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Using vector search and language models, it provides information about:\n\n- Academic programs and courses\n- Campus facilities and navigation\n- Student life and experiences\n- Career guidance and opportunities\n\n## System Architecture\n\n### Core Components\n\n```\n[Streamlit Frontend] \u003c-\u003e [Chat Interface] \u003c-\u003e [Vector Search] \u003c-\u003e [Qdrant]\n                                        |\n                                  [Groq LLM API]\n```\n\n### Technology Stack\n\n- Frontend: Streamlit\n- Vector Database: Qdrant\n- Embeddings: SentenceTransformer (all-MiniLM-L6-v2)\n- LLM: Groq API\n- Environment: Poetry, Nix\n\n## Data Sources\n\n### Academic Information\n\n1. Course Catalog\n   - Scraped course details\n   - Course codes and names\n   - Credit information\n   - Prerequisites\n   - Course descriptions\n\n2. BSP Academic Resources\n   - Course experiences\n   - Study materials\n   - Academic guidance\n   - Student testimonials\n   - Intern Fundae\n\n### Inception Magazine Content\n\nThe freshers' magazine \"Inception\" provides:\n- Campus facility descriptions\n- Hostel information\n- Navigation guides\n- First-year experiences\n- Essential campus knowledge\n\n### Dalle United Magazine Content\n\nBSP's \"Dalle United\" magazine contributes:\n- Student interviews\n- Campus life stories\n- Cultural coverage\n\n## Vector Store Implementation\n\n### Data Processing\n\n1. Text Preprocessing\n   - Cleaning and formatting\n   - Context preservation\n   - Campus terminology handling\n\n2. Vector Generation\n   - Text-to-vector conversion\n   - Semantic embedding creation\n   - Context maintenance\n\n3. Collection Structure\n   - Organized by source type\n   - Optimized for retrieval\n   - Contextual relationships preserved\n\n## Development Setup\n\n### Environment Configuration\n\n```bash\n# Initialize development environment\nnix develop\npoetry install\n\n# Start application\npoetry run streamlit run app.py\n```\n\n### Project Structure\n\n```\npegasus/\n├── LICENSE\n├── README.md\n├── app/app.py\n├── final_courses.json\n├── flake.lock\n├── flake.nix\n├── poetry.lock\n├── pyproject.toml\n└── scripts/ (all the misc scripts)\n```\n\n## Query Processing\n\n### Search Flow\n\n1. Query Analysis\n   - Intent recognition\n   - Context identification\n   - Source prioritization\n\n2. Response Generation\n   - Context-aware answers\n   - Source combination\n   - Natural language output\n   - Session aware\n\n## Planned Enhancements\n\n### Near-term\n\n1. Content Updates\n   - Regular magazine updates\n   - New course information\n   - Fresh student experiences\n   - Add departmental data\n\n2. Search Features\n   - Better context handling\n   - Multi-topic queries\n   - Chat history\n\n### Long-term\n\n1. User Experience\n   - Mobile interface\n   - Response speed\n   - Better error handling\n   - Streaming the text generated for a fluid exp\n\n2. Data Coverage\n   - More student resources\n   - Additional magazines\n   - Updated course content\n\n## Contributing\n\nTo contribute:\n1. Fork the repository\n2. Create a feature branch\n3. Make changes with documentation\n4. Submit a pull request\n\n## License\n\nMIT License. See LICENSE file.\n\n---\n\n*For detailed implementation information, refer to the scripts/ directory and development notebooks.*\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2F0oastro%2Fpegasus","html_url":"https://awesome.ecosyste.ms/projects/github.com%2F0oastro%2Fpegasus","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2F0oastro%2Fpegasus/lists"}