--- title: Code interpreter with Workers AI description: Build a code interpreter using Workers AI GPT-OSS model with the official workers-ai-provider package. image: https://developers.cloudflare.com/dev-products-preview.png --- > Documentation Index > Fetch the complete documentation index at: https://developers.cloudflare.com/sandbox/llms.txt > Use this file to discover all available pages before exploring further. [Skip to content](#%5Ftop) # Code interpreter with Workers AI Build a powerful code interpreter that gives the [gpt-oss model](https://developers.cloudflare.com/workers-ai/models/gpt-oss-120b/) on Workers AI the ability to execute Python code using the Cloudflare Sandbox SDK. **Time to complete:** 15 minutes ## What you'll build A Cloudflare Worker that accepts natural language prompts, uses GPT-OSS to decide when Python code execution is needed, runs the code in isolated sandboxes, and returns results with AI-powered explanations. ## Prerequisites 1. Sign up for a [Cloudflare account ↗](https://dash.cloudflare.com/sign-up/workers-and-pages). 2. Install [Node.js ↗](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm). Node.js version manager Use a Node version manager like [Volta ↗](https://volta.sh/) or [nvm ↗](https://github.com/nvm-sh/nvm) to avoid permission issues and change Node.js versions. [Wrangler](https://developers.cloudflare.com/workers/wrangler/install-and-update/), discussed later in this guide, requires a Node version of `16.17.0` or later. You'll also need: * [Docker ↗](https://www.docker.com/) running locally ## 1\. Create your project Create a new Sandbox SDK project: npm yarn pnpm ``` npm create cloudflare@latest -- workers-ai-interpreter --template=cloudflare/sandbox-sdk/examples/code-interpreter ``` ``` yarn create cloudflare workers-ai-interpreter --template=cloudflare/sandbox-sdk/examples/code-interpreter ``` ``` pnpm create cloudflare@latest workers-ai-interpreter --template=cloudflare/sandbox-sdk/examples/code-interpreter ``` Terminal window ``` cd workers-ai-interpreter ``` ## 2\. Review the implementation The template includes a complete implementation using the latest best practices. Let's examine the key components: TypeScript ``` // src/index.tsimport { getSandbox } from "@cloudflare/sandbox";import { generateText, stepCountIs, tool } from "ai";import { createWorkersAI } from "workers-ai-provider";import { z } from "zod"; const MODEL = "@cf/openai/gpt-oss-120b" as const; async function handleAIRequest(input: string, env: Env): Promise { const workersai = createWorkersAI({ binding: env.AI }); const result = await generateText({ model: workersai(MODEL), messages: [{ role: "user", content: input }], tools: { execute_python: tool({ description: "Execute Python code and return the output", inputSchema: z.object({ code: z.string().describe("The Python code to execute"), }), execute: async ({ code }) => { return executePythonCode(env, code); }, }), }, stopWhen: stepCountIs(5), }); return result.text || "No response generated";} ``` **Key improvements over direct REST API calls:** * **Official packages**: Uses `workers-ai-provider` instead of manual API calls * **Vercel AI SDK**: Leverages `generateText()` and `tool()` for clean function calling * **No API keys**: Uses native AI binding instead of environment variables * **Type safety**: Full TypeScript support with proper typing ## 3\. Check your configuration The template includes the proper Wrangler configuration: * [ wrangler.jsonc ](#tab-panel-10924) * [ wrangler.toml ](#tab-panel-10925) JSONC ``` { "name": "sandbox-code-interpreter-example", "main": "src/index.ts", // Set this to today's date "compatibility_date": "2026-06-30", "ai": { "binding": "AI" }, "containers": [ { "class_name": "Sandbox", "image": "./Dockerfile", "name": "sandbox", "max_instances": 1, "instance_type": "basic" } ], "durable_objects": { "bindings": [ { "class_name": "Sandbox", "name": "Sandbox" } ] }} ``` TOML ``` name = "sandbox-code-interpreter-example"main = "src/index.ts"# Set this to today's datecompatibility_date = "2026-06-30" [ai]binding = "AI" [[containers]]class_name = "Sandbox"image = "./Dockerfile"name = "sandbox"max_instances = 1instance_type = "basic" [[durable_objects.bindings]]class_name = "Sandbox"name = "Sandbox" ``` **Configuration highlights:** * **AI binding**: Enables direct access to Workers AI models * **Container setup**: Configures sandbox container with Dockerfile * **Durable Objects**: Provides persistent sandboxes with state management ## 4\. Test locally Start the development server: Terminal window ``` npm run dev ``` Note First run builds the Docker container (2-3 minutes). Subsequent runs are much faster. Test with curl: Terminal window ``` # Simple calculationcurl -X POST http://localhost:8787/run \ -H "Content-Type: application/json" \ -d '{"input": "Calculate 5 factorial using Python"}' # Complex operationscurl -X POST http://localhost:8787/run \ -H "Content-Type: application/json" \ -d '{"input": "Use Python to find all prime numbers under 20"}' # Data analysiscurl -X POST http://localhost:8787/run \ -H "Content-Type: application/json" \ -d '{"input": "Create a list of the first 10 squares and calculate their sum"}' ``` ## 5\. Deploy Deploy your Worker: Terminal window ``` npx wrangler deploy ``` Warning After first deployment, wait 2-3 minutes for container provisioning before making requests. ## 6\. Test your deployment Try more complex queries: Terminal window ``` # Data visualization preparationcurl -X POST https://workers-ai-interpreter.YOUR_SUBDOMAIN.workers.dev/run \ -H "Content-Type: application/json" \ -d '{"input": "Generate sample sales data for 12 months and calculate quarterly totals"}' # Algorithm implementationcurl -X POST https://workers-ai-interpreter.YOUR_SUBDOMAIN.workers.dev/run \ -H "Content-Type: application/json" \ -d '{"input": "Implement a binary search function and test it with a sorted array"}' # Mathematical computationcurl -X POST https://workers-ai-interpreter.YOUR_SUBDOMAIN.workers.dev/run \ -H "Content-Type: application/json" \ -d '{"input": "Calculate the standard deviation of [2, 4, 4, 4, 5, 5, 7, 9]"}' ``` ## How it works 1. **User input**: Send natural language prompts to the `/run` endpoint 2. **AI decision**: GPT-OSS receives the prompt with an `execute_python` tool available 3. **Smart execution**: Model decides whether Python code execution is needed 4. **Sandbox isolation**: Code runs in isolated Cloudflare Sandbox containers 5. **AI explanation**: Results are integrated back into the AI's response for final output ## What you built You deployed a sophisticated code interpreter that: * **Native Workers AI integration**: Uses the official `workers-ai-provider` package for seamless integration * **Function calling**: Leverages Vercel AI SDK for clean tool definitions and execution * **Secure execution**: Runs Python code in isolated sandbox containers * **Intelligent responses**: Combines AI reasoning with code execution results ## Next steps * [Analyze data with AI](https://developers.cloudflare.com/sandbox/tutorials/analyze-data-with-ai/) \- Add pandas and matplotlib for advanced data analysis * [Code Interpreter API](https://developers.cloudflare.com/sandbox/api/interpreter/) \- Use the built-in code interpreter with structured outputs * [Streaming output](https://developers.cloudflare.com/sandbox/guides/streaming-output/) \- Show real-time execution progress * [API reference](https://developers.cloudflare.com/sandbox/api/) \- Explore all available sandbox methods ## Related resources * [Workers AI](https://developers.cloudflare.com/workers-ai/) \- Learn about Cloudflare's AI platform * [workers-ai-provider package ↗](https://github.com/cloudflare/ai/tree/main/packages/workers-ai-provider) \- Official Workers AI integration * [Vercel AI SDK ↗](https://sdk.vercel.ai/) \- Universal toolkit for AI applications * [GPT-OSS model documentation](https://developers.cloudflare.com/workers-ai/models/gpt-oss-120b/) \- Model details and capabilities ```json {"@context":"https://schema.org","@type":"TechArticle","@id":"https://developers.cloudflare.com/sandbox/tutorials/workers-ai-code-interpreter/#page","headline":"Code interpreter with Workers AI · Cloudflare Sandbox SDK docs","description":"Build a code interpreter using Workers AI GPT-OSS model with the official workers-ai-provider package.","url":"https://developers.cloudflare.com/sandbox/tutorials/workers-ai-code-interpreter/","inLanguage":"en","image":"https://developers.cloudflare.com/dev-products-preview.png","dateModified":"2026-05-05","publisher":{"@type":"Organization","name":"Cloudflare","url":"https://www.cloudflare.com/"},"isPartOf":{"@type":"WebSite","@id":"https://developers.cloudflare.com/#website","name":"Cloudflare Docs","url":"https://developers.cloudflare.com/"}} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"item":{"@id":"/directory/","name":"Directory"}},{"@type":"ListItem","position":2,"item":{"@id":"/sandbox/","name":"Sandbox SDK"}},{"@type":"ListItem","position":3,"item":{"@id":"/sandbox/tutorials/","name":"Tutorials"}},{"@type":"ListItem","position":4,"item":{"@id":"/sandbox/tutorials/workers-ai-code-interpreter/","name":"Code interpreter with Workers AI"}}]} ```