Search Results for "multi-threaded" - Page 6
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Showing 1086 open source projects for "multi-threaded"
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Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
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HunyuanVideo-Avatar
Tencent Hunyuan Multimodal diffusion transformer (MM-DiT) model
HunyuanVideo-Avatar is a multimodal diffusion transformer (MM-DiT) model by Tencent Hunyuan for animating static avatar images into dynamic, emotion-controllable, and multi-character dialogue videos, conditioned on audio. It addresses challenges of motion realism, identity consistency, and emotional alignment. Innovations include a character image injection module, an Audio Emotion Module for transferring emotion cues, and a Face-Aware Audio Adapter to isolate audio effects on faces, enabling multiple characters to be animated in a scene. ... -
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LLM Council
LLM Council works together to answer your hardest questions
...Instead of relying on one provider, this application sends your query simultaneously to several LLMs supported via OpenRouter, collects each model’s independent response, and then orchestrates a multi-stage evaluation where the models critique and rank each other’s outputs anonymously. After this peer-review process, a designated “Chairman” model synthesizes a final consolidated answer drawing on the strengths and insights of all participants. The interface looks like a familiar chat app but under the hood it implements this ensemble and consensus workflow to reduce bias and leverage diverse reasoning styles. -
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ChatGPT-Telegram-Workers
Deploy your own Telegram ChatGPT bot on Cloudflare Workers with ease
The simplest and fastest way to deploy your own ChatGPT Telegram bot. Use Cloudflare Workers, single file, copy and paste directly, no dependencies required, no need to configure local development environment, no domain name required, serverless. You can customize the system initialization information so that your debugged personality never disappears. -
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pi-autoresearch
Autonomous experiment loop extension for pi
...The system likely integrates with external data sources or APIs to retrieve information and process it into structured insights. Its architecture suggests a focus on autonomy, allowing it to run multi-step research pipelines that mimic human investigative processes. This makes it particularly useful for exploratory analysis, trend discovery, or generating structured knowledge from large information spaces. Overall, pi-autoresearch represents a step toward self-directed research agents capable of producing increasingly refined outputs over time. -
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UNO
A Universal Customization Method for Single and Multi Conditioning
UNO is a project by ByteDance introduced in 2025, titled “A Universal Customization Method for Both Single and Multi-Subject Conditioning.” It suggests a framework for image (or more general generative) modeling where the model can be conditioned either on a single subject or multiple subjects — which may correspond to generating or customizing images featuring specific people, styles, or objects, possibly with fine-grained control over subject identity or composition. -
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Matrix
Multi-Agent daTa geneRation Infra and eXperimentation framework
Matrix is a distributed, large-scale engine for multi-agent synthetic data generation and experiments: it provides the infrastructure to run thousands of “agentic” workflows concurrently (e.g. multiple LLMs interacting, reasoning, generating content, data-processing pipelines) by leveraging distributed computing (like Ray + cluster management). The idea is to treat data generation as a “data-to-data” transformation: each input item defines a task, and the runtime orchestrates asynchronous, peer-to-peer agent workflows, avoiding global synchronization bottlenecks. ... -
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DataFrame
C++ DataFrame for statistical, Financial, and ML analysis
...You can join, merge, and group-by the data. You can run various statistical, summarization, financial, and ML algorithms on the data. You can add your custom algorithms easily. You can multi-column sort, custom pick, and delete the data. DataFrame also includes a large collection of analytical algorithms in the form of visitors. These are from basic stats such as Mean, and Std Deviation and return, … to more involved analysis such as Affinity Propagation, Polynomial Fit, and Fast Fourier transform of arbitrary length … including a good collection of trading indicators. ... -
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TreeQuest
A Tree Search Library with Flexible API for LLM Inference-Time Scaling
...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 -
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VT Code
VT Code - semantic AI coding agent
...The system leverages syntax-aware parsing technologies such as tree-sitter and AST-based analysis to understand code structure rather than relying solely on raw text, which enables more accurate and context-aware suggestions. VTCode operates as an agent rather than a simple autocomplete tool, meaning it can interpret user intent, navigate codebases, and assist with multi-step tasks. It is highly configurable, allowing developers to define behavior, prompts, and workflows tailored to their projects. The tool is especially useful for developers who prefer lightweight, local-first environments but still want advanced AI assistance comparable to modern IDE-based tools. -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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LMCache
Supercharge Your LLM with the Fastest KV Cache Layer
...Instead of rebuilding KV states for repeated or shared text segments, LMCache persists and retrieves them from multiple tiers—GPU memory, CPU DRAM, and local disk—then injects them into subsequent requests to reduce TTFT and increase throughput. Its design supports reuse beyond strict prefix matching and enables sharing across serving instances, improving efficiency under real multi-tenant traffic. The broader project includes examples, tests, a server component, and public posts describing cross-engine sharing and inter-GPU KV transfers. These capabilities aim to lower latency, cut GPU cycles, and stabilize performance for production workloads with overlapping prompts or retrieval-augmented contexts. The end result is a cache fabric for LLMs that complements engines rather than replacing them. -
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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, crucial for creating reliable agents. ... -
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Code-Graph-RAG
The ultimate RAG for your monorepo
Code-Graph-RAG is an advanced retrieval-augmented generation system designed specifically for understanding and interacting with large, multi-language codebases by transforming them into structured knowledge graphs. It uses Tree-sitter to parse source code into abstract syntax trees, extracting relationships between functions, classes, and modules to build a graph-based representation of the entire codebase. This structured approach enables more accurate and context-aware querying compared to traditional text-based search methods, allowing users to ask natural language questions about code structure and functionality. ... -
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libvips
A fast image processing library with low memory needs
libvips is a demand-driven, horizontally threaded image processing library. Compared to similar libraries, libvips runs quickly and uses little memory. libvips is licensed under the LGPL 2.1+. It has around 300 operations covering arithmetic, histograms, convolution, morphological operations, frequency filtering, colour, resampling, statistics and others. It supports a large range of numeric types, from 8-bit int to 128-bit complex. -
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Portia SDK Python
Portia Labs Python SDK for building agentic workflows
portia‑sdk‑python is an open-source Python SDK by Portia Labs for creating reliable, stateful, authenticated multi-agent AI workflows. It supports tool-backed agents capable of real-world interactions—like web browsing, API access, and human-in-the-loop clarifications—while maintaining transparency and auditability through structured plans and execution hooks. Designed for production environments, the SDK integrates with local or cloud LLMs (e.g. -
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49 Agents IDE
Open-source 2D IDE for managing AI agents in native CLIs
...Instead of relying on traditional tab-based workflows, it provides a spatial interface where terminals, editors, Git views, and monitoring tools coexist as movable panes, enabling users to manage complex multi-agent systems visually and intuitively. The platform is designed to work across multiple machines simultaneously, allowing agents running on different devices or servers to connect to a unified workspace without requiring SSH, which simplifies distributed development workflows. It supports real-time synchronization across devices, meaning users can monitor and control their agents from laptops, tablets, or phones with the same interface. -
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ADK Go
Code-first Go toolkit for building, evaluating, and deploying AI agent
...ADK-Go applies traditional software engineering principles to agent development, making it easier to structure, test, and maintain complex agent-based systems. It supports building both simple task-oriented agents and more advanced multi-agent architectures that collaborate to perform workflows. It is designed to be modular and flexible, allowing developers to integrate custom tools, external services, or existing functionality into agent workflows. Although optimized for certain AI ecosystems, ADK-Go is model-agnostic and can work with different models and deployment environments. -
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CrewAI
Framework for orchestrating role-playing, autonomous AI agents
...CrewAI is designed to enable AI agents to assume roles, share goals, and operate in a cohesive unit - much like a well-oiled crew. Whether you're building a smart assistant platform, an automated customer service ensemble, or a multi-agent research team, CrewAI provides the backbone for sophisticated multi-agent interactions. -
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OmniRoute
OmniRoute is an AI gateway for multi-provider LLM
OmniRoute is a routing and orchestration framework designed to simplify the handling of requests, workflows, or data flows across multiple services or endpoints in a unified manner. It focuses on providing a flexible abstraction layer where developers can define routing logic that dynamically directs traffic based on conditions, context, or predefined rules. The project emphasizes modularity and extensibility, allowing users to plug in different services or handlers without tightly coupling... -
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RisuAI
Make your own story. User-friendly software for LLM roleplaying
RisuAI (or Risu) is a cross-platform AI roleplay chat application—available as both a desktop and web solution—offering creative story-building and character interaction experiences with support for multiple APIs, in-chat assets, regex capabilities, and more. Supports OpenAI, Claude, Gemini, DeepInfra, Ooba, OpenRouter... and More. Display the image of the current character, according to his/her expressions. Modify model's output by regex, to make a custom GUI and others. -
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OpenMed
Open source healthcare AI
...OpenMed can be used in three main ways: as a simple Python API for scripts and notebooks, as a Docker-friendly FastAPI service for backend integration, and as a batch-processing system for multi-document workflows. -
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CoStrict
Strict AI coder for enterprises, quality first
...The system integrates repository-wide analysis using retrieval-augmented generation, allowing it to understand large codebases and provide context-aware suggestions, reviews, and modifications. It also incorporates multi-agent or multi-expert verification strategies, ensuring that generated code is validated from multiple perspectives before being accepted. -
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ChatGLM2-6B
ChatGLM2-6B: An Open Bilingual Chat LLM
...It upgrades the base model with GLM’s hybrid pretraining objective, 1.4 TB bilingual data, and preference alignment—delivering big gains on MMLU, CEval, GSM8K, and BBH. The context window extends up to 32K (FlashAttention), and Multi-Query Attention improves speed and memory use. The repo includes Python APIs, CLI & web demos, OpenAI-style/FASTAPI servers, and quantized checkpoints for lightweight local deployment on GPUs or CPU/MPS. -
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OpenCV
Open Source Computer Vision Library
OpenCV (Open Source Computer Vision Library) is a comprehensive open-source library for computer vision, machine learning, and image processing. It enables developers to build real-time vision applications ranging from facial recognition to object tracking. OpenCV supports a wide range of programming languages including C++, Python, and Java, and is optimized for both CPU and GPU operations. -
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AutoGen
An Open-Source Programming Framework for Agentic AI
...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 multi-agent conversation framework as a high-level abstraction. With this framework, one can conveniently build LLM workflows. AutoGen offers a collection of working systems spanning a wide range of applications from various domains and complexities. AutoGen supports enhanced LLM inference APIs, which can be used to improve inference performance and reduce cost. -
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Nexent
Zero-code platform for building AI agents from natural language input
...Built on the MCP ecosystem, Nexent integrates a wide range of tools, models, and data sources into a unified environment for agent creation and execution. Nexent supports multi-agent collaboration, enabling multiple intelligent agents to interact and coordinate tasks within complex workflows. It also includes capabilities for data processing, knowledge tracing, and multimodal interaction, allowing agents to work with different input and output formats. Nexent provides built-in agents for common scenarios such as productivity, travel, and daily assistance.
