Search Results for "multi language" - Page 5
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Showing 259 open source projects for "multi language"
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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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Devon
Open source AI pair programmer for coding, debugging, automation
Devon is an open source AI-powered pair programming tool designed to assist developers with software engineering tasks through natural language interaction. It operates as an agent-based system that can explore codebases, edit files, and execute development workflows with minimal manual intervention. Devon uses a client-server architecture with a Python backend and multiple user interfaces, including a terminal interface and an Electron-based desktop application. Devon integrates with... -
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LangGraph
Build resilient language agents as graphs
LangGraph is a library for building stateful, multi-actor applications with LLMs, used to create agent and multi-agent workflows. Compared to other LLM frameworks, it offers these core benefits: cycles, controllability, and persistence. LangGraph allows you to define flows that involve cycles, essential for most agentic architectures, differentiating it from DAG-based solutions. As a very low-level framework, it provides fine-grained control over both the flow and state of your application,... -
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Qwen-Image
Qwen-Image is a powerful image generation foundation model
Qwen-Image is a powerful 20-billion parameter foundation model designed for advanced image generation and precise editing, with a particular strength in complex text rendering across diverse languages, especially Chinese. Built on the MMDiT architecture, it achieves remarkable fidelity in integrating text seamlessly into images while preserving typographic details and layout coherence. The model excels not only in text rendering but also in a wide range of artistic styles, including... -
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Ditto
The simplest self-building coding agent
Ditto is a simple self-building coding agent that generates multi-file Flask applications from natural language descriptions. Users describe the app they want, and the system attempts to plan and create routes, templates, static assets, and supporting files. It uses an LLM loop with basic tools to automate part of the coding process. The project is intentionally lightweight and experimental, making it easier to understand than larger agentic coding platforms. -
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FLUX.2
Official inference repo for FLUX.2 models
FLUX.2 is a state-of-the-art open-weight image generation and editing model released by Black Forest Labs aimed at bridging the gap between research-grade capabilities and production-ready workflows. The model offers both text-to-image generation and powerful image editing, including editing of multiple reference images, with fidelity, consistency, and realism that push the limits of what open-source generative models have achieved. It supports high-resolution output (up to ~4 megapixels),... -
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Conversational Health Agents (CHA)
A Personalized LLM-powered Agent Frameworks
CHA, or Conversational Health Agents, is an open-source framework designed to build intelligent healthcare assistants powered by large language models and external data sources. The system enables developers to create personalized AI agents that can interact with users through natural language while performing multi-step reasoning and task execution. It integrates orchestration capabilities that allow the agent to gather information from APIs, knowledge bases, and external services in order to generate more accurate and context-aware responses. ... -
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Youtu-GraphRAG
Vertically Unified Agents for Graph Retrieval-Augmented Reasoning
Youtu-GraphRAG is a research framework developed by Tencent for performing complex reasoning using graph-based retrieval-augmented generation. The system combines knowledge graphs, retrieval mechanisms, and agent-based reasoning into a unified architecture designed to handle knowledge-intensive tasks. Instead of relying solely on text retrieval, the framework organizes information into structured graph schemas that represent entities, relationships, and attributes. These structures allow the... -
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DeepSearcher
Open Source Deep Research Alternative to Reason and Search
DeepSearcher is an open-source “deep research” style system that combines retrieval with evaluation and reasoning to answer complex questions using private or enterprise data. It is designed around the idea that high-quality answers require more than top-k retrieval, so it orchestrates multi-step search, evidence collection, and synthesis into a comprehensive response. The project integrates with vector databases (including Milvus and related options) so organizations can index internal... -
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FlexLLMGen
Running large language models on a single GPU
FlexLLMGen is an open-source inference engine designed to run large language models efficiently on limited hardware resources such as a single GPU. The system focuses on high-throughput generation workloads where large batches of text must be processed quickly, such as large-scale data extraction or document analysis tasks. Instead of requiring expensive multi-GPU systems, the framework uses techniques such as memory offloading, compression, and optimized batching to run large models on commodity hardware. ... -
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ControlFlow
Take control of your AI agents
ControlFlow is an open-source Python framework developed to help engineers design and orchestrate agentic workflows powered by large language models. The framework provides a structured approach for building AI systems by breaking complex tasks into smaller units called tasks that can be assigned to specialized AI agents. Developers can combine these tasks into flows that define how work is executed, enabling the creation of multi-step reasoning pipelines and collaborative agent systems. ... -
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II Agent
A new open-source framework to build and deploy intelligent agents
II-Agent is an open-source intelligent assistant framework designed to automate complex workflows across multiple domains using large language models and external tools. The platform allows users to interact with multiple AI models within a single environment while connecting those models to external services and knowledge sources. Through a unified interface, users can switch between models, access specialized tools, and execute tasks that require information retrieval, code execution, or... -
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Lingvo
Framework for building neural networks
...It has been used to implement state of the art architectures such as recurrent neural networks, Transformer models, variational autoencoder hybrids, and multi task systems. Lingvo includes reference models and configurations for domains like machine translation, automatic speech recognition, language modeling, image understanding, and 3D object detection. Centralized hyperparameter configuration files allow researchers to share exact experiment setups so others can retrain and compare results reliably. -
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NVIDIA Isaac GR00T
NVIDIA Isaac GR00T N1.5 is the world's first open foundation model
NVIDIA Isaac‑GR00T N1.5 is an open-source foundation model engineered for generalized humanoid robot reasoning and manipulation skills. It accepts multimodal inputs—such as language and images—and uses a diffusion transformer architecture built upon vision-language encoders, enabling adaptive robot behaviors across diverse environments. It is designed to be customizable via post-training with real or synthetic data. The vision-language model remains frozen during both pretraining and... -
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AstrBot
Agentic IM Chatbot infrastructure
AstrBot is an AI-driven chatbot framework designed to help developers build intelligent conversational agents that can be deployed across multiple messaging environments. The project focuses on modular architecture so users can extend the bot with plugins, custom skills, and integrations without modifying the core engine. It is built to support modern large language model workflows, enabling natural language understanding, automated responses, and task execution within chat contexts. AstrBot... -
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ASSERT
Requirement-driven evaluation harness for AI agents and LLM
ASSERT is a requirement-driven evaluation harness for AI agents and LLM applications. It turns natural-language specifications, policies, product requirements, and launch criteria into structured tests that can be reviewed, executed, scored, and improved. The pipeline derives behavior categories, generates single-turn and multi-turn test cases, runs them against a target system, and uses an LLM judge to score conversations against the stated policies. -
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TensorRT LLM
TensorRT LLM provides users with an easy-to-use Python API
TensorRT-LLM is an open-source high-performance inference library specifically designed to optimize and accelerate large language model deployment on NVIDIA GPUs. It provides a Python-based API built on top of PyTorch that allows developers to define, customize, and deploy LLMs efficiently across a variety of hardware configurations, from single GPUs to large multi-node clusters. The library focuses on maximizing throughput and minimizing latency through advanced techniques such as quantization, custom attention kernels, and optimized memory management strategies. ... -
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SkillForge
Ultimate meta-skill for generating best-in-class Claude Code skills
SkillForge is a systematic methodology and tooling framework for creating high-quality AI “skills” specifically optimized for Claude Code integrations, treating skill creation as an engineering discipline rather than an ad-hoc art form. It introduces a multi-phase architecture where every input or request is triaged intelligently, analyzed deeply through structured lenses, specified formally, synthesized with automated generation, and finally subjected to multi-agent review before consideration complete. The system includes tooling that routes natural language inputs to existing skills, augments them, or generates new ones using autonomous phases, enforcing quality, extensibility, security, and timelessness. ... -
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Stanza
Stanford NLP Python library for many human languages
Stanza is a collection of accurate and efficient tools for the linguistic analysis of many human languages. Starting from raw text to syntactic analysis and entity recognition, Stanza brings state-of-the-art NLP models to languages of your choosing. Stanza is a Python natural language analysis package. It contains tools, which can be used in a pipeline, to convert a string containing human language text into lists of sentences and words, to generate base forms of those words, their parts of... -
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NagaAgent
A simple yet powerful agent framework for personal assistants
...It provides abstractions for representing goals, context, and state so that agents can plan sequences of actions, evaluate outcomes, and adjust behavior over time. The project includes mechanisms for semantic memory, reasoning pipelines, and integration points with external data sources and language models so that agents can interpret natural language instructions and produce coherent multi-step outputs. Rather than being a simple chatbot, NagaAgent emphasizes persistent thought cycles, context retention, and the ability to decompose complex tasks into smaller executable units, earning it a place in research explorations of agent design. ... -
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doccano
Open source annotation tool for machine learning practitioners
doccano is an open-source text annotation tool for humans. It provides annotation features for text classification, sequence labeling and sequence-to-sequence tasks. So, you can create labeled data for sentiment analysis, named entity recognition, text summarization and so on. Just create a project, upload data and start annotating. You can build a dataset in hours. -
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FAY
Framework for building AI-powered interactive digital humans and agent
Fay is an open source framework designed to build and deploy interactive digital humans powered by large language models. It acts as a middleware layer that connects digital character technologies with conversational AI systems and business applications. Fay supports various types of digital humans, including 2.5D and 3D avatars, and can be integrated with applications running on mobile devices, PCs, web platforms, and embedded systems. Its architecture allows developers to combine different... -
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DeepCode
DeepCode: Open Agentic Coding
DeepCode is an agentic coding platform built around a multi-agent architecture that turns high-level inputs, including research papers, documents, and natural-language requirements, into working software artifacts. It positions itself as an “open agentic coding” system that can handle tasks like paper-to-code reproduction, frontend generation, and backend implementation by decomposing problems into structured steps and coordinating specialized agents. -
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OSWorld
Benchmarking Multimodal Agents for Open-Ended Tasks
OSWorld is an open-source synthetic world environment designed for embodied AI research and multi-agent learning. It provides a richly simulated 3D world where multiple agents can interact, perform tasks, and learn complex behaviors. OSWorld emphasizes multi-modal interaction, enabling agents to process visual, auditory, and symbolic data for grounded learning in a simulated world. -
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OpenAgents
AI Agent Networks for Open Collaboration
OpenAgents is an ambitious open-source framework for building AI Agent Networks where multiple autonomous AI agents can discover, connect, and collaborate on shared tasks within an extensible, protocol-agnostic ecosystem. The project’s goal is to provide foundational networking infrastructure that lets diverse agents—built using different large language models or tools—interoperate and work together toward complex goals. Agents on OpenAgents can exchange information, share capabilities,... -
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TreeQuest
A Tree Search Library with Flexible API for LLM Inference-Time Scaling
TreeQuest, developed by SakanaAI, is a versatile Python library implementing adaptive tree search algorithms—such as AB‑MCTS—for enhancing inference-time performance of large language models (LLMs). It allows developers to define custom state-generation and scoring functions (e.g., via LLMs), and then efficiently explores possible answer trees during runtime. With support for multi-LLM collaboration, checkpointing, and mixed policies, TreeQuest enables smarter, trial‑and‑error question answering by leveraging both breadth (multiple attempts) and depth (iterative refinement) strategies to find better outputs dynamically
