#Function Calling

The Mistral Inference repository offers a simplified pathway for deploying Mistral AI models. With clear installation instructions via PyPI and local environments, it supports models such as Mistral 7B and 8x22B for various applications including coding assistance and advanced mathematics solutions. Utilize GPU capabilities to enhance deployment efficiency, and explore features like function calling and interaction. Comprehensive documentation and community support are available to further guide users in maximizing AI capabilities. Designed for both enthusiasts and professionals to easily integrate leading AI technologies.

This repository offers essential tools for building function calling models with the OpenAI API, including a calculator, reverse geocoding, map tools, and custom search APIs. Designed for developers looking for ready-to-use solutions to integrate function calls into applications, the tools are user-friendly, supporting Node.js, cloud platforms, and serverless setups. Explore examples that demonstrate practical use cases.

Discover resources for using Large Language Models (LLMs) in generating JSON and other structured outputs, featuring a comprehensive guide on hosted and local models, Python libraries, and tutorials. Understand the advantages of structured generation for enhanced performance and explore tools and models from OpenAI and Google, among others, for integrating LLMs with external systems. Benefit from guided generation techniques using LangChain, Pydantic for effective data extraction and output structuring.

AIChat is a CLI tool offering Shell Assistant and Chat-REPL functionalities, integrating with over 20 LLM platforms like OpenAI and Huggingface. Features include custom roles, sessions, natural language conversion to shell commands, and a robust local server with LLM proxy and Playground.

The AI-driven voice assistant utilizes advanced AI models for diverse functions such as voice input, transcription, text-to-speech conversion, and image processing. Supporting tools like GPT-4 Vision and LLava-Next enhance its intelligent response capabilities, akin to innovative AI devices. Customizable interfaces and optional features are designed for versatile user experiences. The installation involves setting up API keys for essential AI services, allowing flexible deployment options. Contributions from the community are welcomed to further improve this comprehensive AI solution.

The Agents-Flex framework provides a suite of features including prompt templates, memory management, and embeddings to facilitate interactions with AI models like OpenAi, Qwen, and SparkAi. It incorporates efficient chat systems, document handling, and function invocation. This Java-based framework offers both historical chat capabilities and modular configurations for enhanced AI application development, catering to developers in need of effective language model management.