Open Source Python AI Coding Tools - Page 2
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Python AI Coding Tools
View 309 business solutionsBrowse free open source Python AI Coding Tools and projects below. Use the toggles on the left to filter open source Python AI Coding Tools by OS, license, language, programming language, and project status.
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SoftCo: Enterprise Invoice and P2P Automation SoftwareSoftCo Accounts Payable Automation processes all PO and non-PO supplier invoices electronically from capture and matching through to invoice approval and query management. SoftCoAP delivers unparalleled touchless automation by embedding AI across matching, coding, routing, and exception handling to minimize the number of supplier invoices requiring manual intervention. The result is 89% processing savings, supported by a context-aware AI Assistant that helps users understand exceptions, answer questions, and take the right action faster.
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Skillfully - The future of skills based hiringSkillfully transforms hiring through AI-powered skill simulations that show you how candidates actually perform before you hire them. Our platform helps companies cut through AI-generated resumes and rehearsed interviews by validating real capabilities in action. Through dynamic job specific simulations and skill-based assessments, companies like Bloomberg and McKinsey have cut screening time by 50% while dramatically improving hire quality.
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Archon
The knowledge and task management backbone for AI coding assistants
Archon is an open-source “command center” designed to enhance AI coding assistant workflows by giving developers a centralized environment for knowledge management, context engineering, and task coordination across AI agents. It acts as a backend (including an MCP server) that allows different AI coding tools and assistants to share the same structured context, knowledge base, and task lists, improving consistency, productivity, and collaboration across multi-agent interactions. Users can import documentation, project files, and external knowledge so that assistants like Claude Code, Cursor, or other LLM-powered tools work with up-to-date, project-specific context rather than relying on limited prompt memory. Archon’s UI and APIs are intended to streamline how developers interact with their agents, whether for exploratory coding, automated task execution, or integrated RAG workflows, helping reduce friction between manual coding tasks and AI-generated suggestions. -
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CodeGeeX2
CodeGeeX2: A More Powerful Multilingual Code Generation Model
CodeGeeX2 is the second-generation multilingual code generation model from ZhipuAI, built upon the ChatGLM2-6B architecture and trained on 600B code tokens. Compared to the first generation, it delivers a significant boost in programming ability across multiple languages, outperforming even larger models like StarCoder-15B in some benchmarks despite having only 6B parameters. The model excels at code generation, translation, summarization, debugging, and comment generation, and it supports over 100 programming languages. With improved inference efficiency, quantization options, and multi-query/flash attention, CodeGeeX2 achieves faster generation speeds and lightweight deployment, requiring as little as 6GB GPU memory at INT4 precision. Its backend powers the CodeGeeX IDE plugins for VS Code, JetBrains, and other editors, offering developers interactive AI assistance with features like infilling and cross-file completion. -
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CodiumAI Cover-Agent
CodiumAI Cover-Agent: An AI-Powered Tool for Automated Test Generation
CodiumAI Cover Agent aims to help efficiently increasing code coverage, by automatically generating qualified tests to enhance existing test suites. -
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ollama_manager_gui
A graphical manager for ollama that can manage your LLMs
This app will help install ollama and LLMs using the gui provided by this app. It checks for ollama when launched and if it doesn't exist it will help by bringing you to the ollama site for download. This app is heavily upgraded and now also works properly on Linux. It now has progress bars and many many many improvements. It can launch the LLM by clicking the link. it can launch multiple LLMs in separate windows. It can also remove an installed LLM. There is a confirmation dialog when removing or hard resetting an LLM. It can also install LLMs. Reset deletes all data for LLM of your choosing and automatically reinstalls that LLM of your choosing by redownloading. You can also install new LLMs by simply clicking the install button. warning... you can remove custom LLMs with this... Remember with great power comes greater responsibility! I hope this is of use to you, but it has no warranty it has a very nice improved dark mode as of version 1.2 aka 1 -
The Most Powerful Software Platform for EHSQ and ESG ManagementChoose from a complete set of software solutions across EHSQ that address all aspects of top performing Environmental, Health and Safety, and Quality management programs.
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realwatermark
A Python application to add watermarks (text or image) to PDF files
A Python application to add watermarks (text or image) to PDF files, converts them into image and back to PDF with options for OCR and compression. -
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AutoPR
Run AI-powered workflows over your codebase
AutoPR is an AI-driven tool for automating pull request (PR) generation and review processes. It streamlines code contributions by suggesting fixes, generating pull requests, and reviewing code using AI models, reducing manual overhead for developers. -
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Claude Code Hooks Mastery
Master Claude Code Hooks
Claude Code Hooks Mastery is a trending community-centric GitHub repository aimed at helping developers master Claude Code hooks — customizable integration points that let users extend, automate, and augment workflows when using Claude Code, an agentic terminal coding assistant. Although the project itself doesn’t include a single coherent application, it functions as a curated collection of advanced hook examples, best practices, and coding patterns that show how to tailor Claude Code to specific use cases such as automated CI workflows, custom command triggers, and integrations with external tools. The repository is part of a larger ecosystem of Claude Code tooling that enables natural-language-driven coding tasks, and the hooks contained here help users go beyond default behaviors to solve real problems efficiently. -
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Claude Cognitive
Persistent context and multi-instance coordination
Claude Cognitive is an advanced memory and context-management extension designed to address the stateless limitations of Claude Code by giving the model a form of persistent “working memory” and multi-instance coordination. It introduces an attention-based context router that prioritizes files and content relevant to the current development discussion — tagging them as HOT, WARM, or COLD based on recency and keyword activation — so Claude Code doesn’t waste token budget rereading irrelevant code. This context routing dramatically reduces redundant token usage and accelerates large codebase interactions by focusing only on what truly matters to the current task. Additionally, Claude-Cognitive includes a pool coordinator to share state across multiple Claude Code instances, preserving what’s been learned or completed and preventing repetitive debugging or redundant exploration. -
Turn traffic into pipeline and prospects into customersDocket is an AI-powered sales enablement platform designed to unify go-to-market (GTM) data through its proprietary Sales Knowledge Lake™ and activate it with intelligent AI agents. The platform helps marketing teams increase pipeline generation by 15% by engaging website visitors in human-like conversations and qualifying leads. For sales teams, Docket improves seller efficiency by 33% by providing instant product knowledge, retrieving collateral, and creating personalized documents. Built for GTM teams, Docket integrates with over 100 tools across the revenue tech stack and offers enterprise-grade security with SOC 2 Type II, GDPR, and ISO 27001 compliance. Customers report improved win rates, shorter sales cycles, and dramatically reduced response times. Docket’s scalable, accurate, and fast AI agents deliver reliable answers with confidence scores, empowering teams to close deals faster.
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Code World Model (CWM)
Research code artifacts for Code World Model (CWM)
CWM (Code World Model) is a 32-billion-parameter open-weights language model. It is developed by Meta for enhancing code generation and reasoning about programs. It is explicitly trained on execution traces, action-observation trajectories, and agentic interactions in controlled environments. It has been developed to better capture how code, actions, and state interact over time. The repository provides inference code, reproducibility scripts, prompt guides, and more. It has model cards, utilities, demos, and evaluation artifacts. Inference scripts and utilities for code generation tasks. Evaluation benchmarks on code, mathematics, and reasoning tasks. Demos, serving code, and evaluation pipelines. -
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E2B Code Interpreter
Python & JS/TS SDK for running AI-generated code/code
An interactive coding tool enabling real-time code interpretation for multiple languages. -
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GPT All Star
AI-powered code generation tool for scratch development of web apps
AI-powered code generation tool for scratch development of web applications with a team collaboration of autonomous AI agents. This is a research project, and its primary value is to explore the possibility of autonomous AI agents. -
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Habit Tracker
Habit Tracker for the AI Coding Workshop
Habit Tracker is a personal habit-tracking web application designed to help users build and maintain daily habits through intuitive UI and analytics that visualize progress over time. It runs locally with a FastAPI backend (Python) and a React frontend, storing all data in a lightweight SQLite database so there’s no need for user accounts or cloud storage, which keeps habit data fully private and self-contained. The app provides streak tracking and completion rates for each habit, giving users feedback on consistency and motivation by showing how often habits are completed and where they may be lagging. A calendar view lets users see a monthly grid of their habit history with color-coded days to highlight patterns and encourage daily engagement. Habit-Tracker also supports planned absences so users can skip days without breaking their streaks, reducing frustration and keeping long-term habits on track. -
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Leanstral
Open-source code agent designed for Lean 4
Leanstral is an open-weight large language model developed by Mistral AI and specifically designed as a code agent for the Lean 4 proof assistant, enabling advanced interaction with formal mathematics and program verification systems. The model is built to understand and generate Lean 4 code, which is used to express complex mathematical constructs as well as formal software specifications. By focusing on theorem proving and formal reasoning, Leanstral represents a specialized direction within large language models, targeting domains that require strict correctness and logical rigor rather than general conversational tasks. It leverages modern large-scale architectures, likely incorporating mixture-of-experts techniques, to balance efficiency and capability while handling structured symbolic reasoning tasks. The model can assist in writing proofs, exploring mathematical structures, and validating logical properties in code. -
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Mentat
Mentat - The AI Coding Assistant
Mentat is the AI tool that assists you with any coding task, right from your command line. Unlike Copilot, Mentat coordinates edits across multiple locations and files. And unlike ChatGPT, Mentat already has the context of your project, no copy and pasting is required. Run Mentat from within your project directory. Mentat uses Git, so if your project doesn't already have Git set up, run git init. List the files you would like Mentat to read and edit as arguments. Mentat will add each of them to context, so be careful not to exceed the GPT-4 token context limit. -
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RA.Aid
Develop software autonomously
RA.Aid is an AI-powered assistant designed to enhance the efficiency of software development workflows. It integrates seamlessly with various development environments, providing intelligent code suggestions, automated documentation generation, and real-time error detection. By leveraging advanced machine learning models, RA.Aid aims to reduce development time and improve code quality. -
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SERA CLI
A tool to use the Ai2 Open Coding Agents Soft-Verified Agents
SERA CLI is a command-line tool created by AllenAI to enable developers to interact with the SERA (Soft-Verified Efficient Repository Agents) model family using Claude Code as the execution front end. It provides a convenient interface for deploying, testing, and using SERA models without needing to write scaffold code from scratch, acting as both a proxy and utility wrapper to simplify workflows that involve large agent models. Through sera-cli, users can connect to local or cloud-hosted SERA deployments, including via Modal for quick GPU provisioning and model caching, which helps accelerate experiments. The project is targeted at practitioners and researchers in the AI space who need a flexible but powerful CLI interface for model invocation, endpoint configuration, and integration with development pipelines. -
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Sweep AI
Sweep: AI-powered Junior Developer for small features and bug fixes
Let Sweep handle your tech debt so you can focus on the exciting problems. Sweep is an AI junior developer that transforms bug reports & feature requests into code changes. Describe bugs, small features, and refactors like you would to a junior developer and Sweep. -
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mac code
Claude Code, but it runs on your Mac for free
mac code is a local AI coding agent designed to run large language models directly on Apple Silicon machines without relying on cloud services, effectively transforming a Mac into a self-contained AI development environment. The project focuses on enabling models that traditionally exceed available RAM to run efficiently by streaming model weights from SSD storage, thereby overcoming hardware limitations through innovative memory management techniques. It operates as a CLI-based assistant that routes user prompts into different execution paths such as chat, shell commands, or web search, functioning as a multi-purpose development agent. The system integrates with inference engines like llama.cpp and Apple’s MLX framework, allowing users to run models up to 35B parameters locally with varying performance trade-offs.
