{"id":23108201,"url":"https://github.com/jeevanbabu7/eduarc-client","last_synced_at":"2026-06-25T08:31:38.896Z","repository":{"id":268342697,"uuid":"904020093","full_name":"jeevanbabu7/EduArc-client","owner":"jeevanbabu7","description":null,"archived":false,"fork":false,"pushed_at":"2025-04-03T19:31:55.000Z","size":5991,"stargazers_count":0,"open_issues_count":2,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-03T20:31:26.467Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"JavaScript","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/jeevanbabu7.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":"2024-12-16T05:14:13.000Z","updated_at":"2025-04-03T19:31:58.000Z","dependencies_parsed_at":null,"dependency_job_id":"862cf157-6123-45fe-8e96-4a7f82cb78ab","html_url":"https://github.com/jeevanbabu7/EduArc-client","commit_stats":null,"previous_names":["jeevanbabu7/eduarc-client"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/jeevanbabu7/EduArc-client","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jeevanbabu7%2FEduArc-client","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jeevanbabu7%2FEduArc-client/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jeevanbabu7%2FEduArc-client/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jeevanbabu7%2FEduArc-client/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/jeevanbabu7","download_url":"https://codeload.github.com/jeevanbabu7/EduArc-client/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jeevanbabu7%2FEduArc-client/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":34767542,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-06-25T02:00:05.521Z","response_time":101,"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":[],"created_at":"2024-12-17T01:17:50.875Z","updated_at":"2026-06-25T08:31:38.881Z","avatar_url":"https://github.com/jeevanbabu7.png","language":"JavaScript","funding_links":[],"categories":[],"sub_categories":[],"readme":"# EduArc : AI-Powered Learning and Assessment Tool\nA comprehensive app that combines learning aids and performance assessment tools into a unified educational ecosystem built with React Native. Designed to support students in personalized learning, the app offers features such as intelligent text summarization, automated flashcard and quiz generation, a live chatbot for real-time academic assistance, and predictive analytics to highlight key exam topics — providing a holistic and adaptive solution to enhance retention, comprehension, and performance in academic settings.\n\n## Features\n- Summarize lengthy study materials into short, easy-to-understand notes.\n- Generate flashcards automatically from uploaded notes or text.\n- Create quizzes from documents to reinforce learning.\n- Use a live AI chatbot to clear doubts in real time.\n- Predict high-weightage topics using past exam data.\n- Suggest additional resources to aid learning.\n\n## Tech Stack\n- **Frontend :** React Native\n- **Backend :** Express.js, Flask\n- **AI/ML Components :** Llama 3.1, Command-R\n- **Database and Storage :** MongoDB, Chroma\n- **Frameworks :** Unsloth\n- **Other tools :** Appwrite, FFmpeg, LangChain, Firebase, Whisper, Google Colab\n\n## Architecture\n\u003cdiv align=\"center\"\u003e\n\u003ctable border=\"0\"\u003e\n  \u003ctr\u003e\n    \u003ctd align=\"center\"\u003e\n      \u003cimg src=\"assets/img_readme/system_arcitecture.png\" width=\"400\"/\u003e\u003cbr/\u003e\n      \u003cem\u003eSystem Architecture\u003c/em\u003e \u0026nbsp;\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n      \u003cimg src=\"assets/img_readme/detailed_architecture.png\" width=\"400\"/\u003e\u003cbr/\u003e\n      \u003cem\u003eDetailed Architecture\u003c/em\u003e\n    \u003c/td\u003e\n  \u003c/tr\u003e\n  \u003ctr\u003e\n    \u003ctd align=\"center\"\u003e\n      \u003cimg src=\"assets/img_readme/rag_architecture.jpg\" width=\"400\"/\u003e\u003cbr/\u003e\n      \u003cem\u003eRAG Architecture\u003c/em\u003e\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n      \u003cimg src=\"assets/img_readme/dataflow.png\" width=\"400\"/\u003e\u003cbr/\u003e\n      \u003cem\u003eDataflow\u003c/em\u003e\n    \u003c/td\u003e\n  \u003c/tr\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\n\n\n## 📦 Installation \u0026 Setup\n\n### Prerequisites\n\nMake sure the following are installed:\n\n- [Node.js](https://nodejs.org/) (LTS recommended)\n- npm or yarn\n- [Expo CLI](https://docs.expo.dev/get-started/installation/)\n- Git\n- Python 3.8+\n- Android Studio or Xcode (for emulators)  \n  *OR* install **Expo Go** on a physical Android/iOS device\n\n---\n\n### ✅ Frontend Setup (EduArc App)\n\n1. **Clone the frontend repository**\n   ```bash\n   [git clone https://github.com/jeevanbabu7/EduArc-client.git]\n   cd eduarc-frontend\n   ```\n\n2. **Install Expo CLI globally**\n   ```bash\n   npm install -g expo-cli\n   ```\n\n3. **Install frontend dependencies**\n   ```bash\n   npm install\n   # or\n   yarn install\n   ```\n\n4. **Start the development server**\n   ```bash\n   expo start\n   ```\n\n   - Press `i` to run on iOS simulator (macOS only)\n   - Press `a` to run on Android emulator\n   - Or scan the QR code with **Expo Go** on your mobile device\n\n5. **(Optional) Setup environment variables**\n   ```bash\n   touch .env\n   ```\n\n   Add the following to `.env`:\n   ```\n   API_URL=https://your-backend-url.com/api\n   ```\n\n---\n\n### ⚙️ Backend Setup (Flask + Express)\n\n1. **Clone the backend repository**\n   ```bash\n   https://github.com/jeevanbabu7/EduArc-server.git\n   cd server\n   ```\n\n2. **Set up Flask server**\n   ```bash\n   cd RAG\n   python -m venv venv\n   source venv/bin/activate       # On Windows: venv\\Scripts\\activate\n   pip install -r requirements.txt\n   ```\n\n3. **Set up Express server**\n   ```bash\n   cd server\n   npm install\n   ```\n\n4. **Run both backend servers**\n\n   - Start Flask server:\n     ```bash\n     cd server/RAG\n     python app.py\n     ```\n\n   - Start Express server:\n     ```bash\n     cd server\n     npm start\n     ```\n\n---\n\n## UI Design\n\u003cdiv align=\"center\"\u003e\n\u003ctable border=\"0\"\u003e\n  \u003ctr\u003e\n    \u003ctd align=\"center\"\u003e\n      \u003cimg src=\"assets/img_readme/dashboard.jpg\" width=\"250\"/\u003e\u003cbr/\u003e\n      \u003cem\u003eDashboard\u003c/em\u003e\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n      \u003cimg src=\"assets/img_readme/courses.jpg\" width=\"250\"/\u003e\u003cbr/\u003e\n      \u003cem\u003eCourses\u003c/em\u003e\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n      \u003cimg src=\"assets/img_readme/courseMaterials.jpg\" width=\"250\"/\u003e\u003cbr/\u003e\n      \u003cem\u003eMaterials\u003c/em\u003e\n    \u003c/td\u003e\n  \u003c/tr\u003e\n  \u003ctr\u003e\n    \u003ctd align=\"center\"\u003e\n      \u003cimg src=\"assets/img_readme/tools.jpg\" width=\"250\"/\u003e\u003cbr/\u003e\n      \u003cem\u003eTools\u003c/em\u003e\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n      \u003cimg src=\"assets/img_readme/summary.jpg\" width=\"250\"/\u003e\u003cbr/\u003e\n      \u003cem\u003eSummarization\u003c/em\u003e\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n      \u003cimg src=\"assets/img_readme/chatbot.jpg\" width=\"250\"/\u003e\u003cbr/\u003e\n      \u003cem\u003eChatbot\u003c/em\u003e\n    \u003c/td\u003e\n  \u003c/tr\u003e\n  \u003ctr\u003e\n    \u003ctd align=\"center\"\u003e\n      \u003cimg src=\"assets/img_readme/quiz.jpg\" width=\"250\"/\u003e\u003cbr/\u003e\n      \u003cem\u003eQuestions\u003c/em\u003e\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n      \u003cimg src=\"assets/img_readme/flashcard.jpg\" width=\"250\"/\u003e\u003cbr/\u003e\n      \u003cem\u003eFlashcards\u003c/em\u003e\n    \u003c/td\u003e\n    \u003ctd align=\"center\"\u003e\n      \u003cimg src=\"assets/img_readme/quizResult.jpg\" width=\"250\"/\u003e\u003cbr/\u003e\n      \u003cem\u003eResults\u003c/em\u003e\n    \u003c/td\u003e\n  \u003c/tr\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\n## 🤖 Model and Framework Details\n\nEduArc integrates several powerful AI models and frameworks to deliver its intelligent features:\n\n- **LLaMA 3.1 (Meta AI):**  \n  Used for contextual understanding, summarization, and generating natural-language responses in the chatbot module.\n\n- **Command-R (Reka AI):**  \n  Supports robust question generation and flashcard creation by analyzing semantic meaning from uploaded content.\n\n- **LangChain:**  \n  Acts as an orchestration layer for chaining LLM calls with document processing, especially in RAG pipelines.\n\n- **Unsloth:**  \n  Helps in fine-tuning and accelerating LLM training for lightweight deployment and responsiveness on smaller instances.\n\n- **Whisper (OpenAI):**  \n  Integrated for converting spoken lecture recordings or audio content into accurate transcriptions, enabling text-based summarization and search.\n\n- **Chroma DB:**  \n  Vector database used for storing embeddings and performing semantic search over documents and past queries.\n\n- **FFmpeg:**  \n  Used in preprocessing audio/video inputs for Whisper transcription.\n\nThese models collectively power the learning assistant’s capabilities — from extracting insights and summarizing data to answering academic queries and generating quizzes tailored to a student’s course material.\n\n---\n\n## Training Notebooks\n- Topic Weightage Analysis : [Open in Google Colab](https://colab.research.google.com/drive/1RclTiAr8_MUMUVlun5CsPiwQixlGOF45?usp=sharing)\n- Question Generation : [Open in Google Colab](https://colab.research.google.com/drive/1zZNdrRlQJtcBKQ_O30Gs4mvr24BKkSQe?usp=sharing)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjeevanbabu7%2Feduarc-client","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjeevanbabu7%2Feduarc-client","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjeevanbabu7%2Feduarc-client/lists"}