Search Results for "oracle-apex-workflow"
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Showing 73 open source projects for "oracle-apex-workflow"
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Deploy Red Hat Ansible Automation Platform on Microsoft Azure for a strategic automation solution that allows you to orchestrate, govern and operationalize your Azure environment.
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It protects your internal resources such as behind-the-firewall applications, teams, and devices.
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Zed
Code editor from the creators of Atom and Tree-sitter
Zed is a next-generation code editor designed for high-performance collaboration with humans and AI. Written from scratch in Rust to efficiently leverage multiple CPU cores and your GPU. Integrate upcoming LLMs into your workflow to generate, transform, and analyze code. Chat with teammates, write notes together, and share your screen and project. Multibuffers compose excerpts from across the codebase in one editable surface. Evaluate code inline via Jupyter runtimes and collaboratively edit... -
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Gradio
Create UIs for your machine learning model in Python in 3 minutes
... them interact with the model on your computer remotely from their own devices. Once you've created an interface, you can permanently host it on Hugging Face. Hugging Face Spaces will host the interface on its servers and provide you with a link you can share. One of the best ways to share your machine learning model, API, or data science workflow with others is to create an interactive demo that allows your users or colleagues to try out the demo in their browsers. -
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RAGFlow
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding. It offers a streamlined RAG workflow for businesses of any scale, combining LLM (Large Language Models) to provide truthful question-answering capabilities, backed by well-founded citations from various complex formatted data. -
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Raster Vision
Open source framework for deep learning satellite and aerial imagery
Raster Vision is an open source framework for Python developers building computer vision models on satellite, aerial, and other large imagery sets (including oblique drone imagery). There is built-in support for chip classification, object detection, and semantic segmentation using PyTorch. Raster Vision allows engineers to quickly and repeatably configure pipelines that go through core components of a machine learning workflow: analyzing training data, creating training chips, training models... -
As your users rely more and more on Cloud and Internet-based technologies, reliable internet connectivity becomes more and more important to your business. With Bigleaf’s proven SD-WAN architecture, groundbreaking AI, and DDoS attack mitigation, you can finally deliver the reliable internet connectivity your business needs without the limitations of traditional networking platforms. Bigleaf’s Cloud Access Network and plug-and-play router allow for limitless control to and from anywhere your traffic needs to go. Bigleaf’s self-driving AI automatically identifies and adapts to any changing circuit conditions and traffic needs—addressing issues before they impact your users. Bigleaf puts you in the driver’s seat of every complaint and support call with full-path traffic and network performance data, delivered as actionable insights, reports, and alerts.
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website-to-gif
Turn your website into a GIF
This Github Action automatically creates an animated GIF or WebP from a given web page to display on your project README (or anywhere else). In your GitHub repo, create a workflow file or extend an existing one. You have to also include a step to checkout and commit to the repo. You can use the following example gif.yml. Make sure to modify the url value and add any other input you want to use. WebP rendering will take a lot of time to benefit from lossless quality and file size optimization. -
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Unstructured.IO
Open source libraries and APIs to build custom preprocessing pipelines
The unstructured library provides open-source components for ingesting and pre-processing images and text documents, such as PDFs, HTML, Word docs, and many more. The use cases of unstructured revolve around streamlining and optimizing the data processing workflow for LLMs. unstructured modular bricks and connectors form a cohesive system that simplifies data ingestion and pre-processing, making it adaptable to different platforms and is efficient in transforming unstructured data... -
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AutoGen
An Open-Source Programming Framework for Agentic AI
AutoGen is an open-source programming framework for building AI agents and facilitating cooperation among multiple agents to solve tasks. AutoGen aims to provide an easy-to-use and flexible framework for accelerating development and research on agentic AI, like PyTorch for Deep Learning. It offers features such as agents that can converse with other agents, LLM and tool use support, autonomous and human-in-the-loop workflows, and multi-agent conversation patterns. AutoGen provides... -
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Diffgram
Training data (data labeling, annotation, workflow) for all data types
From ingesting data to exploring it, annotating it, and managing workflows. Diffgram is a single application that will improve your data labeling and bring all aspects of training data under a single roof. Diffgram is world’s first truly open source training data platform that focuses on giving its users an unlimited experience. This is aimed to reduce your data labeling bills and increase your Training Data Quality. Training Data is the art of supervising machines through data. This... -
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Codiga VS Code
VS Code plugin that suggests code blocks as you type and check
VS Code plugin that suggests code blocks as you type and check for errors. Works for JavaScript, TypeScript, Python, Java, Scala, Ruby, PHP, Apex, Docker. -
Our robust pre-built connectors and our no-code, drag-and-drop interface makes it easy and fast to automatically sync vendors, invoices, and invoice payment data between Tipalti and your ERP or accounting software.
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promptfoo
Evaluate and compare LLM outputs, catch regressions, improve prompts
Ensure high-quality LLM outputs with automatic evals. Use a representative sample of user inputs to reduce subjectivity when tuning prompts. Use built-in metrics, LLM-graded evals, or define your own custom metrics. Compare prompts and model outputs side-by-side, or integrate the library into your existing test/CI workflow. Use OpenAI, Anthropic, and open-source models like Llama and Vicuna, or integrate custom API providers for any LLM API. -
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Build production-grade data and ML workflows, hassle-free The infinitely scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks. Don’t let friction between development and production slow down the deployment of new data/ML workflows and cause an increase in production bugs. Flyte enables rapid experimentation with production-grade software. Debug in the cloud by iterating on the workflows locally to achieve tighter feedback loops. As your...
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ChatFred
Alfred workflow using ChatGPT, DALL·E 2 and other models for chatting
Alfred workflow using ChatGPT, DALL·E 2 and other models for chatting, image generation and more. Access ChatGPT, DALL·E 2, and other OpenAI models. Language models often give wrong information. Verify answers if they are important. Talk with ChatGPT via the cf keyword. Answers will show as Large Type. Alternatively, use the Universal Action, Fallback Search, or Hotkey. To generate text with InstructGPT models and see results in-line, use the cft keyword. ⤓ Install on the Alfred Gallery... -
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ClearML
Streamline your ML workflow
... and other workflows with ClearML powerful and versatile set of classes and methods. The ClearML Server storing experiment, model, and workflow data, and supports the Web UI experiment manager, and ML-Ops automation for reproducibility and tuning. It is available as a hosted service and open source for you to deploy your own ClearML Server. The ClearML Agent for ML-Ops orchestration, experiment and workflow reproducibility, and scalability. -
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Kubeflow pipelines
Machine Learning Pipelines for Kubeflow
Kubeflow is a machine learning (ML) toolkit that is dedicated to making deployments of ML workflows on Kubernetes simple, portable, and scalable. A pipeline is a description of an ML workflow, including all of the components in the workflow and how they combine in the form of a graph. The pipeline includes the definition of the inputs (parameters) required to run the pipeline and the inputs and outputs of each component. A pipeline component is a self-contained set of user code, packaged... -
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AutoMLPipeline.jl
Package that makes it trivial to create and evaluate machine learning
AutoMLPipeline (AMLP) is a package that makes it trivial to create complex ML pipeline structures using simple expressions. It leverages on the built-in macro programming features of Julia to symbolically process, and manipulate pipeline expressions and makes it easy to discover optimal structures for machine learning regression and classification. To illustrate, here is a pipeline expression and evaluation of a typical machine learning workflow that extracts numerical features (numf) for ica... -
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talos
Hyperparameter Optimization for TensorFlow, Keras and PyTorch
Talos radically changes the ordinary Keras, TensorFlow (tf.keras), and PyTorch workflow by fully automating hyperparameter tuning and model evaluation. Talos exposes Keras and TensorFlow (tf.keras) and PyTorch functionality entirely and there is no new syntax or templates to learn. Talos is made for data scientists and data engineers that want to remain in complete control of their TensorFlow (tf.keras) and PyTorch models, but are tired of mindless parameter hopping and confusing optimization... -
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lightning AI
The most intuitive, flexible, way for researchers to build models
Build in days not months with the most intuitive, flexible framework for building models and Lightning Apps (ie: ML workflow templates) which "glue" together your favorite ML lifecycle tools. Build models and build/publish end-to-end ML workflows that "glue" your favorite tools together. Models are “easy”, the “glue” work is hard. Lightning Apps are community-built templates that stitch together your favorite ML lifecycle tools into cohesive ML workflows that can run on your laptop or any... -
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Prompt flow
Build high-quality LLM apps
Prompt flow is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, and evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality. -
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Kanaries RATH
Next generation of automated data exploratory analysis visualization
RATH is not just an open-source alternative to Data Analysis and Visualization tools such as Tableau, but it automates your Exploratory Data Analysis workflow with an Augmented Analytic engine by discovering patterns, insights, causals and presents those insights with powerful auto-generated multi-dimensional data visualization. -
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Finetuner
Task-oriented finetuning for better embeddings on neural search
Fine-tuning is an effective way to improve performance on neural search tasks. However, setting up and performing fine-tuning can be very time-consuming and resource-intensive. Jina AI’s Finetuner makes fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure in the cloud. With Finetuner, you can easily enhance the performance of pre-trained models, making them production-ready without extensive labeling or expensive hardware. Create high... -
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Arthur Bench
Bench is a tool for evaluating LLMs for production use cases
Bench is a tool for evaluating LLMs for production use cases. Whether you are comparing different LLMs, considering different prompts, or testing generation hyperparameters like temperature and # tokens, Bench provides one touch point for all your LLM performance evaluation. -
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AutoGroq
Revolutionizes the way users interact with Autogen
... of problems, AutoGroq uses the syntax of the users' needs as the basis for constructing the perfect AI team. It's how we wished Autogen worked from the very beginning. With AutoGroq, a fully configured workflow, team of agents, and skillset are just a few clicks and a couple of minutes away, without any programming necessary. Our rapidly growing user base of nearly 8000 developers is a testament to the power and effectiveness of AutoGroq. -
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Spark NLP
State of the Art Natural Language Processing
... components, estimators and transformers. The estimators have a method that secures and trains a piece of data to such an application. The transformer is generally the result of a fitting process and applies changes to the target dataset. These components have been embedded to be applicable to Spark NLP. Pipelines are a mechanism for combining multiple estimators and transformers in a single workflow. They allow multiple chained transformations along a machine-learning task. -
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FEDML Open Source
The unified and scalable ML library for large-scale training
... interconnected AI infrastructure layers: user-friendly MLOps, a well-managed scheduler, and high-performance ML libraries for running any AI jobs across GPU Clouds. A typical workflow is shown in the figure above. When a developer wants to run a pre-built job in Studio or Job Store, TensorOperaLaunch swiftly pairs AI jobs with the most economical GPU resources, and auto-provisions, and effortlessly runs the job, eliminating complex environment setup and management. -
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Featuretools
An open source python library for automated feature engineering
An open source Python framework for automated feature engineering. Featuretools automatically creates features from temporal and relational datasets. Featuretools uses DFS for automated feature engineering. You can combine your raw data with what you know about your data to build meaningful features for machine learning and predictive modeling. Featuretools provides APIs to ensure only valid data is used for calculations, keeping your feature vectors safe from common label leakage problems....