> ## Documentation Index > Fetch the complete documentation index at: https://www.edenai.co/docs/llms.txt > Use this file to discover all available pages before exploring further. # Sandbox > Sandbox tokens let you test your integration without real provider calls and at no cost. export const TechArticleSchema = ({title, description, path, articleSection, about, proficiencyLevel = "Beginner", dependencies, keywords = [], datePublished, dateModified, image, inLanguage = "en"}) => { const baseUrl = "https://www.edenai.co/docs"; const canonicalUrl = `${baseUrl}/${path}`.replace(/\/+$/, ""); const ogParams = new URLSearchParams({ division: articleSection || "", title: title || "", description: description || "" }); const resolvedImage = image || `https://edenai.mintlify.app/_mintlify/api/og?${ogParams.toString()}`; const data = { "@context": "https://schema.org", "@type": "TechArticle", "@id": `${canonicalUrl}#techarticle`, mainEntityOfPage: { "@type": "WebPage", "@id": canonicalUrl }, headline: title, name: title, description: description, url: canonicalUrl, inLanguage: inLanguage, isPartOf: { "@type": "WebSite", name: "Eden AI Documentation", url: baseUrl }, author: [{ "@type": "Organization", name: "Eden AI", url: "https://www.edenai.co/" }], publisher: { "@type": "Organization", name: "Eden AI", url: "https://www.edenai.co/", logo: { "@type": "ImageObject", url: "https://www.edenai.co/assets/logo.png" } } }; if (articleSection) data.articleSection = articleSection; if (about) data.about = { "@type": "Thing", name: about }; if (proficiencyLevel) data.proficiencyLevel = proficiencyLevel; if (dependencies) data.dependencies = dependencies; if (keywords && keywords.length) data.keywords = keywords; if (datePublished) data.datePublished = datePublished; if (dateModified) data.dateModified = dateModified; data.image = Array.isArray(resolvedImage) ? resolvedImage : [resolvedImage]; const json = JSON.stringify(data); const schemaId = `techarticle-${canonicalUrl}`; React.useEffect(() => { if (typeof document === "undefined") return; document.querySelectorAll(`script[data-schema-id="${schemaId}"]`).forEach(n => n.remove()); const script = document.createElement("script"); script.type = "application/ld+json"; script.dataset.schemaId = schemaId; script.textContent = json; document.head.appendChild(script); return () => script.remove(); }, [json, schemaId]); return null; }; Sandbox tokens let you **test your integration without real provider calls and at no cost**. Requests made with a sandbox token return simulated data, so you can build and validate your workflow before going to production. ## Token Types Eden AI supports two token types: | Token Type | Purpose | Real Provider Calls | Cost | | ------------------- | ----------------------- | ------------------- | ----------- | | `api_token` | Production use | Yes | Pay-per-use | | `sandbox_api_token` | Testing and development | No | Free | When you use a sandbox token, Eden AI returns **mock responses** that match the real response structure. This means your code works the same way in development and production — you just swap the token. ## Creating a Sandbox Token You can create sandbox tokens from the [Eden AI dashboard](https://app.edenai.run/) under **API Keys**, or programmatically via the API: ```python Python theme={null} import requests url = "https://api.edenai.run/v2/user/custom_token/" headers = { "Authorization": "Bearer YOUR_API_KEY", "Content-Type": "application/json" } payload = { "name": "dev-testing", "token_type": "sandbox_api_token" } response = requests.post(url, headers=headers, json=payload) sandbox_token = response.json() print(f"Sandbox token: {sandbox_token['token']}") ``` ```bash cURL theme={null} curl -X POST https://api.edenai.run/v2/user/custom_token/ \ -H "Authorization: Bearer YOUR_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "name": "dev-testing", "token_type": "sandbox_api_token" }' ``` ```javascript JavaScript theme={null} const response = await fetch('https://api.edenai.run/v2/user/custom_token/', { method: 'POST', headers: { 'Authorization': 'Bearer YOUR_API_KEY', 'Content-Type': 'application/json' }, body: JSON.stringify({ name: 'dev-testing', token_type: 'sandbox_api_token' }) }); const sandboxToken = await response.json(); console.log(`Sandbox token: ${sandboxToken.token}`); ``` ## Using a Sandbox Token Usage is identical to a production token — just use the sandbox token in the `Authorization` header: ```python Python theme={null} import requests url = "https://api.edenai.run/v3/chat/completions" headers = { "Authorization": "Bearer YOUR_SANDBOX_TOKEN", "Content-Type": "application/json" } payload = { "model": "openai/gpt-4", "messages": [ {"role": "user", "content": "Hello!"} ] } response = requests.post(url, headers=headers, json=payload) result = response.json() # Returns simulated data — same structure as a real response print(result["choices"][0]["message"]["content"]) ``` ```bash cURL theme={null} curl -X POST https://api.edenai.run/v3/chat/completions \ -H "Authorization: Bearer YOUR_SANDBOX_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "model": "openai/gpt-4", "messages": [{"role": "user", "content": "Hello!"}] }' ``` ```javascript JavaScript theme={null} const response = await fetch('https://api.edenai.run/v3/chat/completions', { method: 'POST', headers: { 'Authorization': 'Bearer YOUR_SANDBOX_TOKEN', 'Content-Type': 'application/json' }, body: JSON.stringify({ model: 'openai/gpt-4', messages: [{role: 'user', content: 'Hello!'}] }) }); const result = await response.json(); console.log(result.choices[0].message.content); ``` ## Multi-Environment Setup A common pattern is to create one sandbox token per environment and swap to a production token when you go live: ```python Python theme={null} import os # Use a sandbox token in dev/staging, a real token in production EDENAI_TOKEN = ( os.getenv("EDENAI_SANDBOX_TOKEN") if os.getenv("ENV") != "production" else os.getenv("EDENAI_API_TOKEN") ) headers = {"Authorization": f"Bearer {EDENAI_TOKEN}"} ``` ```javascript JavaScript theme={null} const token = process.env.ENV !== 'production' ? process.env.EDENAI_SANDBOX_TOKEN : process.env.EDENAI_API_TOKEN; const headers = { Authorization: `Bearer ${token}` }; ``` You can create multiple sandbox tokens — one per app or environment — from the dashboard or via the API with different `name` values. ## When to Use Sandbox Tokens Build and iterate on your integration without spending credits. Run automated tests against the API without incurring costs. Show your integration to stakeholders with predictable responses. Validate your architecture and request flow before going live. Sandbox tokens return simulated data. The response structure matches production responses, but the actual content is mock data. Do not use sandbox tokens to evaluate model quality or accuracy.