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gcp-gemini-api-developer

Desenvolvimento Autor: Raishin

Esta skill permite construir, integrar e depurar aplicações da API Gemini na Google Cloud Agent Platform (anteriormente Vertex AI) usando o SDK unificado google-genai. Ela suporta funcionalidades como geração de texto, entradas multimodais, chamada de função e ajuste de modelo em Python, TypeScript/JavaScript, Go, Java e C#.

19estrelas
Atualizado há 4 meses
Ver no GitHub ↗ Licença: Apache-2.0

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#ai #api #javascript #python #typescript

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GCP Gemini API Developer

IMPORTANT BRANDING NOTE

"Agent Platform" (full name: Gemini Enterprise Agent Platform) was previously named "Vertex AI". Many web resources still use "Vertex AI" branding.

CRITICAL SDK NOTE

The following SDKs are DEPRECATED and must NOT be used:

  • google-cloud-aiplatform (Python)
  • @google-cloud/vertexai (Node.js)
  • google-generativeai (Python — Gemini Developer API SDK)

Use ONLY the unified Gen AI SDK:

  • Python: google-genai (pip install google-genai)
  • JavaScript/TypeScript: @google/genai (npm install @google/genai)
  • Go: google.golang.org/genai (go get google.golang.org/genai)
  • Java: com.google.genai:google-genai
  • C#/.NET: Google.GenAI (dotnet add package Google.GenAI)

Authentication

# Application Default Credentials (ADC) — preferred
export GOOGLE_CLOUD_PROJECT='your-project-id'
export GOOGLE_CLOUD_LOCATION='global'  # Use 'global' for automatic region routing
export GOOGLE_GENAI_USE_VERTEXAI=true

Model Selection

  • gemini-3.1-pro-preview — complex reasoning, coding, research (1M tokens)
  • gemini-3-flash-preview — fast, balanced, multimodal (1M tokens)
  • gemini-3.1-flash-lite-preview — high-frequency lightweight tasks
  • gemini-3-pro-image-preview — image generation and editing
  • gemini-live-2.5-flash-native-audio — Live Realtime API (bidirectional audio/video)
  • DEPRECATED (do not use): gemini-2.0-, gemini-1.5-, gemini-1.0-*, gemini-pro

Quick Start (Python)

from google import genai
client = genai.Client  # picks up env vars automatically
response = client.models.generate_content(
    model="gemini-3-flash-preview",
    contents="Explain transformer architecture"
)
print(response.text)

Reference Directory

Load only when needed:

| Scenario | Trigger Keywords | Reference | |---|---|---| | Text + multimodal | chat, image, video, audio, streaming | references/text-multimodal.md | | Function calling + tools | tool use, function call, grounding, code execution | references/tools.md | | Structured output | JSON, schema, structured, typed response | references/structured-output.md | | Embeddings | embedding, semantic search, vector | references/embeddings.md | | Context caching | cache, large context, caching tokens | references/caching.md | | Batch prediction | batch, async, large dataset | references/batch.md | | Live API | live, realtime, voice, video streaming, bidirectional | references/live-api.md | | Model tuning | fine-tune, SFT, preference tuning | references/tuning.md | | Safety | safety filter, threshold, harm category | references/safety.md | | SDK migration | migrate, deprecated, upgrade | references/migration.md |

Core Rules

  • ALWAYS use the unified google-genai SDK family. If user code imports google-cloud-aiplatform, @google-cloud/vertexai, or google-generativeai, flag it as deprecated and provide migration guidance.
  • Use location="global" (global endpoint) by default for automatic capacity routing. Only use a specific region if the user explicitly requests it.
  • Initialize the client without parameters when environment variables are set — don't hardcode project/location in code.
  • gemini-3.1-pro-preview ≠ gemini-3-pro-preview — the latter does NOT exist; use the correct model IDs.
  • Context caching (CachedContent) reduces cost for repeated large contexts (system prompts, documents) — recommend it proactively for production workloads with stable large contexts.
  • For production, consult docs for stable model version aliases rather than using -preview models.
  • Batch prediction (BatchJob) is for async large-dataset inference — use it instead of looping generate_content for bulk processing.

Official Docs

  • https://cloud.google.com/vertex-ai/generative-ai/docs/overview
  • https://cloud.google.com/vertex-ai/generative-ai/docs/sdks/overview
  • https://cloud.google.com/vertex-ai/generative-ai/docs/context-cache/context-cache-overview

Security Notes

Read-only advisory. Never embed API keys or service account credentials in code examples. Use ADC and environment variables. Do not call batch jobs or fine-tuning jobs on production data without explicit user approval.

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