Best AI tools for< Fabricate Parts >

DraftAid is an AI-powered drawing automation tool that streamlines the fabrication drawing process, reducing the time from weeks to minutes. It integrates seamlessly with existing CAD software and offers extensive customization options to align with specific project requirements, delivering consistently accurate and high-quality drawings.

AIOC is an All-in-one-Cable for Ham Radio enthusiasts, providing a cheap and hackable digital mode USB interface with features like sound-card, virtual tty, and CM108 compatible HID endpoint. It supports various software and tested radios for functions like programming, APRS, and Dual-PTT HTs. Users can fabricate and assemble the AIOC using specific instructions, and program it using STM32CubeIDE. The tool can be used for tasks like programming radios, asserting PTT, and accessing audio data channels. Future work includes configurable AIOC settings, virtual-PTT, and virtual-COS features.

PaperQA is a minimal package for question and answering from PDFs or text files, providing very good answers with in-text citations. It uses OpenAI Embeddings to embed and search documents, and follows a process of embedding docs and queries, searching for top passages, creating summaries, scoring and selecting relevant summaries, putting summaries into prompt, and generating answers. Users can customize prompts and use various models for embeddings and LLMs. The tool can be used asynchronously and supports adding documents from paths, files, or URLs.

Chronon is a platform that simplifies and improves ML workflows by providing a central place to define features, ensuring point-in-time correctness for backfills, simplifying orchestration for batch and streaming pipelines, offering easy endpoints for feature fetching, and guaranteeing and measuring consistency. It offers benefits over other approaches by enabling the use of a broad set of data for training, handling large aggregations and other computationally intensive transformations, and abstracting away the infrastructure complexity of data plumbing.

A lightweight, functional, and composable framework for building AI agents that work together to solve complex tasks. Built with TypeScript and designed to be serverless-ready. Fabrice embraces functional programming principles, remains stateless, and stays focused on composability. It provides core concepts like easy teamwork creation, infrastructure-agnosticism, statelessness, and includes all tools and features needed to build AI teams. Agents are specialized workers with specific roles and capabilities, able to call tools and complete tasks. Workflows define how agents collaborate to achieve a goal, with workflow states representing the current state of the workflow. Providers handle requests to the LLM and responses. Tools extend agent capabilities by providing concrete actions they can perform. Execution involves running the workflow to completion, with options for custom execution and BDD testing.

The 'judges' repository is a small library designed for using and creating LLM-as-a-Judge evaluators. It offers a curated set of LLM evaluators in a low-friction format for various use cases, backed by research. Users can use these evaluators off-the-shelf or as inspiration for building custom LLM evaluators. The library provides two types of judges: Classifiers that return boolean values and Graders that return scores on a numerical or Likert scale. Users can combine multiple judges using the 'Jury' object and evaluate input-output pairs with the '.judge()' method. Additionally, the repository includes detailed instructions on picking a model, sending data to an LLM, using classifiers, combining judges, and creating custom LLM judges with 'AutoJudge'.

This repository contains a curated list of resources on generative information retrieval, including research papers, datasets, tools, and applications. Generative information retrieval is a subfield of information retrieval that uses generative models to generate new documents or passages of text that are relevant to a given query. This can be useful for a variety of tasks, such as question answering, summarization, and document generation. The resources in this repository are intended to help researchers and practitioners stay up-to-date on the latest advances in generative information retrieval.

The LLM Engineer Toolkit is a curated repository containing over 120 LLM libraries categorized for various tasks such as training, application development, inference, serving, data extraction, data generation, agents, evaluation, monitoring, prompts, structured outputs, safety, security, embedding models, and other miscellaneous tools. It includes libraries for fine-tuning LLMs, building applications powered by LLMs, serving LLM models, extracting data, generating synthetic data, creating AI agents, evaluating LLM applications, monitoring LLM performance, optimizing prompts, handling structured outputs, ensuring safety and security, embedding models, and more. The toolkit covers a wide range of tools and frameworks to streamline the development, deployment, and optimization of large language models.

The 'awesome-deliberative-prompting' repository focuses on how to ask Large Language Models (LLMs) to produce reliable reasoning and make reason-responsive decisions through deliberative prompting. It includes success stories, prompting patterns and strategies, multi-agent deliberation, reflection and meta-cognition, text generation techniques, self-correction methods, reasoning analytics, limitations, failures, puzzles, datasets, tools, and other resources related to deliberative prompting. The repository provides a comprehensive overview of research, techniques, and tools for enhancing reasoning capabilities of LLMs.

The Intelligence Toolkit is a suite of interactive workflows designed to help domain experts make sense of real-world data by identifying patterns, themes, relationships, and risks within complex datasets. It utilizes generative AI (GPT models) to create reports on findings of interest. The toolkit supports analysis of case, entity, and text data, providing various interactive workflows for different intelligence tasks. Users are expected to evaluate the quality of data insights and AI interpretations before taking action. The system is designed for moderate-sized datasets and responsible use of personal case data. It uses the GPT-4 model from OpenAI or Azure OpenAI APIs for generating reports and insights.

This repository is a collection of resources focused on interpretability in large language models (LLMs). It aims to help beginners get started in the area and keep researchers updated on the latest progress. It includes libraries, blogs, tutorials, forums, tools, programs, papers, and more related to interpretability in LLMs.

Flows AI is a lightweight, type-safe AI workflow orchestrator inspired by Anthropic's agent patterns and built on top of Vercel AI SDK. It provides a simple and deterministic way to build AI workflows by connecting different input/outputs together, either explicitly defining workflows or dynamically breaking down complex tasks using an orchestrator agent. The library is designed without classes or state, focusing on flexible input/output contracts for nodes.

Magick is a groundbreaking visual AIDE (Artificial Intelligence Development Environment) for no-code data pipelines and multimodal agents. Magick can connect to other services and comes with nodes and templates well-suited for intelligent agents, chatbots, complex reasoning systems and realistic characters.

Expert in metals, metalworking, and alloys, providing detailed and informative insights.

Natural stone expert GPT, powered by OpenAI, with advanced capabilities.

Expert on semiconductors, for technical insights.

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Specialist in silver's industrial applications and value.

Hello I'm Boat Patcher, Plastic Assistant! What would you like help with today?

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Build CRAZY WILD monster trucks using your imagination

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