This code defines an async function named analyzeImage that takes an image path, reads the image file, converts it to base64, and uses a Large Language Model (LLM) to analyze the image, returning the result.

Run example

npm run import -- "analyze image with llm"

analyze image with llm

const fs = require('fs')

async function analyzeImage(imagePath) {
  const {llmAnalyze} = await importer.import("llama vision")

  console.log("User: Analyze the image:\n" + imagePath);
  const a0 = await llmAnalyze('Analyze the image:\n' + fs.readFileSync(imagePath).toString('base64'));
  console.log("AI: " + a0);

  return a0
}

module.exports = analyzeImage

const fs = require('fs');
const path = require('path');
const { LLaMA } = require('llama.js');

/**
 * Analyzes an image using the LLaMA vision model.
 * 
 * @param {string} imagePath - The path to the image file.
 * @returns {Promise} - The analysis result from the LLaMA model.
 */
async function analyzeImage(imagePath) {
  // Validate the input path
  if (!path.isAbsolute(imagePath)) {
    throw new Error('Invalid image path. Ensure it is absolute.');
  }

  // Read the image file
  const imageBuffer = await fs.promises.readFile(imagePath);

  // Convert the image to base64 format
  const imageBase64 = imageBuffer.toString('base64');

  // Import the LLaMA vision model
  const { analyze } = new LLaMA({
    // Replace with your own LLaMA server endpoint or token
    endpoint: 'https://api.llama.dev/v1/vision',
    headers: {
      'Authorization': 'Bearer YOUR_TOKEN',
    },
  });

  // Analyze the image using the LLaMA model
  const analysisResult = await analyze(`Analyze the image:\n${imageBase64}`);

  // Print the user input and the AI response
  console.log(`User: Analyze the image:\n${imagePath}`);
  console.log(`AI: ${analysisResult}`);

  // Return the analysis result
  return analysisResult;
}

module.exports = analyzeImage;

Code Breakdown

Importing Modules

const fs = require('fs')

This line imports the built-in fs (File System) module, which provides functions for interacting with the file system.

Defining an Async Function

async function analyzeImage(imagePath) {
 ...
}

This line defines an async function named analyzeImage that takes a single argument imagePath. The function returns a Promise, which allows it to perform asynchronous operations.

Importing LLM Functions

const {llmAnalyze} = await importer.import('llama vision')

This line imports the llmAnalyze function from the llama vision module, which is dynamically imported using the importer object.

Reading the Image File

const imageBuffer = fs.readFileSync(imagePath)
const imageBase64 = imageBuffer.toString('base64')

This code reads the file specified by imagePath into a Buffer using fs.readFileSync, and then converts the Buffer to a base64-encoded string using toString('base64').

Analyzing the Image

const a0 = await llmAnalyze('Analyze the image:\n' + imageBase64)

This line passes the base64-encoded image data to the llmAnalyze function, along with a prompt to analyze the image. The function returns a Promise, which resolves to the result of the analysis.

Logging and Returning the Result

console.log("User: Analyze the image:\n" + imagePath);
console.log("AI: " + a0);
return a0

This code logs the original image path to the console, followed by the result of the analysis. The a0 value is then returned from the function.

Exporting the Function

module.exports = analyzeImage

This line exports the analyzeImage function, making it available for use in other modules.