Best AI tools for< Perform Function Calling >

neurons.bio is an AI application that offers a unique collection of over 100 AI agents designed for drug development, medicine, and life science research. These agents perform specific tasks efficiently, retrieve data from various sources, and provide insights to accelerate research processes. The platform aims to revolutionize drug discovery and development by integrating cutting-edge LLM technology with domain-specific agents, reducing research costs and time to clinic.

ChatGPT Deutsch is an intelligent chatbot tool developed by OpenAI that allows users to interact online with the large GPT language model through the OpenAI API function, enabling them to create text in AI language. The tool is equipped with many features to perform various tasks such as language translation, content creation, and programming support in just a few seconds. ChatGPT Deutsch offers unlimited conversation possibilities based on vast and reliable data sources from various information channels. Users of GPT Deutsch can start asking questions immediately without incurring any fees or complicated account registration.

NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and high-level mathematical functions to perform operations on these arrays. It is the fundamental package for scientific computing with Python and is used in a wide range of applications, including data science, machine learning, and image processing. NumPy is open source and distributed under a liberal BSD license, and is developed and maintained publicly on GitHub by a vibrant, responsive, and diverse community.

Spreadsheet Daddy is an AI-powered add-on for Google Sheets that enables users to automate tasks, generate content, extract data, and perform various other functions using advanced AI models like GPT-4 and GPT-4-32k. It seamlessly integrates with Google Sheets, allowing users to leverage the power of AI within their spreadsheets. With its user-friendly interface and diverse range of features, Spreadsheet Daddy empowers businesses and individuals to enhance their productivity and efficiency.

EnergeticAI is an open-source AI library that can be used in Node.js applications. It is optimized for serverless environments and provides fast cold-start, small module size, and pre-trained models. EnergeticAI can be used for a variety of tasks, including building recommendations, classifying text, and performing semantic search.

Gleen AI is a highly accurate and capable generative AI platform designed for customer success. It leverages AI/ML systems like GPT-4 to provide accurate and relevant responses to customer queries. The platform can perform automatic actions, unify fragmented knowledge from various sources, and is used by over 250 companies to enhance customer interactions and support. Gleen AI is suitable for multiple functions across different industries, offering a seamless integration with various customer service and communication channels.

Martin is a personal AI assistant application that functions as a virtual assistant similar to Jarvis. It helps users manage their to-do lists, calendars, emails, and more by keeping everything in its working memory. Martin can perform tasks like sending messages, setting reminders, managing tasks, and syncing with various tools and platforms. Users can access Martin through voice mode, notifications, and shortcuts, making it a convenient and efficient tool for organizing daily tasks and improving productivity.

functime is an AI tool designed for time-series machine learning at scale. It provides a comprehensive set of functions and resources for users to perform forecasting tasks efficiently. With features like scoring, ranking, and plotting functions, functime simplifies the evaluation process of thousands of forecasts simultaneously. Additionally, it offers an AI copilot feature to analyze and compare trends, seasonality, and causal factors in forecasts. The tool also includes detailed API reference documentation for seamless integration.

AdGen AI is an AI-powered creative generator that helps businesses create high-performing ad copy and visuals for multiple ad channels. It uses machine learning models to analyze product data and generate a variety of ad creatives that are tailored to the target audience. AdGen AI also allows users to publish ads directly from the platform, making it easy to launch and manage ad campaigns.

JobInterview.guru is an AI-powered platform designed to provide personalized interview training for job seekers. Leveraging advanced AI technology, the platform offers realistic job interview simulations, detailed insights into interview questions, and personalized feedback to help users prepare effectively. With a focus on efficiency and cost-effectiveness, JobInterview.guru aims to empower users to confidently navigate their job interviews and land their dream jobs.

LambdaTest is a next-generation mobile apps and cross-browser testing cloud platform that offers a wide range of testing services. It allows users to perform manual live-interactive cross-browser testing, run Selenium, Cypress, Playwright scripts on cloud-based infrastructure, and execute AI-powered automation testing. The platform also provides accessibility testing, real devices cloud, visual regression cloud, and AI-powered test analytics. LambdaTest is trusted by over 2 million users globally and offers a unified digital experience testing cloud to accelerate go-to-market strategies.

Laxis is a revolutionary AI Meeting Assistant designed to capture and distill key insights from every customer interaction effortlessly. It seamlessly integrates across platforms, from online meetings to CRM updates, all with a user-friendly interface. Laxis empowers revenue teams to maximize every customer conversation, ensuring no valuable detail is missed. With Laxis, sales teams can close more deals with AI note-taking and insights from client conversations, business development teams can engage prospects more effectively and grow their business faster, marketing teams can repurpose podcasts, webinars, and meetings into engaging content with a single click, product and market researchers can conduct better research interviews that get to the "aha!" moment faster, project managers can remember key takeaways and status updates, and capture them for progress reports, and product and UX designers can capture and organize insights from their interviews and user research.

CampaignBuilder.AI is an AI-powered platform that enables users to quickly generate and launch AI-optimized advertising campaigns across major ad platforms. The tool offers a range of features to streamline campaign creation, including AI-generated copywriting, audience targeting, and creative building. With full-funnel capabilities, CampaignBuilder.AI aims to help businesses of all sizes improve campaign performance and efficiency. The platform provides users with creative freedom and automation to save time and enhance campaign effectiveness.

Laxis is an AI Meeting Assistant designed to empower revenue teams by capturing and distilling key insights from customer interactions effortlessly. It offers seamless integration across platforms, from online meetings to CRM updates, with a user-friendly interface. Laxis helps users stay focused during meetings, auto-generate meeting summaries, identify customer requirements, and extract valuable insights. It supports multilingual interactions, real-time transcriptions, and provides answers based on past conversations. Trusted by over 35,000 business professionals from 3000 organizations, Laxis saves time, improves note-taking, and enhances communication with clients and prospects.

Ask Blue J is a generative AI tool designed specifically for tax experts. It provides fast, verifiable answers to complex tax questions, helping professionals work smarter and more efficiently. With its extensive database of curated tax content and industry-leading AI technology, Ask Blue J enables users to conduct efficient research, expedite drafting, and enhance their overall productivity.

Blue J is a legal technology company founded in 2015, dedicated to enhancing tax research with the power of AI. Their AI-powered tool, Ask Blue J, provides fast and verifiable answers to tax questions, enabling tax professionals to work more efficiently. Blue J's generative AI technology helps users find authoritative sources quickly, expedite drafting processes, and cater to junior staff's research needs. The tool is trusted by hundreds of leading firms and offers a comprehensive database of curated tax content.

Sales Closer AI is an AI-powered sales tool designed to help businesses scale their sales operations by creating AI agents capable of handling various tasks such as phone calls, scheduling, and conducting personalized discovery calls. The tool integrates seamlessly with existing CRM and marketing tools, enabling users to uncover customer pain points, build rapport, and deliver interactive demos in multiple languages. Sales Closer AI continuously learns and optimizes its approach, providing detailed notes for future reference and boosting conversion rates across different industries.

GPTConsole is an AI-powered platform that helps developers build production-ready applications faster and more efficiently. Its AI agents can generate code for a variety of applications, including web applications, AI applications, and landing pages. GPTConsole also offers a range of features to help developers build and maintain their applications, including an AI agent that can learn your entire codebase and answer your questions, and a CLI tool for accessing agents directly from the command line.

The website is currently displaying a '403 Forbidden' error message, which indicates that the server is refusing to respond to the request. This error is often caused by incorrect permissions on the server or a misconfiguration in the server software. The 'openresty' message suggests that the server is using the OpenResty web platform. Users encountering this error should contact the website administrator for assistance in resolving the issue.

Validator by Yazero is a platform that helps users validate their startup ideas using AI. It provides a community where users can share their ideas, get feedback, and find collaborators. Validator also offers a variety of features to help users improve their ideas, such as idea validation, market research, and financial planning.

ChatLab is a Python package that simplifies experimenting with OpenAI's chat models. It provides an interactive interface for chatting with the models and registering custom functions. Users can easily create chat experiments, visualize color palettes, work with function registry, create knowledge graphs, and perform direct parallel function calling. The tool enables users to interact with chat models and customize functionalities for various tasks.

Nerve is a tool that allows creating stateful agents with any LLM of your choice without writing code. It provides a framework of functionalities for planning, saving, or recalling memories by dynamically adapting the prompt. Nerve is experimental and subject to changes. It is valuable for learning and experimenting but not recommended for production environments. The tool aims to instrument smart agents without code, inspired by projects like Dreadnode's Rigging framework.

The `@samchon/openapi` repository is a collection of OpenAPI types and converters for various versions of OpenAPI specifications. It includes an 'emended' OpenAPI v3.1 specification that enhances clarity by removing ambiguous and duplicated expressions. The repository also provides an application composer for LLM (Large Language Model) function calling from OpenAPI documents, allowing users to easily perform LLM function calls based on the Swagger document. Conversions to different versions of OpenAPI documents are also supported, all based on the emended OpenAPI v3.1 specification. Users can validate their OpenAPI documents using the `typia` library with `@samchon/openapi` types, ensuring compliance with standard specifications.

This repository contains a library for constraining LLM generation to structured output, enforcing a JSON schema for precise data types and property names. It includes an acceptor/state machine framework, JSON acceptor, and JSON schema acceptor for guiding decoding in LLMs. The library provides reference implementations using Apple's MLX library and examples for function calling tasks. The tool aims to improve LLM output quality by ensuring adherence to a schema, reducing unnecessary output, and enhancing performance through pre-emptive decoding. Evaluations show performance benchmarks and comparisons with and without schema constraints.

This repository contains a Spring AI re-implementation of an expert system demo that showcases building an AI-powered system with capabilities such as retrieval augmented generation, function calling using Java methods, and interaction with the user through an LLM. The app requires Java 17+ and an OpenAI API key. It provides examples of integrating with various chat services like OpenAI, VertexAI Gemini, Azure OpenAI, Groq, and Anthropic Claude 3. Users can explore different chat options and models for AI interactions within the system.

Tools4AI is a Java-based Agentic Framework for building AI agents to integrate with enterprise Java applications. It enables the conversion of natural language prompts into actionable behaviors, streamlining user interactions with complex systems. By leveraging AI capabilities, it enhances productivity and innovation across diverse applications. The framework allows for seamless integration of AI with various systems, such as customer service applications, to interpret user requests, trigger actions, and streamline workflows. Prompt prediction anticipates user actions based on input prompts, enhancing user experience by proactively suggesting relevant actions or services based on context.

Akeru.ai is an open-source AI platform leveraging the power of decentralization. It offers transparent, safe, and highly available AI capabilities. The platform aims to give developers access to open-source and transparent AI resources through its decentralized nature hosted on an edge network. Akeru API introduces features like retrieval, function calling, conversation management, custom instructions, data input optimization, user privacy, testing and iteration, and comprehensive documentation. It is ideal for creating AI agents and enhancing web and mobile applications with advanced AI capabilities. The platform runs on a Bittensor Subnet design that aims to democratize AI technology and promote an equitable AI future. Akeru.ai embraces decentralization challenges to ensure a decentralized and equitable AI ecosystem with security features like watermarking and network pings. The API architecture integrates with technologies like Bun, Redis, and Elysia for a robust, scalable solution.

Ollama is a powerful tool for running large language models locally or on your own infrastructure. It provides a full implementation of the Ollama API, support for streaming requests, and tool use capability. Users can interact with Ollama in Elixir to generate completions, chat messages, and perform streaming requests. The tool also supports function calling on compatible models, allowing users to define tools with clear descriptions and arguments. Ollama is designed to facilitate natural language processing tasks and enhance user interactions with language models.

LLM Functions is a project that enables the enhancement of large language models (LLMs) with custom tools and agents developed in bash, javascript, and python. Users can create tools for their LLM to execute system commands, access web APIs, or perform other complex tasks triggered by natural language prompts. The project provides a framework for building tools and agents, with tools being functions written in the user's preferred language and automatically generating JSON declarations based on comments. Agents combine prompts, function callings, and knowledge (RAG) to create conversational AI agents. The project is designed to be user-friendly and allows users to easily extend the capabilities of their language models.

Home LLM is a project that provides the necessary components to control your Home Assistant installation with a completely local Large Language Model acting as a personal assistant. The goal is to provide a drop-in solution to be used as a "conversation agent" component by Home Assistant. The 2 main pieces of this solution are Home LLM and Llama Conversation. Home LLM is a fine-tuning of the Phi model series from Microsoft and the StableLM model series from StabilityAI. The model is able to control devices in the user's house as well as perform basic question and answering. The fine-tuning dataset is a custom synthetic dataset designed to teach the model function calling based on the device information in the context. Llama Conversation is a custom component that exposes the locally running LLM as a "conversation agent" in Home Assistant. This component can be interacted with in a few ways: using a chat interface, integrating with Speech-to-Text and Text-to-Speech addons, or running the oobabooga/text-generation-webui project to provide access to the LLM via an API interface.

Functionary is a language model that interprets and executes functions/plugins. It determines when to execute functions, whether in parallel or serially, and understands their outputs. Function definitions are given as JSON Schema Objects, similar to OpenAI GPT function calls. It offers documentation and examples on functionary.meetkai.com. The newest model, meetkai/functionary-medium-v3.1, is ranked 2nd in the Berkeley Function-Calling Leaderboard. Functionary supports models with different context lengths and capabilities for function calling and code interpretation. It also provides grammar sampling for accurate function and parameter names. Users can deploy Functionary models serverlessly using Modal.com.

Easily integrate Large Language Models into your Python code. Simply use the `@prompt` and `@chatprompt` decorators to create functions that return structured output from the LLM. Mix LLM queries and function calling with regular Python code to create complex logic.

Julep is an advanced platform for creating stateful and functional AI apps powered by large language models. It offers features like statefulness by design, automatic function calling, production-ready deployment, cron-like asynchronous functions, 90+ built-in tools, and the ability to switch between different LLMs easily. Users can build AI applications without the need to write code for embedding, saving, and retrieving conversation history, and can connect to third-party applications using Composio. Julep simplifies the process of getting started with AI apps, whether they are conversational, functional, or agentic.

The Google Gen AI SDK is a Python library that provides access to Google AI and Vertex AI services. It allows users to create clients for different services, work with parameter types, models, generate content, call functions, handle JSON response schemas, stream text and image content, perform async operations, count and compute tokens, embed content, generate and upscale images, edit images, work with files, create and get cached content, tune models, distill models, perform batch predictions, and more. The SDK supports various features like automatic function support, manual function declaration, JSON response schema support, streaming for text and image content, async methods, tuning job APIs, distillation, batch prediction, and more.

LLM-Zero-to-Hundred is a repository showcasing various applications of LLM chatbots and providing insights into training and fine-tuning Language Models. It includes projects like WebGPT, RAG-GPT, WebRAGQuery, LLM Full Finetuning, RAG-Master LLamaindex vs Langchain, open-source-RAG-GEMMA, and HUMAIN: Advanced Multimodal, Multitask Chatbot. The projects cover features like ChatGPT-like interaction, RAG capabilities, image generation and understanding, DuckDuckGo integration, summarization, text and voice interaction, and memory access. Tutorials include LLM Function Calling and Visualizing Text Vectorization. The projects have a general structure with folders for README, HELPER, .env, configs, data, src, images, and utils.

Nous is an open-source TypeScript platform for autonomous AI agents and LLM based workflows. It aims to automate processes, support requests, review code, assist with refactorings, and more. The platform supports various integrations, multiple LLMs/services, CLI and web interface, human-in-the-loop interactions, flexible deployment options, observability with OpenTelemetry tracing, and specific agents for code editing, software engineering, and code review. It offers advanced features like reasoning/planning, memory and function call history, hierarchical task decomposition, and control-loop function calling options. Nous is designed to be a flexible platform for the TypeScript community to expand and support different use cases and integrations.

LLM Datasets is a repository containing high-quality datasets, tools, and concepts for LLM fine-tuning. It provides datasets with characteristics like accuracy, diversity, and complexity to train large language models for various tasks. The repository includes datasets for general-purpose, math & logic, code, conversation & role-play, and agent & function calling domains. It also offers guidance on creating high-quality datasets through data deduplication, data quality assessment, data exploration, and data generation techniques.

The Keras-llm-robot Web UI project is an open-source tool designed for offline deployment and testing of various open-source models from the Hugging Face website. It allows users to combine multiple models through configuration to achieve functionalities like multimodal, RAG, Agent, and more. The project consists of three main interfaces: chat interface for language models, configuration interface for loading models, and tools & agent interface for auxiliary models. Users can interact with the language model through text, voice, and image inputs, and the tool supports features like model loading, quantization, fine-tuning, role-playing, code interpretation, speech recognition, image recognition, network search engine, and function calling.

The llama-cpp-agent framework is a tool designed for easy interaction with Large Language Models (LLMs). Allowing users to chat with LLM models, execute structured function calls and get structured output (objects). It provides a simple yet robust interface and supports llama-cpp-python and OpenAI endpoints with GBNF grammar support (like the llama-cpp-python server) and the llama.cpp backend server. It works by generating a formal GGML-BNF grammar of the user defined structures and functions, which is then used by llama.cpp to generate text valid to that grammar. In contrast to most GBNF grammar generators it also supports nested objects, dictionaries, enums and lists of them.

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