gemini-2.0-flash

Model gemini-2.0-flash is used in 46 notebook(s) in this brain.

Concepts: Agent Engine · Agents & ADK · Applied Use Cases · Embeddings & Vector Search · Evaluation · Function Calling & Tools · Gemini Capabilities · Image & Video Generation · MLOps & Deployment · Open & Partner Models · Prompt Engineering · RAG & Grounding · Responsible AI · Tuning & Customization · Vertex AI Search · Vision

Notebooks

• Get started with embeddings tuning on Agent Platform — Tunes text-embedding-005 for retrieval using synthetic Gemini queries and Document AI PDF chunks.
• Anomaly Detection of Infrastructure Logs using Gemini and BigQuery Vector Search — Detects HDFS log anomalies with Gemini summaries, text embeddings, and BigQuery Vector Search.
• Evaluating a LangChain Agent on Vertex AI Agent Engine (Prebuilt template) — Deploys and evaluates a LangChain Gemini agent on Vertex AI Agent Engine using Gen AI Evaluation.
• Evaluate a LangGraph agent on Vertex AI Agent Engine (Customized template) — Builds a Gemini LangGraph agent on Agent Engine and evaluates tools, trajectories, and responses.
• Building and Deploying a Human-in-the-Loop LangGraph Application with Agent Engine on Vertex AI — Builds, tests, deploys, and resumes a human-in-the-loop LangGraph agent on Vertex AI Agent Engine.
• Building a Multi-Agent RAG Application with LangGraph and Agent Engine — Builds and deploys a LangGraph multi-agent RAG app on Vertex AI Agent Engine with Cloud SQL vector stores.
• Deploying an Agent with Agent Engine and MCP Toolbox for Databases — Deploys a Gemini hotel-booking agent on Agent Engine using Cloud SQL, Cloud Run Toolbox, and LangGraph.
• Monitor batch prediction with Gemini API — Orchestrates and monitors Gemini batch predictions with Vertex AI Pipelines and BigQuery output.
• Evaluate Gemini Structured Output — Evaluates Gemini structured JSON extraction from scanned order forms with Vertex AI Gen AI Evaluation.
• Use Gen AI Evaluation SDK to Evaluate Models in Vertex AI Studio, Model Garden, and Model Registry — Evaluates Gemini, Llama MaaS, Claude, and prompt templates with Vertex AI Gen AI Evaluation SDK.
• Evaluate your ADK agent using Vertex AI Gen AI Evaluation service — Evaluates an ADK product research agent with Vertex AI Gen AI Evaluation metrics.
• Migrating Foundation Models: A Practical Guide with Gen AI Evaluation Serivce — Compares model migration candidates with Vertex AI Gen AI Evaluation and prompt optimization workflows.
• Overview — Evaluates a CrewAI research crew with Phoenix tracing and Vertex AI trajectory metrics.
• Chain of Thought & ReAct — Demonstrates CoT prompting and ReAct agents with Vertex AI, LangChain, Wikipedia, and BigQuery.
• Question Answering with Generative Models on Vertex AI — Shows prompt patterns for Gemini question answering on Vertex AI, including simple fuzzy evaluation.
• Text Classification with Generative Models on Vertex AI — Classifies text with Gemini on Vertex AI using zero-shot, few-shot, and evaluation workflows.
• Text Extraction with Generative Models on Vertex AI — Uses Gemini on Vertex AI to extract structured facts from text with constrained and few-shot prompts.
• Text Summarization with Generative Models on Vertex AI — Demonstrates Gemini text summarization prompts on Vertex AI and evaluates summaries with ROUGE.
• Vertex AI RAG Engine with Vertex AI Search — Build a Vertex AI RAG Engine corpus backed by Vertex AI Search and query it with Gemini.
• Vertex AI RAG Engine with Weaviate — Creates a Vertex AI RAG Engine corpus backed by Weaviate and queries it with Gemini.
• Gen AI & LLM Security for developers — Shows prompt injection attacks against Gemini and layered mitigations with DLP, NL API, safety filters, and embeddings.
• Gen AI and LLM Security - ReAct and RAG attacks & mitigations — Demonstrates ReAct and RAG prompt-injection attacks with Gemini and simple mitigations.
• Building a photo recognition agent: Agent Engine setup — Sets up and deploys a Gemini LangChain agent on Agent Engine with Wikipedia and Vertex AI Search tools.
• Test Document AI Gemini — Compares Document AI entity extraction with Gemini-based extraction on a PDF.
• Use Retrieval Augmented Generation (RAG) with Gemini API — Builds a LangChain RAG pipeline over GitHub code notebooks using Gemini and Vertex AI embeddings.
• Code Vulnerability Scanning & Automated Remediation using Gemini API in Vertex AI (Gemini 2.0) — Scans Python files from GCS with Gemini 2.0 Flash and exports vulnerability reports to CSV and JSON.
• 🛡️ Agentic GraphRAG: Cybersecurity Threat Intelligence — Builds and deploys an ADK GraphRAG threat-intel agent using Neo4j and Vertex AI Agent Engine.
• 🌿 Eco-Nomad Swarm: 100% Real-Data Sustainable Travel Orchestration — Builds a Vertex AI ADK travel swarm using Neo4j GraphRAG and live APIs for sustainable trip briefs.
• ReAct (Reasoning + Acting) + Custom tool for Healthcare NL API + Gemini 2.0 + LangChain — Builds a LangChain ReAct agent using Gemini 2.0 and Healthcare NLP to suggest medical billing codes.
• Creative Content Generation with Gemini in Vertex AI and Imagen — Generates and personalizes GShoe marketing copy with Gemini, then outpaints product images with Imagen.
• Product attributes extraction and detailed descriptions from images using Gemini 2.0 — Extract product attributes and detailed retail descriptions from images with Gemini 2.0 on Vertex AI.
• RAG Based on Sensitive Data Protection using Faker — Builds a RAG flow that anonymizes PII with Cloud DLP, Faker, Firestore, Chroma, and Gemini.
• Intra Knowledge QnA — Builds a Vertex AI and LangChain RAG Q&A app over an IRS PDF using Chroma embeddings.
• 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.
• Building a Multimodal Chatbot for Warranty Claims using Gemini and Vector Search in Vertex AI — Builds a multimodal warranty-claims chatbot with Gemini, RAG, Vector Search, and function calling.
• Production & Scalable RAG Pipeline Using BigFrames — Builds a scalable BigFrames RAG pipeline over Stack Overflow data with BigQuery, Vertex AI, and LangChain.
• Identifcation of Scene Transitions in Movies Using Gemini — Uses Gemini to detect movie scene transitions from a video and matching VTT subtitles.
• Hugging Face DLCs: Using Gemma for running evaluations with Vertex AI Gen AI Evaluation — Deploys Gemma 2 on Vertex AI TGI and evaluates summarization with Gen AI Evaluation.
• Hugging Face DLCs: Serving Gemma 2 with multiple LoRA adapters with Text Generation Inference (TGI) on Vertex AI — Deploys Gemma 2 with SQL and code LoRA adapters on Vertex AI using a Hugging Face TGI custom handler.
• Guess who or what app using Hugging Face Deep Learning container model on Vertex AI — Builds a Gradio riddle game using Gemini and a Hugging Face FLUX model deployed on Vertex AI.
• Gemini Enterprise custom agent with prompt management — Builds a Gemini Enterprise ADK SQL agent using Vertex AI Prompt Management and schema file context.
• 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.

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