Search Results for "software design tools" - Page 2
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Showing 37 open source projects for "software design tools"
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NVIDIA Generative AI Examples
Generative AI reference workflows
NVIDIA GenerativeAIExamples is an open-source repository that provides practical reference implementations and example workflows for building generative AI applications using NVIDIA’s software ecosystem. The project is designed to help developers accelerate the development of AI applications by providing ready-to-run pipelines, notebooks, and tools that demonstrate how to integrate large language models into real-world systems. The repository includes examples covering topics such as retrieval-augmented generation pipelines, agent-based workflows, and multimodal AI applications that combine text, vision, and data processing. ... -
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E2B Desktop Sandbox
E2B Desktop Sandbox for LLMs. E2B Sandbox
...The platform provides isolated virtual machines where applications can be executed safely without affecting the host system. Each sandbox runs independently and can be configured with custom dependencies or tools required by an AI agent or automation workflow. The system allows developers to programmatically create and control these virtual desktops through SDKs available in languages such as Python and JavaScript. Within a sandbox, developers can launch applications like browsers, editors, or other software that an AI agent may need to interact with. ... -
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Magicoder
Empowering Code Generation with OSS-Instruct
Magicoder is an open-source family of large language models designed specifically for code generation and software development tasks. The project focuses on improving the quality and diversity of code generation by training models with a novel dataset construction approach known as OSS-Instruct. This technique uses open-source code repositories as a foundation for generating more realistic and diverse instruction datasets for training language models. By grounding training data in real... -
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Claude Code Skills & Plugins Hub
270+ Claude Code plugins with 739 agent skills
...These plugins cover a wide range of domains including DevOps automation, security testing, API debugging, infrastructure management, and AI workflow orchestration. The project also includes orchestration patterns and best practices that guide how multiple AI agents or tools can collaborate effectively in software development workflows. Developers can install plugins through a package-style plugin system and integrate them with their Claude Code environment using standardized commands. -
Error to trace to log to deploy. One click. No SSH.AppSignal links every error to the trace, the trace to the log, the log to the deploy that shipped it.
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chatd
Chat with your documents using local AI
...Unlike many document-chat tools that require manual installation of model servers, chatd packages the model runner with the application so that users can start interacting with documents immediately after launching the program. -
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Integuru v0
The first AI agent that builds permissionless integrations
...Based on this information, the system generates executable code that can replicate the original action programmatically. This approach allows developers to automate workflows and build integrations with services that do not provide official APIs or developer tools. The project is designed as a research platform for exploring AI-driven automation and integration generation. -
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Qwen2.5-Coder
Qwen2.5-Coder is the code version of Qwen2.5, the large language model
Qwen2.5-Coder, developed by QwenLM, is an advanced open-source code generation model designed for developers seeking powerful and diverse coding capabilities. It includes multiple model sizes—ranging from 0.5B to 32B parameters—providing solutions for a wide array of coding needs. The model supports over 92 programming languages and offers exceptional performance in generating code, debugging, and mathematical problem-solving. Qwen2.5-Coder, with its long context length of 128K tokens, is... -
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AIConfig
AIConfig is a config-based framework to build generative AI apps
...The configuration format is JSON-serializable and integrates with tools such as Python and Node SDKs, allowing the same configuration file to be used across multiple environments. -
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RAGxplorer
Open-source tool to visualise your RAG
...However, RAG systems can be complex because they involve multiple components such as embedding models, vector databases, and retrieval algorithms. RAGxplorer provides visual tools that allow developers to inspect how documents are embedded, retrieved, and used to answer queries. The software can load documents, generate embeddings, and project them into reduced vector spaces so that users can visually explore relationships between queries and retrieved documents. It also includes interactive interfaces that show how retrieval affects the final output of the language model. -
Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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DB-GPT-Hub
A repository that contains models, datasets, and fine-tuning
...The repository includes datasets and experiment configurations that allow researchers to train models on real database schemas and evaluate them using standardized benchmarks. Its design encourages experimentation with different large language models and fine-tuning techniques, including parameter-efficient training approaches. -
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towhee
Framework that is dedicated to making neural data processing
Towhee is an open-source machine-learning pipeline that helps you encode your unstructured data into embeddings. You can use our Python API to build a prototype of your pipeline and use Towhee to automatically optimize it for production-ready environments. From images to text to 3D molecular structures, Towhee supports data transformation for nearly 20 different unstructured data modalities. We provide end-to-end pipeline optimizations, covering everything from data decoding/encoding, to... -
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DomE
Implements a reference architecture for creating information systems
...All these features are generated from the domain model, which is, in turn, continuously evolved from interactions with the user or autonomously by the system itself. Thus, an alternative to the traditional software production processes is proposed, which involves several stages and different actors, sometimes demanding a lot of time and money without obtaining the expected result. With software engineering techniques, self-adaptive systems, and artificial intelligence, it is possible, the integration between design time and execution time.