Hugging Face introduces a unified tool use API across multiple model families, making it easier to implement tool use in language models.
Hugging Face has extended chat templates to support tools, offering a unified approach to tool use with the following features:
- Defining tools: Tools can be defined using JSON schema or Python functions with clear names, accurate type hints, and complete docstrings.
- Adding tool calls to the chat: Tool calls are added as a field of assistant messages, including the tool type, name, and arguments.
- Adding tool responses to the chat: Tool responses are added as tool messages containing the tool name and content.
Hugging Face has extended chat templates to support tools, offering a unified approach to tool use with the following features:
- Defining tools: Tools can be defined using JSON schema or Python functions with clear names, accurate type hints, and complete docstrings.
- Adding tool calls to the chat: Tool calls are added as a field of assistant messages, including the tool type, name, and arguments.
- Adding tool responses to the chat: Tool responses are added as tool messages containing the tool name and content.
Mistral AI has introduced two methods for creating custom AI agents: La Plateforme Agent Builder, a user-friendly interface, and Agent API, a programmatic solution. This allows users to create and configure agents using Mistral's AI models or fine-tuned models.
SerpApi provides a web scraping API to access Google Search and other search engine results. Get structured data for SEO, market research, and more.
This article explains how to run inference on a YOLOv8 object detection model using Docker and create a REST API to orchestrate the process. It includes code implementation and a detailed README in the author's GitHub repository for running the API via REST with Docker.
OnDemand AI provides API services for media, services, and plugins, allowing developers to upload media, use NLP, and deploy machine learning models. It also facilitates serverless application deployment and allows BYOM (Bring Your Own Model) and BYOI (Bring Your Own Inference).
This article discusses how to overcome limitations of retrieval-augmented generation (RAG) models by creating an AI assistant using advanced SQL vector queries. The author uses tools such as MyScaleDB, OpenAI, LangChain, Hugging Face and the HackerNews API to develop an application that enhances the accuracy and efficiency of data retrieval process.
Official Beepy API documentation providing information about getting started, installation, authentication, IP whitelist, request parameters, response examples, webhooks, labels, errors, and changelogs.
Learn how to build an open LLM app using Hermes 2 Pro, a powerful LLM based on Meta's Llama 3 architecture. This tutorial explains how to deploy Hermes 2 Pro locally, create a function to track flight status using FlightAware API, and integrate it with the LLM.
This guide provides an introduction to kubectl, the command-line tool used to communicate with the Kubernetes API. It covers command syntax, useful commands, flags, and tips and tricks. It also discusses the ecosystem of plugins and tools built to expand the functionalities of kubectl and Kubernetes.
A tutorial showing you how how to bring real-time data to LLMs through function calling, using OpenAI's latest LLM GTP-4o.
