ChatGPT 4o real time interaction with audio video and text inputs

GPT builders
1

Hi, how is it possible to make ChatGPT 4o to interact and response to audio video and text input in real time as it is been shown in one youtube video where one person was interacting with ChatGPT 4o asking about the mathematical problem which was opened in same tablet.

2

Demonstrated features of the ‘big announcement day’ video shoot (where Khan and his kid got to make an co-op ad also) have not been further previewed or released, except for continuing ability for attachment of images.

The ‘look at stuff’ is a clever illusion of application-level 1 FPS image capture and sending a buffer of a bunch of images into AI model context when a question is asked. Attaching one image would give better performance.

Voice mode, where audio goes in and out of the AI (to the exclusion of text production) has a very small random deployment of testers in the ChatGPT app.

The model’s image creation is even more distant and not being clamored about, seeming better at text but not imaginative at art.

You can’t “make” ChatGPT do anything not released.

3

hi, I discuss with chatGPT about this thing and he gave me this answer can any body develop the app on the basis of this answer

Detailed Step-by-Step Guide for Integrating ChatGPT-4o with Audio, Vision, and Text on an Android Tablet

Here’s a comprehensive guide to help you set up an application on your Android tablet that integrates ChatGPT-4o to process audio, vision, and text in real time.

Step 1: Setting Up Your Development Environment

  1. Install Android Studio: Download and install Android Studio.
  2. Create a New Project: Start a new project with an empty activity template.

Step 2: Capture Screen Content

  1. Add Permissions: Add permissions for capturing the screen and internet access in your AndroidManifest.xml.

xml

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<uses-permission android:name="android.permission.INTERNET"/>
<uses-permission android:name="android.permission.WRITE_EXTERNAL_STORAGE"/>
<uses-permission android:name="android.permission.READ_EXTERNAL_STORAGE"/>
<uses-permission android:name="android.permission.FOREGROUND_SERVICE"/>
  1. Setup MediaProjection API: Use the MediaProjection API to capture the screen content.

java

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// Inside your MainActivity.java
private static final int REQUEST_CODE = 1000;
private MediaProjectionManager projectionManager;

@Override
protected void onCreate(Bundle savedInstanceState) {
    super.onCreate(savedInstanceState);
    setContentView(R.layout.activity_main);
    
    projectionManager = (MediaProjectionManager) getSystemService(Context.MEDIA_PROJECTION_SERVICE);
    startActivityForResult(projectionManager.createScreenCaptureIntent(), REQUEST_CODE);
}

@Override
protected void onActivityResult(int requestCode, int resultCode, @Nullable Intent data) {
    if (requestCode == REQUEST_CODE && resultCode == RESULT_OK) {
        MediaProjection mediaProjection = projectionManager.getMediaProjection(resultCode, data);
        // Start capturing the screen
    }
}

Step 3: Extract Text Using OCR

  1. Add ML Kit Dependency: Add Google’s ML Kit Text Recognition dependency to your build.gradle.

groovy

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implementation 'com.google.mlkit:text-recognition:16.0.0'
  1. Process Captured Image: Use ML Kit to process the captured screen image and extract text.

java

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import com.google.mlkit.vision.common.InputImage;
import com.google.mlkit.vision.text.Text;
import com.google.mlkit.vision.text.TextRecognition;
import com.google.mlkit.vision.text.TextRecognizer;

// Convert captured image to bitmap and process
InputImage image = InputImage.fromBitmap(capturedBitmap, 0);
TextRecognizer recognizer = TextRecognition.getClient();
recognizer.process(image)
    .addOnSuccessListener(new OnSuccessListener<Text>() {
        @Override
        public void onSuccess(Text visionText) {
            String extractedText = visionText.getText();
            // Use extractedText as needed
        }
    })
    .addOnFailureListener(new OnFailureListener() {
        @Override
        public void onFailure(@NonNull Exception e) {
            // Handle error
        }
    });

Step 4: Integrate Audio Processing

  1. Add Dependencies: Add Google’s Speech-to-Text and Text-to-Speech dependencies.

groovy

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implementation 'com.google.cloud:google-cloud-speech:1.28.0'
implementation 'com.google.cloud:google-cloud-texttospeech:1.0.0'
  1. Speech-to-Text:

java

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// Initialize Speech-to-Text API and process audio input
  1. Text-to-Speech:

java

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// Initialize Text-to-Speech API to convert text responses to speech
TextToSpeech tts = new TextToSpeech(getApplicationContext(), new TextToSpeech.OnInitListener() {
    @Override
    public void onInit(int status) {
        if (status != TextToSpeech.ERROR) {
            tts.setLanguage(Locale.US);
        }
    }
});

tts.speak(responseText, TextToSpeech.QUEUE_FLUSH, null, null);

Step 5: Integrate with ChatGPT-4o

  1. Add Retrofit Dependency: Add Retrofit for making API calls.

groovy

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implementation 'com.squareup.retrofit2:retrofit:2.9.0'
implementation 'com.squareup.retrofit2:converter-gson:2.9.0'
  1. Set Up Retrofit:

java

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import retrofit2.Retrofit;
import retrofit2.converter.gson.GsonConverterFactory;

Retrofit retrofit = new Retrofit.Builder()
    .baseUrl("https://api.openai.com/v1/")
    .addConverterFactory(GsonConverterFactory.create())
    .build();

OpenAIApiService apiService = retrofit.create(OpenAIApiService.class);
  1. Send Data to ChatGPT-4o:

java

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// Define the API call
Call<ChatGPTResponse> call = apiService.getResponse(new ChatGPTRequest(extractedText));
call.enqueue(new Callback<ChatGPTResponse>() {
    @Override
    public void onResponse(Call<ChatGPTResponse> call, Response<ChatGPTResponse> response) {
        if (response.isSuccessful()) {
            String responseText = response.body().getText();
            // Process response text (e.g., display it, convert to speech)
        }
    }

    @Override
    public void onFailure(Call<ChatGPTResponse> call, Throwable t) {
        // Handle error
    }
});

Step 6: Real-time Interaction

  1. Combine Everything: Create a loop to continuously capture, process, and interact with the screen content.

java

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Handler handler = new Handler();
Runnable runnable = new Runnable() {
    @Override
    public void run() {
        // Capture screen
        // Process image with OCR
        // Convert audio input to text
        // Send text to ChatGPT-4o
        // Convert ChatGPT response to speech
        
        handler.postDelayed(this, 5000);  // Adjust interval as needed
    }
};
handler.post(runnable);

Additional Considerations

  • Permissions: Ensure all necessary permissions are handled, including runtime permissions for accessing media and the internet.
  • Error Handling: Implement robust error handling for API calls and processing steps.
  • UI Design: Create a user-friendly interface for better interaction.

This step-by-step guide should help you set up a comprehensive system on your Android tablet to integrate ChatGPT-4o with real-time audio, vision, and text processing. If you need more details or have specific questions, feel free to ask!