vertexai
Please run pip install vertexai to use the Vertex SDK.
Decision gist · record as of 2026-08-14
Yes, if you are building AI agents or generative AI applications on Google Cloud. The package is actively maintained, has low install friction, carries a permissive license, and integrates deeply with Google's managed agent platform. Be aware that major API reorganization is planned (rebranding agent_engines to runtimes, relocating modules) before version 2.0.0; pin to < 2.0.0 if stability is critical. No known vulnerabilities.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Google Cloud credentials and a valid GCP project; API access to Gemini models must be enabled in your project.
- Low install friction with a single runtime dependency (google-cloud-aiplatform).
- Actively maintained with recent commits and steady releases; supports current Python versions (3.8+).
License · maintenance · safety
Apache 2.0 (permissive) — Apache 2.0 permissive license allows commercial and private use with minimal restrictions; suitable for most production and proprietary projects.
last release 2024-10-31 (652 days) · last repo commit 2026-08-14 · 903 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 4,741,294 downloads/mo, #2,242 on PyPI
Alternatives
Verify before relying
pip install vertexai
import vertexai
client = vertexai.Client(project='my-project', location='us-central1')
inference_results = client.evals.run_inference(
model="gemini-2.5-flash-preview-05-20",
src=prompts_df
)- Whether the upcoming rebranding (agent_engines → runtimes, module relocations) will occur before or after version 2.0.0 and what migration path is recommended.
- Performance characteristics and rate limits for concurrent agent deployments and inference calls.
- Compatibility guarantees with specific google-cloud-aiplatform versions beyond the single runtime dependency.
What it is and what it does
The vertexai package is Google's official Python SDK for the Gemini Enterprise Agent Platform, a managed service for building and deploying AI agents. It wraps the underlying google-cloud-aiplatform library and provides high-level APIs for defining agents using the Agent Development Kit (ADK), running generative AI inference and evaluation, optimizing prompts, and deploying agents to a managed runtime. The package handles authentication, API communication, and lifecycle management for agents and generative AI workloads on Google Cloud.
Typical workflows include instantiating a client with your GCP project and location, defining agent functions or using ADK to create agents with tool bindings, running inference or evaluation on model outputs, and deploying agents to Agent Engine for production use. The SDK supports both local testing (async streaming) and remote deployment, making it suitable for developers building conversational agents, question-answering systems, and other AI-driven applications that need to integrate with Google Cloud infrastructure.
Use it for
- Build and deploy multi-turn conversational agents with tool integration using the Agent Development Kit.
- Run batch inference and evaluation on generative AI model outputs using built-in metrics like exact_match and rouge_l_sum.
- Optimize prompts for better model performance using zero-shot or data-driven optimization methods.
- Manage agent sandboxes, sessions, and memory banks for stateful agent interactions.
- Evaluate and compare model responses against reference outputs in production workflows.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are building AI agents or generative AI applications on Google Cloud.
The package is actively maintained, has low install friction, carries a permissive license, and integrates deeply with Google's managed agent platform. Be aware that major API reorganization is planned (rebranding agent_engines to runtimes, relocating modules) before version 2.0.0; pin to < 2.0.0 if stability is critical. No known vulnerabilities.
Install
vertexai on PyPI
Before you install
Low install friction with a single runtime dependency (google-cloud-aiplatform). Actively maintained with recent commits and steady releases; supports current Python versions (3.8+).
Requires Google Cloud credentials and a valid GCP project; API access to Gemini models must be enabled in your project.
License in practice
Apache 2.0 permissive license allows commercial and private use with minimal restrictions; suitable for most production and proprietary projects.
Quickstart
pip install vertexai
import vertexai
client = vertexai.Client(project='my-project', location='us-central1')
inference_results = client.evals.run_inference(
model="gemini-2.5-flash-preview-05-20",
src=prompts_df
)Verify before relying
- Whether the upcoming rebranding (agent_engines → runtimes, module relocations) will occur before or after version 2.0.0 and what migration path is recommended.
- Performance characteristics and rate limits for concurrent agent deployments and inference calls.
- Compatibility guarantees with specific google-cloud-aiplatform versions beyond the single runtime dependency.
Package facts
| License | Apache 2.0 permissive |
| Python support | Supports the current Python release >=3.8 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagegoogle-cloud-aiplatform |
| Maintenance | Actively maintained 652 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 4,741,294 / month, #2,242 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: vertexai-1.71.1-py3-none-any.whl
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See also google-cloud-aiplatform · google-antigravity · google-agents-cli · google-genai · google-adk · google-generativeai · langchain-google-vertexai · livekit-plugins-google · llama-index-llms-vertex · notebooklm-py