Best AI tools for< Chain Functions >

Inventory365 is a leading AI-powered platform for inventory management and growth, empowering modern product sellers to excel by seamlessly linking all sales channels and automating end-to-end order processing. The platform leverages machine learning, connected processes, and heightened visibility across sales, operations, forecasting, supply, replenishment, and inventory functions to adapt to shifting demand. Inventory365 offers features such as multichannel integration, order management, real-time inventory visibility, warehouse management, reporting and analytics, multi-price/multi-currency options, price comparison, demand prediction, and an AI assistant with real-time chat.

Nanonets is an intelligent automation AI platform for business processes that offers data capture and workflows for various documents like invoices, bills of lading, purchase orders, passports, ID cards, bank statements, and receipts. It provides solutions for finance & accounting, supply chain & operations, human resources, customer support, and legal functions across industries such as banking & finance, insurance, healthcare, logistics, and commercial real estate. Nanonets helps automate complex business processes with AI-powered workflows, enabling users to extract valuable information from unstructured data and make faster, more informed decisions. The platform offers measurable ROI in weeks, reduces manual effort, and accelerates setup time compared to industry standards.

Broearn Browser is a Web 3.0 browser that provides users with a secure and private browsing experience. It is based on GPT 4.0 and includes features such as a personal AI assistant, customizable widgets, and a built-in VPN. Broearn Browser also supports multiple chains and decentralized applications (DApps).

BlockBot is an AI bot ecosystem that allows users to create, trade, and monetize AI chatbots on-chain. It empowers users with access to a variety of AI bots and functionalities tailored to different needs and use cases. The platform leverages blockchain technology to provide a secure, fast, and cost-effective way to experience the power of AI technology.

ContractReader is an audit tool designed to simplify the process of reading and understanding smart contracts. It offers features such as syntax highlighting, testnet support, live onchain values, code comparison in-browser, GPT-4 security reviews, and more. Users can enter a contract address or Etherscan URL to access these functionalities. The tool supports various networks like Mainnet, Goerli, Sepolia, Optimism, Polygon, Arbitrum, and BNB Smart Chain. ContractReader aims to make crypto contracts more accessible and comprehensible for users, providing a user-friendly interface for contract analysis.

Vilosia is an AI-powered platform that helps medium and large enterprises with internal development teams to visualize their software architecture, simplify migration, and improve system modularity. The platform uses Gen AI to automatically add event triggers to the codebase, enabling users to understand data flow, system dependencies, domain boundaries, and external APIs. Vilosia also offers AI workflow analysis to extract workflows from function call chains and identify database usage. Users can scan their codebase using CLI client & CI/CD integration and stay updated with new features through the newsletter.

CHAI AI Platform is an AI tool designed for quant traders to build and implement AI algorithms for trading. The platform combines chat functionality with AI capabilities to enhance the trading experience. Based in Palo Alto, CA, CHAI Research Corp. developed the platform to empower traders with advanced AI technology for better decision-making and performance in the financial markets.

SOMA is a Research Automation Platform that accelerates medical innovation by providing up to 100x speedup through process automation. The platform analyzes medical research articles, extracts important concepts, and identifies causal and associative relationships between them. It organizes this information into a specialized database forming a knowledge graph. Researchers can retrieve causal chains, access specific research articles, and perform tasks like concept analysis, drug repurposing, and target discovery. SOMA enhances literature review efficiency by finding relevant articles based on causal chains and keywords specified by the user. It empowers researchers to focus on their research by saving up to 95% of the time spent on pre-processing documents. The platform offers freemium access with extended functionality for 14 days and advanced features available through subscription.

The Value Chain Generator® is an AI & Big Data platform for circular bioeconomy that helps companies, waste processors, and regions maximize the value and minimize the carbon footprint of by-products and waste. It uses global techno-economic and climate intelligence to identify circular opportunities, match with suitable partners and technologies, and create profitable and impactful solutions. The platform accelerates the circular transition by integrating local industries through technology, reducing waste, and increasing profits.

Supply Chain Intelligence is an AI application that offers a comprehensive suite of tools for supply chain management. It provides advanced demand forecasting capabilities, digitization guidance, AI forecast model creation, forecasting segmentation, and assessment of demand forecasting process maturity. The application aims to streamline supply chain operations, enhance decision-making, and optimize planning processes through the use of artificial intelligence technologies.

ToolsGroup is an AI-powered supply chain and retail planning application that helps retailers, distributors, and manufacturers enhance the resilience and performance of their operations. Leveraging AI and real-time data, ToolsGroup offers probabilistic planning solutions for demand forecasting, inventory optimization, replenishment, assortment planning, and more. The application automates manual tasks, guides smarter decisions with AI, and delivers outstanding customer experiences with real-time visibility across the enterprise.

Web3 Summary is an AI-powered platform that simplifies on-chain research across multiple chains and protocols, helping users find trading alpha in the DeFi and NFT space. It offers a range of products including a trading terminal, wallet study tool, Discord bot, mobile app, and Chrome extension. The platform aims to streamline the process of understanding complex crypto projects and tokenomics using AI and ChatGPT technology.

RELEX Solutions is a market-leading supply chain and retail planning platform that leverages artificial intelligence to revolutionize supply chains. The platform offers end-to-end inventory planning, production scheduling, demand forecasting, merchandising, assortment planning, price optimization, promotion planning, and more. RELEX enables retailers and consumer goods companies to align their supply chain and retail operations with actual demand, driving profitability through increased sales and reduced costs while minimizing waste. The platform caters to various industries such as retail, convenience, electronics, grocery, health, beauty, pharmaceutical, and more, providing tailored solutions for each sector.

Endor Labs is an AI-powered software supply chain security solution that helps organizations manage their software bills of materials (SBOM), secure their open source dependencies, optimize CI/CD pipeline security, and enhance application security with secret detection. The platform offers advanced features such as AI-assisted OSS selection, compliance management, reachability-based SCA, and repository security posture management. Endor Labs aims to streamline security processes, reduce false positives, and provide actionable insights to improve software supply chain security.

Laika AI is the world's first Web3-modeled AI ecosystem, designed and optimized for Web3 and blockchain. It offers advanced on-chain AI tools, integrating artificial intelligence and blockchain data to provide users with insights into the crypto landscape. Laika AI stands out with its user-friendly browser extension that empowers users with advanced on-chain analytics without the need for complex setups. The platform continuously learns and improves, leveraging a unique foundation and proprietary algorithms dedicated to Web3. Laika AI offers features such as DeFi research, token contract analysis, wallet insights, AI alerts, and multichain swap capabilities. It is supported by strategic partnerships with leading companies in the Web3 and Web2 space, ensuring security, high performance, and accessibility for users.

Vitrina Business Network is a global platform that connects entertainment companies worldwide, facilitating interactions between content acquirers, distributors, production, post-production, and localization services. The platform leverages data, AI, and human expertise to enhance business growth within the entertainment supply chain. Vitrina offers services such as content licensing, specialist services hiring, and networking opportunities for industry professionals. Through digital storefronts, users can showcase projects and services, fostering partnerships and business opportunities. The platform also provides market intelligence reports, case studies, and industry insights to help users make informed decisions and stay updated on the latest trends in the entertainment industry.

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AiHouse is an AI-powered integrated 3D design tool that provides an all-in-one solution for interior design and manufacturing. It offers a range of features including 2D/3D floor plan creation, room decoration, furniture customization, photo-realistic visualization, 3D walkthrough videos, product visualization, and end-to-end design-to-manufacture solutions. AiHouse is designed to streamline the design process, improve communication with clients, and increase efficiency for interior designers, furniture brands, and manufacturers.

Kinaxis is an AI-powered platform that offers end-to-end supply chain orchestration solutions for businesses. It helps companies respond with agility by coordinating all parts of the supply chain using artificial intelligence. With features like transparency, collaboration, adaptability, and intelligence, Kinaxis enables users to make faster, smarter, and more confident decisions. The platform offers solutions for supply chain control tower, S&OP, demand planning, inventory management, scheduling, order management, transportation, and returns management. Kinaxis is designed to streamline operations, improve efficiency, and drive sustainable supply chain practices.

ThroughPut AI is a supply chain decision intelligence and analytics platform designed for outcome-driven supply chain decision-makers. It provides accurate demand forecasting, capacity planning, logistics management, and financial insights to drive business results. ThroughPut AI offers a single source of truth for supply chain professionals, enabling them to make faster, better, and confident decisions. The platform helps unlock efficiency, profitability, and growth in day-to-day operations by providing intelligent data-driven recommendations.

Semantic Kernel for Java is an SDK that integrates Large Language Models (LLMs) like OpenAI, Azure OpenAI, and Hugging Face with conventional programming languages like C#, Python, and Java. It allows defining plugins that can be chained together in just a few lines of code. The tool automatically orchestrates plugins with AI, enabling users to generate plans to achieve unique goals and execute them. The project welcomes contributions, bug reports, and suggestions from the community.

gollm is a Go package designed to simplify interactions with Large Language Models (LLMs) for AI engineers and developers. It offers a unified API for multiple LLM providers, easy provider and model switching, flexible configuration options, advanced prompt engineering, prompt optimization, memory retention, structured output and validation, provider comparison tools, high-level AI functions, robust error handling and retries, and extensible architecture. The package enables users to create AI-powered golems for tasks like content creation workflows, complex reasoning tasks, structured data generation, model performance analysis, prompt optimization, and creating a mixture of agents.

Kork is an experimental Langchain chain that helps build natural language APIs powered by LLMs. It allows assembling a natural language API from python functions, generating a prompt for correct program writing, executing programs safely, and controlling the kind of programs LLMs can generate. The language is limited to variable declarations, function invocations, and arithmetic operations, ensuring predictability and safety in production settings.

The 'local-talking-llm' repository provides a tutorial on building a voice assistant similar to Jarvis or Friday from Iron Man movies, capable of offline operation on a computer. The tutorial covers setting up a Python environment, installing necessary libraries like rich, openai-whisper, suno-bark, langchain, sounddevice, pyaudio, and speechrecognition. It utilizes Ollama for Large Language Model (LLM) serving and includes components for speech recognition, conversational chain, and speech synthesis. The implementation involves creating a TextToSpeechService class for Bark, defining functions for audio recording, transcription, LLM response generation, and audio playback. The main application loop guides users through interactive voice-based conversations with the assistant.

aiNodes Engine is a Python-based AI image/motion picture generator node engine with a live execution chain, python code editor node, and plug-in support. It offers full modularity, colored background drop, and easy node creation with IDE annotations. The project is officially supported by Deforum and incorporates various open-source projects like ComfyUI. It is designed to be flexible, with an Unreal-like execution chain, supporting features such as Deforum, Stable Diffusion, Upscalers, Kandinsky, ControlNet, and more. The engine allows for background separation, human matting/masking, compositing, drag and drop, subgraphs, and graph saving/loading from image metadata. It aims to provide a unique, controllable manner of working with a strict user-declared execution chain.

Funcchain is a Python library that allows you to easily write cognitive systems by leveraging Pydantic models as output schemas and LangChain in the backend. It provides a seamless integration of LLMs into your apps, utilizing OpenAI Functions or LlamaCpp grammars (json-schema-mode) for efficient structured output. Funcchain compiles the Funcchain syntax into LangChain runnables, enabling you to invoke, stream, or batch process your pipelines effortlessly.

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.

tinyllm is a lightweight framework designed for developing, debugging, and monitoring LLM and Agent powered applications at scale. It aims to simplify code while enabling users to create complex agents or LLM workflows in production. The core classes, Function and FunctionStream, standardize and control LLM, ToolStore, and relevant calls for scalable production use. It offers structured handling of function execution, including input/output validation, error handling, evaluation, and more, all while maintaining code readability. Users can create chains with prompts, LLM models, and evaluators in a single file without the need for extensive class definitions or spaghetti code. Additionally, tinyllm integrates with various libraries like Langfuse and provides tools for prompt engineering, observability, logging, and finite state machine design.

The CryptoToken-Sender-Airdrop-Staking-Liquidity repository provides an ultimate tool for efficient and automated token distribution across blockchain wallets. It is designed for projects, DAOs, and blockchain-based organizations that need to distribute tokens to thousands of wallet addresses with ease. The platform offers advanced integrations with DeFi protocols for staking, liquidity farming, and automated payments. Users can send tokens in bulk, distribute tokens to multiple wallets instantly, optimize gas fees, integrate with DeFi protocols for liquidity provision and staking, set up recurring payments, automate liquidity farming strategies, support multi-chain operations, monitor transactions in real-time, and work with various token standards. The repository includes features for connecting to blockchains, importing and managing wallets, customizing mailing parameters, monitoring transaction status, logging transactions, and providing a user-friendly interface for configuration and operation.

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.

LLMClient is a JavaScript/TypeScript library that simplifies working with large language models (LLMs) by providing an easy-to-use interface for building and composing efficient prompts using prompt signatures. These signatures enable the automatic generation of typed prompts, allowing developers to leverage advanced capabilities like reasoning, function calling, RAG, ReAcT, and Chain of Thought. The library supports various LLMs and vector databases, making it a versatile tool for a wide range of applications.

Dexter is a set of mature LLM tools used in production at Dexa, with a focus on real-world RAG (Retrieval Augmented Generation). It is a production-quality RAG that is extremely fast and minimal, and handles caching, throttling, and batching for ingesting large datasets. It also supports optional hybrid search with SPLADE embeddings, and is a minimal TS package with full typing that uses `fetch` everywhere and supports Node.js 18+, Deno, Cloudflare Workers, Vercel edge functions, etc. Dexter has full docs and includes examples for basic usage, caching, Redis caching, AI function, AI runner, and chatbot.

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.

Mentals AI is a tool designed for creating and operating agents that feature loops, memory, and various tools, all through straightforward markdown syntax. This tool enables you to concentrate solely on the agent’s logic, eliminating the necessity to compose underlying code in Python or any other language. It redefines the foundational frameworks for future AI applications by allowing the creation of agents with recursive decision-making processes, integration of reasoning frameworks, and control flow expressed in natural language. Key concepts include instructions with prompts and references, working memory for context, short-term memory for storing intermediate results, and control flow from strings to algorithms. The tool provides a set of native tools for message output, user input, file handling, Python interpreter, Bash commands, and short-term memory. The roadmap includes features like a web UI, vector database tools, agent's experience, and tools for image generation and browsing. The idea behind Mentals AI originated from studies on psychoanalysis executive functions and aims to integrate 'System 1' (cognitive executor) with 'System 2' (central executive) to create more sophisticated agents.

CodeGeeX4-ALL-9B is an open-source multilingual code generation model based on GLM-4-9B, offering enhanced code generation capabilities. It supports functions like code completion, code interpreter, web search, function call, and repository-level code Q&A. The model has competitive performance on benchmarks like BigCodeBench and NaturalCodeBench, outperforming larger models in terms of speed and performance.

Project Miyagi showcases Microsoft's Copilot Stack in an envisioning workshop aimed at designing, developing, and deploying enterprise-grade intelligent apps. By exploring both generative and traditional ML use cases, Miyagi offers an experiential approach to developing AI-infused product experiences that enhance productivity and enable hyper-personalization. Additionally, the workshop introduces traditional software engineers to emerging design patterns in prompt engineering, such as chain-of-thought and retrieval-augmentation, as well as to techniques like vectorization for long-term memory, fine-tuning of OSS models, agent-like orchestration, and plugins or tools for augmenting and grounding LLMs.

Reinforcement Learning from AI Feedback (RLAIF) is a concept that describes a type of machine learning approach where **an AI agent learns by receiving feedback or guidance from another AI system**. This concept is closely related to the field of Reinforcement Learning (RL), which is a type of machine learning where an agent learns to make a sequence of decisions in an environment to maximize a cumulative reward. In traditional RL, an agent interacts with an environment and receives feedback in the form of rewards or penalties based on the actions it takes. It learns to improve its decision-making over time to achieve its goals. In the context of Reinforcement Learning from AI Feedback, the AI agent still aims to learn optimal behavior through interactions, but **the feedback comes from another AI system rather than from the environment or human evaluators**. This can be **particularly useful in situations where it may be challenging to define clear reward functions or when it is more efficient to use another AI system to provide guidance**. The feedback from the AI system can take various forms, such as: - **Demonstrations** : The AI system provides demonstrations of desired behavior, and the learning agent tries to imitate these demonstrations. - **Comparison Data** : The AI system ranks or compares different actions taken by the learning agent, helping it to understand which actions are better or worse. - **Reward Shaping** : The AI system provides additional reward signals to guide the learning agent's behavior, supplementing the rewards from the environment. This approach is often used in scenarios where the RL agent needs to learn from **limited human or expert feedback or when the reward signal from the environment is sparse or unclear**. It can also be used to **accelerate the learning process and make RL more sample-efficient**. Reinforcement Learning from AI Feedback is an area of ongoing research and has applications in various domains, including robotics, autonomous vehicles, and game playing, among others.

Qlib is an open-source, AI-oriented quantitative investment platform that supports diverse machine learning modeling paradigms, including supervised learning, market dynamics modeling, and reinforcement learning. It covers the entire chain of quantitative investment, from alpha seeking to order execution. The platform empowers researchers to explore ideas and implement productions using AI technologies in quantitative investment. Qlib collaboratively solves key challenges in quantitative investment by releasing state-of-the-art research works in various paradigms. It provides a full ML pipeline for data processing, model training, and back-testing, enabling users to perform tasks such as forecasting market patterns, adapting to market dynamics, and modeling continuous investment decisions.

This repository contains a sophisticated deterministic graph-based solution for answering complex questions using a controllable autonomous agent. The solution is designed to ensure that answers are solely based on the provided data, avoiding hallucinations. It involves various steps such as PDF loading, text preprocessing, summarization, database creation, encoding, and utilizing large language models. The algorithm follows a detailed workflow involving planning, retrieval, answering, replanning, content distillation, and performance evaluation. Heuristics and techniques implemented focus on content encoding, anonymizing questions, task breakdown, content distillation, chain of thought answering, verification, and model performance evaluation.

LangChain Decorators is a layer on top of LangChain that provides syntactic sugar for writing custom langchain prompts and chains. It offers a more pythonic way of writing code, multiline prompts without breaking code flow, IDE support for hinting and type checking, leveraging LangChain ecosystem, support for optional parameters, and sharing parameters between prompts. It simplifies streaming, automatic LLM selection, defining custom settings, debugging, and passing memory, callback, stop, etc. It also provides functions provider, dynamic function schemas, binding prompts to objects, defining custom settings, and debugging options. The project aims to enhance the LangChain library by making it easier to use and more efficient for writing custom prompts and chains.

Vous aide à choisir votre futur chaise gaming en fonction de vos préférences, de votre morphologie ou de votre budget.

Helper for Wardley Map value chain analysis

I'm a GPT that plays Word Chain, responding with words starting with your word's last letter.

your real time expert while you negotiate

I calculate and recommend tire chain sizes based on your tire specs.

This prompt is structured to provide an effective methodology in generating progressively more detailed and specific summaries, focused on key entities.

Innovative, expert supply chain insights on demand. Bring all your operational challenges to us while you focus on growing your business.

Guides you through detailed reasoning to find well-supported answers.

An AI assistant for CCA, a supply chain technology company that focuses on providing digital drayage platform and TMS solution to our importer customers and carrier partners

Chat-driven supply chain wisdom powered by live data and trained on news, tutorials and resources.

Guide for clear, ethical supply chain solutions

On-chain analysis educator for financial pros.

Import Export Compliance | Tariff Classification | Shipping Queries | Logistics & Supply Chain Solutions

Solve math and logic with Smart GPT. Use Tree and Chain of thoughts to organize and find answers.

しりとりするだけで博識に

Expert in UNSPSC Codes (United Nations Standard Products and Services Code®).

Facilitates efficient collaboration between suppliers and the organization.

Pharma procurement expert with RFI/RFP/RFQ knowledge

A knowledgeable and patient teacher in logistics, offering insights and guidance.

Assistant GPT expert en management des achats et approvisionnements