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.
NotebookLM API × Gemini API — Automate Your Research Workflow with Python
Build an automated research pipeline by combining the NotebookLM Enterprise API and Gemini API in Python. Complete with working code examples for paper collection, summarization, podcast generation, and report creation.
Gemini API Context Caching— Cut Document Processing Costs by 90%
Learn how to use Gemini API's context caching to reduce repetitive document processing costs by up to 90%. Includes Python SDK implementation, caching strategies, and cost calculations.
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.
Building an Autonomous Data Analysis Agent with Gemini 3 Pro and LangGraph
Learn how to build a multi-step data analysis agent that autonomously handles CSV parsing, visualization, and report generation using Gemini 3 Pro and LangGraph, with complete code examples.
Generate SQL from Natural Language with Gemini API — A Practical Text-to-SQL Guide
Go beyond the demo: build a production-minded Text-to-SQL system with Gemini API. Measure accuracy by execution match, stop column-name hallucinations before execution, handle JOIN aggregation, and add observability — with working code and measured numbers.
Learn Programming with Gemini — How to Turn AI into Your Coding Tutor
A beginner-friendly guide to learning programming with Google Gemini. From generating code and explaining errors to building custom study plans, discover how to use AI as your personal coding tutor.
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.