Best AI tools for< Python Scripter >

Formulas HQ is an AI-powered formula and script generator for Excel and Sheets. It provides users with a range of tools to simplify complex calculations, automate tasks, and enhance their spreadsheet mastery. With Formulas HQ, users can generate formulas, regular expressions, VBA code, and Apps Script, even without prior programming experience. The platform also offers a chat feature with system prompts to assist users with idea generation and troubleshooting. Formulas HQ is designed to empower users to work smarter and make better business decisions.

Formulas HQ is an AI-powered formula and script generator for Excel and Sheets. It provides users with a variety of tools to simplify complex calculations, automate tasks, and gain insights from data. The platform includes features such as formula generation, regular expression simplification, VBA and Apps Script automation, and chat-based assistance. Formulas HQ is designed to help users improve their productivity and efficiency when working with spreadsheets.

Amazon SageMaker Python SDK is an open source library for training and deploying machine-learned models on Amazon SageMaker. With the SDK, you can train and deploy models using popular deep learning frameworks, algorithms provided by Amazon, or your own algorithms built into SageMaker-compatible Docker images.

LangChain is a framework for developing applications powered by large language models (LLMs). It simplifies every stage of the LLM application lifecycle, including development, productionization, and deployment. LangChain consists of open-source libraries such as langchain-core, langchain-community, and partner packages. It also includes LangGraph for building stateful agents and LangSmith for debugging and monitoring LLM applications.

Scikit-learn is a free software machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.

Google Colab is a free Jupyter notebook environment that runs in the cloud. It allows you to write and execute Python code without having to install any software or set up a local environment. Colab notebooks are shareable, so you can easily collaborate with others on projects.

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.

Mito is a low-code data app infrastructure that allows users to edit spreadsheets and automatically generate Python code. It is designed to help analysts automate their repetitive Excel work and take automation into their own hands. Mito is a Jupyter extension and Streamlit component, so users don't need to set up any new infrastructure. It is easy to get started with Mito, simply install it using pip and start using it in Jupyter or Streamlit.

NLTK (Natural Language Toolkit) is a leading platform for building Python programs to work with human language data. It provides easy-to-use interfaces to over 50 corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning, wrappers for industrial-strength NLP libraries, and an active discussion forum. Thanks to a hands-on guide introducing programming fundamentals alongside topics in computational linguistics, plus comprehensive API documentation, NLTK is suitable for linguists, engineers, students, educators, researchers, and industry users alike.

Quadratic is an infinite spreadsheet with Python, SQL, and AI. It combines the familiarity of a spreadsheet with the power of code, allowing users to analyze data, write code, and create visualizations in a single environment. With built-in Python library support, users can bring open source tools directly to their spreadsheets. Quadratic also features real-time collaboration, allowing multiple users to work on the same spreadsheet simultaneously. Additionally, Quadratic is built for speed and performance, utilizing Web Assembly and WebGL to deliver a smooth and responsive experience.

TimeComplexity.ai is an AI tool that allows users to analyze the runtime complexity of their code. It works seamlessly across different programming languages without the need for headers, imports, or a main statement. Users can input their code and get insights into its performance. However, it is important to note that the results may not always be accurate, so caution is advised when using the tool.

Snorkell.ai is an automated documentation generation tool that uses AI to create and update docstrings for GitHub projects. It supports multiple programming languages, including Python, JavaScript, TypeScript, Java, and Kotlin. Snorkell.ai integrates with GitHub and automatically generates docstrings whenever a pull request is merged, ensuring that documentation is always up-to-date with the codebase. It helps developers save time and effort by automating the documentation process, leading to improved code quality and reduced onboarding time.

Hal9 is an AI coworker creation platform that allows organizations, data teams, and developers to effortlessly build custom AI coworkers with any level of complexity. It provides a secure and customizable model-agnostic AI coworker solution that accelerates the development of AI applications by saving significant engineering time. Hal9 enables users to leverage the best generative AI models, connect their data securely, and start building enterprise-ready AI applications with the necessary engineering components. The platform aims to empower users to leverage AI technology effectively and efficiently in their projects.

Hex is a collaborative data workspace that provides a variety of tools for working with data, including queries, notebooks, reports, data apps, and AI. It is designed to be easy to use for people of all technical skill levels, and it integrates with a variety of other tools and services. Hex is a powerful tool for data exploration, analysis, and visualization.

Vanna.AI is a personalized AI SQL agent that allows users to get actionable insights from their database by simply asking questions. It helps users to write SQL queries efficiently and generate insights without the need for expert SQL knowledge. The application is open-source, highly accurate on complex datasets, designed for security, self-learning, and supports various databases. Vanna.AI is fully customizable to match unique needs and offers enterprise customization options.

Shimoku is an AI application that offers a catalog of AI modules for acquisition, conversion, loyalty, and retention, covering the entire customer lifecycle for marketers and sales teams. It provides AI-driven solutions for ads acquisition, call center operations, lead conversion, client loyalty, and retention. Shimoku uses a multi-layer AI approach combining Machine Learning, Explainability AI, and Generative AI to predict opportunities, explain key factors, and personalize proposals. The application caters to various industries such as auto, ecommerce, insurance, retail, SaaS, and more, helping businesses improve performance and growth.

The AI Maze Generator is an online tool that allows users to create, solve, and download random maze puzzles in various sizes and colors. It utilizes the recursive backtracking algorithm to design mazes and the A* search algorithm to find the shortest path. Users can customize maze specifications like wall thickness, columns, rows, maze entries, and bias. The tool offers a user-friendly interface for maze creation and solving, providing a fun and engaging experience for maze enthusiasts.

Replit is a software creation platform that provides an integrated development environment (IDE), artificial intelligence (AI) assistance, and deployment services. It allows users to build, test, and deploy software projects directly from their browser, without the need for local setup or configuration. Replit offers real-time collaboration, code generation, debugging, and autocompletion features powered by AI. It supports multiple programming languages and frameworks, making it suitable for a wide range of development projects.

Chat Blackbox is an AI tool that specializes in AI code generation, code chat, and code search. It provides a platform where users can interact with AI to generate code, discuss code-related topics, and search for specific code snippets. The tool leverages artificial intelligence algorithms to enhance the coding experience and streamline the development process. With Chat Blackbox, users can access a wide range of features to improve their coding skills and efficiency.

Blackbox is an AI-powered code generation, code chat, and code search tool that helps developers write better code faster. With Blackbox, you can generate code snippets, chat with an AI assistant about code, and search for code examples from a massive database.

AIlice is a fully autonomous, general-purpose AI agent that aims to create a standalone artificial intelligence assistant, similar to JARVIS, based on the open-source LLM. AIlice achieves this goal by building a "text computer" that uses a Large Language Model (LLM) as its core processor. Currently, AIlice demonstrates proficiency in a range of tasks, including thematic research, coding, system management, literature reviews, and complex hybrid tasks that go beyond these basic capabilities. AIlice has reached near-perfect performance in everyday tasks using GPT-4 and is making strides towards practical application with the latest open-source models. We will ultimately achieve self-evolution of AI agents. That is, AI agents will autonomously build their own feature expansions and new types of agents, unleashing LLM's knowledge and reasoning capabilities into the real world seamlessly.

python-sc2 is an easy-to-use library for writing AI Bots for StarCraft II in Python 3. It aims for simplicity and ease of use while providing both high and low level abstractions. The library covers only the raw scripted interface and intends to help new bot authors with added functions. Users can install the library using pip and need a StarCraft II executable to run bots. The API configuration options allow users to customize bot behavior and performance. The community provides support through Discord servers, and users can contribute to the project by creating new issues or pull requests following style guidelines.

ScrapeGraphAI is a web scraping Python library that utilizes LLM and direct graph logic to create scraping pipelines for websites and local documents. It offers various standard scraping pipelines like SmartScraperGraph, SearchGraph, SpeechGraph, and ScriptCreatorGraph. Users can extract information by specifying prompts and input sources. The library supports different LLM APIs such as OpenAI, Groq, Azure, and Gemini, as well as local models using Ollama. ScrapeGraphAI is designed for data exploration and research purposes, providing a versatile tool for extracting information from web pages and generating outputs like Python scripts, audio summaries, and search results.

r2ai is a tool designed to run a language model locally without internet access. It can be used to entertain users or assist in answering questions related to radare2 or reverse engineering. The tool allows users to prompt the language model, index large codebases, slurp file contents, embed the output of an r2 command, define different system-level assistant roles, set environment variables, and more. It is accessible as an r2lang-python plugin and can be scripted from various languages. Users can use different models, adjust query templates dynamically, load multiple models, and make them communicate with each other.

Praison AI is a low-code, centralised framework that simplifies the creation and orchestration of multi-agent systems for various LLM applications. It emphasizes ease of use, customization, and human-agent interaction. The tool leverages AutoGen and CrewAI frameworks to facilitate the development of AI-generated scripts and movie concepts. Users can easily create, run, test, and deploy agents for scriptwriting and movie concept development. Praison AI also provides options for full automatic mode and integration with OpenAI models for enhanced AI capabilities.

This repository contains an MLIR-based toolchain for AI Engine-enabled devices, such as AMD Ryzen™ AI and Versal™. This repository can be used to generate low-level configurations for the AI Engine portion of these devices. AI Engines are organized as a spatial array of tiles, where each tile contains AI Engine cores and/or memories. The spatial array is connected by stream switches that can be configured to route data between AI Engine tiles scheduled by their programmable Data Movement Accelerators (DMAs). This repository contains MLIR representations, with multiple levels of abstraction, to target AI Engine devices. This enables compilers and developers to program AI Engine cores, as well as describe data movements and array connectivity. A Python API is made available as a convenient interface for generating MLIR design descriptions. Backend code generation is also included, targeting the aie-rt library. This toolchain uses the AI Engine compiler tool which is part of the AMD Vitis™ software installation: these tools require a free license for use from the Product Licensing Site.

LMQL is a programming language designed for large language models (LLMs) that offers a unique way of integrating traditional programming with LLM interaction. It allows users to write programs that combine algorithmic logic with LLM calls, enabling model reasoning capabilities within the context of the program. LMQL provides features such as Python syntax integration, rich control-flow options, advanced decoding techniques, powerful constraints via logit masking, runtime optimization, sync and async API support, multi-model compatibility, and extensive applications like JSON decoding and interactive chat interfaces. The tool also offers library integration, flexible tooling, and output streaming options for easy model output handling.

This Python Telegram bot utilizes Google's `gemini-pro` LLM API to generate creative text formats based on user input. It's designed to be an engaging and interactive way to explore the capabilities of large language models. Key features include generating various text formats like poems, code, scripts, and musical pieces. The bot supports real-time streaming of the generation process, allowing users to witness the text unfold. Additionally, it can respond to messages with Bard's creative output and handle image-based inputs for multimodal responses. User authentication is optional, and the bot can be easily integrated with Docker or installed via pipenv.

OpenAdapt is an open-source software adapter between Large Multimodal Models (LMMs) and traditional desktop and web Graphical User Interfaces (GUIs). It aims to automate repetitive GUI workflows by leveraging the power of LMMs. OpenAdapt records user input and screenshots, converts them into tokenized format, and generates synthetic input via transformer model completions. It also analyzes recordings to generate task trees and replay synthetic input to complete tasks. OpenAdapt is model agnostic and generates prompts automatically by learning from human demonstration, ensuring that agents are grounded in existing processes and mitigating hallucinations. It works with all types of desktop GUIs, including virtualized and web, and is open source under the MIT license.

RA.Aid is an AI software development agent powered by `aider` and advanced reasoning models like `o1`. It combines `aider`'s code editing capabilities with LangChain's agent-based task execution framework to provide an intelligent assistant for research, planning, and implementation of multi-step development tasks. It handles complex programming tasks by breaking them down into manageable steps, running shell commands automatically, and leveraging expert reasoning models like OpenAI's o1. RA.Aid is designed for everyday software development, offering features such as multi-step task planning, automated command execution, and the ability to handle complex programming tasks beyond single-shot code edits.

MonikA.I. submod is a project that enhances Monika After Story mod with various AI features. It utilizes multiple AI models for text generation, text-to-speech, speech-to-text, emotion detection, and NLI classification. Users can interact with Monika through chatbots, voice commands, and game actions. The project is compatible with MAS v0.12.15 and supports Windows, Linux, and MacOS. It offers a user-friendly installation process and detailed usage instructions for different AI functionalities.

RAVE is a variational autoencoder for fast and high-quality neural audio synthesis. It can be used to generate new audio samples from a given dataset, or to modify the style of existing audio samples. RAVE is easy to use and can be trained on a variety of audio datasets. It is also computationally efficient, making it suitable for real-time applications.

This repository contains code for training reward models for Deep Reinforcement Learning-based Reward-modulated Hierarchical Fine-tuning (DRL-based RLHF), Iterative Selection Fine-tuning (Rejection sampling fine-tuning), and iterative Decision Policy Optimization (DPO). The reward models are trained using a Bradley-Terry model based on the Gemma and Mistral language models. The resulting reward models achieve state-of-the-art performance on the RewardBench leaderboard for reward models with base models of up to 13B parameters.

The 'nlp-llms-resources' repository is a comprehensive resource list for Natural Language Processing (NLP) and Large Language Models (LLMs). It covers a wide range of topics including traditional NLP datasets, data acquisition, libraries for NLP, neural networks, sentiment analysis, optical character recognition, information extraction, semantics, topic modeling, multilingual NLP, domain-specific LLMs, vector databases, ethics, costing, books, courses, surveys, aggregators, newsletters, papers, conferences, and societies. The repository provides valuable information and resources for individuals interested in NLP and LLMs.

A curated list of Generative AI projects, tools, artworks, and models

This repository, Online RLHF, focuses on aligning large language models (LLMs) through online iterative Reinforcement Learning from Human Feedback (RLHF). It aims to bridge the gap in existing open-source RLHF projects by providing a detailed recipe for online iterative RLHF. The workflow presented here has shown to outperform offline counterparts in recent LLM literature, achieving comparable or better results than LLaMA3-8B-instruct using only open-source data. The repository includes model releases for SFT, Reward model, and RLHF model, along with installation instructions for both inference and training environments. Users can follow step-by-step guidance for supervised fine-tuning, reward modeling, data generation, data annotation, and training, ultimately enabling iterative training to run automatically.

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.

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