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README.md

@@ -1,80 +1,168 @@
 ---
-title: Market Analyst
-emoji: 📈
+app_port: 7860
 colorFrom: blue
 colorTo: gray
-sdk: docker
-app_port: 7860
-pinned: false
+emoji: 📈
 license: mit
-short_description: Multi-Agent AI for Real-Time Stock Analysis & Strategy
+pinned: false
+sdk: docker
+short_description: Multi-agent AI that recommends stock option spreads
+title: AI Market Analyst --- Real-Time Stock & Options Insights
 ---
 
-# 📈 AI Market Analyst
+# 📈 AI Market Analyst --- From Ticker to Strategy
+
+Enter a stock ticker and get **real-time technical analysis, news
+sentiment, and AI-generated option strategies** --- all powered by a
+coordinated **multi-agent system**.
+
+Designed for **learning, demos, and research** in agentic finance
+workflows.
+
+------------------------------------------------------------------------
+
+## 👉 Try it with these tickers
 
-A sophisticated **Multi-Agent System** that performs real-time technical and sentimental analysis on stock tickers to generate actionable option trading strategies with high confidence.
+-   `AAPL` --- Large-cap, steady trend
+-   `TSLA` --- High volatility, news-driven
+-   `NVDA` --- Momentum + sentiment play
+-   `SPY` --- Market-wide signal
+
+⬆️ Start with one ticker and explore how different agents reason
+together.
+
+------------------------------------------------------------------------
+
+## ✨ Why this Space is different
+
+Most market tools show charts.\
+This one **explains the reasoning** behind a strategy.
+
+✔️ Multiple specialized AI agents (not one monolithic model)\
+✔️ Combines **technicals + sentiment + volatility**\
+✔️ Generates **structured option strategies**, not vague advice\
+✔️ Built with strong guardrails to avoid misleading outputs
+
+This Space is a **reference implementation** for agentic AI in finance.
+
+------------------------------------------------------------------------
 
 ## 🚀 Features
 
-- **🧠 Multi-Agent Swarm**:
-  - **Market Analyst**: Calculates technicals (SMA 20/50/200, RSI 14) and analyzes trend/momentum.
-  - **Sentiment Analyst**: Scrapes full news articles and uses **FinBERT** to score sentiment (Bullish/Bearish).
-  - **Strategy Advisor**: Recommends complex option spreads (Iron Condors, Vertical Spreads) with *specific* legs (Strikes/Expiry).
-  - **Risk Manager**: Validates trades against a confidence rubric (>70% required) and volatility regime (VIX).
-- **🕵️ Deep Sentiment Engine**: Goes beyond headlines by fetching and analyzing the full text of news articles using `BeautifulSoup` and `Transformers` (FinBERT).
-- **⚡ High Performance**: Parallelized news fetching for rapid analysis.
-- **🛡️ Guardrails**:
-  - **Market Hours**: Only operates during US Market Open (09:30-16:00 ET) to prevent stale data usage.
-  - **Type Safety**: Pydantic validation for all data pipelines.
-  - **Robustness**: Gracefully handles new IPOs or missing data.
+### 🧠 Multi-Agent Swarm
 
-## 🛠️ Architecture
+Each agent has a single responsibility:
 
-```
-src/market-analyst/
-├── app.py                  # Streamlit UI (Orchestrator)
-├── aagents/                # Agent Definitions
-│   ├── market_analyst.py   # Technical Analysis Agent
-│   ├── sentiment_analyst.py# FinBERT Agent
-│   ├── strategy_advisor.py # Option Strategist
-│   └── risk_manager.py     # Validator
-├── tools/                  # Capability Layer
-│   ├── market_data.py      # yfinance, pandas-ta logic (SMA, RSI, Options)
-│   └── news_data.py        # DDGS, Requests, FinBERT, Pydantic
-└── Dockerfile              # Deployment Configuration
-```
+-   **Market Analyst Agent**
+    -   Computes SMA (20 / 50 / 200), RSI (14)
+    -   Detects trend, momentum, and regime
+-   **Sentiment Analyst Agent**
+    -   Scrapes full news articles (not just headlines)
+    -   Uses **FinBERT** to classify sentiment as Bullish / Bearish /
+        Neutral
+-   **Strategy Advisor Agent**
+    -   Proposes **option spreads** (Iron Condors, Vertical Spreads)
+    -   Includes concrete legs: strikes, expiry, and structure
+-   **Risk Manager Agent**
+    -   Validates strategies against:
+        -   Confidence score (\>70% required)
+        -   Market volatility (VIX regime)
+        -   Data completeness
+
+------------------------------------------------------------------------
+
+### 🕵️ Deep Sentiment Engine
 
-## 📦 Startup
+-   Fetches **full article text** using `requests` + `BeautifulSoup`
+-   Runs transformer-based sentiment analysis (FinBERT)
+-   Aggregates sentiment across multiple sources
+
+------------------------------------------------------------------------
+
+### 🛡️ Built-in Guardrails
+
+-   ⏰ **Market Hours Aware**\
+    Runs only during US market hours (09:30--16:00 ET)
+
+-   🧾 **Type Safety**\
+    End-to-end Pydantic validation
+
+-   🧯 **Robust by Design**\
+    Handles missing data, low-liquidity tickers, and new IPOs gracefully
+
+------------------------------------------------------------------------
+
+## 🔍 How it works (high level)
+
+1.  You enter a stock ticker
+2.  Market data is fetched and technical indicators are computed
+3.  News articles are scraped and sentiment-scored
+4.  Strategy Advisor proposes an option structure
+5.  Risk Manager validates or rejects the strategy
+6.  Final output includes **analysis + rationale**
+
+------------------------------------------------------------------------
+
+## 🧪 Example use cases
+
+-   Learning **options strategy design**
+-   Demonstrating **multi-agent coordination**
+-   Building agentic finance prototypes
+-   Educational demos (no real-money trading)
+
+------------------------------------------------------------------------
+
+## 🔧 Under the hood (for developers)
+
+    src/market-analyst/
+    ├── app.py                  # Streamlit UI (Agent Orchestrator)
+    ├── aagents/                # Agent definitions
+    │   ├── market_analyst.py   # Technical indicators & trends
+    │   ├── sentiment_analyst.py# FinBERT sentiment engine
+    │   ├── strategy_advisor.py # Options strategist
+    │   └── risk_manager.py     # Trade validator
+    ├── tools/                  # Capability layer
+    │   ├── market_data.py      # yfinance, pandas-ta, options chains
+    │   └── news_data.py        # DDGS, requests, FinBERT, Pydantic
+    └── Dockerfile              # HF Spaces deployment
+
+------------------------------------------------------------------------
+
+## ▶️ Run locally
 
 ### Prerequisites
-- Python 3.12+
-- `uv` package manager (optional but recommended)
 
-### Local Run
+-   Python 3.12+
+-   Virtual environment recommended
 
-1. **Install Dependencies**:
-   ```bash
-   pip install -e .
-   ```
+### Install & run
 
-2. **Run Application**:
-   ```bash
-   streamlit run src/market-analyst/app.py
-   ```
-   The app will open at `http://localhost:8501`.
+``` bash
+pip install -e .
+streamlit run src/market-analyst/app.py
+```
 
-## 🐳 Docker / Deployment
+App runs at: `http://localhost:8501`
 
-The project is packaged for **Hugging Face Spaces** (Docker SDK).
+------------------------------------------------------------------------
 
-```bash
-# Build
-docker build -t market-analyst -f src/market-analyst/Dockerfile .
+## 🐳 Docker / Hugging Face Spaces
 
-# Run
+``` bash
+docker build -t market-analyst -f src/market-analyst/Dockerfile .
 docker run -p 7860:7860 market-analyst
 ```
 
-## ⚠️ Disclaimer
+------------------------------------------------------------------------
+
+## ⚠️ Financial Disclaimer
+
+**Educational use only.**\
+This tool is **not** a financial advisor and does **not** provide
+investment advice.\
+Do **not** use for real-money trading.
+
+------------------------------------------------------------------------
 
-**Educational Use Only**. This tool uses AI to analyze financial data. It is not a certified financial advisor. Do not use for real-money trading.
+💡 Like this Space?\
+⭐ Give it a like · 🔁 Duplicate it · 💬 Share feedback

pyproject.toml

@@ -33,6 +33,16 @@ dependencies = [
     "html2text>=2025.4.15",
     "traceloop-sdk>=0.33.0",
 
+    # =======================
+    # MICROSOFT AGENT FRAMEWORK
+    # =======================
+    #"agent-framework==1.0.0b251204",
+    #"agent-framework-azure-ai==1.0.0b251204",
+    #"azure-ai-projects",
+    #"azure-ai-agents",
+    #"azure-ai-agents>=1.2.0b5",
+    #"agent-framework-azure-ai",
+
     # =======================
     # VECTOR DB / INDEXING
     # =======================
@@ -93,6 +103,12 @@ dependencies = [
     "streamlit>=1.51.0",
     "reportlab>=4.4.5",
     "fastapi",
+    "Pillow",
+    "python-docx",
+    "matplotlib",
+    "fpdf",
+    "extra-streamlit-components",
+    "nest_asyncio",
 
     # =======================
     # AUDIO / VIDEO

run.py

@@ -72,6 +72,16 @@ APP_REGISTRY: Dict[str, Dict[str, str]] = {
         "path": "src/market-analyst",
         "entry": "app.py",
         "description": "Market Analyst - Multi-agent market analysis tool"
+    },
+    "image": {
+        "path": "src/image-generator",
+        "entry": "app.py",
+        "description": "Image Generator - Multi-agent image generation tool"
+    },
+    "interview-assistant": {
+        "path": "src/interview-assistant",
+        "entry": "app.py",
+        "description": "Interview Assistant - Multi-agent interview tool"
     }
 }
 

src/market-analyst/README.md

@@ -1,80 +1,168 @@
 ---
-title: Market Analyst
-emoji: 📈
+app_port: 7860
 colorFrom: blue
 colorTo: gray
-sdk: docker
-app_port: 7860
-pinned: false
+emoji: 📈
 license: mit
-short_description: Multi-Agent AI for Real-Time Stock Analysis & Strategy
+pinned: false
+sdk: docker
+short_description: Multi-agent AI that recommends stock option spreads
+title: AI Market Analyst --- Real-Time Stock & Options Insights
 ---
 
-# 📈 AI Market Analyst
+# 📈 AI Market Analyst --- From Ticker to Strategy
+
+Enter a stock ticker and get **real-time technical analysis, news
+sentiment, and AI-generated option strategies** --- all powered by a
+coordinated **multi-agent system**.
+
+Designed for **learning, demos, and research** in agentic finance
+workflows.
+
+------------------------------------------------------------------------
+
+## 👉 Try it with these tickers
 
-A sophisticated **Multi-Agent System** that performs real-time technical and sentimental analysis on stock tickers to generate actionable option trading strategies with high confidence.
+-   `AAPL` --- Large-cap, steady trend
+-   `TSLA` --- High volatility, news-driven
+-   `NVDA` --- Momentum + sentiment play
+-   `SPY` --- Market-wide signal
+
+⬆️ Start with one ticker and explore how different agents reason
+together.
+
+------------------------------------------------------------------------
+
+## ✨ Why this Space is different
+
+Most market tools show charts.\
+This one **explains the reasoning** behind a strategy.
+
+✔️ Multiple specialized AI agents (not one monolithic model)\
+✔️ Combines **technicals + sentiment + volatility**\
+✔️ Generates **structured option strategies**, not vague advice\
+✔️ Built with strong guardrails to avoid misleading outputs
+
+This Space is a **reference implementation** for agentic AI in finance.
+
+------------------------------------------------------------------------
 
 ## 🚀 Features
 
-- **🧠 Multi-Agent Swarm**:
-  - **Market Analyst**: Calculates technicals (SMA 20/50/200, RSI 14) and analyzes trend/momentum.
-  - **Sentiment Analyst**: Scrapes full news articles and uses **FinBERT** to score sentiment (Bullish/Bearish).
-  - **Strategy Advisor**: Recommends complex option spreads (Iron Condors, Vertical Spreads) with *specific* legs (Strikes/Expiry).
-  - **Risk Manager**: Validates trades against a confidence rubric (>70% required) and volatility regime (VIX).
-- **🕵️ Deep Sentiment Engine**: Goes beyond headlines by fetching and analyzing the full text of news articles using `BeautifulSoup` and `Transformers` (FinBERT).
-- **⚡ High Performance**: Parallelized news fetching for rapid analysis.
-- **🛡️ Guardrails**:
-  - **Market Hours**: Only operates during US Market Open (09:30-16:00 ET) to prevent stale data usage.
-  - **Type Safety**: Pydantic validation for all data pipelines.
-  - **Robustness**: Gracefully handles new IPOs or missing data.
+### 🧠 Multi-Agent Swarm
 
-## 🛠️ Architecture
+Each agent has a single responsibility:
 
-```
-src/market-analyst/
-├── app.py                  # Streamlit UI (Orchestrator)
-├── aagents/                # Agent Definitions
-│   ├── market_analyst.py   # Technical Analysis Agent
-│   ├── sentiment_analyst.py# FinBERT Agent
-│   ├── strategy_advisor.py # Option Strategist
-│   └── risk_manager.py     # Validator
-├── tools/                  # Capability Layer
-│   ├── market_data.py      # yfinance, pandas-ta logic (SMA, RSI, Options)
-│   └── news_data.py        # DDGS, Requests, FinBERT, Pydantic
-└── Dockerfile              # Deployment Configuration
-```
+-   **Market Analyst Agent**
+    -   Computes SMA (20 / 50 / 200), RSI (14)
+    -   Detects trend, momentum, and regime
+-   **Sentiment Analyst Agent**
+    -   Scrapes full news articles (not just headlines)
+    -   Uses **FinBERT** to classify sentiment as Bullish / Bearish /
+        Neutral
+-   **Strategy Advisor Agent**
+    -   Proposes **option spreads** (Iron Condors, Vertical Spreads)
+    -   Includes concrete legs: strikes, expiry, and structure
+-   **Risk Manager Agent**
+    -   Validates strategies against:
+        -   Confidence score (\>70% required)
+        -   Market volatility (VIX regime)
+        -   Data completeness
+
+------------------------------------------------------------------------
+
+### 🕵️ Deep Sentiment Engine
 
-## 📦 Startup
+-   Fetches **full article text** using `requests` + `BeautifulSoup`
+-   Runs transformer-based sentiment analysis (FinBERT)
+-   Aggregates sentiment across multiple sources
+
+------------------------------------------------------------------------
+
+### 🛡️ Built-in Guardrails
+
+-   ⏰ **Market Hours Aware**\
+    Runs only during US market hours (09:30--16:00 ET)
+
+-   🧾 **Type Safety**\
+    End-to-end Pydantic validation
+
+-   🧯 **Robust by Design**\
+    Handles missing data, low-liquidity tickers, and new IPOs gracefully
+
+------------------------------------------------------------------------
+
+## 🔍 How it works (high level)
+
+1.  You enter a stock ticker
+2.  Market data is fetched and technical indicators are computed
+3.  News articles are scraped and sentiment-scored
+4.  Strategy Advisor proposes an option structure
+5.  Risk Manager validates or rejects the strategy
+6.  Final output includes **analysis + rationale**
+
+------------------------------------------------------------------------
+
+## 🧪 Example use cases
+
+-   Learning **options strategy design**
+-   Demonstrating **multi-agent coordination**
+-   Building agentic finance prototypes
+-   Educational demos (no real-money trading)
+
+------------------------------------------------------------------------
+
+## 🔧 Under the hood (for developers)
+
+    src/market-analyst/
+    ├── app.py                  # Streamlit UI (Agent Orchestrator)
+    ├── aagents/                # Agent definitions
+    │   ├── market_analyst.py   # Technical indicators & trends
+    │   ├── sentiment_analyst.py# FinBERT sentiment engine
+    │   ├── strategy_advisor.py # Options strategist
+    │   └── risk_manager.py     # Trade validator
+    ├── tools/                  # Capability layer
+    │   ├── market_data.py      # yfinance, pandas-ta, options chains
+    │   └── news_data.py        # DDGS, requests, FinBERT, Pydantic
+    └── Dockerfile              # HF Spaces deployment
+
+------------------------------------------------------------------------
+
+## ▶️ Run locally
 
 ### Prerequisites
-- Python 3.12+
-- `uv` package manager (optional but recommended)
 
-### Local Run
+-   Python 3.12+
+-   Virtual environment recommended
 
-1. **Install Dependencies**:
-   ```bash
-   pip install -e .
-   ```
+### Install & run
 
-2. **Run Application**:
-   ```bash
-   streamlit run src/market-analyst/app.py
-   ```
-   The app will open at `http://localhost:8501`.
+``` bash
+pip install -e .
+streamlit run src/market-analyst/app.py
+```
 
-## 🐳 Docker / Deployment
+App runs at: `http://localhost:8501`
 
-The project is packaged for **Hugging Face Spaces** (Docker SDK).
+------------------------------------------------------------------------
 
-```bash
-# Build
-docker build -t market-analyst -f src/market-analyst/Dockerfile .
+## 🐳 Docker / Hugging Face Spaces
 
-# Run
+``` bash
+docker build -t market-analyst -f src/market-analyst/Dockerfile .
 docker run -p 7860:7860 market-analyst
 ```
 
-## ⚠️ Disclaimer
+------------------------------------------------------------------------
+
+## ⚠️ Financial Disclaimer
+
+**Educational use only.**\
+This tool is **not** a financial advisor and does **not** provide
+investment advice.\
+Do **not** use for real-money trading.
+
+------------------------------------------------------------------------
 
-**Educational Use Only**. This tool uses AI to analyze financial data. It is not a certified financial advisor. Do not use for real-money trading.
+💡 Like this Space?\
+⭐ Give it a like · 🔁 Duplicate it · 💬 Share feedback