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Lower Cost & Latency
The operational expenses associated with Large Language Models (LLMs) can quickly escalate as the number of requests and scale of operations increase. Similarly, with the growing scale, ensuring rapid response times to maintain a smooth user experience is critical. Portkey offers comprehensive caching capabilities that directly address these challenges, aiding in reducing costs and minimizing latency.
Caching plays a significant role in controlling the costs associated with LLMs. Our statistics have shown that using Portkey's caching mechanism, you can achieve up to 5% cost savings with Fixed String Matching Cache and up to 20% savings with Semantic Cache.
- 1.Reduced Redundant Requests: Many application scenarios, especially in chatbots, educational platforms, or customer support systems, can involve repeated requests. Such redundant requests, when handled via caching, result in substantial cost savings.
- 2.Lower Latency: By serving responses from the cache, you can significantly decrease response times. This results in a more seamless and responsive user experience, especially critical in interactive applications such as conversational AI systems.
Let's look at a few examples to illustrate how caching can be beneficial.
Knowledge Base Chat Applications: In these applications, many queries are often repetitive with minor variations in wording or phrasing. Leveraging Semantic Cache can be highly beneficial in this scenario. It can match the input prompt with previously cached requests based on contextual similarity, thereby avoiding the need to make a costly API call. The cache can serve the response instantly, reducing latency and saving costs.
Retrieval Augmented Generations (RAGs): RAGs often involve making repeated API calls to retrieve relevant documents or pieces of information. Caching can play a significant role in reducing these redundant calls, especially when a similar question or document retrieval request is made.
By implementing Portkey's caching feature, you're not only optimizing costs but also improving the performance and responsiveness of your AI-powered applications. This double advantage can be a significant factor in enhancing your application's scalability and user experience.