Summary This post will cover the usage of guardrails in the context of an RAG application using Redis Stack as the vector store.   Nvidia's guardrail package is used for the railed implementation. Langchain LCEL is used for the non-railed implementation. Content from the online Redis vector search documentation is used for the RAG content GUI is implemented with Chainlit Application Architecture This bot is operating within a Chainlit app.  It has two modes of operation:   'chain' - no guardrails 'rails' - NeMo guardrails in place for both user inputs and LLM ..read more

Summary Redis Enterprise has the capability for continuous data integration with 3rd party data sources.  This capability is enabled via the Redis Data Integration (RDI) product.  With RDI, change data capture (CDC) can be achieved with all the major SQL databases for ingress.  Similarly, in the other direction, updates to Redis can be continuously written to 3rd party targets via the write-behind functionality of RDI.   This post covers a demo-grade environment of Redis Enterprise + RDI with ingress and write-behind integrations with the following SQL databases ..read more

Summary In this post, I cover an approach to a document AI problem using a task flow implemented in Apache Airflow.  The particular problem is around the de-duplication of invoices.  This comes up in payment provider space.  I use Azure AI Document Intelligence for OCR, Azure OpenAI for vector embeddings, and Redis Enterprise for vector search. Architecture Code Snippets File Sensor DAG OCR DAG OCR Client (Azure AI Doc Intelligence) Embedding DAG Embedding Client (Azure OpenAI) Vector Search DAG Vector Search Client (Redis Enterprise) Source https://github.com/Redisla ..read more

Summary This post covers comparisons of various data search scenarios of equivalent SQL and Redis Search commands.  The Chinook data set is deployed in Oracle Enterprise.  The Oracle Enterprise data is then continuously populated into Redis JSON objects using Redis Data Integration (RDI). Architecture This entire architecture is deployed in Docker containers. Sample Scenarios Scenario  - Which countries have the most Invoices? SQL Redis Search Scenario  - Which artists have written the most Rock music? This particular query touches 4 different tables in relational db ..read more

Summary This is Part 2 of a two-part series on the implementation of a contact center ACD using Redis data structures.  This part is focused on the network configuration.  In particular, I explain the configuration of HAProxy load balancing with VRRP redundancy in a Redis Enterprise environment.  To boot, I explain some of the complexities of doing this inside a Docker container environment. Part 1:  Basic ACD with Redis Enterprise Part 2:  HAProxy with Redis Enterprise Network Architecture Load Balancing Configuration HAProxy w/Keepalived Docker Container Dockerf ..read more

Summary This post covers a contact ACD implementation I've done utilizing Redis data structures.  The applications are written in Python.  The client interface is implemented as REST API via FastAPI.  An internal Python app (Dispatcher) is used to monitor and administer the ACD data structures in Redis.  Docker containers are used for architectural components. Part 1:  Basic ACD with Redis Enterprise Part 2:  HAProxy with Redis Enterprise Application Architecture Data Structures Contact, Queue Contacts are implemented as Redis JSON objects.  Each cont ..read more

 Summary This post covers a demonstration of the usage of Redis for caching DICOM imagery.  I use a Jupyter Notebook to step through loading and searching DICOM images in a Redis Enterprise environment. Architecture Redis Enterprise Environment Screen-shot below of the resulting environment in Docker. Sample DICOM Image I use a portion of sample images included with the Pydicom lib.  Below is an example: Code Snippets Data Load The code below loops through the Pydicom-included DICOM files.  Those that contain the meta-data that is going to be subsequently ..read more

Summary In this post, I cover a utility I wrote for observing Redis vector data and index sizes with varying data types and index parameters.  The tool creates a single-node, single-shard Redis Enterprise database with the Search and JSON modules enabled. Code Snippets Constants and Enums Redis Index Build and Data Load Sample Results Source https://github.com/Redislabs-Solution-Architects/vss-sizer ..read more

Summary This post covers a very specific use case of Redis in the short-term rental domain.  Specifically, Redis is used to find property availability in a given geographic area and date/time slot. Architecture Code Snippets Data Load The code below loads rental properties as Redis JSON objects and US Postal ZIP codes with their associated lat/longs as Redis strings. Property Search The code below represents an Expressjs route for performing searches on the Redis properties.  The search is performed on rental property type and geographic distance from a given location. Source h ..read more

Summary I'll be covering the use case of providing supplemental context to OpenAI in a question/answer scenario (ChatGPT).  Various news articles will be vectorized and stored in Redis.  For a given question that lies outside of ChatGPT's knowledge, additional context will be fetched from Redis via Vector Similarity Search (VSS).   That context will aid ChatGPT in providing a more accurate answer. Architecture Code Snippets OpenAI Prompt/Collect Helper Function The code below is a simple function for sending a prompt into ChatGPT and then extracting the resulting respon ..read more