Building an AI Code Quality Pipeline with Gemini API and GitHub Actions — Automated PR Reviews, Security Scanning, and Documentation Generation
Learn how to build a production-grade AI code quality pipeline using Gemini API and GitHub Actions that automates PR reviews, security vulnerability scanning, and documentation generation.
Gemini API × BigQuery: AI-Powered Data Analysis — From Natural Language Queries to Actionable Insights
Learn how to combine Gemini API with BigQuery for natural language data analysis. Covers SQL auto-generation, result summarization, and production-ready patterns with practical Python code examples.
Gemini API AI Gateway Design Patterns — Building a Unified Proxy for Rate Limiting, Failover, and Cost Tracking
An advanced guide to designing and implementing an AI gateway (proxy server) for production Gemini API deployments. Learn how to unify rate limiting, automatic failover, token cost tracking, and multi-model routing in a single architecture layer.
Automate Your Daily Tasks with Gemini API — An Engineer's Guide to AI-Powered Workflows
Learn how to automate routine engineering tasks like PR descriptions, code reviews, meeting notes, and release notes using the Gemini API with practical Python examples.
Building a Prompt Evaluation & Optimization Pipeline with Gemini API — Automated Quality Scoring with LLM-as-Judge
Learn how to build a prompt evaluation pipeline using Gemini API. Covers the LLM-as-Judge pattern, A/B testing prompts, automated quality scoring, and cost-quality optimization for production systems.
Running a Gemini + LINE Bot in Production — Reply Token Expiry, Duplicate Replies, and Cold-Start Latency
The first walls you hit putting Gemini behind a LINE Bot are the 30-second reply-token expiry, duplicate replies from webhook redelivery, and Cloud Run cold starts. This guide solves them with loading animations, push-message fallback, idempotency, and Firestore-backed history — with working code and measured numbers.
VS Code + Roo Code + Gemini — Building a Blazing-Fast, Free AI Development Environment
The VS Code + Roo Code + Gemini API combo offers the best balance of cost, speed, and accuracy for AI-powered development. Learn setup, mode switching, and real-world tips.
Build an AI Data Analysis Agent with Gemini API — Combining Code Execution, Function Calling, and Structured Output
Learn how to build a production-ready AI data analysis agent in Python that combines Gemini API's Code Execution, Function Calling, and Structured Output to automatically analyze CSV/Excel data, generate visualizations, and produce structured reports.
Gemini 2.5 Pro × FastAPI: Building a Production-Ready AI Backend
Learn how to build a production-ready AI backend by combining Gemini 2.5 Pro with FastAPI, covering streaming, rate limiting, Function Calling, cost optimization, and Docker deployment.
Fine-Tuning Gemini: Building Specialized Models for Domain-Specific Applications
Complete guide to fine-tuning Gemini models. Learn dataset preparation, training strategies, evaluation metrics, and production deployment for custom AI.