Showing 785 open source projects for "context"

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  • 1
    GLM-5.1

    GLM-5.1

    GLM-5: From Vibe Coding to Agentic Engineering

    ...The model leverages large-scale pretraining, reinforcement learning infrastructure, and sparse attention mechanisms to improve efficiency while maintaining strong long-context understanding. It supports deployment through frameworks such as vLLM, SGLang, xLLM, and KTransformers, enabling scalable local inference for enterprise and research use cases.
    Downloads: 48 This Week
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  • 2
    Aider

    Aider

    Aider is AI pair programming in your terminal

    Aider is an AI pair programming tool that runs directly in your terminal, helping developers build new projects or extend existing codebases faster and more confidently. It works alongside you like a coding partner, using powerful large language models to understand your code and implement precise changes. Aider creates a structured map of your entire repository, allowing it to handle large and complex projects effectively. It supports over 100 programming languages, making it flexible for...
    Downloads: 38 This Week
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  • 3
    OpenAI

    OpenAI

    Swift community driven package for OpenAI public API

    ...The SDK supports a wide range of features including chat completions, embeddings, image generation, audio processing, and structured outputs, making it a comprehensive toolkit for building AI-powered applications. It also includes support for advanced features such as function calling, assistants, and tool integration through protocols like Model Context Protocol, enabling more complex and interactive AI workflows.
    Downloads: 14 This Week
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  • 4
    Groq Desktop

    Groq Desktop

    Local Groq Desktop chat app with MCP support

    Groq Desktop is a cross-platform (Windows / macOS / Linux) local desktop application that provides a graphical chat interface for interacting with Groq-hosted, function-call-capable models. It bundles a built-in MCP (Model Context Protocol) server enabling smart function calling, letting users chat with an AI, send images, or interact with richer multimodal inputs — all from a friendly desktop UI. The app is built with modern web technologies and packaged for native distribution, making it accessible even to non-developer users who just want to experiment with Groq models without writing code. ...
    Downloads: 43 This Week
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  • 5
    GLM-4.5

    GLM-4.5

    GLM-4.5: Open-source LLM for intelligent agents by Z.ai

    ...GLM-4.5 achieves strong performance on 12 industry-standard benchmarks, ranking 3rd overall, while GLM-4.5-Air balances competitive results with greater efficiency. The models support FP8 and BF16 precision, and can handle very large context windows of up to 128K tokens. Flexible inference is supported through frameworks like vLLM and SGLang with tool-call and reasoning parsers included.
    Downloads: 10 This Week
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  • 6
    CodeGraph

    CodeGraph

    Pre-indexed code knowledge graph for Claude Code, Codex, Cursor

    ...CodeGraph stores project data locally, which helps reduce token usage and repeated file exploration. Its main purpose is to make agent-assisted coding faster, cheaper, and more context-aware.
    Downloads: 18 This Week
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  • 7
    Open Notebook

    Open Notebook

    An Open Source implementation of Notebook LM with more flexibility

    ...Open Notebook enables users to organize and analyze multi-modal content such as PDFs, videos, audio files, web pages, and Office documents. It combines full-text and vector search with context-aware AI chat to deliver insights grounded in your own research materials. With advanced features like multi-speaker podcast generation, customizable content transformations, and a comprehensive REST API, Open Notebook provides a powerful and extensible research environment.
    Downloads: 52 This Week
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  • 8
    VT Code

    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.
    Downloads: 1 This Week
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  • 9
    MCP for Unity

    MCP for Unity

    AI bridge enabling assistants to control and automate Unity Editor

    Unity MCP is an open source integration that connects AI assistants with the Unity Editor through the Model Context Protocol (MCP). It acts as a bridge that allows language models and AI coding tools to interact directly with a Unity development environment using structured commands and tools. By linking an AI assistant to a running Unity project, the system enables automated operations such as managing project assets, modifying scenes, editing scripts, and performing other development tasks inside the editor. ...
    Downloads: 1 This Week
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  • 10
    kMCP

    kMCP

    Kubernetes Controller for building, testing and deploying MCP servers

    KMCP is a companion toolchain for building, testing, and deploying MCP servers with a workflow that spans local development through Kubernetes production deployments. It includes a CLI for day-to-day development tasks like scaffolding new MCP projects, managing tools, building container images, and running an MCP server locally for validation. For cluster operations, it includes a Kubernetes controller that manages MCP server lifecycles using a dedicated Custom Resource Definition (CRD),...
    Downloads: 1 This Week
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  • 11
    vJEPA-2

    vJEPA-2

    PyTorch code and models for VJEPA2 self-supervised learning from video

    VJEPA2 is a next-generation self-supervised learning framework for video that extends the “predict in representation space” idea from i-JEPA to the temporal domain. Instead of reconstructing pixels, it predicts the missing high-level embeddings of masked space-time regions using a context encoder and a slowly updated target encoder. This objective encourages the model to learn semantics, motion, and long-range structure without the shortcuts that pixel-level losses can invite. The architecture is designed to scale: spatiotemporal ViT backbones, flexible masking schedules, and efficient sampling let it train on long clips while remaining stable. ...
    Downloads: 1 This Week
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  • 12
    DeepSeek Coder

    DeepSeek Coder

    DeepSeek Coder: Let the Code Write Itself

    ...The models are trained from scratch on a massive corpus (~2 trillion tokens), of which about 87% is code and 13% is natural language. This dataset covers project-level code structure (not just line-by-line snippets), using a large context window (e.g. 16K) and a secondary fill-in-the-blank objective to encourage better contextual completions and infilling. Multiple sizes of the model are offered (e.g. 1B, 5.7B, 6.7B, 33B) so users can trade off inference cost vs capability. The repo provides model weights, documentation on training setup, evaluation results on common benchmarks (HumanEval, MultiPL-E, APPS, etc.), and inference tools.
    Downloads: 1 This Week
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  • 13
    DSH Anchored Standard

    DSH Anchored Standard

    Two-phase DeepSeek Harness preset

    DSH Anchored Standard is a collection of experimental DeepSeek Harness presets designed to combine Minimal-style reasoning behavior with access to broader Standard tools. Its base mode begins a new session with only the real Minimal bash and text-editing tools while suppressing automatically injected context. After a durable tool call or assistant response, the preset promotes the session to a resident phase with discovery tools and restored Standard context. Additional modes experiment with zero-tool anchors, seeded trajectories, permanent Minimal catalogs, and separate thinking and execution stages. Promotion state is derived from persistent session events, so it survives reloads and resumed sessions. ...
    Downloads: 0 This Week
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  • 14
    Kimi Linear

    Kimi Linear

    An expressive, efficient attention architecture

    Kimi Linear is a hybrid linear attention architecture developed for efficient language modeling across short, long-context, and reinforcement learning workloads. Its core mechanism, Kimi Delta Attention, refines the gated delta rule with fine-grained controls for managing finite-state recurrent memory. The architecture combines KDA and global Multi-head Latent Attention layers at a 3:1 ratio to preserve model quality while reducing memory demands. Released Base and Instruct checkpoints contain 48 billion total parameters, activate 3 billion parameters per token, and support contexts up to one million tokens. ...
    Downloads: 0 This Week
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  • 15
    OpenTag

    OpenTag

    Open-source @agent mentions for Slack and GitHub

    ...It connects collaboration platforms such as Slack, GitHub, GitLab, Linear, Telegram, Discord, Microsoft Teams, and Lark or Feishu to local executors. Each request becomes a bounded context packet whose permissions and executor capabilities are checked before work begins. Codex, Claude Code, or another compatible agent performs the task and returns concise results to the original thread. Action receipts show proposed changes and expose an Apply option only when an approved adapter can safely perform them. A local work ledger records the source event, admission decision, context, capabilities, artifacts, callbacks, and final outcome. ...
    Downloads: 0 This Week
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  • 16
    Codey

    Codey

    The home for Codey releases, updates, and the developer community

    ...Codey combines a fast keyboard-driven TUI with a cross-platform desktop app for developers who want AI assistance close to their coding workflow. It can help read, write, refactor, and inspect code while also running commands and coordinating multi-step engineering tasks. The project uses the Model Context Protocol to connect agent workflows with external tools and richer development context. This repository does not contain the private application source, but it hosts releases, installers, updater metadata, guides, prompts, skills, workflows, issues, and discussions. It is useful for developers who want to install Codey, follow updates, contribute resources, or participate in the project community.
    Downloads: 0 This Week
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  • 17
    AI Engineer Coach

    AI Engineer Coach

    Better agentic engineering

    ...The extension reads local logs and turns them into dashboards, practice scores, trends, anti-pattern detection, and actionable feedback. It focuses on agentic engineering habits such as prompt quality, context management, review discipline, tool use, and session hygiene. The project is read-only and emphasizes that data stays on the user’s machine. Its main value is helping developers measure and improve their AI-assisted coding process instead of treating agent use as an untracked black box.
    Downloads: 0 This Week
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  • 18
    SynaBun

    SynaBun

    Persistent vector memory for AI assistants

    Synabun is an open-source AI memory management and augmentation system designed to provide persistent, semantic memory for AI agents and coding assistants, particularly those compatible with the MCP (Model Context Protocol) ecosystem. It functions as a local-first solution that stores and retrieves contextual knowledge across sessions using a built-in vector database powered by embeddings, eliminating the need for external APIs, cloud services, or Docker dependencies. The system integrates tightly with developer workflows by running alongside tools like Claude Code, enabling automatic memory capture, retrieval, and contextual augmentation through lifecycle hooks and commands. ...
    Downloads: 0 This Week
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  • 19
    SEO Machine

    SEO Machine

    A specialized Claude Code workspace for creating long-form

    ...It incorporates real data sources like Google Analytics and Search Console to guide decision-making and improve content effectiveness. The architecture emphasizes context-awareness, using brand voice, style guides, and keyword strategies to maintain consistency across outputs. It also includes performance evaluation tools that score content and suggest improvements before publishing.
    Downloads: 0 This Week
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  • 20
    CoStrict

    CoStrict

    Strict AI coder for enterprises, quality first

    ...This makes it particularly suitable for organizations that require consistency, auditability, and reliability in AI-assisted development. 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.
    Downloads: 0 This Week
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  • 21
    AI Agent Deep Dive

    AI Agent Deep Dive

    AI Agent Source Code Deep Research Report

    ...The project is organized as a learning resource rather than a standalone framework, making it particularly useful for developers who want to move beyond surface-level prompt engineering into full agent system design. It explores how agents interact with environments, execute tasks, and maintain context over time, highlighting both strengths and limitations of current approaches. The repository likely includes diagrams, annotated code samples, and conceptual walkthroughs that mirror real production systems.
    Downloads: 0 This Week
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  • 22
    Youtu-Agent

    Youtu-Agent

    A simple yet powerful agent framework that delivers with models

    ...The system focuses on reducing the complexity traditionally involved in configuring large language model agents by providing a modular architecture that separates execution environments, tools, and context management. This structure allows developers to rapidly assemble agent systems capable of performing tasks such as research, file processing, and data analysis. The framework supports automated generation of agent components, enabling the system to synthesize prompts, tool interfaces, and workflow configurations automatically. Youtu-Agent also incorporates hybrid learning strategies that combine experience accumulation with reinforcement learning to improve agent performance over time. ...
    Downloads: 0 This Week
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  • 23
    Grounded Docs

    Grounded Docs

    Open-Source Alternative to Context7, Nia, and Ref.Tools

    Grounded Docs is an open-source implementation of a Model Context Protocol server designed to expose documentation and structured information as tools that AI agents can query. The project allows language models and agent frameworks to retrieve and interact with documentation through standardized MCP interfaces. By acting as an intermediary layer between documentation sources and AI tools, the server enables models to access structured documentation in a consistent and machine-readable format. ...
    Downloads: 0 This Week
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  • 24
    Gollama

    Gollama

    Go manage your Ollama models

    ...Beyond standard model management, Gollama can display metadata such as size, quantization level, model family, and modification date, which helps users compare models quickly. One of its more distinctive capabilities is a VRAM estimation system that can calculate memory requirements, estimate context limits, and help users choose quantization settings that fit available hardware.
    Downloads: 0 This Week
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  • 25
    12-Factor Agents

    12-Factor Agents

    What are the principles we can use to build LLM-powered software

    ...Inspired by the original Twelve-Factor App methodology, the project reframes best practices specifically for agentic systems and AI software. It outlines patterns such as treating prompts as first-class assets, owning the context window, and converting natural language into structured tool calls. The repository emphasizes operational discipline, arguing that even as models improve, strong engineering patterns remain essential for production-grade AI systems. Rather than providing a traditional framework, it serves as a strategic blueprint that teams can apply to their own agent architectures. ...
    Downloads: 0 This Week
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