Search Results for "fetch"
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Showing 13 open source projects for "fetch"
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Auth0 B2B Essentials: SSO, MFA, and RBAC Built InAuth0's B2B Essentials plan gives you everything you need to ship secure multi-tenant apps. Unlimited orgs, enterprise SSO, RBAC, audit log streaming, and higher auth and API limits included. Add on M2M tokens, enterprise MFA, or additional SSO connections as you scale.
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Gemini 3 and 200+ AI Models on One PlatformBuild, govern, and optimize agents and models with Gemini Enterprise Agent Platform.
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Context Hub
Makes coding agents get smarter with every task
...It gives agents versioned, language-specific reference material instead of forcing them to rely on noisy web searches or stale model memory. The project includes a CLI called chub that agents can use to search for available docs, fetch specific API guidance, and request only the files they need. It also supports local annotations, allowing an agent to remember project-specific notes, pitfalls, or workarounds across future sessions. Feedback can be sent back to maintainers so shared documentation improves over time. Context Hub is especially useful for teams that use AI coding assistants and want more reliable API usage, fewer hallucinated calls, and a transparent source of agent-readable context. -
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opensrc
Fetch source code for npm packages
...When large language models generate code, they often rely only on type definitions or documentation, which can limit their understanding of how a library actually behaves. OpenSrc addresses this limitation by allowing agents to fetch the underlying source code of dependencies and analyze their implementation directly. This gives AI coding assistants richer context about functions, internal logic, and architectural patterns used within external packages. The tool is designed to integrate into AI-driven developer workflows where coding agents explore repositories, inspect dependencies, and reason about how to use libraries correctly. -
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Groq TypeScript / Node.s
The official Node.js / Typescript library for the Groq API
...It exports strongly-typed interfaces for models, chat completions, file uploads (e.g. for audio transcription), and other endpoints, allowing for better type safety and developer experience when using Groq from TypeScript. The library also supports passing different input types (file streams, blobs, fetch responses) for media-related endpoints, making it flexible for diverse environments (backend, browser, serverless). With this SDK, developers can call Groq’s models, transcribe audio, perform file uploads — all with minimal boilerplate — which streamlines creation of AI-enabled applications in the JavaScript/TypeScript ecosystem. -
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Open Vibe
Open Vibe turns Claude Code into a SaaS-building assistant
...The workflow starts with setup instructions that install Node.js, install the Wasp CLI, and verify the local environment. After creating a new Wasp app, the user opens an AI coding agent inside the project and lets it fetch course module instructions. The agent then works as both tutor and pair programmer, explaining the system while helping the user build features from plain-language requests. Progress is tracked through JSON files written into the project, making the learning path structured while still letting the user build their own app idea. -
Forever Free Full-Stack Observability | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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BrowserOS
Agentic browser; privacy-first alternative to ChatGPT Atlas
...The interface remains familiar to users of Chrome (including support for Chrome extensions), but adds new capabilities: the browser can automate tasks for you, help you research by extracting and summarizing content, and enable agent-based workflows (e.g., “go fetch this info,” “fill this form,” “monitor this site”). The project is community-driven and entirely open source under the AGPL-3.0 license, which means you can inspect, fork, and contribute to the codebase. -
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Dexter
An autonomous agent for deep financial research
Dexter is an autonomous agent tailored for deep financial research: you pose complex financial questions (for example, about a company’s revenue growth or financial ratios) and Dexter breaks them down into structured research tasks, fetches relevant real-time data (e.g. income statements, cash flows), performs analysis, and returns data-backed answers. It uses a multi-agent architecture with components such as a planning agent (to decompose queries), an action agent (to run tasks & fetch data), and self-validation mechanisms: after getting results, Dexter checks its own outputs and refines them until it is confident about its answer. This means it's more than a simple script — it’s a research assistant that loops through analysis steps until convergence. -
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LangChain
⚡ Building applications with LLMs through composability ⚡
Large language models (LLMs) are emerging as a transformative technology, enabling developers to build applications that they previously could not. But using these LLMs in isolation is often not enough to create a truly powerful app - the real power comes when you can combine them with other sources of computation or knowledge. This library is aimed at assisting in the development of those types of applications. -
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Bootstrap Your Own Latent (BYOL)
Usable Implementation of "Bootstrap Your Own Latent" self-supervised
Practical implementation of an astoundingly simple method for self-supervised learning that achieves a new state-of-the-art (surpassing SimCLR) without contrastive learning and having to designate negative pairs. This repository offers a module that one can easily wrap any image-based neural network (residual network, discriminator, policy network) to immediately start benefitting from unlabelled image data. There is now new evidence that batch normalization is key to making this technique... -
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FinRobot
An Open-Source AI Agent Platform for Financial Analysis using LLMs
FinRobot is an open-source AI framework focused on automating financial data workflows by combining data ingestion, feature engineering, model training, and automated decision-making pipelines tailored for quantitative finance applications. It provides developers and quants with structured modules to fetch market data, process time series, generate technical indicators, and construct features appropriate for machine learning models, while also supporting backtesting and evaluation metrics to measure strategy performance. Built with modularity in mind, FinRobot allows users to plug in custom models — from classical algorithms to deep learning architectures — and orchestrate components in pipelines that can run reproducibly across experiments. ... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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ArXiv MCP Server
A Model Context Protocol server for searching and analyzing arXiv
arxiv-mcp-server bridges AI assistants and the arXiv repository through a clean MCP interface, enabling search, metadata retrieval, and content access without bespoke scraping. With simple tools like “search” and “fetch,” an agent can find papers, pull abstracts, and download PDFs for downstream summarization or analysis. The project includes packaging and CI to publish to PyPI, plus tests and linting for reliability. Issue threads show feature requests such as extracting embedded LaTeX and improving markdown conversion, reflecting active community use in research flows. ... -
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LLaMA
Inference code for Llama models
...It provides utilities to load pre-trained LLaMA model weights, run inference (text generation, chat, completions), and work with tokenizers. Tokenizer utilities, download scripts, shell helpers to fetch model weights with correct licensing/permissions. Includes example scripts for chat completions and text completions to show how to call the models in code. This repo is a core piece of the Llama model infrastructure, used by researchers and developers to run LLaMA models locally or in their infrastructure. It is meant for inference (not training from scratch) and connects with aspects like model cards, responsible use, licensing, etc. -
12
MTProto
Full-native go implementation of Telegram API
Full-native implementation of MTProto protocol on Golang. All code, from sending requests to encryption serialization is written in pure Golang. You don't need to fetch any additional dependencies. -
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CC-Net
Tools to download and cleanup Common Crawl data
cc_net provides tools to download, segment, clean, and filter Common Crawl to build large-scale text corpora, including monolingual datasets and the multilingual CC-100 collection introduced in the associated paper. It includes pipelines to fetch snapshots, extract text, de-duplicate, identify language, and apply quality filtering based on heuristics and language models. The outputs are intended for pretraining language models and for creating standardized corpora that can be reproduced or updated with new crawls. The repository documents practical concerns like HTTP failures, snapshot differences, and stats JSONs, reflecting community use across many languages. ...
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