How do I set up Python code to record, send, and receive Grok 4 voice responses

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Setting up Python Environment for Grok 4 Voice Interaction

1. Sign up for xAI and get API Key
To interact with Grok 4 programmatically, you first need to get an API key from the xAI platform by creating an account.

2. Install Required Packages
Install the `xai_sdk` Python package, which provides clients for calling Grok 4 API. You may also need additional audio libraries like `pyaudio` or `sounddevice` for recording and playing audio.

3. Configure Environment Variables for Security
Store your API key in environment variables and use the `python-dotenv` package to load them securely in your Python code, preventing hardcoding sensitive information.

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Recording Audio from Microphone in Python

To record voice input that will be sent to Grok 4, use Python audio libraries such as `sounddevice` or `pyaudio`. Here's an example using `sounddevice`:

python
import sounddevice as sd
import numpy as np
import wavio

def record_audio(duration=5, fs=16000, filename="input.wav"):
    print("Recording...")
    audio = sd.rec(int(duration * fs), samplerate=fs, channels=1)
    sd.wait()
    wavio.write(filename, audio, fs, sampwidth=2)
    print(f"Recording saved to {filename}")
    return filename

# Record 5 seconds of audio
record_audio()

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Sending Recorded Audio to Grok 4 API for Voice Response

The Grok 4 voice interaction involves sending the audio input to Grok's endpoint that accepts voice input and returns voice responses. This usually requires:

- Encoding audio in a format accepted by the API (e.g., WAV, base64 encoded).
- Making HTTP POST requests using the `xai_sdk` or other HTTP clients like `requests`.
- Parsing the response which contains audio data of Grok's voice reply.

A basic example of sending audio and receiving voice response could look (in pseudocode) like:

python
from xai_sdk import Client
import os
import base64

# Initialize Grok 4 client
client = Client(api_key=os.getenv('XAI_API_KEY'))

# Read recorded audio file and encode it
with open("input.wav", "rb") as f:
    audio_data = f.read()
audio_base64 = base64.b64encode(audio_data).decode('utf-8')

# Prepare request data (depends on API design, check docs)
request_data = {
    "audio": audio_base64,
    "mode": "voice"
}

# Send voice input to Grok 4
response = client.sampler.sample(
    model="grok-4-0709",
    prompt=request_data,
    temperature=0.4,
    max_tokens=100
)

# The response usually contains a base64 encoded audio reply
audio_response_base64 = response.content  # Adjust according to actual API

# Decode and save Grok's audio response
audio_response = base64.b64decode(audio_response_base64)
with open("grok_response.wav", "wb") as f:
    f.write(audio_response)

You should adjust this example according to the xAI API's exact voice input/output format and endpoint requirements, which include real-time streaming or chunked data exchange for smooth voice interaction.

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Playing Grok's Voice Responses

Once you have Grok's audio response saved locally, play it back using Python libraries such as `sounddevice` or a media player module:

python
import sounddevice as sd
import wavio

def play_audio(filename):
    # Read the WAV file
    audio, fs = wavio.read(filename)
    print("Playing Grok's response...")
    sd.play(audio, fs)
    sd.wait()

play_audio("grok_response.wav")

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Handling Real-Time Conversation Flow

To create a seamless conversation experience, consider implementing a loop that:

1. Records your voice input.
2. Sends the recorded audio to Grok 4 API.
3. Receives the audio response and plays it back.
4. Repeats to continue interaction.

Add error handling for connection issues or recognition errors to improve stability.

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Additional Insights from Grok 4 API Capabilities

Grok 4 supports a large context window (up to 256,000 tokens) and advanced speech compression, reducing latency and improving audio quality. It enables multi-agent collaboration internally to enhance answer accuracy. The API also supports multimodal input, including voice, text, and image input combined for enriched responses.

Optimization tips:
- Set appropriate `temperature` for balanced creativity and control.
- Limit `max_tokens` to control response length and API costs.
- Use iterative prompt refinement for better results.

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Sample Full Python Code Skeleton for Voice Interaction with Grok 4

python
import os
import sounddevice as sd
import wavio
from xai_sdk import Client
import base64

def record_audio(duration=5, fs=16000, filename="input.wav"):
    print("Recording...")
    audio = sd.rec(int(duration * fs), samplerate=fs, channels=1)
    sd.wait()
    wavio.write(filename, audio, fs, sampwidth=2)
    print(f"Recording saved to {filename}")
    return filename

def play_audio(filename):
    audio, fs = wavio.read(filename)
    print("Playing Grok's response...")
    sd.play(audio, fs)
    sd.wait()

def send_audio_to_grok(filename):
    client = Client(api_key=os.getenv('XAI_API_KEY'))
    with open(filename, "rb") as f:
        audio_data = f.read()
    audio_base64 = base64.b64encode(audio_data).decode('utf-8')

    # Send audio to Grok 4 for voice response (adjust to actual API spec)
    response = client.sampler.sample(
        model="grok-4-0709",
        prompt={"audio": audio_base64, "mode": "voice"},
        temperature=0.4,
        max_tokens=100
    )
    return response.content

def save_response_audio(audio_base64, filename="grok_response.wav"):
    audio_response = base64.b64decode(audio_base64)
    with open(filename, "wb") as f:
        f.write(audio_response)
    print(f"Grok's response saved to {filename}")

def main():
    while True:
        record_audio()
        audio_base64 = send_audio_to_grok("input.wav")
        save_response_audio(audio_base64)
        play_audio("grok_response.wav")

if __name__ == "__main__":
    main()

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Summary

To set up a Python system that records voice, sends it to Grok 4, and receives and plays back Grok's voice responses, you need to:

- Register with xAI and obtain an API key.
- Use audio libraries in Python to record input and play output.
- Use the xAI SDK to communicate with the Grok 4 API, sending audio data encoded as base64.
- Receive Grok 4's voice responses similarly encoded, decode, and save them as WAV files.
- Manage conversational flow in a loop to maintain a real-time voice interaction.

Following these guidelines and the provided code examples will enable building a functional voice interaction system with Grok 4 and Python, leveraging Grok's advanced voice response capabilities.