Hi is it possible to swap multiple different languages in a single call, like for example the assistant starts out in English and it gets a response in Hindi, and it switches to Hindi? Is that possible, and if so how?

@Haider Yes, it is possible to switch between multiple languages in a single call with VAPI. The multilingual support feature allows the assistant to start a conversation in one language and switch to another based on the user's response. To implement this, you would typically use language detection to identify the language of the user's response and then switch the assistant's language settings accordingly. Here's a high-level overview of how you could set this up: 1. Start the conversation in the default language (e.g., English). 2. Use language detection to analyze the user's response. 3. If the detected language is different from the current language, switch the assistant's language to the detected one. 4. Continue the conversation in the new language. To provide more specific guidance, I would need to know which LLM provider you're using or if you're using your own server for language processing. If you're using an LLM provider, they often have APIs for language detection that you can integrate with VAPI. If you're using your own server, you would need to implement language detection and switching logic within your application. If you need detailed instructions or assistance with the implementation, please let me know which system you're using, and I can provide more targeted advice.

I am using OpenAI as my LLM

@Haider Great! With OpenAI as your LLM provider, you can implement language switching in your voice application by following these steps: 1. **Language Detection**: Use OpenAI's language detection capabilities to determine the language of the user's response. OpenAI's models are quite adept at recognizing various languages. 2. **Language Switching Logic**: Once the language is detected, you can implement logic in your application to switch the assistant's responses to the detected language. This might involve changing the model or fine-tuning parameters to better suit the detected language. 3. **Dynamic Responses**: Generate responses in the detected language using OpenAI's models, ensuring that the conversation continues smoothly in the new language. Here's a simplified example of how you might handle a language switch in pseudocode:

python
# Assume 'user_response' is the input from the user
detected_language = detect_language(user_response)

if detected_language != current_language:
    current_language = detected_language
    # Update the model or parameters to generate responses in the new language
    update_response_model(current_language)

# Continue the conversation in the new language
response = generate_response(user_response, current_language)

In practice, you would need to handle more nuances, such as maintaining context across language switches and ensuring that the model is capable of generating accurate responses in the new language. If you need assistance with specific OpenAI API calls or further details on implementing this in your VAPI application, please let me know, and I'll be happy to help!

How can I write this in natural language in the Vapi Dashboard?

@Haider To implement language switching in the VAPI Dashboard using natural language, you would describe the desired behavior in a structured way that outlines the steps the system should take. Here's how you might express it: 1. **Start with the default language**: - "Begin the conversation in English." 2. **Detect the user's language**: - "After receiving a response from the user, analyze the text to detect the language. Use OpenAI's language detection capabilities for this step." 3. **Switch to the detected language**: - "If the detected language is different from the current language, switch the assistant's settings to respond in the detected language." 4. **Generate a response in the new language**: - "Continue the conversation by generating responses in the new language, ensuring that the assistant understands and replies accurately." 5. **Maintain context**: - "Ensure that the context of the conversation is maintained when switching languages so that the user experience is seamless." By structuring your instructions in this way, you provide a clear and actionable guide for setting up the language switching feature within the VAPI Dashboard. If you need to execute specific commands or access certain features in the dashboard, you would translate these steps into the corresponding actions or API calls provided by VAPI.

Give me a prompt example for this please

@Haider Certainly! Here's an example of a natural language prompt that you could use to describe the language switching functionality for a voice application using VAPI: --- Prompt for Implementing Language Switching in VAPI Dashboard: "Create a voice interaction flow that starts with the assistant speaking in English. After the user responds, the system should automatically detect the language of the user's input. If the input language is not English, for example, if it's Hindi, the assistant should dynamically switch to communicating in Hindi. To achieve this, integrate OpenAI's language detection model to analyze the user's response and identify the language. Once the language is detected, adjust the assistant's language settings to match the user's language. The assistant should then continue the conversation in the detected language, ensuring that it understands and responds accurately to the user's queries. It's important to maintain the context of the conversation throughout this process, even when the language changes, to provide a seamless user experience. Please implement this feature with careful consideration of the user's language preferences and provide a fallback mechanism in case the language detection is uncertain." --- This prompt outlines the desired behavior for the voice application and provides guidance on how to implement language switching using OpenAI's language detection. It also emphasizes the importance of maintaining context and handling uncertainties in language detection.

Hey @Haider using deepgram's codeSwitchingEnabled set to true and using 11labs mulitlingual voice it's doable.

Where do I enable that haha

Thank you