title	Stock Ticker Agent
emoji	📈
colorFrom	blue
colorTo	green
sdk	gradio
sdk_version	5.16.0
app_file	app.py
pinned	false

At Hugginface Spaces: https://selahf-stock-ticker-agent.hf.space/

IN THE AGENT SANDBOX YOU CAN ASK NL QUESTIONS SUCH AS:

    - Calculate the 30-day rolling annualized volatility of daily returns and plot the rolling volatility trend line for the given ticker.
    - What is the latest RSI and MA structure for the given ticker?
    - What is the correlation of RSI vs Returns, show charts use lagged features.
    - The Sandbox Stress-Test Prompt
            "Identify every instance where the stock experienced a 'Volatility Squeeze'—defined 
            as Bollinger Band Width (upperBand - lowerBand) / ma20 dropping into its lowest 10th percentile 
            over the preceding 60 trading days—while RSI was under 45. 
            For each squeeze event, simulate entering a trade on the following day's open and exiting when either 
            RSI crosses above 65 OR after 15 trading days (whichever occurs first). 
            Calculate the total strategy win rate, average trade duration, 
            cumulative return, and the worst single trade's maximum underwater drawdown during its holding window."

Stock Ticker Agent

FastAPI-based stock analytics agent.

Hot Swappable Prompts for refining technical analysis

Deterministic Technical Snapshot for LLM context and Schema layer

Generated Code with streamed sandbox execution and research synthesis. Evaluation Harness in development

Stock Analytics Agent — Run Locally (Docker Desktop)

This app runs on your computer with Docker Desktop. You do not need to install Python, Node, or any other developer tools.

Time required: about 10 minutes the first time (mostly waiting for the image to build).
Requirements: a Mac or Windows PC with ~8 GB RAM and a stable internet connection.

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What you will need

1. Docker Desktop

   • Mac: https://docs.docker.com/desktop/setup/install/mac-install/
   • Windows: https://docs.docker.com/desktop/setup/install/windows-install/

2. A Groq API key (free tier is enough for demos)

   • Sign up: https://console.groq.com/
   • Create an API key and copy it.

3. This project folder (unzipped), including:

   • Dockerfile
   • docker-compose.yml
   • fused_database5.db
   • application code and index_llm.html

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Step-by-step setup

1. Install and start Docker Desktop

1. Download and install Docker Desktop for your OS (links above).
2. Open Docker Desktop and wait until it says it is running.
3. On Windows, if asked, allow the WSL 2 backend / restart when prompted.

You do not need to change any Docker settings for this app.

2. Add your API key

1. Open the project folder in Finder (Mac) or File Explorer (Windows).

2. Create a new plain-text file named exactly:

   .env

3. Put this single line inside the file .env (paste your real key): GROQ_API_KEY=your_key_here

4. Open the terminal or powershell in the same directory and use the following docker command: docker compose up --build

   First run downloads base images and Python packages (can take 10–15+ minutes). When it is ready, look for a line similar to: Uvicorn running on http://0.0.0.0:8000

    Leave this terminal window open while you use the app.
   

5. Open the app in your browser Go to: http://localhost:8000

    IN THE AGENT SANDBOX YOU CAN ASK NL QUESTIONS SUCH AS:
   
    - Calculate the 30-day rolling annualized volatility of daily returns and plot the rolling volatility trend line for the given ticker.
   
   
    - What is the latest RSI and MA structure for the given ticker?