llm-endpoint.js

// llm-endpoints.js

export function LLMEndpoint() {
    // Other properties and methods can be here if needed
}

LLMEndpoint.callEndpoint = async function(userInput) {
    const URI = "https://api.openai.com/v1/chat/completions";
    const OPENAI_API_KEY = process.env.OPEN_AI; // Ensure you securely access the API key, for example, from environment variables
    const requestPayload = {
        model: "gpt-3.5-turbo", // Adjust the model according to your needs
        messages: [{
            role: "user",
            content: userInput
        }],
        // Add any additional parameters you may need, following OpenAI's API documentation
    };

    try {
        const response = await fetch(URI, {
            method: 'POST',
            headers: {
                'Content-Type': 'application/json',
                'Authorization': `Bearer ${OPENAI_API_KEY}` // Use the API key securely
            },
            body: JSON.stringify(requestPayload)
        });

        if (response.status === 200) {
            const result = await response.json();
            // Assuming you want the last completion's message content
            const lastIndex = result.choices.length - 1;
            const output = result.choices[lastIndex].message.content;

            // Perform any necessary formatting on `output`
            // For example, cleaning up or formatting the response text
            console.log(output);
            return output; // Return the processed output
        } else {
            console.error('Error:', response.status);
            return null;
        }
    } catch (error) {
        console.error('Error:', error);
    }
};