gemma-4-tools

import { LMStudioClient } from "@lmstudio/sdk";

async function main() {
  const client = new LMStudioClient();
  console.log("Connected to LM Studio");

  const modelId = "google/gemma-4-12b-qat";
  const model = await client.llm.model(modelId);

  const imagePath = "C:\\Users\\ankit\\.lmstudio\\user-files\\1781594229448 - 297.jpeg";
  console.log("Preparing image...");
  const image = await client.files.prepareImage(imagePath);
  console.log("Image prepared, type:", typeof image, "constructor:", (image as any)?.constructor?.name);

  console.log("\n=== Text-only ===");
  const textPrediction = model.respond([
    { role: "user", content: "Say exactly: Hello World" },
  ]);
  let textReasoning = "";
  let textFinal = "";
  for await (const chunk of textPrediction) {
    if (chunk.reasoningType === "reasoning") {
      textReasoning += chunk.content;
    } else {
      textFinal += chunk.content;
    }
  }
  console.log("Reasoning length:", textReasoning.length);
  console.log("Final text:", JSON.stringify(textFinal));

  console.log("\n=== Vision (with image) ===");
  const visionPrediction = model.respond([
    {
      role: "user",
      content: "Describe this image in detail. What do you see?",
      images: [image],
    },
  ]);
  let visionReasoning = "";
  let visionFinal = "";
  let reasoningEnded = false;
  for await (const chunk of visionPrediction) {
    if (!reasoningEnded && chunk.reasoningType === "reasoning") {
      visionReasoning += chunk.content;
    } else {
      reasoningEnded = true;
      visionFinal += chunk.content;
    }
  }
  console.log("Vision reasoning length:", visionReasoning.length);
  console.log("Vision response length:", visionFinal.length);
  console.log("Vision response:", JSON.stringify(visionFinal.substring(0, 500)));
}

main().catch((err) => {
  console.error("Error:", err.message, err.stack);
  process.exit(1);
});