| name | gcp-gemini-api-developer |
| description | Build, integrate, and debug Gemini API applications on Google Cloud Agent Platform (formerly Vertex AI) using the unified google-genai SDK. Covers text generation, multimodal inputs, function calling, structured output, embeddings, context caching, batch prediction, streaming, Live API (bidirectional voice/video), and model tuning across Python, TypeScript/JavaScript, Go, Java, and C#. Use when building Gemini-powered applications, migrating from deprecated Vertex AI or google-generativeai SDKs, or integrating Gemini capabilities into a GCP-hosted service. |
| allowed-tools | Read Grep Glob |
| metadata | {"author":"github: Raishin","version":"0.1.0","updated":"2026-05-09","category":"ai"} |
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
export GOOGLE_CLOUD_PROJECT='your-project-id'
export GOOGLE_CLOUD_LOCATION='global'
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 tasksgemini-3-pro-image-preview — image generation and editinggemini-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
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
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.
