Help
Browse files
README.md
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@@ -11,3 +11,298 @@ short_description: Recommends users which Repos/Spaces to look at
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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# π HF Repo Analyzer
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An AI-powered Hugging Face repository discovery and analysis tool that helps you find, evaluate, and explore the best repositories for your specific needs.
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## β¨ Features
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- π€ **AI Assistant**: Intelligent conversation-based repository discovery
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- π **Smart Search**: Auto-detection of repository IDs vs. keywords
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- π **Automated Analysis**: LLM-powered repository evaluation and ranking
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- π **Top 3 Selection**: AI-curated most relevant repositories
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- π¬ **Repository Explorer**: Interactive chat with repository contents
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- π― **Requirements Extraction**: Automatic keyword extraction from conversations
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- π **Comprehensive Results**: Detailed analysis with strengths, weaknesses, and specialities
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## π¦ Quick Start
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### Prerequisites
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- Python 3.8+
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- OpenAI API key (for LLM analysis)
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- Hugging Face access (for repository downloads)
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### Installation
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1. **Clone the repository**
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```bash
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git clone <repository-url>
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cd Agentic_HF_Analyzer
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```
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2. **Install dependencies**
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```bash
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pip install -r requirements.txt
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```
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3. **Set up environment variables**
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```bash
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export modal_api="your_openai_api_key"
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export base_url="your_openai_base_url"
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```
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4. **Run the application**
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```bash
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python app.py
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```
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5. **Open your browser** to `http://localhost:7860`
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## π User Guide
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### π€ Using the AI Assistant (Recommended)
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1. **Start a Conversation**
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- Navigate to the "π€ AI Assistant" tab
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- Describe your project: "I'm building a chatbot for customer service"
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- The AI will ask clarifying questions about your needs
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2. **Automatic Discovery**
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- When the AI has enough information, it will automatically:
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- Extract relevant keywords from your conversation
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- Search for matching repositories
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- Analyze and rank them by relevance
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3. **Review Results**
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- The interface automatically switches to "π¬ Analysis & Results"
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- View the top 3 most relevant repositories
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- Browse all analyzed repositories with detailed insights
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### π Using Smart Search (Direct Input)
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1. **Repository IDs**
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```
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microsoft/DialoGPT-medium
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openai/whisper
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huggingface/transformers
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```
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2. **Keywords**
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```
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text generation
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image classification
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sentiment analysis
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```
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3. **Mixed Input**
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- The system automatically detects the input type
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- Repository IDs (containing `/`) are processed directly
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- Keywords trigger automatic repository search
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### π¬ Analyzing Results
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- **Top 3 Repositories**: AI-selected most relevant based on your requirements
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- **Detailed Analysis**: Strengths, weaknesses, specialities, and relevance ratings
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- **Quick Actions**: Click repository names to visit or explore them
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- **Repository Explorer**: Deep dive into individual repositories with AI chat
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### π Repository Explorer
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1. **Access Methods**:
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- Click "π Open in Repo Explorer" from repository actions
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- Manually enter repository ID in the Repo Explorer tab
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2. **Features**:
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- Automatic repository loading and analysis
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- Interactive chat about repository contents
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- File structure exploration
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- Code analysis and explanations
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## π οΈ Technical Architecture
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### Core Components
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```
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app.py # Main Gradio interface and orchestration
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βββ analyzer.py # Repository analysis and LLM processing
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βββ hf_utils.py # Hugging Face API interactions
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βββ chatbot_page.py # AI assistant conversation logic
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βββ repo_explorer.py # Repository exploration interface
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```
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### Key Features Implementation
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#### π€ AI Assistant
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- **System Prompt**: Focused on requirements gathering, not recommendations
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- **Auto-Extraction**: Detects conversation readiness for keyword extraction
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- **Smart Processing**: Converts natural language to actionable search queries
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#### π Smart Input Detection
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```python
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def is_repo_id_format(text: str) -> bool:
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# Detects if input contains repository IDs (with /) vs keywords
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lines = [line.strip() for line in re.split(r'[\n,]+', text) if line.strip()]
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slash_count = sum(1 for line in lines if '/' in line)
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return slash_count >= len(lines) * 0.5
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```
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#### π LLM-Powered Repository Ranking
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- **Model**: `Orion-zhen/Qwen2.5-Coder-7B-Instruct-AWQ`
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- **Criteria**: Requirements matching, strengths, relevance rating, speciality alignment
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- **Output**: JSON-formatted repository rankings
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#### π Analysis Pipeline
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1. **Download**: Repository files (`.py`, `.md`, `.txt`)
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2. **Combine**: Merge files into single analyzable document
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3. **Analyze**: LLM evaluation for strengths, weaknesses, specialities
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4. **Rank**: User requirement-based relevance scoring
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5. **Select**: Top 3 most relevant repositories
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### Data Flow
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```mermaid
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graph TD
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A[User Input] --> B{Input Type?}
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B -->|Keywords| C[Repository Search]
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B -->|Repo IDs| D[Direct Processing]
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C --> E[Repository List]
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D --> E
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E --> F[Download & Analyze]
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F --> G[LLM Evaluation]
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G --> H[Ranking & Selection]
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H --> I[Results Display]
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I --> J[Repository Explorer]
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```
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### File Structure
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```
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π¦ Agentic_HF_Analyzer/
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βββ π app.py # Main application
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βββ π analyzer.py # Repository analysis logic
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βββ π hf_utils.py # Hugging Face utilities
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βββ π chatbot_page.py # AI assistant functionality
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βββ π repo_explorer.py # Repository exploration
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βββ π requirements.txt # Python dependencies
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βββ π README.md # Documentation
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βββ π repo_ids.csv # Analysis results storage
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βββ π repo_files/ # Temporary repository downloads
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```
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### Dependencies
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```
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gradio>=4.0.0 # Web interface framework
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pandas>=1.5.0 # Data manipulation
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regex>=2022.0.0 # Advanced regex operations
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openai>=1.0.0 # LLM API access
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huggingface_hub>=0.16.0 # HF repository access
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requests>=2.28.0 # HTTP requests
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```
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### Environment Variables
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| Variable | Description | Required |
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|----------|-------------|----------|
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| `modal_api` | OpenAI API key for LLM analysis | β
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| `base_url` | OpenAI API base URL | β
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### LLM Integration
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#### Analysis Prompt Structure
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```python
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ANALYSIS_PROMPT = """
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Analyze this repository and provide:
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1. Strengths and capabilities
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2. Potential weaknesses or limitations
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3. Primary speciality/use case
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4. Relevance rating for: {user_requirements}
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Return valid JSON with: strength, weaknesses, speciality, relevance rating
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"""
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```
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#### Repository Ranking System
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- **Input**: User requirements + repository analysis data
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- **Processing**: LLM evaluates relevance and ranks repositories
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- **Output**: Top 3 most relevant repositories in order
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### UI Components
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#### Modern Design Features
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- **Gradient Backgrounds**: Linear gradients for visual appeal
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- **Glassmorphism**: Backdrop blur effects for modern look
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- **Responsive Layout**: Adaptive to different screen sizes
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- **Interactive Elements**: Hover effects and smooth transitions
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- **Modal System**: Repository action selection popups
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#### Tab Organization
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1. **π€ AI Assistant**: Conversation-based discovery
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2. **π Smart Search**: Direct input processing
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3. **π¬ Analysis & Results**: Comprehensive analysis display
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4. **π Repo Explorer**: Interactive repository exploration
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### Advanced Features
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#### Auto-Navigation
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- Automatic tab switching based on workflow state
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- Smooth scrolling to top on tab changes
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- Progressive disclosure of information
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#### Error Handling
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- Graceful fallbacks for LLM failures
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- CSV update retry mechanisms
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- User-friendly error messages
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#### Performance Optimizations
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- Parallel processing for multiple repositories
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- Progress tracking for long operations
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- Efficient file caching and cleanup
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## π§ Configuration
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### Customizing Analysis
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- Modify `CHATBOT_SYSTEM_PROMPT` for different assistant behavior
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- Adjust repository search limits in `search_top_spaces()`
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- Configure analysis criteria in `get_top_relevant_repos()`
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### Adding File Types
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```python
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# In analyzer.py
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download_filtered_space_files(
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repo_id,
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local_dir="repo_files",
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file_extensions=['.py', '.md', '.txt', '.js', '.ts'] # Add more
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)
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```
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## π€ Contributing
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1. Fork the repository
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2. Create a feature branch
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3. Implement your changes
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4. Add tests if applicable
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5. Submit a pull request
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## π License
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This project is licensed under the MIT License - see the LICENSE file for details.
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## π Acknowledgments
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- **Gradio**: For the amazing web interface framework
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- **Hugging Face**: For the incredible repository ecosystem
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- **OpenAI**: For powerful language model capabilities
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---
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<div align="center">
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<p>Built with β€οΈ for the open source community</p>
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<p>π Happy repository hunting! π</p>
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</div>
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app.py
CHANGED
@@ -603,15 +603,161 @@ def create_ui() -> gr.Blocks:
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"""
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)
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# Global Reset
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with gr.Row():
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with gr.Column(scale=
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pass
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with gr.Column(scale=1):
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reset_all_btn = gr.Button("π Reset Everything", variant="stop", size="lg")
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with gr.Column(scale=1):
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pass
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615 |
with gr.Tabs() as tabs:
|
616 |
# --- AI Assistant Tab (moved to first) ---
|
617 |
with gr.TabItem("π€ AI Assistant", id="chatbot_tab"):
|
@@ -1374,6 +1520,17 @@ def create_ui() -> gr.Blocks:
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|
1374 |
outputs=[repo_ids_state, current_repo_idx_state, user_requirements_state, df_output, top_repos_df, top_repos_section, chatbot, status_box_input, current_requirements_display, extracted_keywords_output]
|
1375 |
)
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1376 |
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1377 |
return app
|
1378 |
|
1379 |
if __name__ == "__main__":
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|
603 |
"""
|
604 |
)
|
605 |
|
606 |
+
# Global Reset and Help Buttons - visible on all tabs
|
607 |
with gr.Row():
|
608 |
+
with gr.Column(scale=3):
|
609 |
pass
|
610 |
+
with gr.Column(scale=1):
|
611 |
+
help_btn = gr.Button("β Help", variant="secondary", size="lg")
|
612 |
with gr.Column(scale=1):
|
613 |
reset_all_btn = gr.Button("π Reset Everything", variant="stop", size="lg")
|
614 |
with gr.Column(scale=1):
|
615 |
pass
|
616 |
|
617 |
+
# Help Modal - visible when help button is clicked
|
618 |
+
with gr.Row():
|
619 |
+
with gr.Column():
|
620 |
+
help_modal = gr.Column(visible=False)
|
621 |
+
with help_modal:
|
622 |
+
gr.Markdown(
|
623 |
+
"""
|
624 |
+
<div style="background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); padding: 20px; border-radius: 16px; text-align: center; margin-bottom: 20px;">
|
625 |
+
<h2 style="color: white; margin: 0; font-size: 2rem;">π How to Use HF Repo Analyzer</h2>
|
626 |
+
<p style="color: rgba(255,255,255,0.9); margin: 10px 0 0 0;">Step-by-step guide to find and analyze repositories</p>
|
627 |
+
</div>
|
628 |
+
"""
|
629 |
+
)
|
630 |
+
|
631 |
+
with gr.Accordion("π Method 1: AI Assistant (Recommended)", open=True):
|
632 |
+
gr.Markdown(
|
633 |
+
"""
|
634 |
+
### **Step 1: Start Conversation**
|
635 |
+
- Go to the **π€ AI Assistant** tab
|
636 |
+
- Describe your project: *"I'm building a sentiment analysis tool"*
|
637 |
+
- The AI will ask clarifying questions about your needs
|
638 |
+
|
639 |
+
### **Step 2: Let AI Work Its Magic**
|
640 |
+
- Answer the AI's questions about your requirements
|
641 |
+
- When ready, the AI will automatically:
|
642 |
+
- Extract keywords from your conversation
|
643 |
+
- Search for matching repositories
|
644 |
+
- Analyze and rank them by relevance
|
645 |
+
|
646 |
+
### **Step 3: Review Results**
|
647 |
+
- Interface automatically switches to **π¬ Analysis & Results**
|
648 |
+
- View **Top 3** most relevant repositories
|
649 |
+
- Browse detailed analysis with strengths/weaknesses
|
650 |
+
- Click repository names to visit or explore them
|
651 |
+
|
652 |
+
**π‘ Tip**: This method gives the best personalized results!
|
653 |
+
"""
|
654 |
+
)
|
655 |
+
|
656 |
+
with gr.Accordion("π Method 2: Smart Search (Direct Input)", open=False):
|
657 |
+
gr.Markdown(
|
658 |
+
"""
|
659 |
+
### **Step 1: Choose Input Type**
|
660 |
+
Go to **π Smart Search** tab and enter either:
|
661 |
+
|
662 |
+
**Repository IDs** (with `/`):
|
663 |
+
```
|
664 |
+
microsoft/DialoGPT-medium
|
665 |
+
openai/whisper
|
666 |
+
huggingface/transformers
|
667 |
+
```
|
668 |
+
|
669 |
+
**Keywords** (no `/`):
|
670 |
+
```
|
671 |
+
text generation
|
672 |
+
image classification
|
673 |
+
sentiment analysis
|
674 |
+
```
|
675 |
+
|
676 |
+
### **Step 2: Auto-Detection & Processing**
|
677 |
+
- System automatically detects input type
|
678 |
+
- Repository IDs β Direct analysis
|
679 |
+
- Keywords β Search + analysis
|
680 |
+
- Enable **π Auto-analyze** for instant results
|
681 |
+
|
682 |
+
### **Step 3: Get Results**
|
683 |
+
- Click **π Find & Process Repositories**
|
684 |
+
- View results in **π¬ Analysis & Results** tab
|
685 |
+
"""
|
686 |
+
)
|
687 |
+
|
688 |
+
with gr.Accordion("π¬ Understanding Analysis Results", open=False):
|
689 |
+
gr.Markdown(
|
690 |
+
"""
|
691 |
+
### **π Top 3 Repositories**
|
692 |
+
- AI-selected most relevant for your needs
|
693 |
+
- Ranked by requirement matching and quality
|
694 |
+
|
695 |
+
### **π Detailed Analysis Table**
|
696 |
+
- **Repository**: Click names to visit/explore
|
697 |
+
- **Strengths**: Key capabilities and advantages
|
698 |
+
- **Weaknesses**: Limitations and considerations
|
699 |
+
- **Speciality**: Primary use case and domain
|
700 |
+
- **Relevance**: How well it matches your needs
|
701 |
+
|
702 |
+
### **π Quick Actions**
|
703 |
+
Click repository names to:
|
704 |
+
- **π Visit Hugging Face Space**: See live demo
|
705 |
+
- **π Open in Repo Explorer**: Deep dive analysis
|
706 |
+
"""
|
707 |
+
)
|
708 |
+
|
709 |
+
with gr.Accordion("π Repository Explorer Deep Dive", open=False):
|
710 |
+
gr.Markdown(
|
711 |
+
"""
|
712 |
+
### **Access Repository Explorer**
|
713 |
+
- Click **π Open in Repo Explorer** from results
|
714 |
+
- Or manually enter repo ID in **π Repo Explorer** tab
|
715 |
+
|
716 |
+
### **Features Available**
|
717 |
+
- **Auto-loading**: Repository content analysis
|
718 |
+
- **AI Chat**: Ask questions about the code
|
719 |
+
- **File Exploration**: Browse repository structure
|
720 |
+
- **Code Analysis**: Get explanations and insights
|
721 |
+
|
722 |
+
### **Sample Questions to Ask**
|
723 |
+
- *"How do I use this repository?"*
|
724 |
+
- *"What are the main functions?"*
|
725 |
+
- *"Show me example usage"*
|
726 |
+
- *"Explain the architecture"*
|
727 |
+
"""
|
728 |
+
)
|
729 |
+
|
730 |
+
with gr.Accordion("π― Pro Tips & Best Practices", open=False):
|
731 |
+
gr.Markdown(
|
732 |
+
"""
|
733 |
+
### **π€ Getting Better AI Results**
|
734 |
+
- Be specific about your use case
|
735 |
+
- Mention programming language preferences
|
736 |
+
- Describe your experience level
|
737 |
+
- Include performance requirements
|
738 |
+
|
739 |
+
### **π Search Optimization**
|
740 |
+
- Use multiple relevant keywords
|
741 |
+
- Try different keyword combinations
|
742 |
+
- Check both general and specific terms
|
743 |
+
|
744 |
+
### **π Analyzing Results**
|
745 |
+
- Read both strengths AND weaknesses
|
746 |
+
- Check speciality alignment with your needs
|
747 |
+
- Use Repository Explorer for detailed investigation
|
748 |
+
- Compare multiple options before deciding
|
749 |
+
|
750 |
+
### **π Workflow Tips**
|
751 |
+
- Start with AI Assistant for personalized results
|
752 |
+
- Use Smart Search for known repositories
|
753 |
+
- Explore multiple repositories before choosing
|
754 |
+
- Save interesting repositories for later comparison
|
755 |
+
"""
|
756 |
+
)
|
757 |
+
|
758 |
+
with gr.Row():
|
759 |
+
close_help_btn = gr.Button("β
Got It, Let's Start!", variant="primary", size="lg")
|
760 |
+
|
761 |
with gr.Tabs() as tabs:
|
762 |
# --- AI Assistant Tab (moved to first) ---
|
763 |
with gr.TabItem("π€ AI Assistant", id="chatbot_tab"):
|
|
|
1520 |
outputs=[repo_ids_state, current_repo_idx_state, user_requirements_state, df_output, top_repos_df, top_repos_section, chatbot, status_box_input, current_requirements_display, extracted_keywords_output]
|
1521 |
)
|
1522 |
|
1523 |
+
# Help modal events
|
1524 |
+
help_btn.click(
|
1525 |
+
fn=lambda: gr.update(visible=True),
|
1526 |
+
outputs=[help_modal]
|
1527 |
+
)
|
1528 |
+
|
1529 |
+
close_help_btn.click(
|
1530 |
+
fn=lambda: gr.update(visible=False),
|
1531 |
+
outputs=[help_modal]
|
1532 |
+
)
|
1533 |
+
|
1534 |
return app
|
1535 |
|
1536 |
if __name__ == "__main__":
|