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Showing 15 open source projects for "file="
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Gemini 3 and 200+ AI Models on One PlatformBuild, govern, and optimize agents and models with Gemini Enterprise Agent Platform.
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OpenHuman
Your Personal AI super intelligence. Private, simple and powerful
...The project connects to common productivity tools, gathers fresh information from integrations, and organizes user knowledge into a local memory system. It also includes practical agent tools such as web search, web fetching, file access, coding utilities, voice input, text-to-speech, and model routing. Its goal is to make an AI assistant feel continuously useful across meetings, messages, documents, tasks, and personal workflows. Since it is still in early beta, it is best suited for technical users and early adopters who want to experiment with a customizable personal AI environment. -
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OpenAI Codex CLI
Lightweight coding agent that runs in your terminal
OpenAI Codex CLI is a lightweight, open-source coding assistant that runs directly in your terminal, designed to bring ChatGPT-level reasoning to your code workflows. It allows developers to interactively query, edit, and generate code within their repositories, all while maintaining version control. The CLI can scaffold new files, run code in sandboxed environments, install dependencies, and commit changes automatically, streamlining chat-driven development. It supports various approval... -
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yek
Serialize repositories into LLM-ready context w/ smart prioritization
...Yek supports multiple directories, individual files, and glob patterns, making it flexible for different workflows. It can stream output when piped or save results to a temporary file, depending on usage. Configuration is handled through a yek.yaml file, allowing users to define ignore rules and priority settings. By consolidating code and documents into a single, ordered format, Yek simplifies preparing repositories for AI-driven analysis, debugging, or automation tasks. -
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Rust Port
The Rust workspace under rust/ is the current systems-language port
...It is often used as a sandbox for exploring how large-scale coding agents behave, including their decision-making processes, tool usage, and workflow orchestration. The system likely includes abstractions for handling file systems, executing commands, and maintaining context across sessions, allowing for more persistent and intelligent coding interactions. -
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Cog
Package and deploy machine learning models using Docker containers
Cog is an open source tool designed to package machine learning models into standardized, production-ready containers. It simplifies the process of deploying models by automatically generating Docker images based on a simple configuration file, eliminating the need to manually write complex Dockerfiles. Developers can define the runtime environment, dependencies, and Python versions required for their models, allowing Cog to build a consistent container environment that follows best practices. Cog also resolves compatibility issues between frameworks and GPU libraries by automatically selecting compatible combinations of CUDA, cuDNN, and machine learning frameworks such as PyTorch or TensorFlow. ... -
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OpenShell
OpenShell is the safe, private runtime for autonomous AI agents.
...Developed by NVIDIA, it provides sandboxed execution spaces that protect system resources, credentials, and data from unauthorized access. Each agent runs inside a containerized sandbox governed by declarative YAML security policies that control network access, file permissions, and process behavior. The platform includes a gateway service that manages sandbox lifecycles and routes AI inference requests through controlled providers. OpenShell also features a privacy-aware routing system that prevents sensitive information from leaving the sandbox environment. By combining container isolation, policy enforcement, and agent orchestration, OpenShell offers a secure infrastructure for developing and operating AI agents. -
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Code2Prompt
Convert codebases into structured prompts optimized for LLM analysis
...It also respects common project conventions such as .gitignore, ensuring that unnecessary files are automatically excluded from the generated prompt. The generated output can be saved to a file, printed to standard output, or copied to the clipboard for immediate use. In addition to the core command line interface, the project also includes a library, Python bindings, and an MCP server. -
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Lance
Modern columnar data format for ML and LLMs implemented in Rust
Lance is a columnar data format that is easy and fast to version, query and train on. It’s designed to be used with images, videos, 3D point clouds, audio and of course tabular data. It supports any POSIX file systems, and cloud storage like AWS S3 and Google Cloud Storage. -
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Bionic GPT
Bionic is an on-premise replacement for ChatGPT
Bionic is an on-premise generative AI platform positioned as a private replacement for ChatGPT, with a strong emphasis on data confidentiality, team collaboration, and enterprise deployment. It can run locally on a laptop for small pilots, but it is also designed to scale into data center and Kubernetes environments for much larger usage. The interface is intentionally familiar, offering a ChatGPT-like experience with customizable branding, fast Rust-based performance, and conversation... -
Secure File Transfer for Windows with Cerberus by RedwoodCerberus supports unlimited users and connections on a single IP, with built-in encryption, 2FA, and a browser-based web client — all deployable in under 15 minutes with a 25-day free trial.
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Extractous
Fast and efficient unstructured data extraction
Extractous is a Rust-based unstructured data extraction library focused on fast local parsing of documents and other content-heavy files. Its purpose is to extract text and metadata efficiently from formats such as PDF, Word, HTML, email archives, images, and more, without depending on external APIs or separate parsing servers. The project emphasizes performance and low memory usage, and its maintainers describe it as a local-first alternative to heavier extraction stacks. For broader format... -
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Simple TTS Reader
A small clipboard reader
Simple TTS Reader is a small utility that reads text from your clipboard using Microsoft Speech API. Whenever you copy any text, the app instantly converts it into spoken words. Select your preferred speech engine from those installed on your system, such as Microsoft Zira, and adjust speed and volume for personalized playback. The application can also be minimized to the system tray. Plus, it is free and comes with an intuitive interface that makes it accessible to everyone. -
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Shinkai: Local AI Agents
Shinkai allows you to create advanced AI (local) agents effortlessly
Shinkai is a free, open-source AI platform that lets anyone create powerful AI agents without coding. These agents can collaborate with each other, handle complex tasks, and operate in decentralized crypto environments. Key Features: - No-Code Agent Creation - Build specialized agents (trading bots, sentiment trackers, etc.) with simple descriptions - Multi-Agent Collaboration - Agents work together to solve complex problems - Crypto Integration - Built-in support for decentralized... -
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ChatGPT Desktop Application
🔮 ChatGPT Desktop Application (Mac, Windows and Linux)
ChatGPT Desktop Application (Mac, Windows and Linux) -
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SmartGPT
A program that provides LLMs with ability to complete complex tasks
SmartGPT is an experimental autonomous agent framework built to help large language models tackle complex tasks with minimal or no additional user input. It works by decomposing larger objectives into smaller steps and gathering information from the internet and other outside sources as needed. The project is written in Rust and emphasizes modularity, allowing developers to compose different “Autos” depending on the workflow they want to build. Its architecture separates responsibility... -
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ModelFox
ModelFox makes it easy to train, deploy, and monitor ML models
...Train a machine learning model by running modelfox train with the path to a CSV file and the name of the column you want to predict. The CLI automatically transforms your data into features, trains a number of linear and gradient boosted decision tree models to predict the target column, and writes the best model to a .modelfox file. If you want more control, you can provide a config file.
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