plugins/llama.js

const axios = require('axios');

const handler = async (req, res) => {
  try {
    const { text, img } = req.query;

    if (!text) {
      return res.status(400).json({
        success: false,
        error: 'Missing required parameter: text'
      });
    }

    const apiKey = process.env.GROQ;

    if (!apiKey) {
      return res.status(500).json({
        success: false,
        error: 'GROQ API key not configured in environment'
      });
    }

    const content = [
      {
        type: "text",
        text: text
      }
    ];

    if (img) {
      content.push({
        type: "image_url",
        image_url: {
          url: img
        }
      });
    }

    const response = await axios.post(
      'https://api.groq.com/openai/v1/chat/completions',
      {
        messages: [
          {
            role: "user",
            content: img ? content : text
          }
        ],
        model: img ? "meta-llama/llama-4-scout-17b-16e-instruct" : "llama-3.1-8b-instant",
        temperature: 1,
        max_completion_tokens: 1024,
        top_p: 1,
        stream: false
      },
      {
        headers: {
          'Content-Type': 'application/json',
          'Authorization': `Bearer ${apiKey}`
        }
      }
    );

    const result = response.data.choices[0].message.content;

    res.json({
      author: "Herza",
      success: true,
      msg: result
    });

  } catch (error) {
    res.status(500).json({
      success: false,
      error: error.response?.data?.error?.message || error.message
    });
  }
};

module.exports = {
  name: 'LLAMA AI',
  description: 'Generate responses using Groq API with text and image support',
  type: 'GET',
  routes: ['api/AI/llama'],
  tags: ['ai', 'Meta AI', 'llama', 'vision'],
  main: ['AI'],
  parameters: ['text', 'img', 'key'],
  enabled: true,
  limit: 8,
  handler
};