Update README.md

README.md

@@ -1,44 +1,52 @@
-# AI-Powered Async Web Scraper
-
-A professional, high-concurrency web scraping pipeline that extracts clean text from URLs, processes it through an LLM (Groq), and stores the structured results in both JSONL and PostgreSQL.
-
-##  Quick Start (Docker)
-
-The easiest way to run the entire stack is using Docker Compose:
-
-1.  **Configure Environment**:
-    Create a `.env` file in the `Backend` directory with your Groq API Key:
-    ```bash
-    GROQ_API_KEY=your_key_here
-    DB_PASSWORD=your_db_password
-    ```
-
-2.  **Launch**:
-    ```bash
-    docker-compose up -d
-    ```
-
-3.  **Access**:
-    - **Frontend**: [http://localhost](http://localhost)
-    - **Backend API**: [http://localhost:8000](http://localhost:8000)
-
-## Architecture
-
-- **Frontend**: A modern dashboard built with **Vite** and **TypeScript** for real-time job monitoring and result downloads.
-- **Backend**: A high-performance **FastAPI** service managing an asynchronous scraping pipeline.
-- **Database**: **PostgreSQL** for persistent storage of parsed text and structured AI extractions.
-- **Scraper**: Uses `curl_cffi` for advanced request impersonation to bypass bot detection.
-- **Parser**: Leverages `trafilatura` for high-quality main-content extraction.
-- **Extraction**: Integrates with **Groq** for lightning-fast LLM-based data structuring.
-
-
-##  Project Structure
-
-- `Backend/`: FastAPI application, database models, and scraper logic.
-- `Frontend/`: Vite/TS dashboard for job status tracking and results visualization.
-- `docker-compose.yml`: Orchestration for the frontend, backend, and persistence layers.
-
----
-For detailed setup and development instructions, see the individual component's documentation:
-- [Backend Documentation](./Backend/README.md)
-- [Frontend Documentation](./Frontend/README.md)
+---
+license: mit
+title: Async Web Scraper
+sdk: docker
+emoji: 🦀
+colorFrom: pink
+colorTo: pink
+---
+# AI-Powered Async Web Scraper
+
+A professional, high-concurrency web scraping pipeline that extracts clean text from URLs, processes it through an LLM (Groq), and stores the structured results in both JSONL and PostgreSQL.
+
+##  Quick Start (Docker)
+
+The easiest way to run the entire stack is using Docker Compose:
+
+1.  **Configure Environment**:
+    Create a `.env` file in the `Backend` directory with your Groq API Key:
+    ```bash
+    GROQ_API_KEY=your_key_here
+    DB_PASSWORD=your_db_password
+    ```
+
+2.  **Launch**:
+    ```bash
+    docker-compose up -d
+    ```
+
+3.  **Access**:
+    - **Frontend**: [http://localhost](http://localhost)
+    - **Backend API**: [http://localhost:8000](http://localhost:8000)
+
+## Architecture
+
+- **Frontend**: A modern dashboard built with **Vite** and **TypeScript** for real-time job monitoring and result downloads.
+- **Backend**: A high-performance **FastAPI** service managing an asynchronous scraping pipeline.
+- **Database**: **PostgreSQL** for persistent storage of parsed text and structured AI extractions.
+- **Scraper**: Uses `curl_cffi` for advanced request impersonation to bypass bot detection.
+- **Parser**: Leverages `trafilatura` for high-quality main-content extraction.
+- **Extraction**: Integrates with **Groq** for lightning-fast LLM-based data structuring.
+
+
+##  Project Structure
+
+- `Backend/`: FastAPI application, database models, and scraper logic.
+- `Frontend/`: Vite/TS dashboard for job status tracking and results visualization.
+- `docker-compose.yml`: Orchestration for the frontend, backend, and persistence layers.
+
+---
+For detailed setup and development instructions, see the individual component's documentation:
+- [Backend Documentation](./Backend/README.md)
+- [Frontend Documentation](./Frontend/README.md)