Evaluate hybrid search for legal question-answering using Qdrant & BM25/mxbai

Evaluate Hybrid Search on Legal Dataset This is the second part of "Hybrid Search with Qdrant & n8n, Legal AI." The first part, ["Indexing"](https://n8n.io/workflows/7945-hybrid-search-with-qdrant-and-n8n-legal-ai-indexing/), covers preparing and uploading the dataset to Qdrant.

Overview This pipeline demonstrates how to perform Hybrid Search on a [Qdrant collection](https://qdrant.tech/documentation/concepts/collections/collections) using questions and text chunks (containing answers) from the [LegalQAEval dataset (isaacus)](https://huggingface.co/datasets/isaacus/LegalQAEval).

On a small subset of questions, it shows: - How to set up hybrid retrieval in Qdrant with: - [BM25](https://en.wikipedia.org/wiki/OkapiBM25)-based keyword retrieval; - [mxbai-embed-large-v1](https://huggingface.co/mixedbread-ai/mxbai-embed-large-v1) semantic retrieval; - Reciprocal Rank Fusion (RRF), a simple zero-shot fusion of the two searches; - How to run a basic evaluation: - Calculate hits@1 — the percentage of evaluation questions where the top-1 retrieved text chunk contains the correct answer

After running this pipeline, you will have a quality estimate of a simple hybrid retrieval setup. From there, you can reuse Qdrant’s Query Points node to build a legal RAG chatbot.

Embedding Inference - By default, this pipeline uses [Qdrant Cloud Inference](https://qdrant.tech/documentation/cloud/inference/) to convert questions to embeddings. - You can also use an external embedding provider (e.g. OpenAI). - In that case, minimally update the pipeline, similar to the adjustments showed in Part 1: Indexing.

Prerequisites - Completed Part 1 pipeline, "Hybrid Search with Qdrant & n8n, Legal AI: Indexing", and the collection created in it; - All the requirements of Part 1 pipeline;

Hybrid Search The example here is a basic hybrid query. You can extend/enhance it with: - Reranking strategies; - Different fusion techniques; - Score boosting based on metadata; - ...

More details: [Hybrid Queries in Qdrant](https://qdrant.tech/documentation/concepts/hybrid-queries/).