RAG Chatbot

Just 2 nodes. Easy indexing of data. Your RAG chatbot is set up - as easy as it can get.

This Needle workflow template creates an intelligent chatbot that can answer questions about your documents using RAG (Retrieval-Augmented Generation). Start by creating a Needle Collection and uploading the files you want your RAG chatbot to have access to. Once your knowledge base is ready, simply put your query in the Trigger node and run the workflow. The AI Agent will search through your documents and provide grounded, accurate responses based on your content.

What This Workflow Does

2 Nodes. That's It.

Manual Trigger - Ask your question

AI Agent - Searches your collection and returns the answer

That's the whole workflow. No complex chains, no prompt engineering, no vector database management.

AI-Powered Search: Ask questions in natural language and get answers from your documents

Document Intelligence: Automatically searches through PDFs, docs, markdown files, and more

Grounded Responses: All answers come from your actual documents - no hallucinations

Multi-Step Reasoning: The AI can iterate up to 3 times to find the best answer

Try It Out!

1. Create Your Knowledge Base

Set Up Your Collection

1. Go to needle.app/dashboard/collections
2. Click "Create Collection"
3. Give it a clear name (like "Product Docs" or "Company Policies")
4. Upload your documents (product docs, policies, research papers, meeting notes - anything)

Supported File Types:

• PDFs
• Word docs
• Markdown files
• Text files
• Google Docs (via export)

2. Configure the Workflow

Connect Your Collection

1. Open the AI Agent node
2. In the tools section, you'll see the

   search_collection

   tool
3. Select your collection by name from the dropdown
4. That's it - you're ready to go!

3. Ask Your Questions

You can ask natural language questions like:

• "What's our refund policy?"
• "How do I set up the API authentication?"
• "What did we decide in last week's meeting about the pricing change?"
• "Does our product support single sign-on?"
• "What are the system requirements mentioned in the docs?"

The AI will search your documents and give you accurate answers with context.

Real Use Cases

Product Documentation Stop manually searching through 200-page docs. Just ask "How do I configure the webhook?" and get the exact answer.

Company Knowledge Base "What's the PTO policy?" "How do I submit expenses?" Let new employees find answers without bothering HR.

Research Papers Uploaded 50 PDFs from your research? Ask "What methods did previous studies use for data collection?" and get a summary.

Customer Support Train a chatbot on your FAQ and support articles. Get consistent, accurate answers every time.

Meeting Notes "What action items were assigned to Sarah in Q1 meetings?" Search across months of notes instantly.

Pro Tips

Increase max_steps for complex questions Default is 3 iterations. For deep research questions, bump it to 5-10. The AI will dig deeper and synthesize information from multiple sources.

Enable Hybrid RAG Add the

search_web

To enable:

1. In the AI Agent node, add

   search_web

   to the tools array
2. Now your chatbot can fact-check internal docs against external sources

Customize the system prompt Default works great, but you can adjust the tone:

• "You are a helpful technical support agent" - Professional, patient
• "You are a concise research assistant" - Brief, academic
• "You are a friendly team wiki bot" - Casual, approachable

Temperature settings

• Keep at 0 for factual Q&A (recommended)
• Bump to 0.3-0.5 if you want more creative interpretation
• Never go above 0.7 for document-based answers

Common Questions

Q: How many documents can I upload? A: No hard limit on the Needle side - collections scale well. Test with 10-20 docs first, then expand.

Q: Does it work with images in PDFs? A: Yes! Text extraction works great. For complex diagrams, you may want to add captions in the original doc.

Q: Can I use this for customer-facing support? A: Absolutely. Just replace the Manual Trigger with a Gmail trigger or Telegram bot trigger to handle incoming questions automatically.

Q: What if my documents are in different languages? A: GPT-4.1 handles 50+ languages. Upload docs in any language and ask questions in that same language.

What's Next?

Once you've got the basic chatbot working, try these upgrades:

Automate it: Replace the Manual Trigger with Gmail, Slack, or Telegram to handle questions automatically

Add memory: Store conversation history so the bot remembers context from previous questions

Multi-collection search: Add multiple

search_collection

Structured output: Use the structured output schema to format answers as JSON for downstream automation

Wrap-up

2 nodes. Easy indexing. Done.

Setting up RAG used to require a team of ML engineers, complex vector databases, and weeks of configuration. Now? Create your collection, connect 2 nodes, ask questions.

That's it. Your RAG chatbot is ready.

Perfect for anyone drowning in documentation, managing a knowledge base, or building AI-powered support systems.