Game Builder uses AI agents to generate, review, and evaluate Python game code, ensuring high-quality and functional game development.
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Updated
Jul 23, 2024 - Python
Game Builder uses AI agents to generate, review, and evaluate Python game code, ensuring high-quality and functional game development.
This repository showcases a comprehensive approach to information retrieval, document re-ranking, and language model integration. It incorporates techniques such as document chunking, embedding projection, and automatic query expansion to enhance the effectiveness of information retrieval systems.
Helping beekeepers save their bees.
Machine Learning sample assets, notebooks and apps.
Workshop em Português para o IBM watsonx Assistant
Simple implementation of RAG using watsonx.ai, capturing the chat history to keep track of the conversation context and answer follow up questions.
This project contains a simple example implementation for a simple question-answering pipeline using inside-search (IBM Cloud Watson Discovery) and prompt (IBM watsonx with prompt-lab).
Using Integrated Custom Skills in IBM Watsonx Orchestrate
A repository to store piece of code...
Document to CSV Generator is a robust application designed to facilitate the efficient transformation of document content into structured CSV files using Generative AI
This is an example using the langchain_ibm implementation for function calling a LLM model running in watsonx.
A deployable architecture solution to deploy IBM Watsonx SaaS resources.
Storing code used in Generative AI Developer Guides on the IBM Developer Website
CustomLLM config to leverage watsonx LLMs with continue.dev.
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