TradingView AI Dashboard

A Streamlit-based dashboard for visualizing TSLA stock data and querying it through an AI chatbot powered by the Gemini API.

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🚀 Features (and tech used)

• 📈 Interactive charts showing TSLA price trends, support, and resistance levels (using a streamlit wrapper of TradingView's LightWeight Charts)
• 🤖 Gemini-powered AI chatbot to answer natural language questions about the data (using Google's Gemini 2.0 flash model)
• 💾 Efficient data loading and preprocessing using caching (using Pandas, NumPy)
• 🧪 Built as a personal project for experimentation with finance and AI

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💬 Example Questions

You can ask the chatbot questions like:

• How many days in 2023 was TSLA bullish?
• What was the longest bullish streak this year?
• How often did TSLA touch a resistance level in Q1?
• When was the last time TSLA switched from SHORT to LONG?
• What are the typical support levels in June?
• What is the average price of TSLA in 2023?
• Plot the TSLA price chart for the First Quarter of 2023.
• Show the number of bullish versus bearish days in Jan 2024.

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📸 Screenshots

Chart Dashboard

AI Chatbot Interface

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🛠 Getting Started

1. Clone the repository:

   git clone https://github.com/your-username/tradingview-ai-dashboard.git
   cd tradingview-ai-dashboard

2. Install dependencies:

   pip install -r requirements.txt

3. Set up your Gemini API key Create a file at .streamlit/secrets.toml and add the following:

   [gemini]
   api_key = "your_api_key_here"
   demo_mode = "false"

   Set demo_mode = "true" if you want to disable live calls and test the UI, and make sure to replace your_api_key_here with your actual Gemini API key.

4. Run the Streamlit app:

   streamlit run streamlit_app.py

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⚠️ Notes

• This is a personal project and not production-ready.
• The Gemini API is used for natural language processing and may incur costs based on usage.
• Only supports a static TSLA dataset (upto 2nd May, 2025) currently, but can be extended to other stocks with some modifications.
• Future improvements could include more advanced analytics, real-time stock data, and context history for the chatbot.