{"id":31687885,"url":"https://github.com/puneetkakkar/interview-insight-ai","last_synced_at":"2026-04-11T09:39:07.429Z","repository":{"id":311855857,"uuid":"1039712857","full_name":"puneetkakkar/interview-insight-ai","owner":"puneetkakkar","description":"AI-powered interview transcript analysis platform built with FastAPI, LangGraph, and Next.js 15. Transform interview transcripts into actionable insights using Claude AI with timeline extraction, entity recognition, and sentiment analysis.","archived":false,"fork":false,"pushed_at":"2025-08-27T05:26:05.000Z","size":1120,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-08-27T10:54:54.631Z","etag":null,"topics":["ai","ai-agents","anthropic","claude-ai","claude-code","containerization","docker","entity-recognition","fastapi","full-stack","interview-analysis","langgraph","multi-agent-ai","natural-language-processing","nextjs","python","scalable-architecture","sentiment-analysis","transcript-analysis","typescript"],"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/puneetkakkar.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,"zenodo":null}},"created_at":"2025-08-17T20:32:37.000Z","updated_at":"2025-08-27T05:26:08.000Z","dependencies_parsed_at":"2025-08-27T10:55:12.837Z","dependency_job_id":"dc22de1c-05b9-4e65-b120-4b0b5ab96ba6","html_url":"https://github.com/puneetkakkar/interview-insight-ai","commit_stats":null,"previous_names":["puneetkakkar/interview-insight-ai"],"tags_count":null,"template":false,"template_full_name":null,"purl":"pkg:github/puneetkakkar/interview-insight-ai","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/puneetkakkar%2Finterview-insight-ai","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/puneetkakkar%2Finterview-insight-ai/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/puneetkakkar%2Finterview-insight-ai/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/puneetkakkar%2Finterview-insight-ai/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/puneetkakkar","download_url":"https://codeload.github.com/puneetkakkar/interview-insight-ai/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/puneetkakkar%2Finterview-insight-ai/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":278931065,"owners_count":26070784,"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":"2025-10-08T02:00:06.501Z","response_time":56,"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":["ai","ai-agents","anthropic","claude-ai","claude-code","containerization","docker","entity-recognition","fastapi","full-stack","interview-analysis","langgraph","multi-agent-ai","natural-language-processing","nextjs","python","scalable-architecture","sentiment-analysis","transcript-analysis","typescript"],"created_at":"2025-10-08T10:31:58.438Z","updated_at":"2025-10-08T10:33:24.461Z","avatar_url":"https://github.com/puneetkakkar.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Interview Insight AI\n\n\u003e **AI-Powered Interview Transcript Analysis Platform**\n\nA production-ready, full-stack AI application that transforms interview transcripts into actionable insights using advanced language models and multi-agent AI systems. Built with modern technologies and industry best practices for developers, recruiters, and HR professionals.\n\n[![Python](https://img.shields.io/badge/Python-3.11+-blue.svg)](https://python.org)\n[![Next.js](https://img.shields.io/badge/Next.js-15-black.svg)](https://nextjs.org)\n[![TypeScript](https://img.shields.io/badge/TypeScript-5.8+-blue.svg)](https://typescriptlang.org)\n[![FastAPI](https://img.shields.io/badge/FastAPI-0.104+-green.svg)](https://fastapi.tiangolo.com)\n[![License](https://img.shields.io/badge/License-MIT-green.svg)](LICENSE)\n\n## 🌟 What is InterviewInsight AI?\n\n**InterviewInsight AI** is a sophisticated platform that leverages cutting-edge AI technology to analyze interview transcripts and extract meaningful insights. Whether you're a developer showcasing AI skills, a recruiter analyzing candidate interviews, or an HR professional reviewing performance discussions, this platform provides enterprise-grade transcript analysis capabilities.\n\n### ✨ Key Features\n\n- **🤖 Advanced AI Analysis**: Multi-agent system powered by LangGraph with Claude 3.5 Haiku integration\n- **📊 Intelligent Insights**: Automatic timeline extraction, entity recognition, and sentiment analysis\n- **🎯 Real-time Processing**: Live analysis with progress indicators and comprehensive results\n- **🏗️ Production-Ready**: Docker containerization, comprehensive testing, and CI/CD ready\n- **🎨 Modern UI/UX**: Responsive design with shadcn/ui components and smooth animations\n- **🔧 Developer-Friendly**: Hot-reload, comprehensive documentation, and excellent tooling\n\n## 🚀 Core Capabilities\n\n### AI-Powered Transcript Analysis\n- **Timeline Extraction**: Automatic parsing of timestamps and event categorization\n- **Entity Recognition**: Identification of people, companies, technologies, and locations\n- **Sentiment Analysis**: Highlights and lowlights extraction with confidence scoring\n- **Topic Modeling**: Key topic identification and categorization\n- **Structured Output**: JSON-formatted results for easy integration and analysis\n\n### Multi-Agent AI System\n- **Research Assistant**: Web search and mathematical calculations using DuckDuckGo\n- **Transcript Analyzer**: Specialized agent for interview analysis with custom tools\n- **Extensible Framework**: Easy addition of new agents and specialized capabilities\n- **Conversation Threading**: Persistent state management across analysis sessions\n\n### Full-Stack Architecture\n- **Backend**: FastAPI with SQLAlchemy 2.0, async operations, and comprehensive API documentation\n- **Frontend**: Next.js 15 with App Router, React 19, and TypeScript 5.8+\n- **Database**: Flexible storage with PostgreSQL (production) or SQLite (development)\n- **DevOps**: Docker Compose environments for development, testing, and production\n\n## 🏗️ Architecture Overview\n\n```mermaid\ngraph TB\n    subgraph \"Frontend (Next.js 15)\"\n        A[React Components] --\u003e B[API Routes]\n        B --\u003e C[Type-Safe Env]\n        A --\u003e D[shadcn/ui Components]\n        A --\u003e E[Tailwind CSS]\n    end\n    \n    subgraph \"Backend (FastAPI)\"\n        F[API Endpoints] --\u003e G[Multi-Agent System]\n        G --\u003e H[LangGraph Agents]\n        H --\u003e I[Claude/OpenAI APIs]\n        F --\u003e J[Database Layer]\n        J --\u003e K[(PostgreSQL/SQLite)]\n    end\n    \n    subgraph \"AI Agents\"\n        L[Research Assistant]\n        M[Transcript Analyzer]\n        N[Custom Agents]\n    end\n    \n    B --\u003e F\n    H --\u003e L\n    H --\u003e M\n    H --\u003e N\n```\n\n## 🛠️ Technology Stack\n\n### Backend Technologies\n- **Framework**: FastAPI (Python 3.11+)\n- **AI/ML**: LangGraph, LangChain, Anthropic Claude, OpenAI\n- **Database**: SQLAlchemy 2.0, PostgreSQL, Alembic migrations\n- **Tools**: Pydantic V2, UV package manager, Pytest\n- **Deployment**: Docker, Gunicorn, health checks\n\n### Frontend Technologies\n- **Framework**: Next.js 15 with App Router\n- **Language**: TypeScript 5.8+ with strict mode\n- **UI/UX**: shadcn/ui, Radix UI, Tailwind CSS 4.0, Framer Motion\n- **Tools**: pnpm, ESLint, Prettier, T3 Env\n\n### DevOps \u0026 Quality\n- **Containers**: Docker \u0026 Docker Compose\n- **Package Managers**: UV (Python), pnpm (Node.js)\n- **Quality**: Ruff, MyPy, ESLint, Prettier\n- **Testing**: pytest, Jest (ready), Playwright (ready)\n\n## 🚀 Quick Start\n\n### Prerequisites\n- **Python 3.11+** (for backend)\n- **Node.js 18+** (for frontend) \n- **Docker \u0026 Docker Compose** (optional, for PostgreSQL)\n- **UV** (Python package manager)\n- **pnpm** (Node.js package manager)\n\n### 1. Clone the Repository\n```bash\ngit clone \u003crepository-url\u003e\ncd interview-insight-ai\n```\n\n### 2. Backend Setup\n\n#### Option A: Quick Start (In-Memory Database)\nPerfect for development and coding interviews:\n\n```bash\ncd backend\ncp env.example .env\necho \"STORAGE_TYPE=memory\" \u003e\u003e .env\n\n# Install dependencies\nuv sync\n\n# Start the backend\nuv run python -m src.app.main\n```\n\n#### Option B: Full Setup (PostgreSQL)\nFor production-like development:\n\n```bash\ncd backend\ncp env.example .env\n# Edit .env with your settings\n\n# Start with Docker\nmake dev-up\n\n# Or manually start PostgreSQL and run:\n# uv run python -m src.app.main\n```\n\n### 3. Frontend Setup\n```bash\ncd frontend\npnpm install\n\n# Start development server\npnpm dev\n```\n\n### 4. Access the Application\n- **Frontend**: http://localhost:3000\n- **Backend API**: http://localhost:8000\n- **API Documentation**: http://localhost:8000/docs\n- **Interactive API**: http://localhost:8000/redoc\n\n### 5. Optional: Add API Keys for AI Features\n```bash\n# In backend/.env\nANTHROPIC_API_KEY=your-anthropic-api-key\nOPENAI_API_KEY=your-openai-api-key\n```\n*Note: The application works without API keys using mock responses for development.*\n\n## 📁 Project Structure\n\n```\ninterview-insight-ai/\n├── backend/                          # FastAPI backend with AI capabilities\n│   ├── src/\n│   │   └── app/\n│   │       ├── agents/               # Multi-agent AI system\n│   │       │   ├── agent.py          # Agent registry and orchestration\n│   │       │   ├── research_assistant.py  # Web search \u0026 calculation agent\n│   │       │   ├── transcript_analyzer.py  # Interview analysis agent\n│   │       │   └── tools.py          # AI tools (search, calculator, etc.)\n│   │       ├── api/                  # REST API endpoints\n│   │       ├── core/                 # Core application logic\n│   │       ├── schemas/              # Pydantic data models\n│   │       └── main.py               # Application entry point\n│   ├── tests/                        # Comprehensive test suite\n│   ├── docker/                       # Environment-specific Docker configs\n│   ├── migrations/                   # Database migrations (PostgreSQL)\n│   ├── pyproject.toml               # Python dependencies and tooling\n│   └── README.md                    # Backend documentation\n├── frontend/                         # Next.js 15 frontend\n│   ├── src/\n│   │   ├── app/                      # Next.js App Router\n│   │   │   ├── page.tsx             # Homepage with transcript analyzer\n│   │   │   ├── analysis/            # Analysis results page\n│   │   │   └── api/                 # Backend proxy API routes\n│   │   ├── components/              # React components\n│   │   │   ├── ui/                  # shadcn/ui component library\n│   │   │   ├── transcript-analyzer.tsx  # Main analysis interface\n│   │   │   ├── analysis-dashboard.tsx   # Results visualization\n│   │   │   └── ...                  # Other app components\n│   │   ├── types/                   # TypeScript type definitions\n│   │   └── env.js                   # Type-safe environment config\n│   ├── package.json                 # Node.js dependencies and scripts\n│   └── README.md                   # Frontend documentation\n└── README.md                       # This file\n```\n\n## 🤖 AI Capabilities\n\n### Available Agents\n\n#### Research Assistant\n- **Web Search**: Real-time information retrieval using DuckDuckGo\n- **Mathematical Calculations**: Safe expression evaluation with NumExpr\n- **General Q\u0026A**: Claude-powered responses with conversation threading\n\n#### Transcript Analyzer\n- **Timeline Extraction**: Automatic parsing of timestamps and event categorization\n- **Entity Recognition**: Identification of people, companies, technologies, locations\n- **Sentiment Analysis**: Highlights and lowlights extraction\n- **Topic Modeling**: Key topic identification and categorization\n- **Structured Output**: JSON-formatted results for frontend integration\n\n### Example Usage\n\n```python\n# Research Assistant\ncurl -X POST http://localhost:8000/api/v1/agent/research-assistant/invoke \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\n    \"message\": \"What is the current population of Tokyo?\",\n    \"model\": \"claude-3-5-haiku-latest\"\n  }'\n\n# Transcript Analyzer\ncurl -X POST http://localhost:8000/api/v1/transcript/analyze \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\n    \"transcript_text\": \"Interviewer: Tell me about your Python experience...\",\n    \"model\": \"claude-3-5-haiku-latest\"\n  }'\n```\n\n## 🛠️ Development Workflows\n\n### Backend Development\n```bash\ncd backend\n\n# Quick development (in-memory)\necho \"STORAGE_TYPE=memory\" \u003e .env\nuv run python -m src.app.main\n\n# Full development (PostgreSQL)\nmake dev-up                    # Start containers\nmake test                      # Run tests\nmake lint                      # Check code quality\nmake format                    # Format code\n\n# Database management\nmake migrate                   # Create and apply migrations\nmake revision                  # Create new migration\nmake upgrade                   # Apply migrations only\n```\n\n### Frontend Development\n```bash\ncd frontend\n\n# Development\npnpm dev                       # Start dev server with Turbo\npnpm build                     # Build for production\npnpm preview                   # Build and serve\n\n# Code quality\npnpm lint                      # ESLint check\npnpm lint:fix                  # Fix ESLint issues\npnpm typecheck                 # TypeScript check\npnpm format:write              # Format with Prettier\n```\n\n### Full-Stack Development\n```bash\n# Terminal 1 - Backend\ncd backend \u0026\u0026 echo \"STORAGE_TYPE=memory\" \u003e .env \u0026\u0026 uv run python -m src.app.main\n\n# Terminal 2 - Frontend  \ncd frontend \u0026\u0026 pnpm dev\n\n# Terminal 3 - Development commands\ncd backend \u0026\u0026 make test        # Run backend tests\ncd frontend \u0026\u0026 pnpm check     # Frontend quality checks\n```\n\n## 🧪 Testing\n\n### Backend Testing\n```bash\ncd backend\n\n# Run all tests\nmake test\n\n# Run with coverage\nmake test-all\n\n# Run in Docker environment\nmake test-env\n\n# Specific test categories\nuv run pytest tests/unit/     # Unit tests only\nuv run pytest tests/integration/  # Integration tests only\n```\n\n### Frontend Testing (Ready for Implementation)\n```bash\ncd frontend\n\n# When implemented:\npnpm test                      # Jest unit tests\npnpm test:watch               # Watch mode\npnpm test:e2e                 # Playwright E2E tests\n```\n\n## 🚀 Deployment\n\n### Production Deployment\n\n#### Backend Production\n```bash\ncd backend\nmake prod-up                   # Start production containers\n```\n\nProduction features:\n- Gunicorn with multiple workers\n- PostgreSQL with persistent volumes\n- Health checks and monitoring\n- Environment-based configuration\n\n#### Frontend Production\n```bash\ncd frontend\npnpm build                     # Build optimized bundle\npnpm start                     # Start production server\n```\n\nProduction features:\n- Optimized bundle with code splitting\n- Static asset optimization\n- Environment variable validation\n- Performance monitoring ready\n\n### Environment Configuration\n\n#### Backend (.env)\n```env\n# Storage\nSTORAGE_TYPE=postgres          # or \"memory\" for development\nPOSTGRES_SERVER=localhost\nPOSTGRES_DB=interview_insight_db\nPOSTGRES_USER=postgres\nPOSTGRES_PASSWORD=your_password\n\n# AI Configuration\nANTHROPIC_API_KEY=your-key\nOPENAI_API_KEY=your-key\n\n# Application\nENVIRONMENT=production\nDEBUG=false\n```\n\n#### Frontend (.env.local)\n```env\n# Backend API URL\nBACKEND_URL=http://localhost:8000\n\n# Skip environment validation for Docker builds\nSKIP_ENV_VALIDATION=false\n```\n\n## 🧹 Code Quality \u0026 Standards\n\n### Backend Standards\n- **Type Safety**: Full MyPy coverage with strict mode\n- **Code Style**: Ruff for linting and formatting (120 char line length)\n- **Testing**: 90%+ test coverage with pytest\n- **Documentation**: Comprehensive docstrings and API documentation\n\n### Frontend Standards\n- **Type Safety**: Strict TypeScript with comprehensive type definitions\n- **Code Style**: ESLint + Prettier with Tailwind class sorting\n- **Components**: shadcn/ui patterns with accessibility standards\n- **Performance**: Optimized bundle sizes and Core Web Vitals\n\n### Shared Standards\n- **Git**: Conventional commits with clear commit messages\n- **Documentation**: README files for each major component\n- **Environment**: Type-safe environment variable validation\n- **Dependencies**: Regular updates with security monitoring\n\n## 🔧 Customization \u0026 Extension\n\n### Adding New AI Agents\n1. Create agent module in `backend/src/app/agents/`\n2. Implement using LangGraph patterns\n3. Register in agent registry\n4. Add API endpoints\n5. Create frontend integration\n\n### Adding Frontend Components\n1. Use shadcn/ui CLI: `pnpx shadcn@latest add \u003ccomponent\u003e`\n2. Follow existing component patterns\n3. Maintain accessibility standards\n4. Add TypeScript definitions\n\n### Database Extensions\n1. Create Pydantic schemas\n2. Add SQLAlchemy models\n3. Generate migrations: `make revision`\n4. Apply migrations: `make upgrade`\n\n## 🤝 Contributing\n\n### Development Process\n1. **Fork** the repository\n2. **Create** feature branch: `git checkout -b feature/amazing-feature`\n3. **Commit** changes: `git commit -m 'feat: add amazing feature'`\n4. **Test** thoroughly: Run test suites and quality checks\n5. **Push** branch: `git push origin feature/amazing-feature`\n6. **Create** Pull Request with detailed description\n\n### Code Review Checklist\n- [ ] Type safety maintained (no TypeScript errors)\n- [ ] Tests added/updated for new functionality\n- [ ] Documentation updated (README, docstrings)\n- [ ] Code quality checks pass (linting, formatting)\n- [ ] Performance impact considered\n- [ ] Accessibility standards maintained\n- [ ] Security implications reviewed\n\n## 📈 Performance \u0026 Scalability\n\n### Backend Performance\n- **Async Operations**: Full async/await support with SQLAlchemy 2.0\n- **Connection Pooling**: Database connection optimization\n- **Caching**: Ready for Redis integration\n- **Monitoring**: Health checks and metrics endpoints\n\n### Frontend Performance\n- **Core Web Vitals**: Optimized for LCP, FID, and CLS\n- **Code Splitting**: Automatic route-based and dynamic imports\n- **Image Optimization**: Next.js built-in image optimization\n- **Bundle Analysis**: Built-in bundle analyzer\n\n### Scaling Considerations\n- **Horizontal Scaling**: Stateless design with external session storage\n- **Database Scaling**: PostgreSQL with read replicas support\n- **CDN Ready**: Static asset optimization for CDN distribution\n- **Load Balancing**: Container-ready for orchestration platforms\n\n## 🔒 Security\n\n### Backend Security\n- **Input Validation**: Pydantic models for all API inputs\n- **SQL Injection Protection**: SQLAlchemy ORM with parameterized queries\n- **Environment Variables**: Secure configuration management\n- **CORS Configuration**: Proper cross-origin resource sharing setup\n\n### Frontend Security\n- **XSS Protection**: React built-in XSS protection\n- **Type Safety**: TypeScript prevents many runtime errors\n- **Environment Validation**: Type-safe environment variable handling\n- **Dependency Scanning**: Regular security updates\n\n### Production Security Checklist\n- [ ] API keys stored securely (not in code)\n- [ ] HTTPS enabled in production\n- [ ] Database credentials secured\n- [ ] CORS configured for production domains\n- [ ] Input validation on all endpoints\n- [ ] Error messages don't leak sensitive information\n\n## 📚 Learning Resources\n\n### Technologies Used\n- **FastAPI**: [Official Documentation](https://fastapi.tiangolo.com/)\n- **Next.js 15**: [App Router Guide](https://nextjs.org/docs/app)\n- **LangGraph**: [Multi-Agent Documentation](https://langchain-ai.github.io/langgraph/)\n- **shadcn/ui**: [Component Library](https://ui.shadcn.com/)\n- **Tailwind CSS**: [Utility-First CSS](https://tailwindcss.com/)\n\n### Best Practices\n- **Python FastAPI**: [Best Practices Guide](https://fastapi.tiangolo.com/tutorial/)\n- **React/Next.js**: [React Patterns](https://reactpatterns.com/)\n- **TypeScript**: [TypeScript Handbook](https://www.typescriptlang.org/docs/)\n- **Testing**: [Testing Best Practices](https://github.com/goldbergyoni/javascript-testing-best-practices)\n\n## 🆘 Support \u0026 Troubleshooting\n\n### Common Issues\n\n#### Backend Issues\n- **Port 8000 in use**: Use `lsof -ti:8000 | xargs kill -9` to free the port\n- **Database connection**: Check PostgreSQL is running and credentials are correct\n- **AI API errors**: Verify API keys are set correctly or use development mode\n\n#### Frontend Issues\n- **Port 3000 in use**: Next.js will automatically use the next available port\n- **Build errors**: Run `pnpm install` to ensure all dependencies are installed\n- **Type errors**: Run `pnpm typecheck` to identify and fix TypeScript issues\n\n#### Environment Issues\n- **UV not found**: Install UV following [official instructions](https://github.com/astral-sh/uv)\n- **pnpm not found**: Install pnpm with `npm install -g pnpm`\n- **Docker issues**: Ensure Docker Desktop is running and up-to-date\n\n### Getting Help\n1. **Check Documentation**: README files in backend/ and frontend/\n2. **Review Issues**: Check existing GitHub issues for similar problems\n3. **Enable Debug Mode**: Set `DEBUG=true` in backend environment\n4. **Check Logs**: Review container logs with `docker logs \u003ccontainer-name\u003e`\n5. **Create Issue**: Open detailed issue with reproduction steps\n\n## 📄 License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n\n## 🙏 Acknowledgments\n\n- **FastAPI** for the excellent async Python framework\n- **Next.js** team for the outstanding React framework\n- **Anthropic** for Claude AI capabilities\n- **Vercel** for shadcn/ui and development tools\n- **LangChain** team for the AI/ML framework\n- **Open Source Community** for the amazing tools and libraries\n\n---\n\n**Built with ❤️ for developers who want to ship AI-powered applications quickly and reliably.**\n\nFor detailed component documentation, see:\n- [Backend Documentation](./backend/README.md)\n- [Frontend Documentation](./frontend/README.md)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpuneetkakkar%2Finterview-insight-ai","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpuneetkakkar%2Finterview-insight-ai","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpuneetkakkar%2Finterview-insight-ai/lists"}