vertex-ai-api-dev
Gemini API in Vertex AI
Access Google's most advanced AI models built for enterprise use cases using the Gemini API in Vertex AI.
Provide these key capabilities:
- Text generation - Chat, completion, summarization
- Multimodal understanding - Process images, audio, video, and documents
- Function calling - Let the model invoke your functions
- Structured output - Generate valid JSON matching your schema
- Context caching - Cache large contexts for efficiency
- Embeddings - Generate text embeddings for semantic search
- Live Realtime API - Bidirectional streaming for low latency Voice and Video interactions
- Batch Prediction - Handle massive async dataset prediction workloads
Core Directives
- Unified SDK: ALWAYS use the Gen AI SDK (
google-genaifor Python,@google/genaifor JS/TS,google.golang.org/genaifor Go,com.google.genai:google-genaifor Java,Google.GenAIfor C#). - Legacy SDKs: DO NOT use
google-cloud-aiplatform,@google-cloud/vertexai, orgoogle-generativeai.
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46gemini-interactions-api
Use this skill when writing code that calls the Gemini API for text generation, multi-turn chat, multimodal understanding, image generation, streaming responses, background research tasks, function calling, structured output, or migrating from the old generateContent API. This skill covers the Interactions API, the recommended way to use Gemini models and agents in Python and TypeScript.
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Use this skill when building real-time, bidirectional streaming applications with the Gemini Live API. Covers WebSocket-based audio/video/text streaming, voice activity detection (VAD), native audio features, function calling, session management, ephemeral tokens for client-side auth, and all Live API configuration options. SDKs covered - google-genai (Python), @google/genai (JavaScript/TypeScript).
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