> ## Documentation Index
> Fetch the complete documentation index at: https://docs.qontext.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Gemini

> Connect Qontext to Gemini via the Agent Development Kit for enterprise context in Google Cloud

Implementing an enterprise-grade connection between **Qontext** and **Gemini** using the **Agent Development Kit (ADK)** lets you provide LLMs with proprietary company context while keeping access secure and permissioned. This guide walks through the integration for Google Cloud: **Secret Manager** for credentials and **ADK Session State** for conversational memory.

## Prerequisites

* A [Qontext](https://app.qontext.ai) account with ingested data
* Access to [Gemini Enterprise](https://console.cloud.google.com/gemini-enterprise) in your Google Cloud project

***

## Installation

### Step 1: Infrastructure and security setup

Set up your Google Cloud project and secure credentials before writing agent code.

<Steps>
  <Step title="Create or select a project">
    Open the [Google Cloud Console](https://console.cloud.google.com/) and create a new project or select an existing one from the project picker in the top bar.

    <img src="https://mintcdn.com/qontext/_QFVW1-CEYS44Oj4/ai-tools/images/gemini/gemini_select_project.png?fit=max&auto=format&n=_QFVW1-CEYS44Oj4&q=85&s=6e508ab86f6901b9541f60264571f0a0" alt="Select project" className="rounded-lg mt-4" style={{ maxWidth: '100%' }} width="2328" height="73" data-path="ai-tools/images/gemini/gemini_select_project.png" />
  </Step>

  <Step title="Enable required APIs">
    In the left navigation go to **APIs & Services → Enabled APIs & services**, then enable:

    * Vertex AI API
    * Secret Manager API
    * Discovery Engine API
    * Generative Language API
    * Gemini for Google Cloud API
    * Cloud Resource Manager API
  </Step>

  <Step title="Create an app (if needed)">
    If you don’t already have one, [create an app in your project](https://console.cloud.google.com/gen-app-builder/engines).
  </Step>

  <Step title="Configure Secret Manager">
    Store your Qontext API key  in Secret Manager so the agent can read them at runtime. Choose either the UI or the CLI.

    <Tabs>
      <Tab title="Via UI">
        1. In the left navigation, open **Security → Secret Manager**.
                   <img src="https://mintcdn.com/qontext/_QFVW1-CEYS44Oj4/ai-tools/images/gemini/gemini_secret_manager_nav.png?fit=max&auto=format&n=_QFVW1-CEYS44Oj4&q=85&s=4da0e68eb288d2da8c374cc2396218e0" alt="Secret manager navigation" className="rounded-lg mt-4" style={{ maxWidth: '70%' }} width="1294" height="1774" data-path="ai-tools/images/gemini/gemini_secret_manager_nav.png" />
        2. Click **Create secret** for each of the following:
           * **Name:** `QONTEXT_API_KEY_SECRET` — value: your Qontext API key
           * **Name:** `QONTEXT_VAULT_ID_SECRET` — value: your vault ID
        3. Grant the agent’s service account access to these secrets:
           * Go to **IAM & Admin → IAM**.
           * Enable **Include Google-provided role grants** (checkbox at top right).
                     <img src="https://mintlify.s3.us-west-1.amazonaws.com/qontext/images/gemini/gemini_secret_manager_account.png" alt="Secret manager account" className="rounded-lg mt-4" style={{ maxWidth: '100%' }} />
           * Find the Vertex AI Reasoning Engine service agent (e.g. `service-PROJECT_NUMBER@gcp-sa-aiplatform-re.iam.gserviceaccount.com`) and ensure it has:
             * **Secret Manager Secret Accessor**
             * **Vertex AI Reasoning Engine Service Agent**
      </Tab>

      <Tab title="Via CLI">
        Connect your local machine to Google Cloud first: [install and initialize the gcloud CLI](https://cloud.google.com/sdk/docs/install) if needed, then run:

        1. Grant your agent’s service account access to the secrets (replace `your-agent-sa` and `your-project` with your service account and project ID):

        ```bash Shell theme={null}
        gcloud secrets add-iam-policy-binding QONTEXT_API_KEY_SECRET \
            --member="serviceAccount:your-agent-sa@your-project.iam.gserviceaccount.com" \
            --role="roles/secretmanager.secretAccessor"

        gcloud secrets add-iam-policy-binding QONTEXT_VAULT_ID_SECRET \
            --member="serviceAccount:your-agent-sa@your-project.iam.gserviceaccount.com" \
            --role="roles/secretmanager.secretAccessor"
        ```

        2. Log in to your Google account locally:

        ```bash Shell theme={null}
        gcloud auth login # Log in to your account
        gcloud config set project YOUR_PROJECT_ID # Set project ID (Find via service account email address)
        gcloud services enable secretmanager.googleapis.com # Enable Secret Manager APIs
        gcloud config list # Verify changes
        ```

        3. Create the following two secrets:

        ```bash Shell theme={null}
        gcloud secrets create QONTEXT_API_KEY_SECRET --replication-policy="automatic"
        gcloud secrets create QONTEXT_VAULT_ID_SECRET --replication-policy="automatic"
        ```

        4. Add the secret values (replace with your real API key and vault ID):

        ```bash Shell theme={null}
        echo -n "your-api-key" | gcloud secrets versions add QONTEXT_API_KEY_SECRET --data-file=-
        echo -n "your-vault-id" | gcloud secrets versions add QONTEXT_VAULT_ID_SECRET --data-file=-
        ```
      </Tab>
    </Tabs>
  </Step>
</Steps>

***

### Step 2: Set up your local development environment

Prepare your machine for ADK development and the example agent.

<Steps>
  <Step title="Create a project directory and virtual environment">
    Run the following to create a dedicated folder for your agent and isolate dependencies in a virtual environment:

    ```bash Shell theme={null}
    mkdir qontext_agent && cd qontext_agent
    python3 -m venv .adk_env
    source .adk_env/bin/activate
    ```
  </Step>

  <Step title="Install the ADK and required libraries">
    Install the Agent Development Kit, Secret Manager client, and an async HTTP client:

    ```bash Shell theme={null}
    pip install google-adk google-cloud-secret-manager aiohttp
    ```
  </Step>

  <Step title="Add the agent code and requirements">
    Use the example agent and requirements file from the Qontext examples repository and add a .env file:

    * [**agent.py**](https://github.com/qontext-ai/examples/blob/main/examples/gemini-agent/agent.py) — main agent logic and Qontext retrieval tool
    * [**requirements.txt**](https://github.com/qontext-ai/examples/blob/main/examples/gemini-agent/requirements.txt) — dependencies for local and deployed runs
    * **.env**: create a .env file in the same folder and save your project ID as `GCP_PROJECT_ID`

    Download or clone these into your `qontext_agent` directory. Adjust the agent (e.g. functions, model, or prompt) to match your use case.
  </Step>
</Steps>

***

### Step 3: Local testing and debugging

Test the agent on your machine with the ADK web UI before deploying.

<Steps>
  <Step title="Run the ADK web UI">
    From the parent directory of your agent folder (so ADK can find the agent module), start the web interface:

    ```bash Shell theme={null}
    adk web
    ```
  </Step>

  <Step title="Test the agent">
    Open [http://127.0.0.1:8000](http://127.0.0.1:8000) in your browser. Verify that:

    * The agent responds to prompts
    * It uses the correct Qontext vault
    * Conversational memory works across turns (ADK session state)
    * If you encounter any problems, reach out to [support@qontext.ai](mailto:support@qontext.ai)
  </Step>
</Steps>

***

### Step 4: Deploy to Vertex AI Agent Engine

After local testing, deploy the agent to Google Cloud’s managed runtime.

From your project root (one level above the agent folder), run:

```bash Shell theme={null}
adk deploy agent_engine \
  --project=YOUR_PROJECT_ID \
  --region=YOUR_REGION \
  --display_name="qontext-agent-example" \
  --requirements_file=qontext_agent/requirements.txt \
  --adk_app_object=root_agent \
  --env_file=qontext_agent/.env \
  --trace_to_cloud \
  qontext_agent
```

Replace `YOUR_PROJECT_ID` and `YOUR_REGION` (e.g. `europe-west1`).

<Info>
  Save the URL that appears in the command output. You will need it for the agent connection in Step 5 (Google Cloud / Gemini Enterprise).
</Info>

***

### Step 5: Connect and go live

Connect your deployed agent to Gemini Enterprise so you can use it in chat.

<Steps>
  <Step title="Open the Agents tab">
    In [Gemini Enterprise](https://console.cloud.google.com/gemini-enterprise), go to your project and region, then open the **Agents** tab for your app (the same app you used in Step 4).

    <img src="https://mintcdn.com/qontext/_QFVW1-CEYS44Oj4/ai-tools/images/gemini/gemini_agents_page.png?fit=max&auto=format&n=_QFVW1-CEYS44Oj4&q=85&s=fe4bcf1d65ef35c1e812dde1ba4ca64c" alt="Agent page" className="rounded-lg mt-4" style={{ maxWidth: '100%' }} width="3024" height="1890" data-path="ai-tools/images/gemini/gemini_agents_page.png" />
  </Step>

  <Step title="Create a custom agent">
    Click on **Add agent** and choose **Custom agent via Agent Engine**.
  </Step>

  <Step title="Skip Authorizations">
    On the Authorizations step, click **Next** to skip.
  </Step>

  <Step title="Name the agent and add the Agent Engine URL">
    Give the agent a meaningful **name** and **description**. In the URL field, enter the **Agent Engine reasoning engine URL** that the CLI returned after Step 4 (when you ran `adk deploy agent_engine`).

    <img src="https://mintcdn.com/qontext/_QFVW1-CEYS44Oj4/ai-tools/images/gemini/gemini_create_agent.png?fit=max&auto=format&n=_QFVW1-CEYS44Oj4&q=85&s=59cb5b959c01431e262c4cbb33f558fe" alt="Agent creation" className="rounded-lg mt-4" style={{ maxWidth: '100%' }} width="3024" height="1890" data-path="ai-tools/images/gemini/gemini_create_agent.png" />
  </Step>

  <Step title="Create and use the agent">
    Click **Create**. Your agent is then available in Gemini Enterprise. You can use it in chat by typing **@** and selecting your agent name (e.g. `@YourAgentName`).
  </Step>
</Steps>

***

Need Help? If you encounter issues with the Gemini integration, reach out to [support@qontext.ai](mailto:support@qontext.ai).

Also, check the [Vertex AI Agent Development Kit docs](https://docs.cloud.google.com/agent-builder/agent-engine/develop/adk) for more deployment and configuration options.