This article provides a complete, practical walkthrough of the Wait Filter Send Webhook n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Intermediate setup in 15-45 minutes. One‑time purchase: €29.

What This Agent Does

This agent orchestrates a reliable automation between HTTP Request, Webhook, handling triggers, data enrichment, and delivery with guardrails for errors and rate limits.

It streamlines multi‑step processes that would otherwise require manual exports, spreadsheet cleanup, and repeated API requests. By centralizing logic in n8n, it reduces context switching, lowers error rates, and ensures consistent results across teams.

Typical outcomes include faster lead handoffs, automated notifications, accurate data synchronization, and better visibility via execution logs and optional Slack/Email alerts.

How It Works

The workflow uses standard n8n building blocks like Webhook or Schedule triggers, HTTP Request for API calls, and control nodes (IF, Merge, Set) to validate inputs, branch on conditions, and format outputs. Retries and timeouts improve resilience, while credentials keep secrets safe.

Third‑Party Integrations

• HTTP Request
• Webhook

Import and Use in n8n

1. Open n8n and create a new workflow or collection.
2. Choose Import from File or Paste JSON.
3. Paste the JSON below, then click Import.
4. Show n8n JSON

   Title:
   Automated PDF Translation Workflow with n8n, Google Drive, and DeepL API
   
   Meta Description:
   Learn how to automate PDF document translations using n8n, Google Drive, and DeepL's API. This no-code workflow detects, translates, and re-uploads documents in your preferred language effortlessly.
   
   Keywords:
   n8n, DeepL API, document translation, Google Drive automation, PDF translator, no-code workflow, file automation, DeepL integration, cloud translation, automate translations
   
   Third-party APIs used:
   - Google Drive API
   - DeepL API
   
   Article:
   
   Automating PDF Translations with n8n, Google Drive, and DeepL
   
   With globalization in full swing and businesses operating in multiple regions, the need for translating documents efficiently has never been greater. Manual translation of files, especially at scale, can be time-consuming and error-prone. Luckily, no-code platforms like n8n make automating such workflows simpler than ever.
   
   In this article, we’ll walk through a ready-to-use n8n workflow that automates the process of translating PDF documents stored in Google Drive using the DeepL API — one of the most accurate language translation services available today.
   
   Overview of the Workflow
   
   This n8n setup takes PDF files from a specified Google Drive folder, checks if they have already been translated, submits them for translation using DeepL, and finally uploads the translated versions back into the same folder — with the target language clearly appended to the filename.
   
   Let’s break down each stage of this automation.
   
   1. Manual Trigger and Configuration
   
   The workflow starts with a Manual Trigger node, allowing the user to run the workflow on-demand. A Set node called ⚙️ config is used to define the following input parameters:
   - folder_url: The URL of the Google Drive folder containing the PDFs.
   - target_lang: The target language for translation (e.g., `FR` for French).
   - source_lang: The source language (optional, as DeepL can auto-detect if not provided).
   
   All supported languages by DeepL are neatly documented in a Sticky Note attached in the n8n canvas to provide quick reference (e.g., `EN-US`, `DE`, `ES`, etc.).
   
   2. Fetch and Filter Files from Google Drive
   
   Next, the workflow uses the Google Drive API to retrieve all files from the specified folder. A Filter node ensures that only PDF files are selected while also excluding those that appear to have already been translated (identified via naming convention with “--{target_lang}”).
   
   This smart condition prevents unnecessary reprocessing of documents, which saves API costs and processing time.
   
   3. Downloading and Sending to DeepL
   
   For each qualifying PDF:
   - The file is first downloaded from Google Drive.
   - Then, an HTTP Request node sends the PDF file to DeepL’s /v2/document endpoint along with the source and target languages. DeepL returns a `document_id` and `document_key`, which are required for tracking the translation status.
   
   4. Monitoring the Translation Status
   
   The translation process is asynchronous. The workflow waits 5 seconds, then checks the translation status using another HTTP Request to the `/v2/document/{document_id}` endpoint. If the response indicates that the translation is not yet "done," the workflow loops and waits again.
   
   Once the status is "done," the workflow proceeds to the next stage.
   
   5. Retrieving and Uploading the Translated File
   
   Another HTTP Request fetches the translated PDF using DeepL’s `/v2/document/{document_id}/result` endpoint. The translated file is then uploaded back to the original Google Drive folder using the Google Drive API.
   
   To maintain clarity, the workflow renames the translated file by appending two dashes and the target language code to the filename. For example:
   - Original: Quarterly-Report.pdf
   - Translated: Quarterly-Report--FR.pdf
   
   6. Rate Limiting and Document Delays
   
   Between documents, a short 2-second wait is implemented to avoid overwhelming the DeepL API or Google Drive with rapid requests — helping ensure stability and comply with rate limits.
   
   Supported Languages
   
   DeepL provides an extensive list of supported languages, including but not limited to:
   - 🇬🇧 English (EN-GB, EN-US)
   - 🇫🇷 French (FR)
   - 🇩🇪 German (DE)
   - 🇪🇸 Spanish (ES)
   - 🇨🇳 Chinese (ZH)
   - 🇯🇵 Japanese (JA)
   
   The Sticky Note in the workflow references this list and links to the official DeepL documentation for updated information.
   
   Why This Workflow Is Useful
   
   - Saves time: Automates time-consuming file processing across your team or department.
   - Multilingual support: Enables you to process documents in nearly 30 languages.
   - Scalable: Works with large document batches and supports translation on the fly.
   - No code required: Perfect for non-developers using the visual workflow builder in n8n.
   
   Conclusion
   
   This powerful automation leverages n8n’s integration flexibility with Google Drive and DeepL to fully automate document translations with minimal human input. Whether you work in international business, legal, education, or content localization, automating your translations can enhance productivity and reduce errors.
   
   Start using this workflow to modernize your processes, facilitate global collaboration, and eliminate repetitive manual tasks.
   
   If you're new to n8n, head to their official documentation and explore more integrations to take your workflows to the next level.
   
   Happy automating!

5. Set credentials for each API node (keys, OAuth) in Credentials.
6. Run a test via Execute Workflow. Inspect Run Data, then adjust parameters.
7. Enable the workflow to run on schedule, webhook, or triggers as configured.

Tips: keep secrets in credentials, add retries and timeouts on HTTP nodes, implement error notifications, and paginate large API fetches.

Validation: use IF/Code nodes to sanitize inputs and guard against empty payloads.

Why Automate This with AI Agents

AI‑assisted automations offload repetitive, error‑prone tasks to a predictable workflow. Instead of manual copy‑paste and ad‑hoc scripts, your team gets a governed pipeline with versioned state, auditability, and observable runs.

n8n’s node graph makes data flow transparent while AI‑powered enrichment (classification, extraction, summarization) boosts throughput and consistency. Teams reclaim time, reduce operational costs, and standardize best practices without sacrificing flexibility.

Compared to one‑off integrations, an AI agent is easier to extend: swap APIs, add filters, or bolt on notifications without rewriting everything. You get reliability, control, and a faster path from idea to production.

Best Practices

• Credentials: restrict scopes and rotate tokens regularly.
• Resilience: configure retries, timeouts, and backoff for API nodes.
• Data Quality: validate inputs; normalize fields early to reduce downstream branching.
• Performance: batch records and paginate for large datasets.
• Observability: add failure alerts (Email/Slack) and persistent logs for auditing.
• Security: avoid sensitive data in logs; use environment variables and n8n credentials.

FAQs

Can I swap integrations later? Yes. Replace or add nodes and re‑map fields without rebuilding the whole flow.

How do I monitor failures? Use Execution logs and add notifications on the Error Trigger path.

Does it scale? Use queues, batching, and sub‑workflows to split responsibilities and control load.

Is my data safe? Keep secrets in Credentials, restrict token scopes, and review access logs.