Search Results for "python code generator" - Page 5
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370 projects for "python code generator" with 2 filters applied:
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AestheticsPro Medical Spa SoftwareAestheticsPro is the most complete Aesthetics Software on the market today. HIPAA Cloud Compliant with electronic charting, integrated POS, targeted marketing and results driven reporting; AestheticsPro delivers the tools you need to manage your medical spa business. It is our mission To Provide an All-in-One Cutting Edge Software to the Aesthetics Industry.
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Premier Construction SoftwareRated #1 Construction Accounting Software by Forbes Advisor in 2022 & 2023. Our modern SAAS solution is designed to meet the needs of General Contractors, Developers/Owners, Homebuilders & Specialty Contractors.
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AutoTrain Advanced
Faster and easier training and deployments
AutoTrain Advanced is an open-source machine learning training framework developed by Hugging Face that simplifies the process of training and fine-tuning state-of-the-art AI models. The project provides a no-code and low-code interface that allows users to train models using custom datasets without needing extensive expertise in machine learning engineering. It supports a wide range of tasks including text classification, sequence-to-sequence modeling, token classification, sentence... -
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Sage Chat
Chat with any codebase in under two minutes | Fully local
Sage is an open-source AI developer assistant designed to help engineers understand and work with complex codebases more effectively. The tool functions similarly to an intelligent research agent that can analyze a repository and answer questions about how the software works. Instead of focusing solely on code generation, Sage emphasizes code comprehension, system architecture analysis, and integration guidance. Developers can ask natural language questions about a project, and the system... -
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ai-cookbook
Examples and tutorials to help developers build AI systems
ai-cookbook is an open-source repository that provides practical tutorials, code examples, and reusable snippets designed to help developers build real-world artificial intelligence applications quickly. The project focuses on delivering hands-on engineering guidance rather than theoretical explanations, allowing developers to copy, adapt, and integrate working code directly into their own systems. The repository contains examples that demonstrate how to build AI workflows using modern tools... -
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MLC LLM
Universal LLM Deployment Engine with ML Compilation
MLC LLM is a machine learning compiler and deployment framework designed to enable efficient execution of large language models across a wide range of hardware platforms. The project focuses on compiling models into optimized runtimes that can run natively on devices such as GPUs, mobile processors, browsers, and edge hardware. By leveraging machine learning compilation techniques, mlc-llm produces high-performance inference engines that maintain consistent APIs across platforms. The system... -
Simplify Purchasing For Your BusinessSimplify every aspect of buying for your business in Order.co. From sourcing products to scaling purchasing across locations to automating your AP and approvals workstreams, Order.co is the platform of choice for growing businesses.
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Google Research: Language
Shared repository for open-sourced projects from the Google AI Lang
Google Research: Language is a shared repository maintained by Google Research that contains open-source projects developed by the Google AI Language team. The repository hosts multiple subprojects related to natural language processing, machine learning, and large-scale language understanding systems. Many of the projects included in the repository correspond to research papers released by Google researchers and provide implementations of new NLP algorithms or experimental frameworks. These... -
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AI-Tutorials/Implementations Notebooks
Codes/Notebooks for AI Projects
AI-Tutorials/Implementations Notebooks repository is a comprehensive collection of artificial intelligence tutorials and implementation examples intended for developers, students, and researchers who want to learn by building practical AI projects. The repository contains numerous Jupyter notebooks and code samples that demonstrate modern techniques in machine learning, deep learning, data science, and large language model workflows. It includes implementations for a wide range of AI topics... -
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OpenAGI
When LLM Meets Domain Experts
OpenAGI is a package for AI agent creation designed to connect large language models with domain-specific tools and workflows in the AIOS (AI Operating System) ecosystem. It provides a structured Python framework, pyopenagi, for defining agents as modular units that encapsulate execution logic, configuration, and dependency metadata. Agents are organized in a well-defined folder structure that includes code (agent.py), configuration (config.json), and extra requirements (meta_requirements.txt), which makes them easy to package, share, and reuse. ... -
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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... -
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AutoAgent
AutoAgent: Fully-Automated and Zero-Code LLM Agent Framework
AutoAgent is a fully automated, zero-code LLM agent framework that lets users create agents and workflows using natural language instead of manual coding and configuration. It is structured around modes that cover both “use” and “build” scenarios: a user mode for running a ready-made multi-agent research assistant, plus editors for creating individual agents or multi-agent workflows from conversational requirements. The framework emphasizes self-managing workflow generation, where it can... -
Outbound sales softwareAdversus is an outbound dialing solution that helps you streamline your call strategies, automate manual processes, and provide valuable insights to improve your outbound workflows and efficiency.
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Tiktoken
tiktoken is a fast BPE tokeniser for use with OpenAI's models
...It also offers extension mechanisms so that custom encodings can be registered. Internally, it includes the core tokenizer logic (often implemented in Rust or efficient lower-level code), APIs for encoding, decoding, and counting tokens, and binding layers to Python (and sometimes other languages) for easy use. -
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SAM 3D Objects
Models for object and human mesh reconstruction
SAM 3D Objects is a foundation model that reconstructs full 3D geometry, texture, and spatial layout of objects and scenes from a single image. Given one RGB image and object masks (for example, from the Segment Anything family), it can generate a textured 3D mesh for each object, including pose and approximate scene layout. The model is specifically designed to be robust in real-world images with clutter, occlusions, small objects, and unusual viewpoints, where many earlier 3D-from-image... -
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Search with Lepton
Lightweight demo to build a conversational AI search engine quickly
...It retrieves information from supported search engines and uses that context to generate responses through a retrieval-augmented generation approach. The implementation is intentionally minimal, containing fewer than 500 lines of code while still providing a complete working example of an AI-powered search system. It includes both a backend service written in Python and a web interface that allows users to interact with the search engine in a conversational format. Developers can configure different search providers and language models through environment variables, making it flexible for experimentation and prototyping. -
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graphify
AI coding assistant skill (Claude Code, Codex, OpenCode, OpenClaw)
graphify is a data visualization and transformation tool designed to convert structured or semi-structured data into graph-based representations, enabling better understanding of relationships and dependencies. It focuses on building visual models such as nodes and edges that represent entities and their connections, making complex datasets easier to interpret. The system likely supports dynamic updates, allowing graphs to evolve as data changes or new inputs are introduced. It is... -
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DeepAnalyze
Autonomous LLM agent for end-to-end data science workflows
DeepAnalyze is an open source project that introduces an agentic large language model designed to perform autonomous data science tasks from start to finish. It is built to handle the entire data science pipeline, including data preparation, analysis, modeling, visualization, and report generation without requiring continuous human guidance. DeepAnalyze is capable of conducting open-ended data research across multiple data formats such as structured tables, semi-structured files, and... -
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LaVague
Framework for building AI agents that automate complex web tasks
LaVague is an open source framework designed to help developers build AI-powered web agents capable of automating tasks across websites and web applications. It implements the concept of a Large Action Model framework, allowing agents to interpret a user-provided objective and translate it into a sequence of actions performed in a browser. These agents can navigate web pages, retrieve information, fill out forms, and execute multi-step workflows automatically. LaVague is centered around a... -
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Context Engineering Template
Context engineering is the new vibe coding
Context Engineering Template is a comprehensive template and workflow repository designed to teach and implement context engineering, a structured approach to preparing and organizing the information necessary for AI coding assistants to complete complex tasks reliably. Instead of relying solely on short prompts, this project encourages developers to create rich, structured context files that include project rules, examples, and validation criteria so that AI systems can act more like... -
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DINOv2
PyTorch code and models for the DINOv2 self-supervised learning
DINOv2 is a self-supervised vision learning framework that produces strong, general-purpose image representations without using human labels. It builds on the DINO idea of student–teacher distillation and adapts it to modern Vision Transformer backbones with a carefully tuned recipe for data augmentation, optimization, and multi-crop training. The core promise is that a single pretrained backbone can transfer well to many downstream tasks—from linear probing on classification to retrieval,... -
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DeepSeek-V3.2-Exp
An experimental version of DeepSeek model
DeepSeek-V3.2-Exp is an experimental release of the DeepSeek model family, intended as a stepping stone toward the next generation architecture. The key innovation in this version is DeepSeek Sparse Attention (DSA), a sparse attention mechanism that aims to optimize training and inference efficiency in long-context settings without degrading output quality. According to the authors, they aligned the training setup of V3.2-Exp with V3.1-Terminus so that benchmark results remain largely... -
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PipesHub
Workplace AI platform for enterprise search and workflow automation
PipesHub AI is an open-source, enterprise-grade workplace AI platform designed to unify search, knowledge management, and workflow automation across distributed organizational systems. It connects to a wide range of enterprise tools such as Google Workspace, Slack, Jira, and Confluence, aggregating data into a centralized knowledge layer that can be queried using natural language. The platform uses knowledge graphs and ranking algorithms to provide context-rich answers along with traceable... -
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dots.ocr
Multilingual Document Layout Parsing in a Single Vision-Language Model
dots.ocr is a cutting-edge multilingual document parsing system built on a unified vision-language model that combines layout detection, text recognition, and structural understanding into a single architecture. Unlike traditional OCR pipelines that rely on multiple specialized components, dots.ocr integrates these processes end-to-end, reducing error propagation and improving consistency across tasks. The model is designed to recognize virtually any human script, making it highly effective... -
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CLIP
CLIP, Predict the most relevant text snippet given an image
CLIP (Contrastive Language-Image Pretraining) is a neural model that links images and text in a shared embedding space, allowing zero-shot image classification, similarity search, and multimodal alignment. It was trained on large sets of (image, caption) pairs using a contrastive objective: images and their matching text are pulled together in embedding space, while mismatches are pushed apart. Once trained, you can give it any text labels and ask it to pick which label best matches a given... -
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Depth Anything 3
Recovering the Visual Space from Any Views
Depth Anything 3 is a research-driven project that brings accurate and dense depth estimation to any input image or video, enabling foundational understanding of 3D structure from 2D visual content. Designed to work across diverse scenes, lighting conditions, and image types, it uses advanced neural networks trained on large, heterogeneous datasets, producing depth maps that reveal scene depth relationships and object surfaces with strong fidelity. The model can be applied to photography,... -
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AutoViz
Automatically Visualize any dataset, any size
AutoViz is a Python data visualization library designed to automate exploratory data analysis by generating multiple visualizations with minimal code. The primary goal of the project is to help data scientists and analysts quickly understand patterns, relationships, and anomalies within datasets without manually writing complex plotting code. With a single command, the library can automatically generate dozens of charts and graphs that reveal insights into the structure and quality of the data. ... -
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machine learning tutorials
machine learning tutorials (mainly in Python3)
machine-learning is a continuously updated repository documenting the author’s learning journey through data science and machine learning topics using practical tutorials and experiments. The project presents educational notebooks that combine mathematical explanations with code implementations using Python’s scientific computing ecosystem. Topics covered include classical machine learning algorithms, deep learning models, reinforcement learning, model deployment, and time-series analysis.... -
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Agent Lightning
The absolute trainer to light up AI agents
Agent Lightning is an open-source framework developed by Microsoft to train and optimize AI agents using techniques like reinforcement learning (RL), supervised fine-tuning, and automatic prompt optimization, with minimal or zero changes to existing agent code. It’s designed to be compatible with a wide range of agent architectures and frameworks — from LangChain and OpenAI Agent SDKs to AutoGen and custom Python agents — making it broadly applicable across different agent tooling ecosystems. Agent-Lightning introduces a lightweight training pipeline that observes agents’ execution traces, converts them into structured data, and feeds them into training algorithms, enabling users to improve agent behaviors systematically. ...
