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-description = """"""
+description = """
+**DB Assistant** is an interactive **AI-powered SQL agent** built with **Gradio** and **LangChain**.  
+It enables users to connect to any relational database, ask natural language questions, and receive data-driven answers in real time — no manual SQL writing required.
+
+---
+
+#### 🚀 Key Features
+
+- **Natural Language to SQL Conversion**  
+  Ask questions like _“Which genre has the longest tracks?”_ or _“List the top 5 customers by purchase amount.”_  
+  The assistant automatically generates and executes optimized SQL queries against your connected database.
+
+- **Live SQL Agent Streaming**  
+  The model’s reasoning, query generation, and intermediate steps are streamed to the interface, allowing you to see exactly how the LLM builds and refines its queries.
+
+- **Collapsible Debug Panels (AI & Tool Messages)**  
+  Intermediate tool calls and SQL executions are neatly displayed in collapsible **accordions**, making the output transparent yet organized.
+
+- **Multi-Provider LLM Support**  
+  Choose from a variety of providers:
+  - 🧠 **Google GenAI** (Gemini 2.x)
+  - 💬 **OpenAI** (GPT-4, GPT-4o, GPT-3.5)
+  - 🦣 **Anthropic** (Claude-3 series)
+  - ☁️ **Azure OpenAI**, **AWS Bedrock**, **xAI**, **DeepSeek**, **Perplexity**, and more.  
+  The interface automatically updates the available model list based on your provider choice.
+
+- **Secure Database Connectivity**  
+  Connect to SQL databases via a simple connection string — supporting **SQLite**, **PostgreSQL**, **MySQL**, and others through LangChain’s `SQLDatabase` utility.
+
+- **Transparent Query Execution**  
+  The agent inspects tables, analyzes schemas, and constructs precise SQL queries, always respecting safety rules (no DML statements like INSERT, UPDATE, DELETE, DROP).
+
+- **Intuitive Gradio Interface**  
+  Built with `gr.Blocks()` for clean layout:
+  - **Left Panel:** LLM setup and database connection  
+  - **Right Panel:** Interactive chatbot and conversation history  
+  - **Expandable sections** for metadata and project credits
+
+---
+
+#### ⚙️ Tech Stack Overview
+
+| Component | Purpose |
+|------------|----------|
+| **LangChain** | Framework for connecting LLMs with external data tools |
+| **SQLDatabaseToolkit** | Provides database inspection, schema parsing, and safe query execution |
+| **Gradio** | Creates a user-friendly web UI for chatting with the agent |
+| **Python** | Core application logic and integration |
+| **Markdown + HTML** | Enhanced output formatting with collapsible accordions |
+| **Base64 Encoding** | Used to embed custom logo images directly in the interface |
+
+---
+
+#### 🧩 How It Works
+
+1. **Setup LLM**  
+   Select your preferred provider and model, enter the corresponding API key, and click **Setup LLM**.
+
+2. **Connect Database**  
+   Paste your SQL connection string (e.g., `sqlite:///Chinook.db` or `postgresql+psycopg2://user:pass@host/db`) and click **Connect**.  
+   The app automatically lists available tables.
+
+3. **Ask Questions**  
+   Type a natural language question in the chat box — the agent:
+   - Retrieves the database schema,
+   - Generates SQL queries,
+   - Executes them safely,
+   - Returns a human-readable explanation and result summary.
+
+4. **Inspect Reasoning**  
+   Expand the *AI Message* or *Tool Message* accordions to see exactly what the model did under the hood (SQL statements, schema checks, etc.).
+
+---
+
+#### 🧠 Example Interaction
+
+**User:**  
+> Which genre on average has the longest tracks?
+
+**AI Assistant:**  
+- 📊 Generates a SQL query joining `Track` and `Genre` tables  
+- 🧩 Computes average `Milliseconds` per genre  
+- 🧠 Returns:
+
+> On average, the genre with the longest tracks is **"Sci-Fi & Fantasy"**,  
+> followed by **"Science Fiction"**, **"Drama"**, and **"TV Shows"**.
+
+---
+
+#### 🧑‍💻 Ideal Use Cases
+
+- Data analysts and engineers exploring new databases  
+- BI professionals needing quick insights without SQL writing  
+- Educators demonstrating database–AI integration  
+- Developers testing and debugging database schemas via conversational interface
+
+---
+
+#### 🪄 Future Enhancements
+
+- ✅ Add visualizations (bar charts, pie charts) for query results  
+- ✅ Support multiple database sessions  
+- ✅ Enable query caching and history tracking  
+- ✅ Integrate authentication for enterprise deployments  
+
+---
+
+#### 💡 Credits
+
+Developed using:
+- **LangChain Community Modules**
+- **Gradio UI Framework**
+- **Python 3.12+**
+
+This project bridges the gap between **conversational AI** and **structured data analytics**, giving everyone a personal **SQL-powered data assistant** at their fingertips. 🤖💾
+
+---
+
+"""
 
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