Showing 12 open source projects for "flask"

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  • 1
    Ditto

    Ditto

    The simplest self-building coding agent

    ...Its modular structure separates generated Flask components into cleaner directories for routes, templates, and static files. It is best suited for prototyping, learning, and exploring how natural-language app generation can work in a small local project.
    Downloads: 2 This Week
    Last Update:
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  • 2
    supabase-py

    supabase-py

    Python Client for Supabase. Query Postgres from Flask, Django

    Python Client for Supabase. Query Postgres from Flask, Django, FastAPI. Python user authentication, security policies, edge functions, file storage, and realtime data streaming. Good first issue.
    Downloads: 0 This Week
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  • 3
    NErlNet

    NErlNet

    Nerlnet is a framework for research and development

    NErlNet is a research-grade framework for distributed machine learning over IoT and edge devices. Built with Erlang (Cowboy HTTP), OpenNN, and Python (Flask), it enables simulation of clusters on a single machine or real deployment across heterogeneous devices.
    Downloads: 0 This Week
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  • 4
    python-whatsapp-bot

    python-whatsapp-bot

    Build AI WhatsApp Bots with Pure Python

    python-whatsapp-bot is an open-source framework that demonstrates how to build AI-powered WhatsApp bots using pure Python and the official WhatsApp Cloud API. The project provides a practical implementation of a messaging automation system using the Flask web framework to handle webhook events and process incoming messages in real time. Developers can configure the bot to receive user messages through the WhatsApp API, route them through application logic, and generate automated responses powered by AI services such as large language models. The repository includes example scripts and project structures that illustrate how to integrate OpenAI or similar AI models into the bot workflow, enabling conversational agents capable of answering questions or performing automated tasks.
    Downloads: 11 This Week
    Last Update:
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    OpenAI Quickstart Python

    OpenAI Quickstart Python

    Python example app from the OpenAI API quickstart tutorial

    ...Each example is designed to be easily runnable with minimal setup—requiring only Python, a virtual environment, and an API key. The repository also includes environment setup guides and example scripts, such as a simple Flask web app for chat interactions, allowing developers to test OpenAI API integrations locally. Overall, openai-quickstart-python serves as an essential starting point for developers looking to prototype and experiment with OpenAI-powered apps.
    Downloads: 3 This Week
    Last Update:
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  • 6
    TF2DeepFloorplan

    TF2DeepFloorplan

    TF2 Deep FloorPlan Recognition using a Multi-task Network

    TF2 Deep FloorPlan Recognition using a Multi-task Network with Room-boundary-Guided Attention. Enable tensorboard, quantization, flask, tflite, docker, github actions and google colab. This repo contains a basic procedure to train and deploy the DNN model suggested by the paper 'Deep Floor Plan Recognition using a Multi-task Network with Room-boundary-Guided Attention'. It rewrites the original codes from zlzeng/DeepFloorplan into newer versions of Tensorflow and Python.
    Downloads: 1 This Week
    Last Update:
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  • 7
    Nhom10_NhanDienKhuonMat_

    Nhom10_NhanDienKhuonMat_

    Face Recognition web app built on Python using Flask.

    Face Recognition web app built on Python using Flask. Students' final project.
    Downloads: 0 This Week
    Last Update:
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  • 8
    Riffusion

    Riffusion

    Real-time music generation using stable diffusion techniques AI

    ...It includes both developer-oriented tools and user-facing components such as a command-line interface and an interactive Streamlit application for experimentation. Additionally, it can run as a Flask server to expose model inference through an API, enabling integration with other applications or services.
    Downloads: 0 This Week
    Last Update:
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  • 9
    BudgetML

    BudgetML

    Deploy a ML inference service on a budget in 10 lines of code

    Deploy a ML inference service on a budget in less than 10 lines of code. BudgetML is perfect for practitioners who would like to quickly deploy their models to an endpoint, but not waste a lot of time, money, and effort trying to figure out how to do this end-to-end. We built BudgetML because it's hard to find a simple way to get a model in production fast and cheaply. Deploying from scratch involves learning too many different concepts like SSL certificate generation, Docker, REST,...
    Downloads: 0 This Week
    Last Update:
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  • 10
    Text2Video

    Text2Video

    Software tool that converts text to video for more engaging experience

    ...I plan to further work on the project targeting young college students who are aged between 18 to 23 because they tend to prefer learning through videos over books based on the survey I found. The technologies I used for the project are HTML, CSS, Javascript, Node.js, CCapture.js, ffmpegserver.js, Amazon Polly, Python, Flask, gevent, spaCy, and Pixabay API.
    Downloads: 1 This Week
    Last Update:
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  • 11
    commit-autosuggestions

    commit-autosuggestions

    A tool that AI automatically recommends commit messages

    ...However, most code changes are not made only by add of the code, and some parts of the code are deleted. We plan to slowly conquer languages that are not currently supported. To run this project, you need a flask-based inference server (GPU) and a client (commit module). If you don't have a GPU, don't worry, you can use it through Google Colab.
    Downloads: 0 This Week
    Last Update:
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  • 12

    Face Recognition

    World's simplest facial recognition api for Python & the command line

    Face Recognition is the world's simplest face recognition library. It allows you to recognize and manipulate faces from Python or from the command line using dlib's (a C++ toolkit containing machine learning algorithms and tools) state-of-the-art face recognition built with deep learning. Face Recognition is highly accurate and is able to do a number of things. It can find faces in pictures, manipulate facial features in pictures, identify faces in pictures, and do face recognition on a...
    Downloads: 2 This Week
    Last Update:
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