Add example scripts and README for Gemini API usage with ADC authentication

2026-06-10 17:51:14 +02:00
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+# Gemini API Python Examples (Gemini Enterprise Agent Platform (Vertex AI) / ADC Authentication)
+
+This directory contains examples for interacting with the Gemini API using the **`google-genai`** Python SDK and the **`gemini-3.5-flash`** model.
+
+To comply with enterprise security policies that disable static API keys, these examples use the **Gemini Enterprise Agent Platform** (Vertex AI) authenticated via secure **Application Default Credentials (ADC)**.
+
+## Core Features
+
+* **Gemini 3.5 Flash**: Offers frontier-level intelligence, advanced reasoning, and pro-level coding capability inside an ultra-fast, cost-efficient Flash tier.
+* **Agentic Capabilities**: Optimized out of the box for handling complex, multi-step agentic workflows and sustained reasoning tasks.
+* **Gemini Enterprise Agent Platform (Vertex AI) Integration**: Uses native Google Cloud IAM authorization instead of long-lived API keys.
+
+---
+
+## Prerequisites
+
+1. **Google Cloud Project**: You need an active Google Cloud Project.
+2. **Gemini Enterprise Agent Platform (Vertex AI) API Enabled**: Make sure the API (`aiplatform.googleapis.com`) is enabled in your project.
+3. **IAM Permissions**: Your Google account (or service account) must have the **Gemini Enterprise Agent Platform User** (Vertex AI User) (`roles/aiplatform.user`) role.
+4. **Google Cloud SDK (`gcloud`)**: Installed and configured on your machine.
+
+---
+
+## Setup Guide
+
+### 1. Install Dependencies
+Create a virtual environment (optional but recommended) and install the required dependencies:
+
+```bash
+# Create and activate a virtual environment
+python3 -m venv venv
+source venv/bin/activate
+
+# Install the modern google-genai library
+pip install -r requirements.txt
+```
+
+### 2. Authenticate locally with Application Default Credentials (ADC)
+Generate local credentials that the SDK will automatically detect:
+
+```bash
+gcloud auth application-default login
+```
+
+### 3. Set Environment Variables
+Specify your Google Cloud project and region:
+
+```bash
+# Set your GCP Project ID (Required)
+export GOOGLE_CLOUD_PROJECT="your-gcp-project-id"
+
+# Set your preferred location (Optional, defaults to us-central1)
+export GOOGLE_CLOUD_LOCATION="us-central1"
+```
+
+---
+
+## Running the Examples
+
+Run the script to verify the connection and see both standard content generation and config-based content generation in action:
+
+```bash
+python call_gemini.py
+```
+
+---
+
+## Troubleshooting
+
+### "Gemini Enterprise Agent Platform (Vertex AI) API has not been used in project..."
+Enable the API on your Google Cloud Console or use the `gcloud` CLI:
+```bash
+gcloud services enable aiplatform.googleapis.com --project="your-gcp-project-id"
+```
+
+### "Permission denied..." or "Lack of IAM permissions..."
+Ensure your authenticated user or active service account has the **Gemini Enterprise Agent Platform User** (Vertex AI User) role on your project:
+```bash
+gcloud projects add-iam-policy-binding your-gcp-project-id \
+  --member="user:your-email@example.com" \
+  --role="roles/aiplatform.user"
+```