by System Admin
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by System Admin
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by Jenny
Evaluate Hybrid Search on Legal Dataset This is the second part of *"Hybrid Search with Qdrant & n8n, Legal AI."** The first part, "Indexing", covers preparing and uploading the dataset to Qdrant.* Overview This pipeline demonstrates how to perform Hybrid Search on a Qdrant collection using questions and text chunks (containing answers) from the LegalQAEval dataset (isaacus). On a small subset of questions, it shows: How to set up hybrid retrieval in Qdrant with: BM25-based keyword retrieval; 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 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. P.S. To ask retrieval in Qdrant-related questions, join the Qdrant Discord. Star Qdrant n8n community node repo <3
by System Admin
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by System Admin
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by Harshil Agrawal
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by Harshil Agrawal
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by Lucas Peyrin
How it works This template is a hands-on, practical exam designed to help you master n8n Expressions—the key to accessing and manipulating data in your workflows. If the 🎓 Expressions Tutorial Template was the theory lesson, this is the practical driving test. You'll learn how to navigate through complex data structures to get the exact piece of information you need. All challenges will reference a single "Source Data" node, which acts as our data "map". The test is a series of six sequential challenges that build in complexity: Basic Access: Getting a simple value from an object. Array Access: Targeting a specific item in a list. Nested Object Access: Reaching data inside another object. Array of Objects: Combining array and object skills to get a specific value from a list of objects. Using JavaScript: Applying simple JavaScript functions (like .toUpperCase()) to your data. Combining Text & Expressions: Creating dynamic strings that mix static text with data from previous nodes. For each challenge, you'll write an expression in a "Test" node. When you execute the workflow, an IF node will instantly validate your answer, giving you a green path for success or a red path with a hint if you need to try again. Set up steps Setup time: < 1 minute This workflow is a self-contained test and requires no setup or credentials. Read the instructions on the main sticky note to understand the goal. Start with the first challenge, "Test - Basic Access". Modify the node by writing the correct expression in the value field, according to the instructions on the purple sticky note. Click "Execute Workflow". If the execution path is green, you've passed! The next "Test" node in the sequence will automatically be enabled for you to continue. If the path is red, read the hint in the error message and try again. Repeat the process until you reach the final success message and become an expressions pro. Good Luck!
by amudhan
Companion workflow for Edit Image node docs
by tanaypant
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by Harshil Agrawal
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by Harshil Agrawal
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