Aug 11Member-onlyHow to Connect Wikipedia with ChatGPT and LangChainChatGPT integration with Wikipedia using LangChain — ChatGPT’s knowledge is limited to its training data, which has the cutoff year of 2021. This implies that we cannot extract information for cases that have occurred after the cutoff year. However, we can integrate Wikipedia with ChatGPT. We will go straightforward with an example. …ChatGPT2 min readChatGPT2 min read
Aug 3Member-onlyHow to Save and Load Prompt Templates with LangChainDid you know that you can save and load your prompts? — In a previous tutorial, we showed you how to work with LangChain Prompt Templates. Clearly, the prompt templates allow us to automate some tasks and to work much more efficiently. The good news is that you can save your templates as JSON objects, allowing you to use them later or…Langchain2 min readLangchain2 min read
Aug 3Member-onlyHow to Generate Structured Outputs of JSON with Lists And Dictionaries with LangChainHow to generate complicated structured outputs with LangChain — The output of the LLMs is plain text. However, many times we want to get structured responses in order to be able to analyze them better. The LangChain library contains several output parser classes that can structure the responses of the LLMs. …Langchain5 min readLangchain5 min read
Aug 2Member-onlyHow to Work with Date Range SQL Parameters in Sigma ComputingA practical example of using Date Range Control Elements in SQL queries as parameters — Sigma Computing is a cloud analytics platform that uses a familiar spreadsheet interface to give business users instant access to explore and get insights from their cloud data warehouse. In this tutorial, I will share with you my experience with Date Range parameters that I found really challenging. Sigma has…Business Intelligence3 min readBusiness Intelligence3 min read
Jul 26Member-onlyGet Started With Langchain Prompt TemplatesPractical examples of Langchain prompt templates in Python — In the majority of cases, LLM applications don’t directly input user input into an LLM. Instead, they utilize a larger piece of text known as a “prompt template” to include the user input along with additional context related to the specific task. They encapsulate all the necessary logic to transform…OpenAI4 min readOpenAI4 min read
Jul 13Member-onlyThe Benjamini-Hochberg Procedure (FDR) And P-Value Adjusted ExplainedHow to calculate the P-Value Adjusted in R, Python and Excel — In this tutorial, we will show you how to apply the Benjamini-Hochberg procedure in order to calculate the False Discovery Rate (FDR) and the P-Value Adjusted. The Benjamini-Hochberg procedure, also known as the False Discovery Rate (FDR) procedure, is a statistical method used in multiple hypothesis testing to control the…Statistics4 min readStatistics4 min read
Jun 20Member-onlyHow to read CSV in Pandas with Column Names or Regular ExpressionsA practical example of how to load columns based on columns names or using regex — A common scenario is to work with massive datasets consisting of many columns which are not needed for our analysis. Usually, we tend to load the whole dataset and then keep the columns of our interest. Let’s see a more efficient way to load only the columns of our interest. …Python3 min readPython3 min read
May 5Member-onlyHow to Connect External Data with GPT-3 Using LlamaIndexA gentle introduction to how to connect custom external data with LLM using LlmaIndex — In this tutorial, we will show you how to connect external data with OpenAI GPT3 using LlamaIndex. For this example, we will connect the book Alice’s Adventures in Wonderland, by Lewis Carroll. By connecting the book with OpenAI GPT3 we will be able to make questions and receive answers related…Llamaindex6 min readLlamaindex6 min read
May 4Member-onlyAnalyze Pandas Dataframes With OpenAI and LlamaIndexDid you know that you can pass a pandas data frame into OpenAI — LlamaIndex is used to connect LLMs with external data. In this tutorial, we will show you how to use the OpenAI GPT-3 text-davinci-003 model to query structured data and more particularly pandas dataframes. Installation Using pip you can install the LlamaIndex library as follows: pip install llama-index Query Pandas Dataframes with LlamaIndexLlamaindex3 min readLlamaindex3 min read
Apr 21Member-onlyUnlock the Power of ChatGPT with the Python OpenAI Chat APIA practical example of how to interact with the OpenAI Chat API in Python — Most of us are familiar with the ChatGPT UI, and we are impressed with the stunning results that it generates. Clearly, this is a revolution in the AI world. The UI of the ChatGPT is really friendly, and it allows us to start experimenting with different prompts, but in order…OpenAI7 min readOpenAI7 min read
