Integrations
Integrate Redis for Enhanced AI Chat Context
Use Redis as a vector database to provide external context to AI chat models, overcoming knowledge cutoffs and improving response quality.
Without it
Piece it together by hand, every time.
With it
Leverage Redis as a high-speed context memory to augment AI chat capabilities, enabling more informed responses on topics beyond the model's knowledge cutoff.
What you get
- Set up Redis with Search and JSON modules for vector storage.
- Index external data into Redis for retrieval.
- Embed user queries and perform vector similarity search in Redis.
- Incorporate retrieved context into OpenAI chat prompts for improved accuracy.
Use this prompt chain
Redis as a Context Store with OpenAI Chat
This notebook demonstrates how to use Redis as high-speed context memory with ChatGPT.
Prerequisites
- Redis instance with the Redis Search and Redis JSON modules
- Redis-py client lib
- OpenAI Python client lib
- OpenAI API key
Installation
Install Python modules necessary for the examples.
OpenAI API Key
Create a .env file and add your OpenAI key to it
OpenAI Setup
Key load + helper function for chat completion
Experiment - Chat Completion on a Topic outside of the Model's Knowledge Cutoff Date
Gpt-3.5-turbo was trained on data up to Sep 2021. Let's ask it a question about something that is beyond that date. In this case, the FTX/Sam Bankman-Fried scandal. We are using an old model here for demonstration. Newer models such as got-4o has later knowledge cutoffs (late 2023) and will work here as well.
Incomplete Information
An unfortunate behavior of these AI systems is the system will provide a confident-sounding response - even when the system is not confident with its result. One way to mitigate this is prompt re-engineering, as seen below.
Additional Context
Another way to combat incomplete information is to give the system more information such that it can make intelligent decisions vs guessing. We'll use Redis as the source for that additional context. We'll pull in business news articles from after the GPT knowledge cut-off date such that the system will have a better understanding of how FTX was actually managed.
Start the Redis Stack Docker container
Connect Redis client
Create Index
Load Data Files into Redis as JSON Objects with Text and Vector Fields
Embed the Question and Perform VSS to find the most relevant document
Repeat the Question to OpenAI with context
Now that we have relevant context, add that to the prompt to OpenAI and get a very different response.