BigQuery

Google Cloud's serverless data warehouse. Used in this repo for vector storage, BigQuery ML generative functions, and as a grounding/RAG data source. · Official docs

Related concepts

• Getting Started · Gemini Capabilities · Prompt Engineering · Function Calling & Tools · Agents & ADK · Agent Engine · RAG & Grounding · Vertex AI Search · Embeddings & Vector Search · Vision · Evaluation · Tuning & Customization · Open & Partner Models · MLOps & Deployment · Applied Use Cases

Used in 41 notebooks

Agents & ADK (5)

• Get started with Cloud API Registry on Vertex AI Agent Engine — Builds and deploys an ADK BigQuery data analyst agent using Cloud API Registry on Vertex AI Agent Engine.
• Gemini Data Analytics: A2A HTTP API Sample — Calls Gemini Data Analytics DataA2AService over HTTP for agent cards, messages, artifacts, and cancellation.
• Gemini Data Analytics: A2A SDK API Sample — Uses the A2A Python SDK to send synchronous-style requests to Gemini Data Analytics.
• Intro to Gemini Data Analytics — Shows REST-based Gemini Data Analytics agents over BigQuery, Looker, or Looker Studio data.
• Intro to Gemini Data Analytics — Shows how to create Gemini Data Analytics agents over BigQuery, Looker, or Looker Studio and chat with them.

Embeddings & Vector Search (6)

• 🛡️ AI Brand Safety: Three-Tier Agent Anomaly Detection — Builds ADK agent anomaly detection with Gemini baselines, Vector Search scoring, and tiered audits.
• Import from BigQuery into Vector Search — Imports BigQuery embedding rows into a Vertex AI Vector Search index using the import REST API.
• Use Gemini and OSS Text-Embedding Models Against Your BigQuery Data — Generate BigQuery embeddings with Gemini and a deployed OSS E5 model.
• Getting Started with Text Embeddings + Agent Platform Vector Search — Builds text embeddings from Stack Overflow titles and serves semantic search with Vector Search.
• Log Anomaly Detection & Investigation with Text Embeddings + BigQuery Vector Search — Detects audit log anomalies using text-embedding-005 embeddings and BigQuery VECTOR_SEARCH.
• Anomaly Detection of Infrastructure Logs using Gemini and BigQuery Vector Search — Detects HDFS log anomalies with Gemini summaries, text embeddings, and BigQuery Vector Search.

Gemini (24)

• Function Calling Agent — Builds a Gemini function-calling retail assistant over Cymbal Retail data in BigQuery.
• Intro to Batch Inference with the Gemini API — Runs Gemini batch inference jobs using Cloud Storage and BigQuery inputs and outputs.
• Monitor batch prediction with Gemini API — Orchestrates and monitors Gemini batch predictions with Vertex AI Pipelines and BigQuery output.
• Evaluating prompts at scale with Gemini Batch Prediction API — Evaluates Gemini image-classification prompts at scale with Batch Prediction and BigQuery.
• Intro to Request and Response Logging with Gemini — Shows how to enable Gemini request-response logging to BigQuery, query logs, and disable logging.
• Intro to Model Context Protocol (MCP) integration with Vertex AI — Shows how to connect Gemini on Vertex AI to custom and prebuilt MCP servers.
• Intro to Agent Platform Multimodal Datasets — Builds Agent Platform multimodal datasets for Gemini tuning validation, resource estimates, tuning, and batch prediction.
• Chain of Thought & ReAct — Demonstrates CoT prompting and ReAct agents with Vertex AI, LangChain, Wikipedia, and BigQuery.
• Vertex AI RAG Engine with Vertex AI Feature Store — Builds a Vertex AI RAG Engine corpus backed by Vertex AI Feature Store and queries it with Gemini.
• AI-Assisted Data Science Workflows in BigQuery — Builds a BigQuery multimodal housing workflow with Gemini enrichment, BQML clustering, and vector search.
• Analyzing movie posters in BigQuery with Gemini — Analyzes movie poster images in BigQuery with Gemini, embeddings, and vector search.
• Semantic Analysis in BigQuery with AI Functions — Uses BigQuery AI functions with Gemini to rank, classify, filter, join, and enrich pet product data.
• BigQuery DataFrames ML: Prescription Drug Name Generation — Generates pharmaceutical brand name ideas with BigQuery DataFrames ML and Gemini.
• Text + multimodal embedding generation and vector search in BigQuery — Builds text and image embeddings in BigQuery for semantic product search.
• Introduction to Generative AI functions in BigQuery — Introduces BigQuery generative AI functions for SQL-based text analysis and forecasting.
• Analyze Multimodal Data in BigQuery — Shows BigQuery multimodal analysis over structured tables and GCS media using ObjectRefs and Gemini.
• Performing Semantic Search in BigQuery — Builds semantic search over Stack Overflow questions in BigQuery with Vertex AI text embeddings.
• Patents Document Understanding with Gemini — Uses Gemini batch prediction on Vertex AI to extract structured fields and figure boxes from patent PDFs.
• Data Curation Pipeline: Splitting and Transcoding — Deduplicates video clips using video embeddings and BigQuery vector search.
• Retrieval Augmented Generation(RAG) with AlloyDB — Builds a RAG workflow over patent abstracts using AlloyDB vector search and Gemini on Vertex AI.
• Building a Gen AI RAG application with Vertex AI Feature Store and BigQuery — Builds a LangChain RAG Q&A app using BigQuery Vector Search and Vertex AI Feature Store.
• Augment Gemini Output with Vector Embeddings from BigQuery — Builds BigQuery vector-search RAG over patent abstracts and uses Gemini to generate project ideas.
• Run RAG Pipelines in BigQuery with BQML and Vector Search — Builds a BigQuery RAG pipeline over a PDF using Document AI, embeddings, vector search, and Gemini.
• Production & Scalable RAG Pipeline Using BigFrames — Builds a scalable BigFrames RAG pipeline over Stack Overflow data with BigQuery, Vertex AI, and LangChain.

Open Models (2)

• Running a Gemma 2-based agentic RAG with Ollama on Vertex AI and LangGraph — Deploys a Gemma 2 Ollama container on Vertex AI and uses it in a LangGraph SQL RAG agent.
• Use Any OSS Gen AI Model Against Your BigQuery Data — Deploys Llama 3.3 70B on Vertex AI and calls it from BigQuery ML for medical transcript analytics.

SDK (1)

• Getting started with Google Generative AI using the Gen AI SDK — Introduces Google Gen AI SDK on Vertex AI for Gemini prompts, tools, caching, batches, and embeddings.

Vertex AI Search (3)

• Custom Embeddings with Vertex AI Search — Builds a Vertex AI Search app using custom text-embedding-005 embeddings from Stack Overflow data.
• Gemini Enterprise answer eval using BLEU, ROUGE, BERT, Similarity Score — Evaluates Gemini Enterprise answers against a golden dataset with NLP metrics and saves results.
• MCP Server with Gemini Enterprise — Builds an MCP HR leave tool on Cloud Run, connects it to an ADK Gemini agent, and registers it with Gemini Enterprise.

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