Hello prompt engineers, I’ve been reading about how to improve the process of reasoning over long documents by optimizing the chunking process (how to break up the text into pieces) and then summarizing before creating embeddings to achieve better responses. In this blog post we’ll try to apply that philosophy to the Jetchat demo’s confe...
Hello prompt engineers, This week we’re taking a break from code samples to highlight the general availability of Azure AI Content Safety. In this blog series we’ve touched briefly on the using prompt engineering to restrict the types of responses an LLM will provide, such as setting the system prompt to set boundaries on what questions ...
Hello prompt engineers, Over the course of this blog series, we have investigated different ways of augmenting the information available to an LLM when answering user queries, such as: However, there is still a challenge getting the model to answer with up-to-date “general information” (for example, if the ques...
Hello prompt engineers, The past few weeks we’ve been extending JetchatAI’s sliding window which manages the size of the chat API calls to stay under the model’s token limit. The code we’ve written so far has used a VERY rough estimate for determining the number of tokens being used in our LLM requests: This very simple approxim...
