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Showing 14 open source projects for "run python on cellphone"
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Secure remote access solution to your private network, in the cloud or on-prem.OpenVPN is here to bring simple, flexible, and cost-effective secure remote access to companies of all sizes, regardless of where their resources are located.
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1
Lama Cleaner
Image inpainting tool powered by SOTA AI Model
... their work. Completely free and open-source, fully self-hosted, supports CPU & GPU. Windows 1-Click Installer, classical image inpainting algorithm powered by cv2. Multiple SOTA AI models, and various inpainting strategies. Run as a desktop application. Interactive Segmentation on any object. -
2
TensorFlow.js
TensorFlow.js is a library for machine learning in JavaScript
TensorFlow.js is a library for machine learning in JavaScript. Develop ML models in JavaScript, and use ML directly in the browser or in Node.js. Use off-the-shelf JavaScript models or convert Python TensorFlow models to run in the browser or under Node.js. Retrain pre-existing ML models using your own data. Build and train models directly in JavaScript using flexible and intuitive APIs. Tensors are the core datastructure of TensorFlow.js They are a generalization of vectors and matrices... -
3
WalletConnect v2.x.x
WalletConnect Monorepo
... python cli is linked (required to build some npm modules). Install workspace dependencies i.e. run npm install from root folder. Install redis. We recommend running it as a brew service. Pull and start ts-relay server (separate repo) Ensure everything runs correctly by executing npm run check. -
4
Chainlit
Build Python LLM apps in minutes
... and run experiments together. Chainlit is compatible with all Python programs and libraries. That being said, it comes with a set of integrations with popular libraries and frameworks. -
Crowdtesting That Delivers | TesteumTesteum connects your software, app, or website to a worldwide network of testers, delivering detailed feedback in under 48 hours. Ensure functionality and refine UX on real devices, all at a fraction of traditional costs. Trusted by startups and enterprises alike, our platform streamlines quality assurance with actionable insights.
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5
OpenHands
Open-source autonomous AI software engineer
... in the open on GitHub, under the MIT license. Our agents can do anything a human developer can: they write code, run commands, and use the web. We're partnering with AI safety experts like Invariant Labs to balance innovation with security. -
6
Laminar
Open-source all-in-one platform for engineering AI products
.... Tracing of text and image models is supported, audio models are coming soon. You can set up LLM-as-a-judge or Python script evaluators to run on each received span. Evaluators label spans, which is more scalable than human labeling, and especially helpful for smaller teams. Laminar lets you go beyond a single prompt. You can build and host complex chains, including mixtures of agents or self-reflecting LLM pipelines. -
7
D-Tale
Visualizer for pandas data structures
D-Tale is the combination of a Flask backend and a React front-end to bring you an easy way to view & analyze Pandas data structures. It integrates seamlessly with ipython notebooks & python/ipython terminals. Currently, this tool supports such Pandas objects as DataFrame, Series, MultiIndex, DatetimeIndex & RangeIndex. D-Tale was the product of a SAS to Python conversion. What was originally a perl script wrapper on top of SAS's insight function is now a lightweight web client on top of Pandas... -
8
Pyright
Static type checker for Python
Pyright is a fast type checker meant for large Python source bases. It can run in a “watch” mode and performs fast incremental updates when files are modified. Pyright supports configuration files that provide granular control over settings. Different “execution environments” can be associated with subdirectories within a source base. Each environment can specify different module search paths, python language versions, and platform targets. Type inference for function return values, instance... -
9
GPT-Code UI
An open source implementation of OpenAI's ChatGPT Code interpreter
An open source implementation of OpenAI's ChatGPT Code interpreter. Simply ask the OpenAI model to do something and it will generate & execute the code for you. You can put a .env in the working directory to load the OPENAI_API_KEY environment variable. For Azure OpenAI Services, there are also other configurable variables like deployment name. See .env.azure-example for more information. Note that model selection on the UI is currently not supported for Azure OpenAI Services. -
Sales CRM and Pipeline Management Software | PipedrivePipedrive’s simple interface empowers salespeople to streamline workflows and unite sales tasks in one workspace. Unlock instant sales insights with Pipedrive’s visual sales pipeline and fine-tune your strategy with robust reporting features and a personalized AI Sales Assistant.
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10
Hydrogen
Run code interactively, inspect data, and plot
Hydrogen is an interactive coding environment that supports Python, R, JavaScript and other Jupyter kernels. Hydrogen was inspired by Bret Victor's ideas about the power of instantaneous feedback and the design of Light Table. Running code inline and in real-time is a more natural way to develop. By bringing the interactive style of Light Table to the rock-solid usability of Atom, Hydrogen makes it easy to write code the way you want to. You also may be interested in our latest project... -
11
Shinkai: Local AI Agents
Shinkai allows you to create advanced AI (local) agents effortlessly
... payments and transactions - Flexible AI Models - Choose from cloud models (GPT-4, Claude) or run locally - Universal Compatibility - Works with Model Context Protocol (MCP) for cross-platform integration - Local Security - Crypto keys and computations stay on your device Shinkai transforms AI from single-task tools into collaborative, autonomous systems that can operate in decentralized networks while maintaining privacy and security. -
12
TensorFlow.js models
Pretrained models for TensorFlow.js
... run the unit tests for any of the models by running "yarn test" inside a directory. Use off-the-shelf JavaScript models or convert Python TensorFlow models to run in the browser or under Node.js. Build and train models directly in JavaScript using flexible and intuitive APIs. Develop ML models in JavaScript, and use ML directly in the browser or in Node.js. -
13
0x Monorepo
0x protocol monorepo - includes our smart contracts
...-maintained packages. All packages maintained with this monorepo are listed. You will also need to have Python 3 installed, in order to build and run the tests of abi-gen's command-line interface, which is integrated with the yarn build, yarn test, and yarn lint commands described below. More specifically, your local pip should resolve to the Python 3 version of pip, not a Python 2.x version. -
14
Oyente
An Analysis Tool for Smart Contracts
... used for the paper. Benchmarks are not for direct comparison. To run the benchmarks, it is best to use the docker container as it includes the blockchain snapshot necessary. In the container, run batch_run.py after activating the virtualenv. Results are in results.json once the benchmark completes.
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