# Build a Private Documentation Chatbot with Flowise and Regolo (No-Code) 👉[Try Regolo on Flowise](https://dashboard.regolo.ai) Building a custom AI chatbot usually requires a mess of Python scripts, API keys, and vector database management. Non-developers are locked out, and even developers waste hours setting up boilerplate just to "talk" to their own PDFs. Worse, standard no-code tools often force you to upload sensitive docs to US servers, creating a privacy nightmare for European businesses. **Launch a fully private, GDPR-aligned documentation chatbot in under 10 minutes. Visual drag-and-drop builder (Flowise) + European inference (Regolo) = Zero code, zero data leaks.** ## **Outcome** - **Visual Simplicity:** Connect nodes like Lego blocks (Document Loader -> Embedder -> LLM) to build complex agents without writing a single line of code. - **Data Sovereignty:** By using Regolo as the LLM and Embedding provider, your document vectors and chat queries stay strictly within EU infrastructure. - **Instant Deployment:** Flowise generates a ready-to-use chat widget or API endpoint for your website instantly—no frontend development needed. ## **Prerequisites (Fast)** - [**Regolo API Key**:](http://dashboard.regolo.ai) From your dashboard. - **Docker**: To run Flowise locally. - **Documents**: A URL or file to chat with (e.g., your company docs) ## **Step-by-Step (Code Blocks)** ### **1) Install Flowise (Docker)** Get the visual builder running on your machine. ``` git clone git@github.com:FlowiseAI/Flowise.git cd Flowise docker build --no-cache -t flowise . docker run -d --name flowise -p 3000:3000 flowiseCode language: Bash (bash) ``` Expected output: Access the Flowise UI at **http://localhost:3000** ### **2) Create the Document Pipeline** We need to load your docs and turn them into vectors. 1. **Node 1**: Cheerio Web Scraper (or File Loader). Paste your URL. 2. **Node 2**: Recursive Character Text Splitter (chunk size: 1000). 3. **Node 3**: OpenAI Embeddings Custom (This is the trick!). - **Base URL**: https://api.regolo.ai/v1 - **Model Name**: gte-Qwen2 (High-performance European embedding) - **API Key**: YOUR\_REGOLO\_KEY ### **3) Create the Chat Pipeline** Now connect the "Brain" to the vectors. 1. **Node 4**: Chat OpenAI Custom (The reasoning engine). - **Base URL**: https://api.regolo.ai/v1 - **Model Name**: Llama-3.1-8B-Instruct (or gpt-oss-120b). - **API Key**: YOUR\_REGOLO\_KEY. 2. **Node 5**: In-Memory Vector Store (or Pinecone for production). - Connect **Document** to the Loader. - Connect **Embeddings** to the Regolo Embedder. 3. **Node 6**: Conversational Retrieval QA Chain. - Connect **Chat Model** -> Node 4. - Connect **Vector Store** -> Node 5. ### **4) "Upsert" Your Data** Save the flow. You'll see a database icon (Upsert). Click it. Flowise will scrape your URL, chunk the text, send it to Regolo for embedding (gte-Qwen2), and store the vectors locally. ### **5) Chat with Your Docs** Click the **Chat** bubble in Flowise. *Query: "How do I configure the API?"* Expected output: The chatbot retrieves the relevant chunk from your docs and answers using Llama-3, citing the source. ## **Production-Ready: Embed Widget** Don't just keep it in Flowise. Add it to your app. 1. Click the **</>** (Embed) icon in Flowise. 2. Copy the script tag. 3. Paste it into your website's <body>. ``` Code language: HTML, XML (xml) ``` Expected output: A floating chat bubble on your site powered by Regolo. ## **Benchmarks & Costs** | **Feature** | **Regolo (via Flowise)** | **Proprietary Chatbots (Chatbase etc)** | |---|---|---| | **Data Privacy** | **High (EU Inference)**. | Low. Docs often stored in US. | | **Model Choice** | **Open (Llama/Qwen/Mistral)**. | Locked to GPT-3.5/4 usually. | | **Cost** | **Pay-per-token** (~€0.01 queries). | Monthly sub (€20-100/mo). | | **Customization** | **Full**. Edit prompt, temperature, RAG. | Limited black box. | ## 👉[Start Building Visually](https://dashboard.regolo.ai) ![](https://regolo.ai/wp-content/uploads/2025/07/Screenshot-From-2025-07-02-18-04-40-1024x557.png)--- ## **Resources & Community** **Official Documentation:** - [Flowise AI](https://flowiseai.com/) - Flowise AI website - [Regolo Platform](https://regolo.ai) - European LLM provider, Zero Data-Retention and 100% Green **Related Guides:** - [Boost Your Workflows with Regolo AI on n8n](https://regolo.ai/boost-your-workflows-with-regolo-ai-on-n8n/) - [Build Multi-Agent Workflows with crewAI Teams](https://regolo.ai/build-multi-agent-workflows-with-crewai-teams/) **Join the Community:** Open discussion on our[ Subreddit Community](https://www.reddit.com/r/regolo_ai/) [Regolo Discord](https://discord.gg/ZzZvuR2y) - Share your automation builds [CheshireCat GitHub](https://github.com/cheshire-cat-ai) - Contribute plugins Follow Us on X[ @regolo\_ai](https://x.com/regolo_ai) - Show your integrations! --- ## **🚀 Ready to Deploy?** ## [**Get Free Regolo Credits →**](https://dashboard.regolo.ai) --- > *Built with ❤️ by the Regolo team. Questions? support@regolo.ai*