Table of Contents Why RAG?Large Language Models (LLMs)Vector embeddingsVectors applied to wordsVectors applied to dataSimilarity searchWrapping up!Resources Retrieval Augmented Generation (RAG) may sound complex, but it accurately represents the process of the system. RAG is a method that enhances the …
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Understanding BSON: A Beginner’s Guide to MongoDB’s Data Format
Table of Contents What is BSON?Why not just JSON?BSON vs. JSONCommon BSON data types (and their Java equivalents)BSON and MongoDB internalsSetup and project structureBSON data types and document creationNested fields and arraysWhy use nested structures?Raw BSON manipulationQuerying with BSONAggregation with …
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Building a Real-Time AI Fraud Detection System with Spring Kafka and MongoDB
Table of Contents What we are buildingPrerequisitesCreate our MongoDB databaseCreate a Vector Search indexCreate a Spring applicationSetting up configurationMongoDB configurationSpring AI configurationKafka configurationGenerate our synthetic customer profilesThe customer modelCustomer seedingHow the sample customers are structuredThe transaction modelGenerating random transactionsHow do …
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GenAI blood, sweat, and tears: Loading data to Pinecone
Table of Contents Getting startedIssue #1: APIs, SDKs, and rapid changeIssue #2: ConfigIssue #3: JSON formatIssue #4: Loading data to Pinecone1. Metadata keysAlternative embeddings – Book descriptionsWrapping up!Resources As someone who is pretty familiar with relational and graph databases, I …
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Semantic Search with Spring Boot & Redis
Table of Contents Redis as a Vector DatabaseRedis OM SpringDatasetBuilding the Application0. GitHub Repository1. Add the required dependencies2. Define the Movie entity3. Repository Interface4. Search Service5. Movie Service for Data Loading5. Search Controller6. Application Bootstrap7. Sample RequestsWrapping upMore AI ResourcesStay …
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Breaktime Tech Talks (Ep39): Why embedding models should match + Advice for starting a blog
Table of Contents Why embedding models should matchDifferences in similarity searchAdvice for starting a blogWrapping up! This is episode 39 of the Breaktime Tech Talks podcast. I’m at a conference this week presenting on a variety of different topics, but …
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Breaktime Tech Talks (Ep37): Vector Database Frustration + Microsoft LazyGraphRAG
Table of Contents Devnexus conference shout-outVector database explorationIssues getting up and runningOverall experienceMicrosoft LazyGraphRAGWrapping up! This is episode 37 of the Breaktime Tech Talks. You are listening to the Breaktime Tech Talks podcast, a bite-sized tech podcast for busy developers, …
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Book Review: DuckDB in Action
Table of Contents FactsChaptersPros and consConclusion Disclaimer: this post includes affiliate links; I may receive compensation if you purchase the book from the different links provided in this post. This review is about DuckDB in Action by JoMark Needham, Michael …
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Sliding Window Counter Rate Limiter (Redis & Java)
Table of Contents IndexHow It Works1. Define a Time Window2. Track Requests3. Remove Expired Intervals4. Rate Limit CheckHow to Implement It with Redis1. Track Requests by Sub-Interval2. Remove Expired Intervals3. Sum Counts for the Active WindowImplementing it with JedisAdd Jedis …
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Spring Data Neo4j: How to update an entity
Table of Contents Spring save() methodPatch YearCustom CypherProjectionsProjection as MovieMovie entity as projectionWrapping Up!Resources After working on a new online Spring Data Neo4j course, I learned a couple more things about updating an entity. The course required a different set …
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Token Bucket Rate Limiter (Redis & Java)
Table of Contents How It Works1. Define a Token Refill Rate2. Track Token Consumption3. Refill Tokens4. Rate Limit CheckHow to Implement It with Redis and Java1. Retrieve current token count and last refill time2. Refill tokens if necessary and update …