update README

README.md

@@ -1,156 +1,9 @@
-# Web Research and Report Generation System
+---
+title: Analyst
+emoji: ⚡
+colorFrom: pink
+colorTo: blue
+sdk: static
+pinned: false
+---
 
-An advanced AI-powered system for automated web research and report generation. This system uses AI agents to search, analyze, and compile comprehensive reports on any given topic.
-
-## Features
-
-- **Intelligent Web Search**
-  - Multi-source search using DuckDuckGo and Google
-  - Smart retry mechanism with rate limit handling
-  - Configurable search depth and result limits
-  - Domain filtering for trusted sources
-
-- **Advanced Report Generation**
-  - Beautiful HTML reports with modern styling
-  - Automatic keyword extraction
-  - Source validation and relevance scoring
-  - Comprehensive logging of research process
-
-- **Smart Caching**
-  - Caches search results for faster repeat queries
-  - Configurable cache directory
-  - Cache invalidation management
-
-- **Error Handling**
-  - Graceful fallback between search engines
-  - Rate limit detection and backoff
-  - Detailed error logging
-  - Automatic retry mechanisms
-
-## Installation
-
-1. Clone the repository:
-```bash
-git clone [repository-url]
-cd phidata_analyst
-```
-
-2. Install dependencies:
-```bash
-pip install -r requirements.txt
-```
-
-3. Set up your API keys:
-   - Create a `.env` file in the project root
-   - Add your API keys:
-     ```
-     NVIDIA_API_KEY=your-nvidia-api-key
-     GOOGLE_API_KEY=your-google-api-key
-     ```
-
-## Usage
-
-### Basic Usage
-
-```python
-from web_search import create_blog_post_workflow
-
-# Create a workflow instance
-workflow = create_blog_post_workflow()
-
-# Generate a report
-for response in workflow.run("Your research topic"):
-    print(response.message)
-```
-
-### Advanced Usage
-
-```python
-from web_search import BlogPostGenerator, SqlWorkflowStorage
-from phi.llm import Nvidia
-from phi.tools import DuckDuckGo, GoogleSearch
-
-# Configure custom agents
-searcher = Agent(
-    model=Nvidia(
-        id="meta/llama-3.2-3b-instruct",
-        temperature=0.3,
-        top_p=0.1
-    ),
-    tools=[DuckDuckGo(fixed_max_results=10)]
-)
-
-# Initialize with custom configuration
-generator = BlogPostGenerator(
-    searcher=searcher,
-    storage=SqlWorkflowStorage(
-        table_name="custom_workflows",
-        db_file="path/to/db.sqlite"
-    )
-)
-
-# Run with caching enabled
-for response in generator.run("topic", use_cache=True):
-    print(response.message)
-```
-
-## Output
-
-The system generates:
-1. Professional HTML reports with:
-   - Executive summary
-   - Detailed analysis
-   - Source citations
-   - Generation timestamp
-2. Detailed logs of:
-   - Search process
-   - Keyword extraction
-   - Source relevance
-   - Download attempts
-
-Reports are saved in:
-- Default: `./reports/YYYY-MM-DD-HH-MM-SS/`
-- Custom: Configurable via `file_handler`
-
-## Configuration
-
-Key configuration options:
-
-```python
-DUCK_DUCK_GO_FIXED_MAX_RESULTS = 10  # Max results from DuckDuckGo
-DEFAULT_TEMPERATURE = 0.3             # Model temperature
-TOP_P = 0.1                          # Top-p sampling parameter
-```
-
-Trusted domains can be configured in `BlogPostGenerator.trusted_domains`.
-
-## Logging
-
-The system uses `phi.utils.log` for comprehensive logging:
-- Search progress and results
-- Keyword extraction details
-- File downloads and failures
-- Report generation status
-
-Logs are color-coded for easy monitoring:
-- INFO: Normal operations
-- WARNING: Non-critical issues
-- ERROR: Critical failures
-
-## Contributing
-
-1. Fork the repository
-2. Create your feature branch (`git checkout -b feature/amazing-feature`)
-3. Commit your changes (`git commit -m 'Add amazing feature'`)
-4. Push to the branch (`git push origin feature/amazing-feature`)
-5. Open a Pull Request
-
-## License
-
-This project is licensed under the MIT License - see the LICENSE file for details.
-
-## Acknowledgments
-
-- Built with [Phi](https://github.com/phidatahq/phidata)
-- Uses NVIDIA AI models
-- Search powered by DuckDuckGo and Google