)

app/components/chart.py

@@ -0,0 +1,142 @@
+"""Chart creation utilities for the financial dashboard."""
+
+import plotly.graph_objects as go
+import pandas as pd
+
+
+def get_dark_theme_layout():
+    """Get common dark theme layout settings for all charts."""
+    return dict(
+        plot_bgcolor="#0d1117",
+        paper_bgcolor="#0e1117",
+        font=dict(color="#e6edf3", size=12, family="Arial, sans-serif"),
+        xaxis=dict(
+            gridcolor="#30363d",
+            showgrid=True,
+            zeroline=False,
+            color="#8b949e"
+        ),
+        yaxis=dict(
+            gridcolor="#30363d",
+            showgrid=True,
+            zeroline=False,
+            color="#8b949e"
+        ),
+        legend=dict(
+            bgcolor="rgba(13, 17, 23, 0.8)",
+            bordercolor="#30363d",
+            borderwidth=1,
+            font=dict(color="#e6edf3")
+        ),
+        hoverlabel=dict(
+            bgcolor="#0d1117",
+            bordercolor="#30363d",
+            font=dict(color="#e6edf3")
+        )
+    )
+
+
+def create_price_chart(df: pd.DataFrame, symbol: str, period: int) -> go.Figure:
+    """Create price chart with SMA and EMA indicators."""
+    fig = go.Figure()
+
+    fig.add_trace(go.Scatter(
+        x=df.index, y=df["close"],
+        name="Close Price",
+        line=dict(color="#0066ff", width=2.5)
+    ))
+    fig.add_trace(go.Scatter(
+        x=df.index, y=df["SMA"],
+        name=f"SMA {period}",
+        line=dict(color="#00d084", width=2, dash="dash")
+    ))
+    fig.add_trace(go.Scatter(
+        x=df.index, y=df["EMA"],
+        name=f"EMA {period}",
+        line=dict(color="#ffa500", width=2, dash="dot")
+    ))
+
+    layout = get_dark_theme_layout()
+    fig.update_layout(
+        title=f"{symbol} - Price with Moving Averages",
+        xaxis_title="Date",
+        yaxis_title="Price ($)",
+        hovermode="x unified",
+        template="plotly_dark",
+        height=500,
+        margin=dict(l=0, r=0, t=40, b=0),
+        **layout
+    )
+
+    return fig
+
+
+def create_rsi_chart(df: pd.DataFrame, symbol: str) -> go.Figure:
+    """Create RSI (Relative Strength Index) chart."""
+    fig = go.Figure()
+
+    fig.add_trace(go.Scatter(
+        x=df.index, y=df["RSI"],
+        name="RSI",
+        line=dict(color="#ff3838", width=2.5),
+        fill="tozeroy",
+        fillcolor="rgba(255, 56, 56, 0.15)"
+    ))
+
+    fig.add_hline(y=70, line_dash="dash", line_color="rgba(255, 165, 0, 0.6)",
+                  annotation_text="Overbought (70)")
+    fig.add_hline(y=30, line_dash="dash", line_color="rgba(0, 208, 132, 0.6)",
+                  annotation_text="Oversold (30)")
+    fig.add_hline(y=50, line_dash="dot", line_color="rgba(139, 148, 158, 0.3)")
+
+    layout = get_dark_theme_layout()
+    layout["yaxis"]["range"] = [0, 100]
+
+    fig.update_layout(
+        title=f"{symbol} - Relative Strength Index (RSI)",
+        xaxis_title="Date",
+        yaxis_title="RSI",
+        hovermode="x unified",
+        template="plotly_dark",
+        height=500,
+        margin=dict(l=0, r=0, t=40, b=0),
+        **layout
+    )
+
+    return fig
+
+
+def create_financial_chart(income_data: pd.DataFrame) -> go.Figure:
+    """Create financial revenue and net income chart."""
+    fig = go.Figure()
+
+    fig.add_trace(go.Bar(
+        x=income_data['period_ending'],
+        y=income_data['total_revenue'],
+        name="Total Revenue",
+        marker=dict(color='#0066ff', opacity=0.9),
+        yaxis='y1'
+    ))
+
+    fig.add_trace(go.Bar(
+        x=income_data['period_ending'],
+        y=income_data['net_income'],
+        name="Net Income",
+        marker=dict(color='#00d084', opacity=0.9),
+        yaxis='y1'
+    ))
+
+    layout = get_dark_theme_layout()
+    fig.update_layout(
+        title="Revenue & Net Income (Annual)",
+        xaxis_title="Period",
+        yaxis_title="Amount ($)",
+        hovermode="x unified",
+        template="plotly_dark",
+        height=400,
+        barmode='group',
+        margin=dict(l=0, r=0, t=40, b=0),
+        **layout
+    )
+
+    return fig

app/components/data_sources.py

@@ -0,0 +1,81 @@
+"""Data fetching and processing utilities for the financial dashboard."""
+
+import pandas as pd
+from openbb import sdk
+import streamlit as st
+
+
+@st.cache_data(ttl=3600)
+def load_stock_data(symbol: str) -> pd.DataFrame:
+    """Load historical stock price data with caching."""
+    df = sdk.equity.price.historical(symbol=symbol).to_dataframe()
+    return df
+
+
+@st.cache_data(ttl=86400)
+def load_company_profile(symbol: str):
+    """Load company profile information with caching."""
+    profile_response = sdk.equity.profile(symbol=symbol)
+    profile_info = profile_response.results[0] if hasattr(profile_response, 'results') and profile_response.results else None
+    return profile_info
+
+
+@st.cache_data(ttl=86400)
+def load_income_statement(symbol: str) -> pd.DataFrame:
+    """Load company income statement data with caching."""
+    income_stmt = sdk.equity.fundamental.income(symbol=symbol).to_dataframe()
+    return income_stmt
+
+
+def calculate_technical_indicators(df: pd.DataFrame, period: int) -> pd.DataFrame:
+    """Calculate SMA, EMA, and RSI indicators."""
+    df = df.copy()
+    df["SMA"] = df["close"].rolling(period).mean()
+    df["EMA"] = df["close"].ewm(span=period, adjust=False).mean()
+
+    # Calculate RSI
+    delta = df["close"].diff()
+    gain = delta.clip(lower=0)
+    loss = -1 * delta.clip(upper=0)
+    avg_gain = gain.rolling(period).mean()
+    avg_loss = loss.rolling(period).mean()
+    rs = avg_gain / avg_loss
+    df["RSI"] = 100 - (100 / (1 + rs))
+
+    return df
+
+
+def get_price_metrics(df: pd.DataFrame) -> dict:
+    """Calculate key price metrics."""
+    current_price = df["close"].iloc[-1]
+    prev_close = df["close"].iloc[-2] if len(df) > 1 else df["close"].iloc[0]
+    price_change = current_price - prev_close
+    price_change_pct = (price_change / prev_close) * 100 if prev_close != 0 else 0
+
+    return {
+        "current_price": current_price,
+        "price_change": price_change,
+        "price_change_pct": price_change_pct,
+        "high_52w": df['high'].max(),
+        "low_52w": df['low'].min(),
+    }
+
+
+def get_profitability_metrics(income_data: pd.Series) -> dict:
+    """Calculate profitability metrics from income statement."""
+    total_rev = income_data.get('total_revenue', 0)
+    gross_prof = income_data.get('gross_profit', 0)
+    net_inc = income_data.get('net_income', 0)
+    operating_inc = income_data.get('operating_income', 0)
+
+    metrics = {}
+
+    if total_rev and total_rev > 0:
+        metrics["gross_margin"] = (gross_prof / total_rev) * 100 if pd.notna(gross_prof) else 0
+        metrics["net_margin"] = (net_inc / total_rev) * 100 if pd.notna(net_inc) else 0
+        if operating_inc:
+            metrics["operating_margin"] = (operating_inc / total_rev) * 100
+    else:
+        metrics = {"gross_margin": 0, "net_margin": 0}
+
+    return metrics

app/components/styles.py

@@ -0,0 +1,331 @@
+"""Dark theme CSS styles for the financial dashboard."""
+
+DARK_THEME_CSS = """
+    <style>
+    :root {
+        --primary-color: #0066ff;
+        --secondary-color: #1f77e2;
+        --success-color: #00d084;
+        --danger-color: #ff3838;
+        --warning-color: #ffa500;
+        --bg-dark: #0e1117;
+        --bg-darker: #010409;
+        --text-primary: #e6edf3;
+        --text-secondary: #8b949e;
+        --border-color: #30363d;
+    }
+
+    /* Main background */
+    html, body {
+        background-color: var(--bg-darker) !important;
+        color: var(--text-primary) !important;
+        margin: 0 !important;
+        padding: 0 !important;
+    }
+
+    /* Streamlit containers */
+    .main, [data-testid="stAppViewContainer"] {
+        background-color: var(--bg-dark) !important;
+    }
+
+    /* Hide header and footer */
+    [data-testid="stHeader"] {
+        background-color: var(--bg-dark) !important;
+    }
+
+    [data-testid="stToolbar"] {
+        background-color: var(--bg-dark) !important;
+    }
+
+    .stApp {
+        background-color: var(--bg-dark) !important;
+    }
+
+    [data-testid="stDecoration"] {
+        background-color: var(--bg-dark) !important;
+    }
+
+    [data-testid="stSidebar"] {
+        background-color: #0d1117 !important;
+        border-right: 1px solid var(--border-color);
+    }
+
+    /* Text colors */
+    p, span, div, h1, h2, h3, h4, h5, h6, label, li, a {
+        color: var(--text-primary) !important;
+    }
+
+    /* Headings */
+    h1, h2, h3 {
+        color: var(--text-primary) !important;
+        font-weight: 700 !important;
+    }
+
+    /* Links */
+    a {
+        color: var(--primary-color) !important;
+        text-decoration: none !important;
+    }
+
+    a:hover {
+        color: var(--secondary-color) !important;
+        text-decoration: underline !important;
+    }
+
+    /* Labels and text inputs */
+    label {
+        color: var(--text-primary) !important;
+        font-weight: 500 !important;
+    }
+
+    /* Paragraph text */
+    p {
+        color: var(--text-primary) !important;
+        line-height: 1.6 !important;
+    }
+
+    /* Metric card styling */
+    [data-testid="metric-container"] {
+        background: linear-gradient(135deg, #1f2937 0%, #111827 100%) !important;
+        border: 1px solid var(--border-color) !important;
+        border-radius: 10px !important;
+        padding: 1.5rem !important;
+        box-shadow: 0 4px 6px rgba(0, 0, 0, 0.3) !important;
+    }
+
+    .metric-card {
+        background: linear-gradient(135deg, #1f2937 0%, #111827 100%);
+        padding: 1.5rem;
+        border-radius: 10px;
+        border: 1px solid var(--border-color);
+        box-shadow: 0 4px 6px rgba(0, 0, 0, 0.3);
+    }
+
+    .metric-value {
+        font-size: 2.5rem;
+        font-weight: 700;
+        color: var(--primary-color);
+        margin: 0.5rem 0;
+    }
+
+    .metric-label {
+        font-size: 0.875rem;
+        color: var(--text-secondary);
+        text-transform: uppercase;
+        letter-spacing: 0.05em;
+    }
+
+    .section-title {
+        color: var(--text-primary);
+        border-bottom: 2px solid var(--primary-color);
+        padding-bottom: 1rem;
+        margin-top: 2rem;
+        margin-bottom: 1.5rem;
+    }
+
+    /* Button styling */
+    .stButton > button {
+        background: linear-gradient(135deg, var(--primary-color) 0%, var(--secondary-color) 100%) !important;
+        color: #ffffff !important;
+        border: none !important;
+        border-radius: 8px !important;
+        padding: 0.75rem 2rem !important;
+        font-weight: 700 !important;
+        transition: all 0.3s ease !important;
+        box-shadow: 0 4px 6px rgba(0, 102, 255, 0.2) !important;
+    }
+
+    .stButton > button:hover {
+        box-shadow: 0 8px 16px rgba(0, 102, 255, 0.4) !important;
+        transform: translateY(-2px) !important;
+    }
+
+    .stButton > button:active {
+        transform: translateY(0) !important;
+    }
+
+    /* Input fields */
+    [data-testid="stTextInput"] input,
+    [data-testid="stSlider"] input {
+        background-color: #161b22 !important;
+        border: 1px solid var(--border-color) !important;
+        color: var(--text-primary) !important;
+        border-radius: 6px !important;
+    }
+
+    [data-testid="stTextInput"] input::placeholder {
+        color: var(--text-secondary) !important;
+    }
+
+    /* Slider */
+    [data-testid="stSlider"] {
+        color: var(--primary-color) !important;
+    }
+
+    /* Tabs */
+    [data-testid="stTabs"] [role="tablist"] {
+        background-color: transparent !important;
+        border-bottom: 2px solid var(--border-color) !important;
+    }
+
+    [data-testid="stTabs"] [role="tab"] {
+        color: var(--text-secondary) !important;
+        background-color: transparent !important;
+        border: none !important;
+        padding: 1rem 1.5rem !important;
+    }
+
+    [data-testid="stTabs"] [role="tab"][aria-selected="true"] {
+        color: var(--primary-color) !important;
+        border-bottom: 3px solid var(--primary-color) !important;
+    }
+
+    /* Dataframe */
+    [data-testid="dataframe"] {
+        background-color: #0d1117 !important;
+    }
+
+    .dataframe {
+        background-color: #0d1117 !important;
+        color: var(--text-primary) !important;
+    }
+
+    /* Info/Error boxes */
+    [data-testid="stInfo"],
+    [data-testid="stSuccess"],
+    [data-testid="stWarning"],
+    [data-testid="stError"] {
+        background-color: rgba(0, 102, 255, 0.1) !important;
+        border-left: 4px solid var(--primary-color) !important;
+        border-radius: 6px !important;
+    }
+
+    [data-testid="stError"] {
+        background-color: rgba(255, 56, 56, 0.1) !important;
+        border-left-color: var(--danger-color) !important;
+    }
+
+    /* Markdown */
+    [data-testid="stMarkdown"] {
+        color: var(--text-primary) !important;
+    }
+
+    /* Expander */
+    [data-testid="stExpander"] {
+        background-color: #161b22 !important;
+        border: 1px solid var(--border-color) !important;
+        border-radius: 6px !important;
+    }
+
+    /* Metric text styling */
+    [data-testid="metric-container"] p {
+        color: var(--text-primary) !important;
+    }
+
+    [data-testid="metric-container"] [data-testid="stMetricValue"] {
+        color: var(--primary-color) !important;
+        font-weight: 700 !important;
+    }
+
+    /* Slider label color */
+    [data-testid="stSlider"] label {
+        color: var(--text-primary) !important;
+    }
+
+    /* Text input label */
+    [data-testid="stTextInput"] label {
+        color: var(--text-primary) !important;
+    }
+
+    /* Write and markdown text */
+    [data-testid="stMarkdownContainer"] p {
+        color: var(--text-primary) !important;
+    }
+
+    [data-testid="stMarkdownContainer"] strong {
+        color: var(--primary-color) !important;
+        font-weight: 600 !important;
+    }
+
+    /* Spinner text */
+    [data-testid="stSpinner"] {
+        color: var(--primary-color) !important;
+    }
+
+    /* Column separators */
+    hr {
+        border-color: var(--border-color) !important;
+    }
+
+    /* Scrollbar */
+    ::-webkit-scrollbar {
+        width: 8px;
+        height: 8px;
+    }
+
+    ::-webkit-scrollbar-track {
+        background: #0d1117;
+    }
+
+    ::-webkit-scrollbar-thumb {
+        background: var(--border-color);
+        border-radius: 4px;
+    }
+
+    ::-webkit-scrollbar-thumb:hover {
+        background: var(--primary-color);
+    }
+
+    /* Selection highlighting */
+    ::selection {
+        background-color: var(--primary-color);
+        color: #fff;
+    }
+
+    /* Fix all white backgrounds */
+    .stApp > header {
+        background-color: var(--bg-dark) !important;
+    }
+
+    .stApp > header::before {
+        background: none !important;
+    }
+
+    .stApp > header::after {
+        background: none !important;
+    }
+
+    /* Streamlit elements background */
+    [data-testid="stVerticalBlock"] {
+        background-color: transparent !important;
+    }
+
+    [data-testid="stVerticalBlockBorderWrapper"] {
+        background-color: transparent !important;
+    }
+
+    /* Remove white decorative elements */
+    .st-emotion-cache-1gvbgyg {
+        background-color: var(--bg-dark) !important;
+    }
+
+    .st-emotion-cache-1jicfl2 {
+        background-color: var(--bg-dark) !important;
+    }
+
+    /* Ensure all root divs are dark */
+    div[class*="st-"] {
+        background-color: transparent !important;
+    }
+
+    /* Modal and overlay backgrounds */
+    .stModal {
+        background-color: var(--bg-dark) !important;
+    }
+
+    /* Alert boxes background */
+    .stAlert {
+        background-color: rgba(0, 102, 255, 0.1) !important;
+    }
+    </style>
+"""

app/components/ui.py

@@ -0,0 +1,174 @@
+"""UI component functions for the financial dashboard."""
+
+import streamlit as st
+import pandas as pd
+import sys
+import os
+
+# Add parent directory to path for imports
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+from utils.formatters import format_financial_value
+from components.data_sources import get_profitability_metrics
+
+
+def display_price_metrics(metrics: dict):
+    """Display key price metrics in columns."""
+    st.markdown('<div class="section-title">📊 Price Metrics</div>', unsafe_allow_html=True)
+
+    col1, col2, col3, col4 = st.columns(4)
+
+    with col1:
+        st.metric("Current Price", f"${metrics['current_price']:.2f}",
+                 f"{metrics['price_change']:+.2f}", delta_color="normal")
+
+    with col2:
+        st.metric("Day Change %", f"{metrics['price_change_pct']:+.2f}%",
+                 None, delta_color="normal")
+
+    with col3:
+        st.metric("52W High", f"${metrics['high_52w']:.2f}")
+
+    with col4:
+        st.metric("52W Low", f"${metrics['low_52w']:.2f}")
+
+
+def display_company_info(profile_info):
+    """Display company information."""
+    st.markdown('<div class="section-title">📋 Company Information</div>', unsafe_allow_html=True)
+
+    if profile_info:
+        info_col1, info_col2 = st.columns(2)
+        with info_col1:
+            st.write(f"**Company Name:** {getattr(profile_info, 'name', 'N/A')}")
+            st.write(f"**Sector:** {getattr(profile_info, 'sector', 'N/A')}")
+            st.write(f"**Industry:** {getattr(profile_info, 'industry', 'N/A')}")
+
+        with info_col2:
+            st.write(f"**Country:** {getattr(profile_info, 'country', 'N/A')}")
+            st.write(f"**Exchange:** {getattr(profile_info, 'exchange', 'N/A')}")
+            st.write(f"**Website:** {getattr(profile_info, 'website', 'N/A')}")
+
+
+def display_financial_metrics(income_stmt: pd.DataFrame):
+    """Display financial metrics from income statement."""
+    st.markdown('<div class="section-title">💰 Financial Metrics</div>', unsafe_allow_html=True)
+
+    latest_income = income_stmt.iloc[0] if len(income_stmt) > 0 else None
+
+    if latest_income is not None:
+        # First row of metrics
+        fin_col1, fin_col2, fin_col3, fin_col4 = st.columns(4)
+
+        with fin_col1:
+            revenue = latest_income.get('total_revenue', 0)
+            if pd.notna(revenue) and revenue > 0:
+                st.metric("Total Revenue", format_financial_value(revenue))
+            else:
+                st.metric("Total Revenue", "N/A")
+
+        with fin_col2:
+            net_income = latest_income.get('net_income', 0)
+            if pd.notna(net_income) and net_income > 0:
+                st.metric("Net Income", format_financial_value(net_income))
+            else:
+                st.metric("Net Income", "N/A")
+
+        with fin_col3:
+            gross_profit = latest_income.get('gross_profit', 0)
+            if pd.notna(gross_profit) and gross_profit > 0:
+                st.metric("Gross Profit", format_financial_value(gross_profit))
+            else:
+                st.metric("Gross Profit", "N/A")
+
+        with fin_col4:
+            operating_income = latest_income.get('operating_income', 0)
+            if pd.notna(operating_income) and operating_income > 0:
+                st.metric("Operating Income", format_financial_value(operating_income))
+            else:
+                st.metric("Operating Income", "N/A")
+
+        # Second row of metrics
+        fin_col5, fin_col6, fin_col7, fin_col8 = st.columns(4)
+
+        with fin_col5:
+            eps = latest_income.get('diluted_earnings_per_share', 0)
+            if pd.notna(eps):
+                st.metric("EPS (Diluted)", f"${eps:.2f}")
+            else:
+                st.metric("EPS (Diluted)", "N/A")
+
+        with fin_col6:
+            ebitda = latest_income.get('ebitda', 0)
+            if pd.notna(ebitda) and ebitda > 0:
+                st.metric("EBITDA", format_financial_value(ebitda))
+            else:
+                st.metric("EBITDA", "N/A")
+
+        with fin_col7:
+            cogs = latest_income.get('cost_of_revenue', 0)
+            if pd.notna(cogs) and cogs > 0:
+                st.metric("Cost of Revenue", format_financial_value(cogs))
+            else:
+                st.metric("Cost of Revenue", "N/A")
+
+        with fin_col8:
+            rd_expense = latest_income.get('research_and_development_expense', 0)
+            if pd.notna(rd_expense) and rd_expense > 0:
+                st.metric("R&D Expense", format_financial_value(rd_expense))
+            else:
+                st.metric("R&D Expense", "N/A")
+
+
+def display_income_statement(income_stmt: pd.DataFrame):
+    """Display formatted income statement table."""
+    st.markdown("### Income Statement")
+
+    if not income_stmt.empty:
+        display_columns = [
+            'period_ending',
+            'total_revenue',
+            'cost_of_revenue',
+            'gross_profit',
+            'operating_income',
+            'net_income',
+            'diluted_earnings_per_share',
+            'ebitda'
+        ]
+
+        available_cols = [col for col in display_columns if col in income_stmt.columns]
+        financial_display = income_stmt[available_cols].copy()
+
+        for col in financial_display.columns:
+            if col != 'period_ending':
+                financial_display[col] = financial_display[col].apply(
+                    lambda x: format_financial_value(x)
+                )
+
+        st.dataframe(financial_display, use_container_width=True, hide_index=True)
+
+
+def display_profitability_metrics(income_stmt: pd.DataFrame):
+    """Display profitability metrics."""
+    st.markdown("### Profitability Metrics")
+
+    prof_col1, prof_col2 = st.columns(2)
+    latest_data = income_stmt.iloc[0]
+    metrics = get_profitability_metrics(latest_data)
+
+    with prof_col1:
+        if "gross_margin" in metrics:
+            st.metric("Gross Margin", f"{metrics['gross_margin']:.2f}%")
+        if "net_margin" in metrics:
+            st.metric("Net Profit Margin", f"{metrics['net_margin']:.2f}%")
+
+    with prof_col2:
+        if "operating_margin" in metrics:
+            st.metric("Operating Margin", f"{metrics['operating_margin']:.2f}%")
+
+        if len(income_stmt) > 1:
+            prev_revenue = income_stmt.iloc[1].get('total_revenue', 0)
+            total_rev = latest_data.get('total_revenue', 0)
+            if prev_revenue and prev_revenue > 0:
+                revenue_growth = ((total_rev - prev_revenue) / prev_revenue) * 100
+                st.metric("Revenue Growth (YoY)", f"{revenue_growth:+.2f}%")

app/pages/01_Stocks.py

@@ -0,0 +1,145 @@
+"""Stock Analysis Page - Comprehensive stock analysis with technical indicators."""
+
+import streamlit as st
+import sys
+import os
+
+# Add parent directory to path for imports
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+from components.styles import DARK_THEME_CSS
+from components.data_sources import (
+    load_stock_data,
+    load_company_profile,
+    load_income_statement,
+    calculate_technical_indicators,
+    get_price_metrics,
+)
+from components.chart import (
+    create_price_chart,
+    create_rsi_chart,
+    create_financial_chart,
+)
+from components.ui import (
+    display_price_metrics,
+    display_company_info,
+    display_financial_metrics,
+    display_income_statement,
+    display_profitability_metrics,
+)
+
+
+# ---- Page Configuration ----
+st.set_page_config(
+    page_title="Stocks - Financial Dashboard",
+    page_icon="📈",
+    layout="wide",
+    initial_sidebar_state="expanded",
+)
+
+# ---- Apply Dark Theme ----
+st.markdown(DARK_THEME_CSS, unsafe_allow_html=True)
+
+# ---- Header ----
+st.markdown("# 📈 Stock Analysis")
+st.markdown("Real-time technical analysis with comprehensive financial metrics")
+
+# ---- Sidebar Configuration ----
+with st.sidebar:
+    st.markdown("## ⚙️ Settings")
+    symbol = st.text_input("Stock Ticker", "AAPL", help="Enter a valid stock ticker symbol").upper()
+    period = st.slider("Indicator Period", 5, 50, 20, help="Period for SMA, EMA, and RSI calculations")
+
+    st.markdown("---")
+    st.markdown("### About")
+    st.info("Analyze stocks with technical indicators, financials, and TradingView charts.")
+
+
+def main():
+    """Main stock analysis logic."""
+    if st.button("📊 Load Stock Data", key="load_btn", use_container_width=True):
+        try:
+            # Load data
+            with st.spinner("Loading data..."):
+                df = load_stock_data(symbol)
+                profile_info = load_company_profile(symbol)
+                income_stmt = load_income_statement(symbol)
+
+            # Calculate technical indicators
+            df = calculate_technical_indicators(df, period)
+
+            # Display price metrics
+            metrics = get_price_metrics(df)
+            display_price_metrics(metrics)
+
+            # Display company information
+            display_company_info(profile_info)
+
+            # Display financial metrics
+            if not income_stmt.empty:
+                display_financial_metrics(income_stmt)
+
+                # Financial history chart
+                st.markdown('<div class="section-title">📊 Revenue & Net Income Trend</div>', unsafe_allow_html=True)
+                income_chart_data = income_stmt[['period_ending', 'total_revenue', 'net_income']].dropna()
+
+                if len(income_chart_data) > 0:
+                    fig_financial = create_financial_chart(income_chart_data)
+                    st.plotly_chart(fig_financial, use_container_width=True)
+
+            # ---- Tabs ----
+            tab1, tab2, tab3, tab4 = st.tabs([
+                "📈 Price & Moving Averages",
+                "📊 RSI Indicator",
+                "📉 TradingView",
+                "📋 Financials"
+            ])
+
+            # Tab 1: Price & Moving Averages
+            with tab1:
+                fig_price = create_price_chart(df, symbol, period)
+                st.plotly_chart(fig_price, use_container_width=True)
+
+            # Tab 2: RSI Indicator
+            with tab2:
+                fig_rsi = create_rsi_chart(df, symbol)
+                st.plotly_chart(fig_rsi, use_container_width=True)
+
+            # Tab 3: TradingView
+            with tab3:
+                tradingview_html = f"""
+                <div class="tradingview-widget-container">
+                  <div id="tradingview_{symbol}"></div>
+                  <script type="text/javascript" src="https://s3.tradingview.com/tv.js"></script>
+                  <script type="text/javascript">
+                    new TradingView.widget({{
+                      "width": "100%",
+                      "height": 600,
+                      "symbol": "{symbol}",
+                      "interval": "D",
+                      "timezone": "Etc/UTC",
+                      "theme": "dark",
+                      "style": "1",
+                      "locale": "en",
+                      "enable_publishing": false,
+                      "allow_symbol_change": true,
+                      "container_id": "tradingview_{symbol}"
+                    }});
+                  </script>
+                </div>
+                """
+                st.components.v1.html(tradingview_html, height=650)
+
+            # Tab 4: Detailed Financials
+            with tab4:
+                if not income_stmt.empty:
+                    display_income_statement(income_stmt)
+                    display_profitability_metrics(income_stmt)
+
+        except Exception as e:
+            st.error(f"Error loading data for {symbol}: {str(e)}")
+            st.info("Please check the ticker symbol and try again.")
+
+
+if __name__ == "__main__":
+    main()

app/pages/02_Crypto.py

@@ -0,0 +1,74 @@
+"""Cryptocurrency Analysis Page - Track and analyze cryptocurrencies."""
+
+import streamlit as st
+import sys
+import os
+
+# Add parent directory to path for imports
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+from components.styles import DARK_THEME_CSS
+
+
+# ---- Page Configuration ----
+st.set_page_config(
+    page_title="Crypto - Financial Dashboard",
+    page_icon="₿",
+    layout="wide",
+    initial_sidebar_state="expanded",
+)
+
+# ---- Apply Dark Theme ----
+st.markdown(DARK_THEME_CSS, unsafe_allow_html=True)
+
+# ---- Header ----
+st.markdown("# ₿ Cryptocurrency Analysis")
+st.markdown("Track and analyze major cryptocurrencies with real-time market data")
+
+st.markdown("---")
+
+# ---- Sidebar Configuration ----
+with st.sidebar:
+    st.markdown("## ⚙️ Settings")
+    crypto_symbol = st.selectbox(
+        "Cryptocurrency",
+        ["BTC/USD", "ETH/USD", "BNB/USD", "ADA/USD", "SOL/USD"],
+        help="Select a cryptocurrency pair"
+    )
+    period = st.slider("Indicator Period", 5, 50, 20, help="Period for technical indicators")
+
+    st.markdown("---")
+    st.markdown("### About")
+    st.info("Analyze cryptocurrencies with technical indicators and real-time market data.")
+
+
+# ---- Main Content ----
+st.info("🚧 This page is under development. Cryptocurrency analysis features coming soon!")
+
+st.markdown("""
+### Planned Features:
+
+- **Real-time Price Data**: Live cryptocurrency prices from Binance
+- **Market Metrics**: 24h volume, market cap, price changes
+- **Technical Indicators**: SMA, EMA, RSI, MACD for crypto assets
+- **TradingView Charts**: Interactive crypto charts
+- **Market Sentiment**: Community sentiment analysis
+- **Top Movers**: Biggest gainers and losers in 24h
+
+Stay tuned for updates!
+""")
+
+# Placeholder metrics
+col1, col2, col3, col4 = st.columns(4)
+
+with col1:
+    st.metric("Current Price", "N/A", "N/A")
+
+with col2:
+    st.metric("24h Change", "N/A", "N/A")
+
+with col3:
+    st.metric("24h Volume", "N/A")
+
+with col4:
+    st.metric("Market Cap", "N/A")

app/pages/03_Forex.py

@@ -0,0 +1,74 @@
+"""Forex Trading Analysis Page - Analyze foreign exchange pairs."""
+
+import streamlit as st
+import sys
+import os
+
+# Add parent directory to path for imports
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+from components.styles import DARK_THEME_CSS
+
+
+# ---- Page Configuration ----
+st.set_page_config(
+    page_title="Forex - Financial Dashboard",
+    page_icon="💱",
+    layout="wide",
+    initial_sidebar_state="expanded",
+)
+
+# ---- Apply Dark Theme ----
+st.markdown(DARK_THEME_CSS, unsafe_allow_html=True)
+
+# ---- Header ----
+st.markdown("# 💱 Forex Trading Analysis")
+st.markdown("Foreign exchange analysis for major, minor, and exotic currency pairs")
+
+st.markdown("---")
+
+# ---- Sidebar Configuration ----
+with st.sidebar:
+    st.markdown("## ⚙️ Settings")
+    forex_pair = st.selectbox(
+        "Currency Pair",
+        ["EUR/USD", "GBP/USD", "USD/JPY", "USD/CHF", "AUD/USD", "USD/CAD"],
+        help="Select a forex pair"
+    )
+    period = st.slider("Indicator Period", 5, 50, 20, help="Period for technical indicators")
+
+    st.markdown("---")
+    st.markdown("### About")
+    st.info("Analyze forex pairs with technical indicators and real-time exchange rates.")
+
+
+# ---- Main Content ----
+st.info("🚧 This page is under development. Forex analysis features coming soon!")
+
+st.markdown("""
+### Planned Features:
+
+- **Real-time Exchange Rates**: Live forex rates from multiple sources
+- **Major, Minor & Exotic Pairs**: Comprehensive coverage
+- **Technical Analysis**: Full suite of technical indicators
+- **Pip Calculator**: Calculate pip values for position sizing
+- **Economic Calendar**: Important economic events
+- **TradingView Charts**: Interactive forex charts
+
+Stay tuned for updates!
+""")
+
+# Placeholder metrics
+col1, col2, col3, col4 = st.columns(4)
+
+with col1:
+    st.metric("Current Rate", "N/A", "N/A")
+
+with col2:
+    st.metric("24h Change", "N/A", "N/A")
+
+with col3:
+    st.metric("Bid Price", "N/A")
+
+with col4:
+    st.metric("Ask Price", "N/A")

app/pages/04_Screener.py

@@ -0,0 +1,74 @@
+"""Market Screener Page - Find investment opportunities across markets."""
+
+import streamlit as st
+import sys
+import os
+
+# Add parent directory to path for imports
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+from components.styles import DARK_THEME_CSS
+
+
+# ---- Page Configuration ----
+st.set_page_config(
+    page_title="Screener - Financial Dashboard",
+    page_icon="🔍",
+    layout="wide",
+    initial_sidebar_state="expanded",
+)
+
+# ---- Apply Dark Theme ----
+st.markdown(DARK_THEME_CSS, unsafe_allow_html=True)
+
+# ---- Header ----
+st.markdown("# 🔍 Market Screener")
+st.markdown("Advanced screening tools to find investment opportunities across markets")
+
+st.markdown("---")
+
+# ---- Sidebar Configuration ----
+with st.sidebar:
+    st.markdown("## ⚙️ Screening Filters")
+
+    asset_type = st.selectbox(
+        "Asset Type",
+        ["Stocks", "Crypto", "Forex"],
+        help="Select asset type to screen"
+    )
+
+    st.markdown("### Price Filters")
+    min_price = st.number_input("Min Price ($)", value=0.0, step=1.0)
+    max_price = st.number_input("Max Price ($)", value=1000.0, step=10.0)
+
+    st.markdown("### Technical Filters")
+    rsi_min = st.slider("Min RSI", 0, 100, 30)
+    rsi_max = st.slider("Max RSI", 0, 100, 70)
+
+    volume_min = st.number_input("Min Volume", value=1000000, step=100000)
+
+    st.markdown("---")
+    if st.button("🔍 Run Screener", use_container_width=True):
+        st.info("Screening in progress...")
+
+
+# ---- Main Content ----
+st.info("🚧 This page is under development. Market screener features coming soon!")
+
+st.markdown("""
+### Planned Features:
+
+- **Multi-Asset Screening**: Stocks, crypto, and forex
+- **Technical Filters**: RSI, MACD, moving averages, volume
+- **Fundamental Filters**: P/E ratio, market cap, revenue growth
+- **Pattern Recognition**: Chart patterns and technical setups
+- **Custom Criteria**: Build your own screening rules
+- **Export Results**: Download screening results as CSV
+- **Saved Screens**: Save your favorite screening criteria
+
+Stay tuned for updates!
+""")
+
+# Placeholder table
+st.markdown("### Screening Results")
+st.info("No screening results yet. Configure filters and run the screener.")

app/pages/05_Dashboard.py

@@ -0,0 +1,96 @@
+"""News & AI Dashboard Page - AI-powered market insights and news aggregation."""
+
+import streamlit as st
+import sys
+import os
+
+# Add parent directory to path for imports
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+from components.styles import DARK_THEME_CSS
+
+
+# ---- Page Configuration ----
+st.set_page_config(
+    page_title="Dashboard - Financial Dashboard",
+    page_icon="🤖",
+    layout="wide",
+    initial_sidebar_state="expanded",
+)
+
+# ---- Apply Dark Theme ----
+st.markdown(DARK_THEME_CSS, unsafe_allow_html=True)
+
+# ---- Header ----
+st.markdown("# 🤖 News & AI Dashboard")
+st.markdown("AI-powered market insights with sentiment analysis and trading recommendations")
+
+st.markdown("---")
+
+# ---- Sidebar Configuration ----
+with st.sidebar:
+    st.markdown("## ⚙️ Settings")
+
+    news_source = st.multiselect(
+        "News Sources",
+        ["All", "Reuters", "Bloomberg", "CNBC", "Yahoo Finance"],
+        default=["All"],
+        help="Filter news by source"
+    )
+
+    sentiment_filter = st.select_slider(
+        "Sentiment Filter",
+        options=["Very Negative", "Negative", "Neutral", "Positive", "Very Positive"],
+        value="Neutral"
+    )
+
+    st.markdown("---")
+    st.markdown("### AI Analysis")
+    ai_enabled = st.checkbox("Enable AI Insights", value=False)
+
+    if ai_enabled:
+        st.info("⚠️ AI insights require API key configuration.")
+
+
+# ---- Main Content ----
+st.info("🚧 This page is under development. News and AI features coming soon!")
+
+st.markdown("""
+### Planned Features:
+
+#### 📰 News Aggregation
+- **Real-time News Feed**: Latest financial news from multiple sources
+- **Sentiment Analysis**: AI-powered sentiment scoring for each article
+- **Ticker-based Filtering**: See news for specific stocks
+- **Source Filtering**: Choose your preferred news sources
+
+#### 🤖 AI-Powered Insights
+- **Market Analysis**: AI analysis of market conditions
+- **Price Predictions**: ML-based price trend predictions
+- **Support/Resistance**: Automated technical level detection
+- **Trading Signals**: Buy/sell/hold recommendations
+- **Risk Assessment**: Position risk analysis
+
+#### 📊 Market Overview
+- **Trending Tickers**: Most active and trending securities
+- **Sector Performance**: Real-time sector rotation analysis
+- **Market Breadth**: Advance/decline metrics
+
+Stay tuned for updates!
+""")
+
+# Placeholder sections
+col1, col2 = st.columns([2, 1])
+
+with col1:
+    st.markdown("### 📰 Latest News")
+    st.info("No news articles available yet. Configure your API keys to enable news aggregation.")
+
+with col2:
+    st.markdown("### 🤖 AI Chat")
+    st.info("AI chat interface coming soon! You'll be able to ask questions about market conditions, get trading ideas, and receive personalized insights.")
+
+st.markdown("---")
+
+st.markdown("### 📈 Trending Tickers")
+st.info("Trending ticker data will be displayed here.")

app/utils/config.py

@@ -0,0 +1,34 @@
+"""Configuration management for the financial dashboard."""
+
+import os
+from dotenv import load_dotenv
+
+# Load environment variables
+load_dotenv()
+
+
+class Config:
+    """Application configuration."""
+
+    # API Keys
+    DEEPSEEK_API_KEY = os.getenv("DEEPSEEK_API_KEY", "")
+    NEWS_SERVICE_URL = os.getenv("NEWS_SERVICE_URL", "")
+    ALPHA_VANTAGE_KEY = os.getenv("ALPHA_VANTAGE_KEY", "")
+
+    # Cache settings
+    PRICE_DATA_TTL = 3600  # 1 hour
+    FUNDAMENTAL_DATA_TTL = 86400  # 24 hours
+    NEWS_DATA_TTL = 900  # 15 minutes
+
+    # App settings
+    DEFAULT_STOCK_SYMBOL = "AAPL"
+    DEFAULT_CRYPTO_SYMBOL = "BTC/USD"
+    DEFAULT_FOREX_SYMBOL = "EUR/USD"
+    DEFAULT_INDICATOR_PERIOD = 20
+
+    # Data source settings
+    MAX_RETRY_ATTEMPTS = 3
+    REQUEST_TIMEOUT = 30
+
+
+config = Config()

app/utils/formatters.py

@@ -0,0 +1,29 @@
+"""Data formatting utilities for the financial dashboard."""
+
+import pandas as pd
+
+
+def format_financial_value(value) -> str:
+    """Format financial values with appropriate units."""
+    if pd.isna(value):
+        return "N/A"
+    if abs(value) >= 1e9:
+        return f"${value/1e9:.2f}B"
+    elif abs(value) >= 1e6:
+        return f"${value/1e6:.2f}M"
+    else:
+        return f"${value:.2f}"
+
+
+def format_percentage(value: float, decimals: int = 2) -> str:
+    """Format percentage values."""
+    if pd.isna(value):
+        return "N/A"
+    return f"{value:.{decimals}f}%"
+
+
+def format_currency(value: float, decimals: int = 2) -> str:
+    """Format currency values."""
+    if pd.isna(value):
+        return "N/A"
+    return f"${value:,.{decimals}f}"

requirements.txt

@@ -1,6 +1,6 @@
-openbb
-streamlit
-plotly
-pandas
-python-dotenv
-ta-lib
+streamlit>=1.30.0
+pandas>=2.0.0
+plotly>=5.18.0
+openbb>=4.0.0
+python-dotenv>=1.0.0
+requests>=2.31.0