Vertex AI Search Notebooks
20 notebooks from the
search/area of GoogleCloudPlatform/generative-ai.
(top Level) (1)
- Create a Vertex AI Datastore and Search Engine — Creates a Vertex AI Search datastore, imports GCS PDFs, creates an enterprise search engine, and queries it.
Custom Embeddings (1)
- Custom Embeddings with Vertex AI Search — Builds a Vertex AI Search app using custom text-embedding-005 embeddings from Stack Overflow data.
Custom Ranking (1)
- Clearbox for Ranking Tuning — Tunes Vertex AI Search ranking with ClearBox using BEIR FIQA signals and recall-based validation.
Gemini Enterprise (6)
- Gemini Enterprise answer eval using BLEU, ROUGE, BERT, Similarity Score — Evaluates Gemini Enterprise answers against a golden dataset with NLP metrics and saves results.
- Gemini Enterprise custom agent with prompt management — Builds a Gemini Enterprise ADK SQL agent using Vertex AI Prompt Management and schema file context.
- Gemini Enterprise custom agent with Vertex AI session — Builds a Gemini Enterprise travel agent using ADK sub-agents and persistent Vertex AI sessions.
- Intro to Gemini Enterprise — Shows how to call Gemini Enterprise search and answer APIs with the Discovery Engine Python SDK.
- 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.
- Open Source Models (Gemma) as a agent with Gemini Enterprise — Deploys Gemma on Cloud Run, wraps it with ADK, deploys to Agent Engine, and registers it in Gemini Enterprise.
Ranking API (1)
- Setup — Evaluates Discovery Engine semantic ranking on BEIR datasets with NDCG and ROC AUC metrics.
Tuning (1)
- Search tuning in Vertex AI Search — Tunes Vertex AI Search with JSONL/TSV Q&A data and tests a search app over Cloud Storage PDFs.
Vais Building Blocks (7)
- Defining custom attributes based on URL patterns in Vertex AI Search Website Datastores — Shows how to add URL-pattern custom attributes to a Vertex AI Search website datastore.
- Ingestion of Unstructured Documents with Metadata in Vertex AI Search — Ingests PDFs with metadata into Vertex AI Search and queries results with metadata filters.
- Inline Ingestion of Documents into Vertex AI Search — Shows inline rawBytes document ingestion, document operations, search, filters, and cleanup in Vertex AI Search.
- Event-based Triggering of Manual Recrawl for Vertex AI Search Advanced Website Datastores — Automates Vertex AI Search manual recrawl from JSON URL lists uploaded to Cloud Storage.
- Parsing and Chunking in Vertex AI Search: Featuring BYO Capabilities — Retrieves, reviews, exports, and reimports Vertex AI Search parsed and chunked documents with BYOC.
- Query-Level Boosting, Filtering, and Facets for Vertex AI Search Website Datastores — Configures Vertex AI Search website datastore schema, filters, facets, and boosting via REST.
- Recording Real-Time User Events in Vertex AI Search Datastores — Records real-time search and view-item user events for a Vertex AI Search website datastore.
vertexai Search Options (2)
- Q&A Chatbot with Vertex AI Search for summarized website results without advanced indexing — Builds a Q&A flow that searches a Vertex AI Search website data store, fetches the top page, and summarizes it with Gemini.
- Building Search Applications with Vertex AI Search — Builds Vertex AI Search workflows using Search API, Gemini grounding, and LangChain retrieval.