{"id":20683370,"url":"https://github.com/muhammadadilnaeem/rag-query-application","last_synced_at":"2026-05-18T19:43:51.052Z","repository":{"id":248406375,"uuid":"828599950","full_name":"muhammadadilnaeem/RAG-Query-Application","owner":"muhammadadilnaeem","description":"This project is a Flask web application that allows users to ask questions and get answers using a Retrieval-Augmented Generation (RAG) model. Users input their questions, and the application returns relevant answers based on the indexed documents.","archived":false,"fork":false,"pushed_at":"2024-07-14T16:34:28.000Z","size":484,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-06-08T17:02:37.715Z","etag":null,"topics":["flask","llama-index","openai-api","python3","simpledirectoryreader","storagecontext","vectorstoreindex"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/muhammadadilnaeem.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-07-14T16:24:25.000Z","updated_at":"2025-03-25T17:23:41.000Z","dependencies_parsed_at":"2024-07-14T18:07:51.512Z","dependency_job_id":"220c54ae-9ccb-4a36-8841-3a8fc47a7058","html_url":"https://github.com/muhammadadilnaeem/RAG-Query-Application","commit_stats":null,"previous_names":["muhammadadilnaeem/rag-query-application"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/muhammadadilnaeem/RAG-Query-Application","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/muhammadadilnaeem%2FRAG-Query-Application","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/muhammadadilnaeem%2FRAG-Query-Application/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/muhammadadilnaeem%2FRAG-Query-Application/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/muhammadadilnaeem%2FRAG-Query-Application/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/muhammadadilnaeem","download_url":"https://codeload.github.com/muhammadadilnaeem/RAG-Query-Application/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/muhammadadilnaeem%2FRAG-Query-Application/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":270330595,"owners_count":24565816,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-08-13T02:00:09.904Z","response_time":66,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["flask","llama-index","openai-api","python3","simpledirectoryreader","storagecontext","vectorstoreindex"],"created_at":"2024-11-16T22:16:24.970Z","updated_at":"2026-05-18T19:43:46.020Z","avatar_url":"https://github.com/muhammadadilnaeem.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# **Query Application Documentation**\n\n## **Introduction**\nThe Query Application allows users to input questions and receive answers based on the data provided. The application utilizes a RAG (Retrieval-Augmented Generation) model to process the questions and generate responses. Users interact with the application through a web interface designed with a focus on professional and user-friendly UX/UI design, including hover effects and bold fonts for emphasis.\n\n## **Features**\n- User-friendly web interface for querying.\n- Processes questions using a RAG model.\n- Displays answers in a bold and clear format.\n- Enhanced user experience with hover effects.\n\n## **How to Use the App**\n\nhttps://github.com/user-attachments/assets/358a88e4-fa38-4319-86ff-c4f66033833f\n\n### **Home Page**\n#### **Enter a Question**\n1. **Input Field**: Users can type their question into the input field labeled \"Enter your question\".\n2. **Submit Button**: Once a question is entered, users click the \"Ask\" button to submit their query.\n\n### **Displaying the Response**\n- **Answer Display**: After submitting a question, the response from the RAG model is displayed on the same page in a highlighted format.\n- **Real-time Processing**: The application processes the question in real-time and updates the answer dynamically.\n\n## **Code Structure**\n### **Flask Application Setup**\n1. **Import Libraries**: The application imports necessary libraries including Flask and the RAG model components.\n2. **Initialize Flask**: A Flask application is created and configured.\n\n### **HTML Template**\n- **Form for Input**: The HTML template includes a form with an input field for questions and a submit button.\n- **Response Display**: The response section dynamically shows the answer after the form is submitted.\n\n### **CSS Styling**\n- **Responsive Design**: The CSS ensures the application is responsive and visually appealing.\n- **Hover Effects**: Buttons and interactive elements have hover effects for better UX.\n- **Bold Fonts**: Answers are displayed in bold fonts to make them stand out.\n\n## **Example Usage**\n\n### **Entering a Question**\n1. **Open the Application**: Navigate to the home page of the Query Application.\n2. **Type a Question**: In the input field, type a question like \"List down names of all candidates?\".\n3. **Submit**: Click the \"Ask\" button to submit your question.\n\n### **Viewing the Response**\n- **Response Section**: The answer to your question will be displayed below the input field in a bold and clear format.\n\n## **Conclusion**\nThis documentation provides a comprehensive overview of the Query Application. Users can enter questions, receive answers, and enjoy a professional and engaging user experience. The application leverages a RAG model for processing queries and provides real-time responses with enhanced UX/UI features.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmuhammadadilnaeem%2Frag-query-application","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmuhammadadilnaeem%2Frag-query-application","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmuhammadadilnaeem%2Frag-query-application/lists"}