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Ge Api Wif Gcs

ASecurity

Sets up, tests, and tears down a GCS Data Store linked to a Gemini Enterprise engine, with support for Workforce Identity Federation (WIF) access. Use when the user requests linking Cloud Storage buckets to Gemini Enterprise or testing WIF-based GCS search.

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  • Added June 12, 2026
toolsgobashgcptestingapi

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  • api

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A100/100

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Scanned June 12, 2026

npx -y skills add jchavezar/vertex-ai-samples --skill ge_api_wif_gcs --agent claude-code

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SKILL.md
---
name: integrating-wif-gcs-streamassist
description: Sets up, tests, and tears down a GCS Data Store linked to a Gemini Enterprise engine, with support for Workforce Identity Federation (WIF) access. Use when the user requests linking Cloud Storage buckets to Gemini Enterprise or testing WIF-based GCS search.
---

# Integrating WIF, GCS, and StreamAssist

This skill provides recipes and automations to deploy an unstructured Google Cloud Storage (GCS) Data Store, hook it up to a Gemini Enterprise engine, and run testing using Workforce Identity Federation (WIF) or standard Application Default Credentials (ADC).

## When to use this skill
- Setting up a temporary or persistent GCS bucket for document search.
- Indexing PDFs from local storage (like `~/Downloads`) to GCP.
- Connecting unstructured data stores to an existing Gemini Enterprise app.
- Querying the `streamAssist` API with specific data store constraints.
- Cleaning up all resources after testing.

## Workflow

To execute the deployment and verify it:

1.  **Preparation**: Ensure you are logged into GCP and have selected the target project (`vtxdemos`).
2.  **Deployment**: Execute `setup.py` using `uv run`. This creates the bucket, uploads a PDF, creates the Data Store, imports the document, and attaches it.
3.  **Verification**: Execute `test_search.py` using `uv run`. Pass an optional query. By default it uses local ADC, but will auto-detect WIF token if `/tmp/entra_token.txt` is present.
4.  **Teardown**: Execute `teardown.py` using `uv run` to delete the bucket, datastore, and detach it from the engine.

```mermaid
graph TD
    A[Start] --> B[setup.py]
    B --> B1[Create gs://bucket]
    B1 --> B2[Upload PDF from Downloads]
    B2 --> B3[Create Data Store]
    B3 --> B4[Import GCS to Data Store]
    B4 --> B5[Attach to Gemini Engine]
    B5 --> C[test_search.py]
    C --> D[teardown.py]
    D --> D1[Detach Data Store]
    D1 --> D2[Delete Data Store]
    D2 --> D3[Delete gs://bucket]
    D3 --> E[End]
```

## Instructions

### 1. Running the Setup
Execute the following command in the workspace root:
```bash
uv run agy-recipes/ge_api_wif_gcs/scripts/setup.py
```
This script saves the generated resource names to `last_setup_resources.json` to allow clean teardown.

### 2. Testing the Search
To search the newly created GCS index using standard ADC credentials:
```bash
uv run agy-recipes/ge_api_wif_gcs/scripts/test_search.py "What are the financial highlights?"
```

To test using WIF, write your Microsoft Entra ID JWT token to `/tmp/entra_token.txt` first:
```bash
echo "YOUR_ENTRA_JWT_TOKEN" > /tmp/entra_token.txt
uv run agy-recipes/ge_api_wif_gcs/scripts/test_search.py "What are the financial highlights?"
```

### 3. Cleaning Up
To delete all resources created during setup and avoid any costs:
```bash
uv run agy-recipes/ge_api_wif_gcs/scripts/teardown.py
```

## Resources
- [Setup Script](scripts/setup.py)
- [Teardown Script](scripts/teardown.py)
- [Test Script](scripts/test_search.py)
- [Deployment Workflow](../../.agent/workflows/deploy-ge-wif-gcs.md)
- [Destroy Workflow](../../.agent/workflows/destroy-ge-wif-gcs.md)

Files in this skill

  • .env.example1.4 KB
  • README.md11.3 KB
  • SKILL.md3.1 KB
  • scripts/setup.py10.4 KB
  • scripts/teardown.py6.6 KB
  • scripts/test_search.py6.7 KB
  • tester/index.html25.1 KB
  • tester/minimal.html6.1 KB
  • tester/serve.py5.4 KB

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