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‎.devcontainer/devcontainer.json‎

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{
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"customizations": {
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"vscode": {
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"extensions": ["unifiedjs.vscode-mdx"]
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}
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}
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}

‎.devcontainer/info.md‎

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# Devcontainer, the Gihub Codespaces configuration file
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This configuration is intended for [Github Codespaces](https://docs.github.com/en/codespaces) users.
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The `devcontainer.json` file allows to specify a configuration that can be used to create a Codespace.
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Refer to the official [Codespaces devcontainers documentation](https://docs.github.com/en/codespaces/setting-up-your-project-for-codespaces/adding-a-dev-container-configuration) for more information.
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## Elements
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The code below forces the installation of the MDX extension for VSCode inside a Codespace.
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```json
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{
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"customizations": {
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"vscode": {
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"extensions": ["unifiedjs.vscode-mdx"]
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}
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}
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}
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```
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**Note:** The identifier of the extension (e.g. `unifiedjs.vscode-mdx`) can be found on the VSCode extension page, under "More info".

‎.github/CODEOWNERS‎

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#This is a list of people who will be tagged whenever a PR is opened to edit one of the files listed below.
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# Samy
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storage/object/ @SamyOubouaziz
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serverless/containers/ @SamyOubouaziz
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storage/object/ @SamyOubouaziz
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serverless/functions/ @SamyOubouaziz
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console/ @farhakennar @SamyOubouaziz @ldecarvalho-doc
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serverless/containers/ @SamyOubouaziz
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serverless/jobs/ @SamyOubouaziz
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serverless/sql-databases/ @SamyOubouaziz
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console/account/ @SamyOubouaziz @pshambulingappa
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developer-tools/ @SamyOubouaziz
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# Rowena
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network/vpc/ @RoRoJ
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serverless/messaging/ @RoRoJ
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# Benedikt
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compute/gpu/ @bene2k1
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compute/instances/ @bene2k1
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bare-metal/dedibox/ @bene2k1
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bare-metal/elastic-metal/ @bene2k1
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compute/ @bene2k1
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bare-metal/ @bene2k1
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containers/kubernetes/ @bene2k1
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storage/block/ @bene2k1 @ldecarvalho-doc
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managed-services/webhosting/ @bene2k1
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dedibox/ @bene2k1
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dedibox-network/ @bene2k1
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dedibox-console/ @bene2k1
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ai-data/ @bene2k1
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# Néda
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managed-services/transactional-email/ @nerda-codes
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observability/ @nerda-codes
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network/domains-and-dns/ @nerda-codes
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identity-and-access-management/secret-manager/ @nerda-codes
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storage/block/ @nerda-codes
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# Luiza
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identity-and-access-management/iam/ @ldecarvalho-doc
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managed-databases/document-database/ @ldecarvalho-doc
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managed-databases/postgresql-and-mysql/ @ldecarvalho-doc
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managed-databases/redis/ @ldecarvalho-doc
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containers/container-registry/ @ldecarvalho-doc
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labs/ @ldecarvalho-doc
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# Farha
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bare-metal/apple-silicon/ @farhakennar
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managed-services/iot-hub/ @farhakennar
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console/billing/ @ldecarvalho-doc @pshambulingappa
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managed-services/transactional-email/ @ldecarvalho-doc

‎.github/ISSUE_TEMPLATE/doc_bug.yaml‎

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attributes:
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value: |
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* Please check that there is not an existing open [issue](https://github.com/scaleway/docs-content/issues) before you create a new one.
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* Read the [writing guidelines](https://github.com/scaleway/docs-content/blob/main/docs/CONTRIBUTING.md#writing-guidelines) before you continue.
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* Read the [writing guidelines](https://www.scaleway.com/en/docs/guidelines/) before you continue.
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- type: input
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attributes:
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label: What content on scaleway.com/en/docs is affected?

‎.github/workflows/docs-review-bot.yml‎

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name: 📖 Review Documentation Bot
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on:
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workflow_dispatch:
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inputs:
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dryRun:
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description: 'Run the bot without sending notifications'
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required: false
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default: 'false'
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schedule:
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- cron: '0 8 * * 1'
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env:
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SLACK_BOT_TOKEN: ${{ secrets.SLACK_BOT_TOKEN }}
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DRY_RUN: false
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jobs:
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review-docs:
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runs-on: ubuntu-latest
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steps:
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- name: Checkout repository
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uses: actions/checkout@v2
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- name: Set up Python
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uses: actions/setup-python@v2
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with:
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python-version: '3.x'
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip
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pip install -r requirements.txt
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- name: Run Documentation Review Bot in dry run mode
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if: github.event_name == 'workflow_dispatch' && github.event.inputs.dryRun == 'true'
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env:
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DRY_RUN: true
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run: |
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python bin/check-review-dates.py
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- name: Run Documentation Review Bot in normal mode
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if: github.event_name != 'workflow_dispatch' || github.event.inputs.dryRun != 'true'
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run: |
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python bin/check-review-dates.py

‎.github/workflows/markdown-link-checker.yml‎

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name: Check Markdown links
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on: push
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jobs:
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markdown-link-check:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@master
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- uses: gaurav-nelson/github-action-markdown-link-check@v1
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with:
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base-branch: 'main'
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use-quiet-mode: 'yes'
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check-modified-files-only: 'yes'
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file-extension: '.mdx'
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config-file: '.link_checker_config.json'

‎.link_checker_config.json‎

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{
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"ignorePatterns": [
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{
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"pattern": "^http://scaleway.com"
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}
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],
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"replacementPatterns": [
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{
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"pattern": "^/.attachments",
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"replacement": "https://scaleway.com/en/docs/.attachments"
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},
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{
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"pattern": "^/",
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"replacement": "https://scaleway.com/en/docs/"
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},
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{
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"pattern": "%20",
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"replacement": "-",
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"global": true
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}
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],
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"httpHeaders": [
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{
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"urls": ["https://scaleway.com/en/docs"]
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}
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],
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"timeout": "20s",
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"retryOn429": true,
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"retryCount": 5,
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"fallbackRetryDelay": "30s",
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"aliveStatusCodes": [200, 206, 401, 403, 0]
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}

‎ai-data/generative-apis/api-cli/index.mdx‎

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---
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meta:
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title: Generative APIs - API/CLI
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description: Generative APIs API/CLI
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content:
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h1: Generative APIs - API/CLI
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paragraph: Generative APIs API/CLI
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---

‎ai-data/generative-apis/api-cli/understanding-errors.mdx‎

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---
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meta:
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title: Understanding errors
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description: This page explains how to understand errors with Generative APIs
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content:
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h1: Understanding errors
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paragraph: This page explains how to understand errors with Generative APIs
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tags: generative-apis ai-data understanding-data
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dates:
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validation: 2024-10-31
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posted: 2024-09-02
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---
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Scaleway uses conventional HTTP response codes to indicate the success or failure of an API request.
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In general, codes in the 2xx range indicate success, codes in the 4xx range indicate an error caused by the information provided, and codes in the 5xx range show an error from Scaleway servers.
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If the response code is not within the 2xx range, the response will contain an error object structured as follows:
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```
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{
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"error": string,
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"status": number,
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"message": string
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}
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```
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Below are usual HTTP error codes:
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- 400 - **Bad Request**: The format or content of your payload is incorrect. The body may be too large, or fail to parse, or the content-type is mismatched.
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- 401 - **Unauthorized**: The `authorization` header is missing. Find required headers in [this page](/ai-data/generative-apis/api-cli/using-generative-apis/)
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- 403 - **Forbidden**: Your API key does not exist or does not have the necessary permissions to access the requested resource. Find required permission sets in [this page](/ai-data/generative-apis/api-cli/using-generative-apis/)
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- 404 - **Route Not Found**: The requested resource could not be found. Check your request is being made to the correct endpoint.
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- 422 - **Model Not Found**: The `model` key is present in the request payload, but the corresponding model is not found.
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- 422 - **Missing Model**: The `model` key is missing from the request payload.
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- 429 - **Too Many Requests**: You are exceeding your current quota for the requested model, calculated in requests per minute. Find rate limits on [this page](/ai-data/generative-apis/reference-content/rate-limits/)
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- 429 - **Too Many Tokens**: You are exceeding your current quota for the requested model, calculated in tokens per minute. Find rate limits on [this page](/ai-data/generative-apis/reference-content/rate-limits/)
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- 500 - **API error**: An unexpected internal error has occurred within Scaleway's systems. If the issue persists, please [open a support ticket](https://console.scaleway.com/support/tickets/create).
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For streaming responses via SSE, 5xx errors may occur after a 200 response has been returned.

‎ai-data/generative-apis/api-cli/using-chat-api.mdx‎

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---
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meta:
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title: Using Chat API
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description: This page explains how to use the Chat API to query models
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content:
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h1: Using Chat API
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paragraph: This page explains how to use the Chat API to query models
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tags: generative-apis ai-data chat-api
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dates:
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validation: 2024-09-03
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posted: 2024-09-03
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---
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Scaleway Generative APIs are designed as a drop-in replacement for the OpenAI APIs. If you have an LLM-driven application that uses one of OpenAI's client libraries, you can easily configure it to point to Scaleway Chat API, and get your existing applications running using open-weight instruct models hosted at Scaleway.
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## Create chat completion
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Creates a model response for the given chat conversation.
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**Request sample:**
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```
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curl --request POST \
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--url https://api.scaleway.ai/v1/chat/completions \
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--header 'Authorization: Bearer ${SCW_SECRET_KEY}' \
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--header 'Content-Type: application/json' \
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--data '{
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"model": "llama-3.1-8b-instruct",
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"messages": [
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{
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"role": "system",
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"content": "<string>"
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},
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{
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"role": "user",
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"content": "<string>"
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}
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],
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"max_tokens": integer,
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"temperature": float,
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"top_p": float,
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"presence_penalty": float,
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"stop": "<string>",
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"stream": boolean,
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}'
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```
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## Headers
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Find required headers in [this page](/ai-data/generative-apis/api-cli/using-generative-apis/).
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## Body
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### Required parameters
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| Param | Type | Description |
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| ------------- |-------------|-------------|
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| **messages*** | array of objects | A list of messages comprising the conversation so far. |
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| **model*** | string | The name of the model to query. |
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Our chat API is OpenAI compatible. Use OpenAI’s [API reference](https://platform.openai.com/docs/api-reference/chat/create) for more detailed information on the usage.
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### Supported parameters
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- temperature
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- top_p
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- max_tokens
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- stream
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- presence_penalty
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- [response_format](/ai-data/generative-apis/how-to/use-structured-outputs)
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- logprobs
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- stop
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- seed
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- [tools](/ai-data/generative-apis/how-to/use-function-calling)
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- [tool_choice](/ai-data/generative-apis/how-to/use-function-calling)
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### Unsupported parameters
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- frequency_penalty
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- n
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- top_logprobs
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- logit_bias
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- user
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If you have a use case requiring one of these unsupported parameters, please [contact us via Slack](https://slack.scaleway.com/) on #ai channel.
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## Going further
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1. [Python code examples](/ai-data/generative-apis/how-to/query-language-models/#querying-language-models-via-api) to query text models using Scaleway's Chat API.
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2. [How to use structured outputs](/ai-data/generative-apis/how-to/use-structured-outputs) with the `response_format` parameter
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3. [How to use function calling](/ai-data/generative-apis/how-to/use-function-calling) with `tools` and `tool_choice`

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