Skip to main content

Documentation Index

Fetch the complete documentation index at: https://docs.tensormesh.ai/llms.txt

Use this file to discover all available pages before exploring further.

Tool calling lets the model choose arguments for functions defined by your application. With tensormesh(modelId), AI SDK tool calls are sent through /v1/chat/completions. 
import { streamText, stepCountIs, tool } from "ai";
import { tensormesh } from "@tensormesh/ai-sdk-provider";
import { z } from "zod";

const modelId = "Qwen/Qwen3-Coder-30B-A3B-Instruct";

const result = streamText({
  model: tensormesh(modelId),
  prompt: "What is 128 multiplied by 7? Use the calculator tool.",
  tools: {
    calculator: tool({
      description: "Run one arithmetic operation.",
      inputSchema: z.object({
        operation: z.enum(["add", "subtract", "multiply", "divide"]),
        left: z.number(),
        right: z.number(),
      }),
      execute: async ({ operation, left, right }) => {
        switch (operation) {
          case "add":
            return { result: left + right };
          case "subtract":
            return { result: left - right };
          case "multiply":
            return { result: left * right };
          case "divide":
            return { result: right === 0 ? null : left / right };
        }
      },
    }),
  },
  prepareStep: async ({ stepNumber }) =>
    stepNumber === 0
      ? {
          toolChoice: modelId.toLowerCase().includes("gpt-oss")
            ? "auto"
            : "required",
        }
      : {},
  stopWhen: stepCountIs(3),
});

for await (const text of result.textStream) {
  process.stdout.write(text);
}
Use toolChoice: "auto" for GPT OSS models. Use toolChoice: "required" when the selected model supports it and you want to force a tool call in a demo or test.

​
Responses API Tool Calls

The package also exposes raw /v1/responses helpers. When you call the Responses API directly, use the endpoint payload shape and include a boolean strict value for function tools. 
import { tensormesh } from "@tensormesh/ai-sdk-provider";

const response = await tensormesh.responses.create({
  model: "openai/gpt-oss-20b",
  input: "What is the weather in Bangkok? Use the weather tool.",
  tools: [
    {
      type: "function",
      name: "weather",
      description: "Return weather for a city.",
      strict: true,
      parameters: {
        type: "object",
        properties: {
          city: { type: "string" },
        },
        required: ["city"],
        additionalProperties: false,
      },
    },
  ],
  tool_choice: "auto",
});

console.log(response);