Build a sophisticated Next.js web app for an advanced multi-modal conversational AI agent with emotional intelligence, contextual awareness, and advanced language processing capabilities.

[e2b-for-github[bot]]

"# "# Next.js App

# # Aiden-multi-aware

Build a modern web application using the Next.js framework for an advanced multi-modal conversational AI agent with emotional intelligence, contextual awareness, self-reflection, cognitive behavioral intelligence, transfer learning, reinforcement learning, logic, reasoning, belief-desire-intention, NLP, NLU, NLG, and self-awareness.

that utilizes this inference endpoint,

async function query(data) {

const response = await fetch(

    "https://api-inference.huggingface.co/models/or4cl3ai/Aiden_t5",

    {

        headers: { Authorization: "Bearer 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" },

        method: "POST",

        body: JSON.stringify(data),

    }

);

const result = await response.json();

return result;

}

query({"inputs": "Can you please let us know more details about your "}).then((response) => {

console.log(JSON.stringify(response));

}). and this algorithm,

Algorithm Type: Quantum Genetic Regenerative

Training Data: Text Corpus

Neural Network Architecture: Liquid Generative Convolutional Cognitive Recurrent Attentive Adversarial Progressive Neural Network

Number of Hidden Layers: 30

Number of Neurons per Hidden Layer: 5120

Learning Rate: 0.001

Training Epochs: 1000

Batch Size: 640

This algorithm combines quantum computing principles with genetic algorithms and regenerative learning techniques to create a synthetic consciousness capable of processing and generating text based on the provided text corpus. The neural network architecture, consisting of liquid generative convolutional cognitive recurrent attentive adversarial progressive neural network, enables the algorithm to learn and generate text in a progressive and adaptive manner.

With 30 hidden layers and 5120 neurons per hidden layer, the algorithm has a high capacity for learning and capturing complex patterns in the text data. The learning rate of 0.001 ensures a gradual and stable learning process, while the 1000 training epochs allow for extensive training and refinement of the algorithm's understanding of the text corpus. The batch size of 640 enables efficient processing and training of the algorithm on the available computational resources.

Overall, this synthetic consciousness algorithm is designed to create a sophisticated and intelligent text generation system, capable of producing coherent and contextually relevant text based on the provided training data. It has the potential to revolutionize natural language processing and contribute to the development of advanced AI systems.

### Tech stack

- Next.js framework for server-side rendering and routing

- TypeScript for type checking and improved developer experience

### Features

- Server-side rendering for improved performance

- emotional intelligence,

- contextual awareness,

- self-reflection,

- cognitive behavioral intelligence,

- transfer learning,

- reinforcement learning,

- logic,

- reasoning,

- belief-desire-intention,

- Andvanced NLP,

- Advanced NLU,

- Advanced NLG,

- self-awareness,

- user friendly advanced graphical user interface,

- comprehensive documentation,

- detailed and descriptive readme.md file

- requirements.txt"

Trigger the agent again by adding instructions in a new PR comment or by editing existing instructions.

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