Production-Ready Gemini API Integration — From Prototype to Scale
Building with the Gemini API is easy to start, hard to get right in production. These 12 prompts give you battle-tested patterns for function calling, streaming, caching, and error handling that survive real-world traffic.
What's Inside (12 Developer Prompts)
- Function Calling Setup with Tools — Complete function declaration schema, parameter validation, multi-function routing, and response handling. Includes a working weather + calculator + search example.
- Structured JSON Output for APIs — Force consistent JSON responses with responseSchema configuration. Covers nested objects, arrays, enums, optional fields, and schema evolution patterns.
- Streaming Chat Implementation — Server-sent events setup with chunk assembly, partial response rendering, error recovery mid-stream, and connection timeout handling.
- Context Caching for Production — Cache large documents (up to 1M tokens) for repeated queries. Setup includes TTL management, cache invalidation, cost comparison calculator, and usage monitoring.
- Embedding Search System — Build semantic search with Gemini embeddings: index creation, query embedding, cosine similarity ranking, and hybrid search with keyword fallback.
- RAG Pipeline with Gemini — Complete retrieval-augmented generation setup: document chunking, embedding storage, context retrieval, prompt assembly with citations, and hallucination checking.
- Multi-Turn Conversation Management — Manage conversation history efficiently: token counting per turn, history pruning strategies, summarization of old turns, and context window optimization.
- Safety Filter Configuration — Configure safety thresholds for business applications. Covers all harm categories, threshold levels, blocked response handling, and appeal-safe content strategies.
- Batch API Processing — Process thousands of requests efficiently: batching strategies, concurrent request management, progress tracking, failure retry with exponential backoff, and cost estimation.
- Webhook Integration — Set up async Gemini processing with webhooks: request queuing, status callbacks, timeout handling, and idempotency for reliable delivery.
- Rate Limit Handling — Production-grade rate limiter: token bucket implementation, request queuing, 429 retry with jitter, quota monitoring, and automatic model fallback when limits hit.
- Model Fallback Strategy — Automatic failover between Gemini Flash → Pro → other providers. Includes health checking, latency-based routing, cost tracking, and quality comparison logging.
How to Use
- Get your Gemini API key from Google AI Studio
- Choose the integration pattern you need
- Copy the prompt — it generates complete, production-ready code
- Adapt the generated code to your framework (Python, Node.js, or REST)
- Each prompt includes testing instructions and common pitfall warnings
Works With
Gemini API (Python SDK, Node.js SDK, REST). Compatible with Gemini 2.0 Flash, Gemini 2.0 Pro, and Gemini 1.5 models. Code examples in Python and TypeScript.
