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View on GitHubSample code and notebooks for Generative AI on Google Cloud, with Gemini Enterprise Agent Platform
Google Cloud's official collection of Jupyter notebooks and code samples for building on Gemini and Vertex AI, covering agents, RAG/grounding, embeddings, vector search, vision, audio, and open models. Best used as a hands-on reference for GCP generative AI development.
Use Cases
Build and deploy Gemini-powered agents with ADKImplement RAG and grounding pipelinesGenerate and tune text/multimodal embeddingsVector search and hybrid search over documentsImage generation and editing with ImagenVideo generation with VeoSpeech-to-text and translation with ChirpFunction calling and tool use with GeminiBenchmark and evaluate open models on Vertex AIBuild enterprise search engines over private dataDocument summarization workflowsExplore GenAI via runnable Colab notebooks
Built With
- Language
- Jupyter Notebook
- Frameworks
- Google Gen AI SDK · Vertex AI SDK · LangChain · Agent Development Kit (ADK) · Vertex AI Vector Search · BigQuery ML · Model Garden SDK · Terraform
Tags
gemini · vertex-ai · google-cloud · jupyter-notebooks · agents · rag · embeddings · multimodal · vector-search · llm · genai-samples · function-calling · image-generation · speech · enterprise-search · model-garden