Showing 459 open source projects for "context"

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  • Build Agents and Models on One Platform Icon
    Build Agents and Models on One Platform

    Everything you need to build production-ready agents and models. Access 200+ Google and third-party AI models and tools.

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    Train ML Models With SQL You Already Know

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  • 1
    Gitingest

    Gitingest

    Create prompt-friendly codebase digests from any Git repository URL

    ...It analyzes a repository and produces a consolidated textual representation that includes the file structure and code content in an organized format. This makes it easier to provide meaningful code context when working with AI systems that require compact, readable inputs. Developers can generate these digests from either a local directory or a remote repository by supplying a repository path or URL. The generated output is optimized for prompt usage, helping AI models understand codebases more effectively without requiring manual file aggregation. ...
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  • 2
    Prompt Poet

    Prompt Poet

    Streamlines and simplifies prompt design for both developers

    ...By separating prompt structure from program logic, Prompt Poet encourages iterative prompt design and experimentation without requiring constant changes to application code. The framework supports dynamic prompts that adapt to runtime data, allowing developers to inject variables, context, and examples directly into templates. This approach is particularly useful in production environments where prompt consistency, maintainability, and versioning are important.
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  • 3
    LLM Colosseum

    LLM Colosseum

    Benchmark LLMs by fighting in Street Fighter 3

    LLM-Colosseum is an experimental benchmarking framework designed to evaluate the capabilities of large language models through gameplay interactions rather than traditional text-based benchmarks. The system places language models inside the environment of the classic video game Street Fighter III, where they must interpret the game state and decide which actions to perform during combat. This setup creates a dynamic environment that tests reasoning, situational awareness, and decision-making...
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  • 4
    ModernBERT

    ModernBERT

    Bringing BERT into modernity via both architecture changes and scaling

    ModernBERT is an open-source research project that modernizes the classic BERT encoder architecture by incorporating recent advances in transformer design, training techniques, and efficiency improvements. The goal of the project is to bring BERT-style models up to date with the capabilities of modern large language models while preserving the strengths of bidirectional encoder architectures used for tasks such as classification, retrieval, and semantic search. ModernBERT introduces...
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  • Veeam Data Platform v13.1 - Get Your Free Trial Icon
    Veeam Data Platform v13.1 - Get Your Free Trial

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  • 5
    LongWriter

    LongWriter

    Unleashing 10,000+ Word Generation from Long Context LLMs

    LongWriter is an open-source framework and set of large language models designed to enable ultra-long text generation that can exceed 10,000 words while maintaining coherence and structure. Traditional large language models can process large inputs but often struggle to generate long outputs due to limitations in training data and alignment strategies. LongWriter addresses this challenge by introducing a specialized dataset and training approach that encourages models to produce longer...
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  • 6
    CUDA Agent

    CUDA Agent

    Large-Scale Agentic RL for High-Performance CUDA Kernel Generation

    CUDA Agent is a research-driven agentic reinforcement learning system designed to automatically generate and optimize high-performance CUDA kernels for GPU workloads. The project addresses the long-standing challenge that efficient CUDA programming typically requires deep hardware expertise by training an autonomous coding agent capable of iterative improvement through execution feedback. Its architecture combines large-scale data synthesis, a skill-augmented CUDA development environment,...
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  • 7
    AudioNotes

    AudioNotes

    Extract audio and video content and organize it into a Markdown note

    AudioNotes is an application (or proof-of-concept) that likely combines audio recording or playback with note-taking or annotation functionality — enabling users to record voice or audio and attach textual or timestamped notes, making it ideal for lectures, interviews, meetings, or personal memos. Such a tool offers a more expressive and flexible way to capture and revisit information: instead of just typed notes or raw audio, users get both audio context and structured notes. As an open-source repository, AudioNotes provides developers or power users the opportunity to customize how audio is captured, stored, annotated, and replayed — e.g. adding playback speed control, export to standard formats, or synchronization between notes and audio timeline. It may support simple UI for starting/stopping recordings, writing or editing notes, and navigating through recorded sessions.
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  • 8
    Timesketch

    Timesketch

    Collaborative forensic timeline analysis

    ...Powerful search, aggregations, and saved views help you pivot quickly, highlight anomalies, and preserve investigative steps for later review. The system supports tagging, sketch notes, and story building so teams can annotate findings and share context without losing the raw data trail. Integrations with popular DFIR pipelines make ingestion repeatable, while role-based access and audit logs support enterprise workflows. By combining scale, collaboration, and reproducibility, Timesketch moves incident response beyond ad-hoc spreadsheets to a durable, team-oriented investigation record.
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  • 9
    NVIDIA Isaac GR00T

    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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  • Host LLMs in Production With On-Demand GPUs Icon
    Host LLMs in Production With On-Demand GPUs

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  • 10
    JC

    JC

    CLI tool and python library

    ...The default representation uses a strict schema per parser and converts known numbers to int/float JSON values. Certain known values of None are converted to JSON null, known boolean values are converted, and, in some cases, additional semantic context fields are added.
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  • 11
    Build Your Own OpenClaw

    Build Your Own OpenClaw

    A step-by-step guide to build your own AI agent

    ...It begins with foundational concepts like conversational loops and tool integration, then expands into more advanced capabilities such as dynamic skill loading, web interaction, and context management. As the tutorial progresses, it introduces architectural improvements including event-driven systems, WebSocket communication, and configuration hot-reloading to support scalability and real-time interaction.
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  • 12
    MCP UI

    MCP UI

    SDK for building interactive UI components over MCP for AI tools

    mcp-ui is a software development kit designed to bring interactive user interface capabilities to applications built on the Model Context Protocol (MCP). It enables developers to create rich, dynamic UI components that can be delivered from an MCP server and rendered seamlessly by a compatible client. Instead of returning only text responses, tools can provide structured UI resources such as HTML or remote-rendered components, allowing more engaging and functional interactions. mcp-ui introduces a standardized approach where tools and their associated interfaces are linked through metadata, enabling clients to automatically discover and display the correct UI. ...
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  • 13
    NVIDIA NeMo Agent Toolkit

    NVIDIA NeMo Agent Toolkit

    Library for efficiently connecting and optimizing teams of AI agents

    NVIDIA NeMo Agent Toolkit is an open-source framework designed to build, optimize, and manage AI agents across different development ecosystems. It provides enterprise-grade tools for improving agent performance, reliability, and observability throughout the development lifecycle. The toolkit integrates with popular agent frameworks such as LangChain, LlamaIndex, CrewAI, Microsoft Semantic Kernel, and Google ADK. Developers can monitor agent execution, trace workflows, and analyze...
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  • 14
    openbench

    openbench

    Provider-agnostic, open-source evaluation infrastructure

    openbench is an open-source, provider-agnostic evaluation infrastructure designed to run standardized, reproducible benchmarks on large language models (LLMs), enabling fair comparison across different model providers. It bundles dozens of evaluation suites — covering knowledge, reasoning, math, code, science, reading comprehension, long-context recall, graph reasoning, and more — so users don’t need to assemble disparate datasets themselves. With a simple CLI interface (e.g. bench eval <benchmark> --model <model-id>), you can quickly evaluate any model supported by Groq or other providers (OpenAI, Anthropic, HuggingFace, local models, etc.). openbench also supports private/local evaluations: you can integrate your own custom benchmarks or data (e.g. internal test suites, domain-specific tasks) to evaluate models in a privacy-preserving way.
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  • 15
    PokeeResearch-7B

    PokeeResearch-7B

    Pokee Deep Research Model Open Source Repo

    ...It is built to operate end-to-end: planning a research strategy, gathering sources, reasoning over conflicting claims, and writing a grounded response. The repository includes evaluation results on multi-step QA and research benchmarks, illustrating how web-time context boosts accuracy. Because the system is modular, you can swap the search component, reader, or policy to fit private deployments or different data domains. It’s aimed at developers who want a transparent, hackable research agent they can run locally or wire into existing workflows.
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  • 16
    Claude Code Security Reviewer

    Claude Code Security Reviewer

    An AI-powered security review GitHub Action using Claude

    The claude-code-security-review repository implements a GitHub Action that uses Claude (via the Anthropic API) to perform semantic security audits of code changes in pull requests. Rather than relying purely on pattern matching or static analysis, this action feeds diffs and surrounding context to Claude to reason about potential vulnerabilities (e.g. injection, misconfigurations, secrets exposure, etc). When a PR is opened, the action analyzes only the changed files (diff-aware scanning), generates findings (with explanations, severity, and remediation suggestions), filters false positives using custom prompt logic, and posts comments directly on the PR. ...
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  • 17
    Dagster

    Dagster

    An orchestration platform for the development, production

    Dagster is an orchestration platform for the development, production, and observation of data assets. Dagster as a productivity platform: With Dagster, you can focus on running tasks, or you can identify the key assets you need to create using a declarative approach. Embrace CI/CD best practices from the get-go: build reusable components, spot data quality issues, and flag bugs early. Dagster as a robust orchestration engine: Put your pipelines into production with a robust...
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  • 18
    GLM-4.5V

    GLM-4.5V

    GLM-4.6V/4.5V/4.1V-Thinking, towards versatile multimodal reasoning

    ...GLM-4.5V emerged from a training framework that leverages scalable reinforcement learning (with curriculum sampling) to boost performance across tasks ranging from STEM problem solving to long-context reasoning, giving it broad applicability beyond narrow benchmarks. When it was released, it achieved state-of-the-art results on a large collection of public multimodal benchmarks for open-source models.
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  • 19
    Robyn

    Robyn

    Experimental, AI/ML-powered and open sourced Marketing Mix Modeling

    ...Its goal is to democratize rigorous MMM: what traditionally required expert statisticians and expensive consulting becomes accessible to any company with data. Robyn takes in historical data (spends on different marketing channels, conversions, or revenue, and optional context or organic-media variables) and uses a combination of techniques, regularized regression (Ridge), time-series decomposition (trend, seasonality, holiday effects), and hyperparameter optimization (via evolutionary algorithms), to estimate the incremental impact of each marketing channel. It explicitly models “carry-over” (adstock) and diminishing-returns (saturation) effects per channel, enabling realistic modeling of how advertising persists over time and saturates.
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  • 20
    UI-TARS

    UI-TARS

    UI-TARS-desktop version that can operate on your local personal device

    UI-TARS is an open-source multimodal “GUI agent” created by ByteDance: a model designed to perceive raw screenshots (or rendered UI frames), reason about what needs to be done, and then perform real interactions with graphical user interfaces (GUIs) — like clicking, typing, navigating menus — across desktop, browser, mobile, or game environments. Rather than relying on rigid, manually scripted UI automation, UI-TARS uses a unified vision-language model (VLM) that integrates perception,...
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  • 21
    Step-Audio 2

    Step-Audio 2

    Multi-modal large language model designed for audio understanding

    Step-Audio2 is an advanced, end-to-end multimodal large language model designed for high-fidelity audio understanding and natural speech conversation: unlike many pipelines that separate speech recognition, processing, and synthesis, Step-Audio2 processes raw audio, reasons about semantic and paralinguistic content (like emotion, speaker characteristics, non-verbal cues), and can generate contextually appropriate responses — including potentially generating or transforming audio output. It...
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  • 22
    Vidi2

    Vidi2

    Large Multimodal Models for Video Understanding and Editing

    Vidi is a family of large multimodal models developed for deep video understanding and editing tasks, integrating vision, audio, and language to allow sophisticated querying and manipulation of video content. It’s designed to process long-form, real-world videos and answer complex queries such as “when in this clip does X happen?” or “where in the frame is object Y during that moment?” — offering temporal retrieval, spatio-temporal grounding (i.e. locating objects over time + space), and...
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  • 23
    Mini Agent

    Mini Agent

    A minimal yet professional single agent demo project

    Mini-Agent is a minimal yet production-minded demo project that shows how to build a serious command-line AI agent around the MiniMax-M2 model. It is designed both as a reference implementation and as a usable agent, demonstrating a full execution loop that includes planning, tool calls, and iterative refinement. The project exposes an Anthropic-compatible API interface and fully supports interleaved thinking, letting the agent alternate between reasoning steps and tool invocations during...
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  • 24
    Rhino

    Rhino

    On-device Speech-to-Intent engine powered by deep learning

    Rhino is Picovoice's Speech-to-Intent engine. It directly infers intent from spoken commands within a given context of interest, in real-time. The end-to-end platform for embedding private voice AI into any software in a few lines of code. Design with no limits on top of a modular platform. Create use-case-specific voice AI models in seconds. Develop voice features with a few lines of code using intuitive and cross-platform SDKs. Deliver voice AI everywhere: on-device, mobile, web browsers, on-premise, or cloud. ...
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  • 25
    Python-Spider

    Python-Spider

    Python3 web crawler practice

    Python-Spider is a repository intended to teach or provide examples for writing web spiders / crawlers in Python — part of a broader learning and resource collection by its author. The code and documentation are oriented toward beginners or intermediate learners who want to learn how to fetch, parse, and extract data from websites programmatically. As part of the author’s public learning-path repositories, python-spider likely includes examples of HTTP requests, HTML parsing, maybe...
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