Search Results for "python-bibtex" - Page 68

Showing 19119 open source projects for "python-bibtex"

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  • 1
    Cog

    Cog

    Package and deploy machine learning models using Docker 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. Cog automatically generates a RESTful HTTP API for running predictions, enabling models to be accessed programmatically through a built-in prediction server.
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  • 2
    FuzzyAI Fuzzer

    FuzzyAI Fuzzer

    A powerful tool for automated LLM fuzzing

    FuzzyAI is an open-source fuzzing framework designed to test the security and reliability of large language model applications. The tool automates the process of generating adversarial prompts and input variations to identify vulnerabilities such as jailbreaks, prompt injections, or unsafe model responses. It allows developers and security researchers to systematically evaluate the robustness of LLM-based systems by simulating a wide range of malicious or unexpected inputs. The framework can...
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  • 3
    TokenCost

    TokenCost

    Easy token price estimates for 400+ LLMs. TokenOps

    TokenCost is an open-source developer utility designed to estimate the cost of using large language model APIs by calculating token usage and translating it into real monetary values. The tool focuses on helping developers understand how much their prompts and generated completions cost when interacting with commercial AI models. It works by counting tokens in prompts and responses before or after sending requests and then applying pricing information associated with different models. This...
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  • 4
    Integuru v0

    Integuru v0

    The first AI agent that builds permissionless integrations

    Integuru is an open-source AI agent designed to automatically create integrations between software platforms by reverse-engineering their internal APIs. Instead of relying on official developer documentation or publicly available APIs, the system analyzes network traffic generated by user interactions within a web application. Developers capture browser requests and authentication data, which the agent then uses to infer the structure of the platform’s internal API endpoints. Based on this...
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  • 5
    llmware

    llmware

    Unified framework for building enterprise RAG pipelines

    llmware is an open source framework designed to simplify the creation of enterprise-grade applications powered by large language models. The platform focuses on building secure and private AI workflows that can run locally on laptops, edge devices, or self-hosted servers without relying exclusively on cloud APIs. It provides a unified interface for constructing retrieval-augmented generation pipelines, agent workflows, and document intelligence applications. One of the framework’s defining...
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  • 6
    Vanna 2.0

    Vanna 2.0

    Chat with your SQL database

    Vanna is an open-source Python framework that enables natural language interaction with databases by converting user questions into executable SQL queries using large language models. The framework uses a retrieval-augmented generation architecture that learns from database schemas, documentation, and past query examples to generate accurate queries tailored to a specific dataset.
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  • 7
    BettaFish

    BettaFish

    Public opinion analysis system

    BettaFish is an open-source, multi-agent public opinion analysis system built to automate the collection, deep analysis, and reporting of social media data at scale through conversational queries. It uses a modular architecture of specialized agents that collaborate to crawl mainstream platforms, extract multimodal content like text and short video, and synthesize insights through both statistical and large language model techniques. With a design that lets users pose questions in natural...
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  • 8
    ZAPI

    ZAPI

    ZAPI by Adopt AI is an open-source Python library

    ZAPI is a developer-centric API framework that streamlines building, testing, and deploying APIs with strong type safety and minimal boilerplate, helping teams deliver backend services faster with fewer errors. It emphasizes a declarative router and schema model that uses types to define request and response formats, providing clear contracts for frontend and backend teams while automatically generating documentation. Zapi abstracts many repetitive tasks such as validation, authentication...
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  • 9
    TimeTracker

    TimeTracker

    Open-source and free to self-host

    TimeTracker by DRYTRIX is a comprehensive self-hosted time tracking and project management application that helps individuals, teams, and small businesses take control of their productivity and billing. Built on a modern web stack (Python/Flask backend with a responsive frontend), TimeTracker enables users to track hours, manage projects and clients, visualize data with interactive charts, and even generate professional invoices directly from tracked time. It embraces privacy and flexibility by running entirely on your own servers, ensuring sensitive business data stays under your control, and supports real-time timer persistence via WebSockets so timers continue even if the browser is closed. ...
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  • 10
    MiniMax-MCP

    MiniMax-MCP

    Official MiniMax Model Context Protocol (MCP) server

    ...It acts as a bridge between tools like Claude Desktop, Cursor, Windsurf, OpenAI Agents, and the MiniMax platform, exposing capabilities such as text-to-speech, voice cloning, image generation, text-to-image, video generation, image-to-video, text-to-video, and music generation. The server is written in Python and distributed under the MIT license, with a pyproject.toml and uv-based workflow that makes installation and execution reproducible. Configuration is handled through JSON files that tell MCP clients how to launch the server (typically via uvx minimax-mcp) and which environment variables to use for the API key, host, and output directory. ...
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  • 11
    DevOps Exercises

    DevOps Exercises

    Linux, Jenkins, AWS, SRE, Prometheus, Docker, Python, Ansible, Git

    DevOps Exercises is a massive, community-maintained collection of questions, tasks, and mini-challenges that cover the breadth of modern DevOps and platform engineering. It spans Linux, networking, Docker, Kubernetes, CI/CD, monitoring, cloud providers, security, and even soft skills and troubleshooting. The idea is to give candidates and teams a realistic practice ground for interviews, certifications, and day-to-day operational work. Because it’s structured as Q&A and exercises, you can go...
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  • 12
    Behaviour Suite Reinforcement Learning

    Behaviour Suite Reinforcement Learning

    bsuite is a collection of carefully-designed experiments

    bsuite is a research framework developed by Google DeepMind that provides a comprehensive collection of experiments for evaluating the core capabilities of reinforcement learning (RL) agents. Its main goal is to identify, measure, and analyze fundamental aspects of learning efficiency and generalization in RL algorithms. The library enables researchers to benchmark their agents on standardized tasks, facilitating reproducible and transparent comparisons across different approaches. Each...
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  • 13
    DualPipe

    DualPipe

    A bidirectional pipeline parallelism algorithm

    DualPipe is a bidirectional pipeline parallelism algorithm open-sourced by DeepSeek, introduced in their DeepSeek-V3 technical framework. The main goal of DualPipe is to maximize overlap between computation and communication phases during distributed training, thus reducing idle GPU time (i.e. “pipeline bubbles”) and improving cluster efficiency. Traditional pipeline parallelism methods (e.g. 1F1B or staggered pipelining) leave gaps because forward and backward phases can’t fully overlap...
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  • 14
    Superduper

    Superduper

    Superduper: Integrate AI models and machine learning workflows

    Superduper is a Python-based framework for building end-2-end AI-data workflows and applications on your own data, integrating with major databases. It supports the latest technologies and techniques, including LLMs, vector-search, RAG, and multimodality as well as classical AI and ML paradigms. Developers may leverage Superduper by building compositional and declarative objects that out-source the details of deployment, orchestration versioning, and more to the Superduper engine. ...
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  • 15
    OSXPhotos

    OSXPhotos

    Python app to work with pictures and associated metadata

    OSXPhotos provides the ability to interact with and query Apple's Photos.app library on macOS and Linux. You can query the Photos library database — for example, file name, file path, and metadata such as keywords/tags, persons/faces, albums, etc. You can also easily export both the original and edited photos. OSXPhotos also works with iPhoto libraries though some features are available only for Photos. Limited support is also provided for exporting photos and metadata from iPhoto libraries....
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  • 16
    Core ML Tools

    Core ML Tools

    Core ML tools contain supporting tools for Core ML model conversion

    Use Core ML Tools (coremltools) to convert machine learning models from third-party libraries to the Core ML format. This Python package contains the supporting tools for converting models from training libraries. Core ML is an Apple framework to integrate machine learning models into your app. Core ML provides a unified representation for all models. Your app uses Core ML APIs and user data to make predictions, and to fine-tune models, all on the user’s device.
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  • 17
    AutoMLOps

    AutoMLOps

    Build MLOps Pipelines in Minutes

    AutoMLOps is a service that generates, provisions, and deploys CI/CD integrated MLOps pipelines, bridging the gap between Data Science and DevOps. AutoMLOps provides a repeatable process that dramatically reduces the time required to build MLOps pipelines. The service generates a containerized MLOps codebase, provides infrastructure-as-code to provision and maintain the underlying MLOps infra, and provides deployment functionalities to trigger and run MLOps pipelines. AutoMLOps gives...
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  • 18
    AtomAI

    AtomAI

    Deep and Machine Learning for Microscopy

    AtomAI is a Pytorch-based package for deep and machine-learning analysis of microscopy data that doesn't require any advanced knowledge of Python or machine learning. The intended audience is domain scientists with a basic understanding of how to use NumPy and Matplotlib. It was developed by Maxim Ziatdinov at Oak Ridge National Lab. The purpose of the AtomAI is to provide an environment that bridges the instrument-specific libraries and general physical analysis by enabling the seamless deployment of machine learning algorithms including deep convolutional neural networks, invariant variational autoencoders, and decomposition/unmixing techniques for image and hyperspectral data analysis. ...
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  • 19
    GemGIS

    GemGIS

    Spatial data processing for geomodeling

    GemGIS is a Python-based, open-source geographic information processing library. It is capable of preprocessing spatial data such as vector data (shape files, geojson files, geopackages,…), raster data (tif, png,…), data obtained from online services (WCS, WMS, WFS) or XML/KML files (soon). Preprocessed data can be stored in a dedicated Data Class to be passed to the geomodeling package GemPy in order to accelerate the model-building process.
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  • 20
    Changelog CI

    Changelog CI

    Changelog CI is a GitHub Action that enables a project

    Changelog CI is a GitHub Action that enables a project to automatically generate changelogs. Changelog CI can be triggered on pull_request, workflow_dispatch, and any other events that can provide the required inputs. Changelog CI uses python and GitHub API to generate a changelog for a repository. First, it tries to get the latest release from the repository (If available). Then, it checks all the pull requests/commits merged after the last release using the GitHub API. After that, it parses the data and generates the changelog. It is able to use Markdown or reStructuredText to generate a Changelog. ...
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  • 21
    HASS Configurator

    HASS Configurator

    Configuration UI for Home Assistant

    ...YAML files (the default language for Home Assistant configuration files) will be automatically checked for syntax errors while editing. The configurator fetches JavaScript libraries, CSS and fonts from CDNs. Hence it does NOT work when your client device is offline. And it is only available for Python 3.
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  • 22
    QuTiP

    QuTiP

    QuTiP: Quantum Toolbox in Python

    QuTiP is open-source software for simulating the dynamics of open quantum systems. The QuTiP library depends on the excellent Numpy, Scipy, and Cython numerical packages. In addition, graphical output is provided by Matplotlib. QuTiP aims to provide user-friendly and efficient numerical simulations of a wide variety of Hamiltonians, including those with arbitrary time-dependence, commonly found in a wide range of physics applications such as quantum optics, trapped ions, superconducting...
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  • 23
    Mosec

    Mosec

    A high-performance ML model serving framework, offers dynamic batching

    Mosec is a high-performance and flexible model-serving framework for building ML model-enabled backend and microservices. It bridges the gap between any machine learning models you just trained and the efficient online service API.
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  • 24
    Population Shift Monitoring

    Population Shift Monitoring

    Monitor the stability of a Pandas or Spark dataframe

    popmon is a package that allows one to check the stability of a dataset. popmon works with both pandas and spark datasets. popmon creates histograms of features binned in time-slices, and compares the stability of the profiles and distributions of those histograms using statistical tests, both over time and with respect to a reference. It works with numerical, ordinal, categorical features, and the histograms can be higher-dimensional, e.g. it can also track correlations between any two...
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  • 25
    BertViz

    BertViz

    BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)

    BertViz is an interactive tool for visualizing attention in Transformer language models such as BERT, GPT2, or T5. It can be run inside a Jupyter or Colab notebook through a simple Python API that supports most Huggingface models. BertViz extends the Tensor2Tensor visualization tool by Llion Jones, providing multiple views that each offer a unique lens into the attention mechanism. The head view visualizes attention for one or more attention heads in the same layer. It is based on the excellent Tensor2Tensor visualization tool. ...
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