wehub-resource-sync
544 lines
22 KiB
Plaintext
544 lines
22 KiB
Plaintext
{
|
|
"cells": [
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "oXnEutuDQa9c"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"# Copyright 2025 Google LLC\n",
|
|
"#\n",
|
|
"# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
|
|
"# you may not use this file except in compliance with the License.\n",
|
|
"# You may obtain a copy of the License at\n",
|
|
"#\n",
|
|
"# https://www.apache.org/licenses/LICENSE-2.0\n",
|
|
"#\n",
|
|
"# Unless required by applicable law or agreed to in writing, software\n",
|
|
"# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
|
|
"# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
|
|
"# See the License for the specific language governing permissions and\n",
|
|
"# limitations under the License."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "JAPoU8Sm5E6e"
|
|
},
|
|
"source": [
|
|
"# Getting Started with the Live API Native Audio\n",
|
|
"\n",
|
|
"\n",
|
|
"<table align=\"left\">\n",
|
|
" <td style=\"text-align: center\">\n",
|
|
" <a href=\"https://colab.research.google.com/github/GoogleCloudPlatform/generative-ai/blob/main/gemini/multimodal-live-api/intro_live_api_native_audio.ipynb\">\n",
|
|
" <img width=\"32px\" src=\"https://www.gstatic.com/pantheon/images/bigquery/welcome_page/colab-logo.svg\" alt=\"Google Colaboratory logo\"><br> Open in Colab\n",
|
|
" </a>\n",
|
|
" </td>\n",
|
|
" <td style=\"text-align: center\">\n",
|
|
" <a href=\"https://console.cloud.google.com/vertex-ai/colab/import/https:%2F%2Fraw.githubusercontent.com%2FGoogleCloudPlatform%2Fgenerative-ai%2Fmain%2Fgemini%2Fmultimodal-live-api%2Fintro_live_api_native_audio.ipynb\">\n",
|
|
" <img width=\"32px\" src=\"https://lh3.googleusercontent.com/JmcxdQi-qOpctIvWKgPtrzZdJJK-J3sWE1RsfjZNwshCFgE_9fULcNpuXYTilIR2hjwN\" alt=\"Google Cloud Colab Enterprise logo\"><br> Open in Colab Enterprise\n",
|
|
" </a>\n",
|
|
" </td>\n",
|
|
" <td style=\"text-align: center\">\n",
|
|
" <a href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/GoogleCloudPlatform/generative-ai/main/gemini/multimodal-live-api/intro_live_api_native_audio.ipynb\">\n",
|
|
" <img src=\"https://www.gstatic.com/images/branding/gcpiconscolors/vertexai/v1/32px.svg\" alt=\"Vertex AI logo\"><br> Open in Vertex AI Workbench\n",
|
|
" </a>\n",
|
|
" </td>\n",
|
|
" <td style=\"text-align: center\">\n",
|
|
" <a href=\"https://github.com/GoogleCloudPlatform/generative-ai/blob/main/gemini/multimodal-live-api/intro_live_api_native_audio.ipynb\">\n",
|
|
" <img width=\"32px\" src=\"https://raw.githubusercontent.com/primer/octicons/refs/heads/main/icons/mark-github-24.svg\" alt=\"GitHub logo\"><br> View on GitHub\n",
|
|
" </a>\n",
|
|
" </td>\n",
|
|
"</table>\n",
|
|
"\n",
|
|
"<div style=\"clear: both;\"></div>\n",
|
|
"\n",
|
|
"<p>\n",
|
|
"<b>Share to:</b>\n",
|
|
"\n",
|
|
"<a href=\"https://www.linkedin.com/sharing/share-offsite/?url=https%3A//github.com/GoogleCloudPlatform/generative-ai/blob/main/gemini/multimodal-live-api/intro_live_api_native_audio.ipynb\" target=\"_blank\">\n",
|
|
" <img width=\"20px\" src=\"https://upload.wikimedia.org/wikipedia/commons/8/81/LinkedIn_icon.svg\" alt=\"LinkedIn logo\">\n",
|
|
"</a>\n",
|
|
"\n",
|
|
"<a href=\"https://bsky.app/intent/compose?text=https%3A//github.com/GoogleCloudPlatform/generative-ai/blob/main/gemini/multimodal-live-api/intro_live_api_native_audio.ipynb\" target=\"_blank\">\n",
|
|
" <img width=\"20px\" src=\"https://upload.wikimedia.org/wikipedia/commons/7/7a/Bluesky_Logo.svg\" alt=\"Bluesky logo\">\n",
|
|
"</a>\n",
|
|
"\n",
|
|
"<a href=\"https://twitter.com/intent/tweet?url=https%3A//github.com/GoogleCloudPlatform/generative-ai/blob/main/gemini/multimodal-live-api/intro_live_api_native_audio.ipynb\" target=\"_blank\">\n",
|
|
" <img width=\"20px\" src=\"https://upload.wikimedia.org/wikipedia/commons/5/5a/X_icon_2.svg\" alt=\"X logo\">\n",
|
|
"</a>\n",
|
|
"\n",
|
|
"<a href=\"https://reddit.com/submit?url=https%3A//github.com/GoogleCloudPlatform/generative-ai/blob/main/gemini/multimodal-live-api/intro_live_api_native_audio.ipynb\" target=\"_blank\">\n",
|
|
" <img width=\"20px\" src=\"https://redditinc.com/hubfs/Reddit%20Inc/Brand/Reddit_Logo.png\" alt=\"Reddit logo\">\n",
|
|
"</a>\n",
|
|
"\n",
|
|
"<a href=\"https://www.facebook.com/sharer/sharer.php?u=https%3A//github.com/GoogleCloudPlatform/generative-ai/blob/main/gemini/multimodal-live-api/intro_live_api_native_audio.ipynb\" target=\"_blank\">\n",
|
|
" <img width=\"20px\" src=\"https://upload.wikimedia.org/wikipedia/commons/5/51/Facebook_f_logo_%282019%29.svg\" alt=\"Facebook logo\">\n",
|
|
"</a>\n",
|
|
"</p>"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "84f0f73a0f76"
|
|
},
|
|
"source": [
|
|
"| Authors |\n",
|
|
"| --- |\n",
|
|
"| [Eric Dong](https://github.com/gericdong) |\n",
|
|
"| [Holt Skinner](https://github.com/holtskinner) |"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "tvgnzT1CKxrO"
|
|
},
|
|
"source": [
|
|
"## Overview\n",
|
|
"\n",
|
|
"This notebook demonstrates how to connect to the Gemini Live API using the Google Gen AI SDK for Python, focusing on **Native Audio** features like **Proactive Audio** and **Affective Dialog**.\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "gPiTOAHURvTM"
|
|
},
|
|
"source": [
|
|
"## Getting Started"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "CHRZUpfWSEpp"
|
|
},
|
|
"source": [
|
|
"### Install Google Gen AI SDK for Python\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "sG3_LKsWSD3A"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"%pip install --upgrade --quiet google-genai"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "HlMVjiAWSMNX"
|
|
},
|
|
"source": [
|
|
"### Authenticate your notebook environment (Colab only)\n",
|
|
"\n",
|
|
"If you are running this notebook on Google Colab, run the cell below to authenticate your environment."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "12fnq4V0SNV3"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import sys\n",
|
|
"\n",
|
|
"if \"google.colab\" in sys.modules:\n",
|
|
" from google.colab import auth\n",
|
|
"\n",
|
|
" auth.authenticate_user()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "0Ef0zVX-X9Bg"
|
|
},
|
|
"source": [
|
|
"### Import libraries\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "LymmEN6GSTn-"
|
|
},
|
|
"source": [
|
|
"### Set Google Cloud project information and create client\n",
|
|
"\n",
|
|
"To get started using Vertex AI, you must have an existing Google Cloud project and [enable the Vertex AI API](https://console.cloud.google.com/flows/enableapi?apiid=aiplatform.googleapis.com).\n",
|
|
"\n",
|
|
"Learn more about [setting up a project and a development environment](https://cloud.google.com/vertex-ai/docs/start/cloud-environment)."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "Nqwi-5ufWp_B"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"# Use the environment variable if the user doesn't provide Project ID.\n",
|
|
"import os\n",
|
|
"from typing import Any\n",
|
|
"\n",
|
|
"import numpy as np\n",
|
|
"from IPython.display import Audio, Markdown, display\n",
|
|
"from google.genai.types import (\n",
|
|
" AudioTranscriptionConfig,\n",
|
|
" Content,\n",
|
|
" LiveConnectConfig,\n",
|
|
" Part,\n",
|
|
" ProactivityConfig,\n",
|
|
")\n",
|
|
"\n",
|
|
"# fmt: off\n",
|
|
"PROJECT_ID = \"[your-project-id]\" # @param {type: \"string\", placeholder: \"[your-project-id]\", isTemplate: true}\n",
|
|
"# fmt: on\n",
|
|
"if not PROJECT_ID or PROJECT_ID == \"[your-project-id]\":\n",
|
|
" PROJECT_ID = str(os.environ.get(\"GOOGLE_CLOUD_PROJECT\"))\n",
|
|
"\n",
|
|
"LOCATION = \"us-central1\"\n",
|
|
"\n",
|
|
"from google import genai\n",
|
|
"\n",
|
|
"client = genai.Client(enterprise=True, project=PROJECT_ID, location=LOCATION)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "ff2e5eefc586"
|
|
},
|
|
"source": [
|
|
"## Using the Gemini 2.5 Flash Native Audio\n",
|
|
"\n",
|
|
"\n",
|
|
"Gemini 2.5 Flash with Live API features native audio dialog capabilities.\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "86b26e8aa6ad"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"MODEL_ID = \"gemini-live-2.5-flash-native-audio\" # @param {type: \"string\"}"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "0zJJHEJnNN4C"
|
|
},
|
|
"source": [
|
|
"## Reusable Live API Modules\n",
|
|
"\n",
|
|
"The following functions are designed to manage the session configuration, handle a single conversational turn, and execute a multi-turn session.\n",
|
|
"\n",
|
|
"### `configure_session`\n",
|
|
"\n",
|
|
"This function creates a flexible `LiveConnectConfig` object to enable or disable features like system instruction, transcription, proactivity, and affective dialog."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "TrwmaJnEVOaz"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"def configure_session(\n",
|
|
" system_instruction: str | None = None,\n",
|
|
" enable_transcription: bool = True,\n",
|
|
" enable_proactivity: bool = False,\n",
|
|
" enable_affective_dialog: bool = False,\n",
|
|
") -> LiveConnectConfig:\n",
|
|
" \"\"\"Creates a configuration object for the Live Connect session.\"\"\"\n",
|
|
" input_transcription = AudioTranscriptionConfig() if enable_transcription else None\n",
|
|
" output_transcription = AudioTranscriptionConfig() if enable_transcription else None\n",
|
|
" # NOTE: Proactive Audio requires proactive_audio=True in ProactivityConfig\n",
|
|
" proactivity = (\n",
|
|
" ProactivityConfig(proactive_audio=True) if enable_proactivity else None\n",
|
|
" )\n",
|
|
"\n",
|
|
" config = LiveConnectConfig(\n",
|
|
" response_modalities=[\"AUDIO\"],\n",
|
|
" system_instruction=system_instruction,\n",
|
|
" input_audio_transcription=input_transcription,\n",
|
|
" output_audio_transcription=output_transcription,\n",
|
|
" proactivity=proactivity,\n",
|
|
" enable_affective_dialog=enable_affective_dialog,\n",
|
|
" )\n",
|
|
"\n",
|
|
" return config"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "n2Y1k4RlAvsC"
|
|
},
|
|
"source": [
|
|
"### `send_and_receive_turn`\n",
|
|
"\n",
|
|
"This asynchronous function manages a single user turn: it sends the text, streams the audio and transcription messages back from the model, and displays the results."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "CWqqbDY97tEz"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"async def send_and_receive_turn(\n",
|
|
" session: genai.live.AsyncSession, text_input: str\n",
|
|
") -> dict[str, Any]:\n",
|
|
" \"\"\"Sends a single text turn to the Live Connect session and processes the streaming response.\"\"\"\n",
|
|
" display(Markdown(\"\\n---\"))\n",
|
|
" display(Markdown(f\"**Input:** {text_input}\"))\n",
|
|
"\n",
|
|
" # 1. Send the user's content\n",
|
|
" await session.send_client_content(\n",
|
|
" turns=Content(role=\"user\", parts=[Part(text=text_input)])\n",
|
|
" )\n",
|
|
"\n",
|
|
" audio_data = []\n",
|
|
" input_transcriptions = []\n",
|
|
" output_transcriptions = []\n",
|
|
"\n",
|
|
" # 2. Process the streaming response messages\n",
|
|
" async for message in session.receive():\n",
|
|
" # Collect input transcription (what the model heard the user say)\n",
|
|
" if (\n",
|
|
" message.server_content.input_transcription\n",
|
|
" and message.server_content.input_transcription.text\n",
|
|
" ):\n",
|
|
" input_transcriptions.append(message.server_content.input_transcription.text)\n",
|
|
"\n",
|
|
" # Collect output transcription (the model's spoken response text)\n",
|
|
" if (\n",
|
|
" message.server_content.output_transcription\n",
|
|
" and message.server_content.output_transcription.text\n",
|
|
" ):\n",
|
|
" output_transcriptions.append(\n",
|
|
" message.server_content.output_transcription.text\n",
|
|
" )\n",
|
|
"\n",
|
|
" # Collect audio data (the model's spoken response audio chunks)\n",
|
|
" if (\n",
|
|
" message.server_content.model_turn\n",
|
|
" and message.server_content.model_turn.parts\n",
|
|
" ):\n",
|
|
" for part in message.server_content.model_turn.parts:\n",
|
|
" if part.inline_data:\n",
|
|
" # Assuming the audio data is always in np.int16 format (24000Hz rate)\n",
|
|
" audio_data.append(\n",
|
|
" np.frombuffer(part.inline_data.data, dtype=np.int16)\n",
|
|
" )\n",
|
|
"\n",
|
|
" # 3. Display the results\n",
|
|
" results = {\n",
|
|
" \"audio_data\": audio_data,\n",
|
|
" \"input_transcription\": \"\".join(input_transcriptions),\n",
|
|
" \"output_transcription\": \"\".join(output_transcriptions),\n",
|
|
" }\n",
|
|
"\n",
|
|
" if results[\"input_transcription\"]:\n",
|
|
" display(Markdown(f\"**Input transcription >** {results['input_transcription']}\"))\n",
|
|
"\n",
|
|
" if results[\"audio_data\"]:\n",
|
|
" # Concatenate all audio chunks into one array\n",
|
|
" full_audio = np.concatenate(results[\"audio_data\"])\n",
|
|
" display(\n",
|
|
" Audio(full_audio, rate=24000, autoplay=True)\n",
|
|
" ) # NOTE: 24000 is the required rate\n",
|
|
" else:\n",
|
|
" # This will be triggered on the turns where the model remains silent due to the system instruction\n",
|
|
" display(\n",
|
|
" Markdown(\n",
|
|
" \"**Model Response:** *No audio response received (filtered by system instruction).*\"\n",
|
|
" )\n",
|
|
" )\n",
|
|
"\n",
|
|
" if results[\"output_transcription\"]:\n",
|
|
" display(\n",
|
|
" Markdown(f\"**Output transcription >** {results['output_transcription']}\")\n",
|
|
" )\n",
|
|
"\n",
|
|
" return results"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "jFA_gCdiBw3u"
|
|
},
|
|
"source": [
|
|
"### `run_live_session`\n",
|
|
"\n",
|
|
"This function manages the full conversational context, establishing the connection and running a series of defined `turns`.\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "28Jh1_xTBHfm"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"async def run_live_session(\n",
|
|
" model_id: str,\n",
|
|
" config: LiveConnectConfig,\n",
|
|
" turns: list[str],\n",
|
|
"):\n",
|
|
" \"\"\"Establishes the Live Connect session and runs a series of conversational turns.\"\"\"\n",
|
|
" display(Markdown(\"## Starting Live Connect Session...\"))\n",
|
|
" system_instruction = config.system_instruction\n",
|
|
" display(Markdown(f\"**System Instruction:** *{system_instruction}*\"))\n",
|
|
"\n",
|
|
" try:\n",
|
|
" # Use an asynchronous context manager to establish and manage the session lifecycle\n",
|
|
" async with client.aio.live.connect(\n",
|
|
" model=model_id,\n",
|
|
" config=config,\n",
|
|
" ) as session:\n",
|
|
" display(\n",
|
|
" Markdown(f\"**Status:** Session established with model: `{model_id}`\")\n",
|
|
" )\n",
|
|
"\n",
|
|
" all_results = []\n",
|
|
" for turn in turns:\n",
|
|
" # Send each user input sequentially\n",
|
|
" result = await send_and_receive_turn(session, turn)\n",
|
|
" all_results.append(result)\n",
|
|
"\n",
|
|
" display(Markdown(\"\\n---\"))\n",
|
|
" display(Markdown(\"**Status:** All turns complete. Session closed.\"))\n",
|
|
" return all_results\n",
|
|
" except Exception as e:\n",
|
|
" display(Markdown(f\"**Error:** Failed to connect or run session: {e}\"))\n",
|
|
" return []"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "48b169cdce9c"
|
|
},
|
|
"source": [
|
|
"## Scenario 1: Proactive Audio (Chime-in Behavior)\n",
|
|
"\n",
|
|
"This example uses a **System Instruction** and **Proactive Audio** to test the model's ability to remain silent when the topic is off-subject (French cuisine) and chime in only when the conversation shifts to the instructed topic (Italian cooking).\n",
|
|
"\n",
|
|
"### Conversation Setup and Execution"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "cdcuYAaJAu5H"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"session_config = configure_session(\n",
|
|
" system_instruction=\"You are an AI assistant in Italian cooking, chime in only when the topic is about Italian cooking.\",\n",
|
|
" enable_proactivity=True,\n",
|
|
")\n",
|
|
"\n",
|
|
"conversation_turns = [\n",
|
|
" # Speaker A speaks, general topic, the model should be silent.\n",
|
|
" \"Hey, I was just thinking about my dinner plans. I really love cooking.\",\n",
|
|
" # Speaker B speaks, off-topic (French cuisine). The model should be silent.\n",
|
|
" \"Oh yes, me too. I love French cuisine, especially making a good coq au vin. I think I'll make that tonight.\",\n",
|
|
" # Speaker A speaks, shifts to Italian topic. The model should chime in.\n",
|
|
" \"Hmm, that sounds complicated. I prefer Italian food. Say, do you know how to make a simple Margherita pizza recipe?\",\n",
|
|
"]\n",
|
|
"\n",
|
|
"results = await run_live_session(MODEL_ID, session_config, conversation_turns)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "645d33adaabd"
|
|
},
|
|
"source": [
|
|
"## Scenario 2: Affective Dialog (Empathy)\n",
|
|
"\n",
|
|
"This scenario enables **Affective Dialog** (`enable_affective_dialog=True`) and uses a system instruction to create a senior technical advisor persona. The user's input is phrased to convey **frustration**, prompting an empathetic and helpful response from the model.\n",
|
|
"\n",
|
|
"### Configuration and Execution"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "LHT8O-oNy8aQ"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"affective_config = configure_session(\n",
|
|
" enable_transcription=False,\n",
|
|
" enable_proactivity=False,\n",
|
|
" enable_affective_dialog=True,\n",
|
|
" system_instruction=\"You are a senior technical advisor for a complex AI project.\",\n",
|
|
")\n",
|
|
"\n",
|
|
"affective_dialog_turns = [\n",
|
|
" \"I have been staring at this API docs for two hours now! It's so confusing and I can't even find where to start the streaming request. I'm completely stuck!\",\n",
|
|
" # A follow-up turn to see if the model maintains the helpful persona\n",
|
|
" \"Okay, thanks. I'm using Python. What is the single most important parameter I need to set up for a successful streaming connection?\",\n",
|
|
"]\n",
|
|
"\n",
|
|
"results = await run_live_session(MODEL_ID, affective_config, affective_dialog_turns)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "usjiqTDXfk_6"
|
|
},
|
|
"source": [
|
|
"## What's next\n",
|
|
"\n",
|
|
"- See the [Live API reference docs](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/multimodal-live).\n",
|
|
"- Explore other notebooks in the [Google Cloud Generative AI GitHub repository](https://github.com/GoogleCloudPlatform/generative-ai)."
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"colab": {
|
|
"name": "intro_live_api_native_audio.ipynb",
|
|
"toc_visible": true
|
|
},
|
|
"kernelspec": {
|
|
"display_name": "Python 3",
|
|
"name": "python3"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 0
|
|
}
|