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The website displays a 404 error message indicating that the deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::5gxj8-1724610730976-98928b92138b) for reference. Users are directed to check the documentation for further information and troubleshooting.

The website displays a '404: NOT_FOUND' error message indicating that the requested deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::jntwg-1724870915314-921108c25634) for reference. Users are directed to consult the documentation for further information and troubleshooting.

The website displays a '404: NOT_FOUND' error message indicating that the deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::22md2-1720772812453-4893618e160a) for reference. Users are directed to check the documentation for further information and troubleshooting.

The website displays a 404 error message indicating that the deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::qhrjt-1726765433586-bc18f7adaa0c) for reference. Users are directed to check the documentation for further information and troubleshooting.

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The website displays a '404: NOT_FOUND' error message indicating that the deployment cannot be found. It provides a code 'DEPLOYMENT_NOT_FOUND' and an ID 'sin1::jzd5h-1725561052162-b87af43bcd4a'. Users are directed to refer to the documentation for further information and troubleshooting.

Cloudflare is a platform that offers a range of products and services to help improve website performance, security, and reliability. It provides solutions such as web analytics, troubleshooting errors, domain registration, and content delivery network services. Cloudflare also offers developer products like Workers and AI products like RAG Workers, AI Vectorize, and AI Gateway. The platform aims to simplify website management and enhance user experience by leveraging cloud-based technologies.

Continue is an open-source AI code assistant that enhances developers' productivity by providing custom autocomplete and chat experiences within IDEs like VS Code and JetBrains. It allows developers to connect any models and contexts to optimize their coding workflow. With features like autocomplete, reference and chat, and code highlighting, Continue accelerates development and helps developers stay in flow while coding. It empowers users to evolve their code assistant with new capabilities and integrate it seamlessly with their existing stack.

MDN Web Docs is a comprehensive web technology reference for developers, offering detailed information on HTML, CSS, JavaScript, HTTP, Web APIs, and more. It provides guides, tutorials, and resources to help developers learn and enhance their skills in front-end development. Additionally, MDN Web Docs features a learning area, curriculum, blog, tools like Playground and HTTP Observatory, and real-time assistance through AI Help. The platform aims to make web technologies accessible and promote web sustainability.

The website displays a 404 error message indicating that the deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::54zqq-1725301437179-012f02729302). Users are directed to refer to the documentation for further information and troubleshooting.

The website displays a 404 error message indicating that the deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::7crbp-1720289011850-d12041b250e9) for reference. Users are directed to check the documentation for further information and troubleshooting.

The website page displays a 404 error message indicating that the deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::4wq5g-1718736845999-777f28b346ca) for reference. Users are advised to consult the documentation for further information and troubleshooting.

The website displays a 404 error message indicating that the deployment cannot be found. It provides a code and an ID for reference, along with a suggestion to check the documentation for more information and troubleshooting.

The website displays a 404 error message indicating that the deployment cannot be found. It provides a code and an ID for reference, along with a suggestion to check the documentation for more information and troubleshooting.

The website displays a 404 error message indicating that the deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::l44g5-1727283130745-f99c9f7f28f4) for reference. Users are directed to check the documentation for further information and troubleshooting.

The website displays a 404 error message indicating that the deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::n894q-1726678978147-1c9e4ad82a70) for reference. Users are directed to check the documentation for further information and troubleshooting.

The website displays a 404 error message indicating that the deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::vphzj-1726938947015-5b9ee22b5622) for reference. Users are directed to check the documentation for further information and troubleshooting.

The website displays a 404 error message indicating that the deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::lpcgw-1726939089118-f134fdcd683c) for reference. Users are directed to consult the documentation for further information and troubleshooting.

The website displays a 404 error message indicating that the deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::4r7dt-1725214813419-e08d08701f4a) for reference. Users are directed to check the documentation for further information and troubleshooting.

The website displays a 404 error message indicating that the deployment cannot be found. It provides a code (DEPLOYMENT_NOT_FOUND) and an ID (sin1::7rd4m-1725901316906-8c71a7a2cbd7) for reference. Users are directed to check the documentation for further information and troubleshooting.

Amadeus Java SDK provides a rich set of APIs for the travel industry, allowing developers to access various functionalities such as flight search, booking, airport information, and more. The SDK simplifies interaction with the Amadeus API by providing self-contained code examples and detailed documentation. Developers can easily make API calls, handle responses, and utilize features like pagination and logging. The SDK supports various endpoints for tasks like flight search, booking management, airport information retrieval, and travel analytics. It also offers functionalities for hotel search, booking, and sentiment analysis. Overall, the Amadeus Java SDK is a comprehensive tool for integrating Amadeus APIs into Java applications.

Amadeus Node SDK provides a rich set of APIs for the travel industry. It allows developers to interact with various endpoints related to flights, hotels, activities, and more. The SDK simplifies making API calls, handling promises, pagination, logging, and debugging. It supports a wide range of functionalities such as flight search, booking, seat maps, flight status, points of interest, hotel search, sentiment analysis, trip predictions, and more. Developers can easily integrate the SDK into their Node.js applications to access Amadeus APIs and build travel-related applications.

COMFYUI LLM PARTY is a node library designed for LLM workflow development in ComfyUI, an extremely minimalist UI interface primarily used for AI drawing and SD model-based workflows. The project aims to provide a complete set of nodes for constructing LLM workflows, enabling users to easily integrate them into existing SD workflows. It features various functionalities such as API integration, local large model integration, RAG support, code interpreters, online queries, conditional statements, looping links for large models, persona mask attachment, and tool invocations for weather lookup, time lookup, knowledge base, code execution, web search, and single-page search. Users can rapidly develop web applications using API + Streamlit and utilize LLM as a tool node. Additionally, the project includes an omnipotent interpreter node that allows the large model to perform any task, with recommendations to use the 'show_text' node for display output.

LangChain.dart is a Dart port of the popular LangChain Python framework created by Harrison Chase. LangChain provides a set of ready-to-use components for working with language models and a standard interface for chaining them together to formulate more advanced use cases (e.g. chatbots, Q&A with RAG, agents, summarization, extraction, etc.). The components can be grouped into a few core modules: * **Model I/O:** LangChain offers a unified API for interacting with various LLM providers (e.g. OpenAI, Google, Mistral, Ollama, etc.), allowing developers to switch between them with ease. Additionally, it provides tools for managing model inputs (prompt templates and example selectors) and parsing the resulting model outputs (output parsers). * **Retrieval:** assists in loading user data (via document loaders), transforming it (with text splitters), extracting its meaning (using embedding models), storing (in vector stores) and retrieving it (through retrievers) so that it can be used to ground the model's responses (i.e. Retrieval-Augmented Generation or RAG). * **Agents:** "bots" that leverage LLMs to make informed decisions about which available tools (such as web search, calculators, database lookup, etc.) to use to accomplish the designated task. The different components can be composed together using the LangChain Expression Language (LCEL).

Skyvern automates browser-based workflows using LLMs and computer vision. It provides a simple API endpoint to fully automate manual workflows, replacing brittle or unreliable automation solutions. Traditional approaches to browser automations required writing custom scripts for websites, often relying on DOM parsing and XPath-based interactions which would break whenever the website layouts changed. Instead of only relying on code-defined XPath interactions, Skyvern adds computer vision and LLMs to the mix to parse items in the viewport in real-time, create a plan for interaction and interact with them. This approach gives us a few advantages: 1. Skyvern can operate on websites it’s never seen before, as it’s able to map visual elements to actions necessary to complete a workflow, without any customized code 2. Skyvern is resistant to website layout changes, as there are no pre-determined XPaths or other selectors our system is looking for while trying to navigate 3. Skyvern leverages LLMs to reason through interactions to ensure we can cover complex situations. Examples include: 1. If you wanted to get an auto insurance quote from Geico, the answer to a common question “Were you eligible to drive at 18?” could be inferred from the driver receiving their license at age 16 2. If you were doing competitor analysis, it’s understanding that an Arnold Palmer 22 oz can at 7/11 is almost definitely the same product as a 23 oz can at Gopuff (even though the sizes are slightly different, which could be a rounding error!) Want to see examples of Skyvern in action? Jump to #real-world-examples-of- skyvern

Kernel Memory (KM) is a multi-modal AI Service specialized in the efficient indexing of datasets through custom continuous data hybrid pipelines, with support for Retrieval Augmented Generation (RAG), synthetic memory, prompt engineering, and custom semantic memory processing. KM is available as a Web Service, as a Docker container, a Plugin for ChatGPT/Copilot/Semantic Kernel, and as a .NET library for embedded applications. Utilizing advanced embeddings and LLMs, the system enables Natural Language querying for obtaining answers from the indexed data, complete with citations and links to the original sources. Designed for seamless integration as a Plugin with Semantic Kernel, Microsoft Copilot and ChatGPT, Kernel Memory enhances data-driven features in applications built for most popular AI platforms.

spaCy is an industrial-strength Natural Language Processing (NLP) library in Python and Cython. It incorporates the latest research and is designed for real-world applications. The library offers pretrained pipelines supporting 70+ languages, with advanced neural network models for tasks such as tagging, parsing, named entity recognition, and text classification. It also facilitates multi-task learning with pretrained transformers like BERT, along with a production-ready training system and streamlined model packaging, deployment, and workflow management. spaCy is commercial open-source software released under the MIT license.

The collection of pre-trained, state-of-the-art AI models. ailia SDK is a self-contained, cross-platform, high-speed inference SDK for AI. The ailia SDK provides a consistent C++ API across Windows, Mac, Linux, iOS, Android, Jetson, and Raspberry Pi platforms. It also supports Unity (C#), Python, Rust, Flutter(Dart) and JNI for efficient AI implementation. The ailia SDK makes extensive use of the GPU through Vulkan and Metal to enable accelerated computing. # Supported models 323 models as of April 8th, 2024

ChatGPT is a large language model that can generate human-like text, translate languages, write different kinds of creative content, and answer your questions in a conversational way. It is trained on a massive amount of text data, and it is able to understand and respond to a wide range of natural language prompts. Here are 5 jobs suitable for this tool, in lowercase letters: 1. content writer 2. chatbot assistant 3. language translator 4. creative writer 5. researcher

The AI-Gateway repository explores the AI Gateway pattern through a series of experimental labs, focusing on Azure API Management for handling AI services APIs. The labs provide step-by-step instructions using Jupyter notebooks with Python scripts, Bicep files, and APIM policies. The goal is to accelerate experimentation of advanced use cases and pave the way for further innovation in the rapidly evolving field of AI. The repository also includes a Mock Server to mimic the behavior of the OpenAI API for testing and development purposes.

Liger Kernel is a collection of Triton kernels designed for LLM training, increasing training throughput by 20% and reducing memory usage by 60%. It includes Hugging Face Compatible modules like RMSNorm, RoPE, SwiGLU, CrossEntropy, and FusedLinearCrossEntropy. The tool works with Flash Attention, PyTorch FSDP, and Microsoft DeepSpeed, aiming to enhance model efficiency and performance for researchers, ML practitioners, and curious novices.

This repository provides a systematic and comprehensive review of efficient LLMs research. We organize the literature in a taxonomy consisting of three main categories, covering distinct yet interconnected efficient LLMs topics from **model-centric** , **data-centric** , and **framework-centric** perspective, respectively. We hope our survey and this GitHub repository can serve as valuable resources to help researchers and practitioners gain a systematic understanding of the research developments in efficient LLMs and inspire them to contribute to this important and exciting field.

Simulator Controller is a modular administration and controller application for Sim Racing, featuring a comprehensive plugin automation framework for external controller hardware. It includes voice chat capable Assistants like Virtual Race Engineer, Race Strategist, Race Spotter, and Driving Coach. The tool offers features for setup, strategy development, monitoring races, and more. Developed in AutoHotkey, it supports various simulation games and integrates with third-party applications for enhanced functionality.

DOM to Semantic Markdown is a tool that converts HTML DOM to Semantic Markdown for use in Large Language Models (LLMs). It maximizes semantic information, token efficiency, and preserves metadata to enhance LLMs' processing capabilities. The tool captures rich web content structure, including semantic tags, image metadata, table structures, and link destinations. It offers customizable conversion options and supports both browser and Node.js environments.

Langroid is a Python framework that makes it easy to build LLM-powered applications. It uses a multi-agent paradigm inspired by the Actor Framework, where you set up Agents, equip them with optional components (LLM, vector-store and tools/functions), assign them tasks, and have them collaboratively solve a problem by exchanging messages. Langroid is a fresh take on LLM app-development, where considerable thought has gone into simplifying the developer experience; it does not use Langchain.

The Aleph Alpha Intelligence Layer️ offers a comprehensive suite of development tools for crafting solutions that harness the capabilities of large language models (LLMs). With a unified framework for LLM-based workflows, it facilitates seamless AI product development, from prototyping and prompt experimentation to result evaluation and deployment. The Intelligence Layer SDK provides features such as Composability, Evaluability, and Traceability, along with examples to get started. It supports local installation using poetry, integration with Docker, and access to LLM endpoints for tutorials and tasks like Summarization, Question Answering, Classification, Evaluation, and Parameter Optimization. The tool also offers pre-configured tasks for tasks like Classify, QA, Search, and Summarize, serving as a foundation for custom development.

I help developers understand and use APIs, referencing a YAML model.

Ruby doc searcher for Ruby reference and Rurema

A GPT pre-trained on duneSQL Farcaster tables, complex examples, and duneSQL syntax. Please reference the dune docs or contact @shoni.eth for errors

質問するとMQL4リファレンスに基づいて解答してくれます。

Expert in providing accurate, up-to-date, and validated responses, cross-references information with reliable web sources and informs users about the confidence level of its responses.

Your documentation guide for OpenAI, loaded with the latest guides and API references.

参考文献格式化和注释体例专家

Formats academic references to specific styles.

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A reference tool for UK energy transmission campaigners.

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Expert in article-based reference generation and formatting.

Expert in citation styles and reference generation.

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