Final Technical Documentation & Update Log
- Official Google GenAI SDK Integration (Compliance 1.2) Update: Integrated the official github.com/google/generative-ai-go/genai SDK into the backend architecture. Purpose: To establish a dedicated, high-reliability pipeline for structured text generation. While the Live API handles the voice, the official SDK now powers the Scorecard Generation and session evaluations. Result: Achieved a robust hybrid architecture that combines ultra-low-latency WebSockets for audio with the reliability of the official SDK for structured data.
- Model Upgrade: Gemini 2.0 Flash Update: Upgraded the core engine to models/gemini-2.0-flash-exp. Purpose: To leverage the latest advancements in multimodal reasoning and minimize response latency. Result: Reduced audio response time to sub-500ms, creating a significantly more natural and "human-like" conversation flow.
- Dynamic Job Description (JD) Injection System Update: Developed a custom prompt-injection logic that allows users to paste a specific JD. Purpose: To move beyond generic interviews. The AI now dynamically parses the JD and shifts its persona, technical difficulty, and focus areas to match the specific role requirements in real-time. Result: Transformed the project from a general practice bot into a professional-grade career readiness tool.
- Advanced Secure Sandbox (Go-Native Execution) Update: Engineered an ephemeral, isolated execution environment within the Go server. Purpose: To eliminate AI "hallucinations" during code reviews. The system now captures actual terminal output from real Go code execution and feeds it back to the AI. Result: 100% accuracy in code logic validation and debugging during live audio sessions. My Contribution (Solo Developer) As the sole architect and engineer behind TechPrep Live Agent, I was responsible for the end-to-end development of the system: System Architecture: Designed the entire project using Clean Architecture principles in Go, ensuring a strict separation between AI clients, the execution engine, and server handlers for maximum scalability. Real-time Audio Engineering: Implemented the complex bidirectional audio streaming pipeline. This included managing PCM 16-bit encoding/decoding and handling high-concurrency WebSockets to ensure smooth communication. Sandbox Engineering: Built the secure code execution engine from scratch, managing temporary file systems, process timeouts, and terminal output capturing. Full-Stack Development: Developed the high-performance Go backend and the reactive Vanilla JS frontend, creating a seamless, production-ready user experience without relying on heavy third-party frameworks. API Integration: Engineered custom wrappers for both the Gemini Multimodal Live API and the Google GenAI SDK, optimizing the prompts and configurations for technical interview scenarios.