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fix: sampling rate fix for openai realtime

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Abhishek Kumar 2026-05-16 17:44:49 +05:30
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docs/configurations/inference-providers.mdx
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@ -120,4 +120,68 @@ To use Gemini 3.1 Live with Dograh, you need a Google Gemini API key. Follow the
<Note>
When using a Realtime provider like Gemini Live, you do not need to configure separate TTS and STT services — the realtime model handles speech in and out. However, you **must** still configure an **LLM** under the LLM tab: it powers variable extraction and QA analysis, which the realtime service does not perform.
</Note>
## Gemini Live on Vertex AI
If you want to run Gemini Live through your own Google Cloud project — for billing consolidation, VPC controls, regional residency, or enterprise IAM — Dograh also supports Gemini Live via **Vertex AI** as a separate provider (`google_vertex_realtime`). The default model is `google/gemini-live-2.5-flash-native-audio`.
Unlike Google AI Studio (which uses a single Gemini API key), Vertex AI authenticates with a **service account** belonging to your Google Cloud project.
### Prerequisites
1. A Google Cloud project with billing enabled.
2. The Vertex AI API enabled on that project:
```bash
gcloud services enable aiplatform.googleapis.com --project=YOUR_PROJECT_ID
```
3. A service account with the **Vertex AI User** role (`roles/aiplatform.user`) on the project:
```bash
gcloud projects add-iam-policy-binding YOUR_PROJECT_ID \
--member="serviceAccount:YOUR_SA@YOUR_PROJECT_ID.iam.gserviceaccount.com" \
--role="roles/aiplatform.user"
```
4. A **JSON** key for that service account (P12 keys are not supported).
### Creating the service account key
1. In the GCP Console, go to **IAM & Admin → Service Accounts**.
2. Pick an existing service account (or create a new one).
3. Open the **Keys** tab → **Add Key → Create new key**.
4. Choose **JSON** as the key type and click **Create**.
5. The key file will download to your computer — store it securely and treat it as a secret.
<Note>
Always pick **JSON**, not P12. The Vertex AI client libraries used by Dograh only accept service-account JSON keys; P12 is a legacy format retained for older Google Workspace integrations.
</Note>
### Configuring Vertex AI Realtime in Dograh
1. Go to **Model Configurations** in your Dograh dashboard.
2. Enable the **Realtime** toggle.
3. Under the **Realtime** section, select `google_vertex_realtime` as the provider.
4. Fill in the fields:
| Field | What to put in |
|---|---|
| **Model** | Vertex publisher/model id, e.g. `google/gemini-live-2.5-flash-native-audio` |
| **Voice** | One of the built-in voices (Puck, Charon, Kore, Fenrir, Aoede) |
| **Language** | BCP-47 code (e.g. `en-US`) |
| **Project Id** | The `project_id` value from your service-account JSON |
| **Location** | GCP region where the model is available (e.g. `us-east4`) |
| **Credentials** | Paste the **entire contents** of the service-account JSON file |
| **API Key** | Leave blank — Vertex AI does not use API keys |
5. Save the configuration.
<Note>
Paste the whole JSON file into the **Credentials** field — including `private_key`, `client_email`, and all other entries. Don't try to extract individual fields. If `Credentials` is left blank, Dograh falls back to **Application Default Credentials (ADC)** from the host environment, which is useful when running Dograh on a GCP VM or GKE pod with an attached service account.
</Note>
<Note>
IAM changes can take up to ~60 seconds to propagate. If you see `Permission 'aiplatform.endpoints.predict' denied`, wait a minute and retry — or double-check that the role was granted to the same service account whose JSON you pasted.
</Note>