Search Results for "multi-threaded" - Page 6
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Showing 1291 open source projects for "multi-threaded"
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Neuro SAN Studio
A playground for neuro-san
...The system also includes mechanisms for secure data handling, ensuring sensitive information is not exposed directly to language models. Neuro SAN Studio offers built-in examples, tutorials, and debugging tools, which help users quickly prototype and refine multi-agent workflows. -
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Eigent
The Open Source Cowork Desktop to Unlock Your Exceptional Productivity
Eigent is an open-source cowork desktop application designed to help you build, manage, and deploy a custom AI workforce. It enables multiple specialized AI agents to collaborate in parallel, turning complex workflows into automated, end-to-end tasks. Built on the CAMEL-AI multi-agent framework, Eigent emphasizes productivity, flexibility, and transparent system design. You can run Eigent fully locally for maximum privacy and data control, or choose a cloud-connected experience for quick access. The platform supports a wide range of AI models and integrates powerful tools through the Model Context Protocol (MCP). ... -
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Yahoo! Finance market data downloader
Yahoo! Finance market data downloader
Ever since Yahoo! finance decommissioned their historical data API, many programs that relied on it to stop working. yfinance aims to solve this problem by offering a reliable, threaded, and Pythonic way to download historical market data from Yahoo! finance. yfinance aimed to offer a temporary fix to the problem by scraping the data from Yahoo! Finance and returning a the data in the same format as pandas_datareader's get_data_yahoo(), thus keeping the code changes in existing software to a minimum. The latest version of yfinance is a complete re-write of the libray, offering a reliable method of downloading historical market data from Yahoo! ... -
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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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Loggifly
Get Alerts from your Docker Container Logs
...Instead of manually scanning logs for issues or relying solely on centralized monitoring stacks, LoggiFly proactively inspects streams of container output and notifies users through services like Ntfy, Slack, Discord, Telegram, or webhooks when significant events occur. It supports plain text, regex, and multi-line pattern matching, and its flexible alert templating lets operators tailor messages for clarity and context, including attaching relevant log excerpts. Beyond notifications, LoggiFly can take automated actions such as restarting or stopping containers when specific critical patterns are detected, which is especially useful for preventing damage from misbehaving services. -
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Wizarr
User invitation and management system for Jellyfin, Plex, Emby etc.
...Initially conceived to enable administrators to create unique invite links that automatically register new users on their media servers, Wizarr abstracts many of the manual account-creation tasks typical of media server setups. It features a web interface and wizard-style processes for creating, customizing, and tracking user invites, with support for multi-server management, single-sign-on integrations, and automated notification workflows. Documentation highlights the ability to guide invited users through required downloads and configuration, and the system includes features for securing invitations and tailoring invitation templates. -
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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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RobotCode
RobotFramework support for Visual Studio Code
An extension that brings support for RobotFramework to Visual Studio Code, including features like code completion, debugging, test explorer, refactoring and more! With RobotCode you can edit your code with auto-completion, code navigation, syntax checking and many more. -
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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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Every Code
Local AI coding agent CLI with multi-agent orchestration tools
...It is a community-driven fork of the Codex CLI, with a strong emphasis on improving real-world developer ergonomics and workflows. Every Code enhances the traditional coding assistant model by introducing multi-agent orchestration, allowing multiple AI agents to collaborate, compare solutions, and refine outputs in parallel. It supports integration with various AI providers, enabling users to route tasks across different models depending on their needs. Every Code also includes browser integration and automation capabilities, extending its usefulness beyond simple code generation into more complex development tasks. ... -
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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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ClawTeam
ClawTeam: Agent Swarm Intelligence (One Command → Full Automation)
ClawTeam is an advanced multi-agent orchestration framework that enables AI agents to form collaborative swarms capable of solving complex tasks autonomously. Instead of relying on a single agent, the system allows a leader agent to spawn and coordinate multiple specialized sub-agents, each responsible for different aspects of a problem. These agents communicate, share insights, and dynamically adapt their strategies based on real-time feedback, creating a form of collective intelligence. ... -
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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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PAL MCP
The power of Claude Code / GeminiCLI / CodexCLI
PAL MCP is an open-source Model Context Protocol (MCP) server designed to act as a powerful middleware layer that connects AI clients and tools—like Claude Code, Codex CLI, Cursor, and IDE plugins—to a broad range of underlying AI models, enabling collaborative multi-model workflows rather than relying on a single model. It lets developers orchestrate interactions across multiple models (including Gemini, OpenAI, Grok, Azure, Ollama, OpenRouter, and custom/self-hosted models), preserving conversation context seamlessly as tasks evolve and substeps run across tools. By supporting conversation threading and context passing, pal-mcp-server helps maintain continuity during complex processes like code reviews, automated planning, implementation, and validation, allowing models to “debate” or weigh in on specific subtasks for better outcomes. -
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MaxKB
Open-source platform for building enterprise-grade agents
...It focuses on practical deployments such as customer support, internal knowledge bases, research assistants, and education, bundling tools for data ingestion, chunking, embedding, retrieval, and answer synthesis. The system exposes flexible tool-use (including MCP), supports multi-model backends, and provides dashboards for dataset management and evaluation. It’s backed by an active org that also builds adjacent ops tooling, and there’s a dedicated documentation repo for configuration and contribution. Community posts describe “self-host your ChatGPT-style assistant” positioning, with integrations and workflows to move from demo to production. ... -
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Agno
Lightweight framework for building Agents with memory, knowledge, etc.
...It provides a flexible framework for modeling reasoning, memory, decision-making, and planning, aimed at long-term AI research beyond narrow learning. Agno embraces multi-agent environments and symbolic reasoning as part of its core design, enabling experiments with structured knowledge, goal-oriented behaviors, and meta-learning. It’s designed for researchers seeking an extensible platform to explore AGI components without being tied to black-box models. -
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Autobahn|Python
WebSocket and WAMP in Python for Twisted and asyncio
...Autobahn Python is useful for dashboards, IoT systems, collaborative apps, backend services, messaging platforms, and applications that need real-time communication across components. It works especially well with a WAMP router such as Crossbar.io when building routed multi-service systems. -
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Clawith
OpenClaw for Teams
...The system likely emphasizes integration with external tools and services, allowing agents to extend their capabilities beyond internal reasoning. Its architecture suggests support for multi-agent collaboration, enabling distributed problem-solving and task delegation. It may also include monitoring and control features to ensure that agent behavior remains aligned with user goals. The project reflects a broader trend toward building AI systems that act as autonomous operators rather than passive assistants. Overall, Clawith serves as a foundation for building advanced, action-oriented AI workflows. -
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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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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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Norfair
Lightweight Python library for adding real-time multi-object tracking
Norfair is a customizable lightweight Python library for real-time multi-object tracking. Using Norfair, you can add tracking capabilities to any detector with just a few lines of code. Any detector expressing its detections as a series of (x, y) coordinates can be used with Norfair. This includes detectors performing tasks such as object or keypoint detection. It can easily be inserted into complex video processing pipelines to add tracking to existing projects. -
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FlashAttention
Fast and memory-efficient exact attention
...By improving both forward and backward pass efficiency, it enables training and inference of large language models with longer sequence lengths and higher throughput. The library integrates with PyTorch and supports various attention configurations, including causal masking, multi-query attention, and rotary embeddings. -
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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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AI-Tutorials/Implementations Notebooks
Codes/Notebooks for AI Projects
...It includes implementations for a wide range of AI topics such as computer vision, agent systems, federated learning, distributed systems, adversarial attacks, and generative AI. Many of the tutorials focus on building AI agents, multi-agent systems, and workflows that integrate language models with external tools or APIs. The codebase acts as a hands-on learning resource, allowing users to experiment with new frameworks, architectures, and machine learning workflows through guided examples. -
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deepfakes_faceswap
Deepfakes Software For All
Faceswap is the leading free and open source multi-platform deepfakes software. When faceswapping was first developed and published, the technology was groundbreaking, it was a huge step in AI development. It was also completely ignored outside of academia because the code was confusing and fragmentary. It required a thorough understanding of complicated AI techniques and took a lot of effort to figure it out.
