Building Your First RAG Pipeline
ANKA Team
Product
Getting Started with RAG Pipelines
Creating a document intelligence pipeline with ANKA is straightforward. This guide walks you through the entire process, from initial setup to production deployment.
Step 1: Define Your Knowledge Base
Before building, clearly define which documents your pipeline should cover. Common use cases include internal wikis, compliance documents, product manuals, and research papers. A well-defined scope ensures better retrieval accuracy.
Step 2: Configure Indexing
Set up your document indexing pipeline with the right chunking strategy and embedding model. ANKA's workspace interface makes it easy to upload documents, configure parsing options, and customize chunking parameters.
Step 3: Integration Setup
Connect your pipeline to your existing tools. ANKA integrates with popular LLM providers (Ollama, OpenAI, Anthropic), vector databases (Qdrant, Pinecone), and storage systems out of the box.
Step 4: Test and Iterate
Always test with real queries before going live. Use ANKA's evaluation tools to measure retrieval accuracy, answer quality, and citation correctness. Monitor the analytics dashboard to identify areas for improvement.
Best Practices
- Start with a focused document set and expand gradually
- Use meaningful metadata tags for better filtering
- Set up hybrid search combining semantic and keyword approaches
- Monitor retrieval metrics and refine chunking based on real usage
