Search Results for "input-leap"
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Showing 45 open source projects for "input-leap"
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MetaGPT
The Multi-Agent Framework
The Multi-Agent Framework: Given one line Requirement, return PRD, Design, Tasks, Repo. Assign different roles to GPTs to form a collaborative software entity for complex tasks. MetaGPT takes a one-line requirement as input and outputs user stories / competitive analysis/requirements/data structures / APIs / documents, etc. Internally, MetaGPT includes product managers/architects/project managers/engineers. It provides the entire process of a software company along with carefully orchestrated SOPs. -
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Purple Llama
Set of tools to assess and improve LLM security
Purple Llama is an umbrella safety initiative that aggregates tools, benchmarks, and mitigations to help developers build responsibly with open generative AI. Its scope spans input and output safeguards, cybersecurity-focused evaluations, and reference shields that can be inserted at inference time. The project evolves as a hub for safety research artifacts like Llama Guard and Code Shield, along with dataset specs and how-to guides for integrating checks into applications. CyberSecEval, one of its flagship components, provides repeatable evaluations for security risk, including agent-oriented tasks such as automated patching benchmarks. ... -
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CogVLM2
GPT4V-level open-source multi-modal model based on Llama3-8B
...Built on Meta-Llama-3-8B-Instruct, CogVLM2 significantly improves over its predecessor by providing stronger performance across multimodal benchmarks such as TextVQA, DocVQA, and ChartQA, while introducing extended context length support of up to 8K tokens and high-resolution image input up to 1344×1344. The series includes models for both image understanding and video understanding, with CogVLM2-Video supporting up to 1-minute videos by analyzing keyframes. It supports bilingual interaction (Chinese and English) and has open-source versions optimized for dialogue and video comprehension. Notably, the Int4 quantized version allows efficient inference on GPUs with only 16GB of memory. ... -
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E2M
E2M converts various file types (doc, docx, epub, html, htm, url
E2M is a SourceForge mirror of the e2m open-source project, which focuses on providing tools or services designed to convert or process content between different formats or systems. Projects with similar naming conventions typically emphasize automation workflows where input data from one environment is transformed into another representation or output structure. The mirrored repository allows users to access the project’s codebase independently from its original hosting platform while preserving the development history and release artifacts. Systems like e2m often serve as middleware components that connect different software systems or facilitate data processing pipelines. ... -
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LLM Guard
The Security Toolkit for LLM Interactions
...The toolkit also helps prevent sensitive information leaks by identifying secrets such as API keys or credentials before they are processed by the model. LLM Guard supports both input and output filtering pipelines, allowing developers to sanitize prompts and validate generated responses in real time. The library integrates easily with existing AI frameworks and can be deployed in production environments to enhance the security posture of LLM-based applications. -
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NExT-GPT
Code and models for ICML 2024 paper, NExT-GPT
NExT-GPT is an open-source research framework that implements an advanced multimodal large language model capable of understanding and generating content across multiple modalities. Unlike traditional models that primarily handle text, NExT-GPT supports input and output combinations involving text, images, video, and audio in a unified architecture. The system connects a large language model with multimodal encoders and diffusion-based decoders so it can interpret information from different sensory formats and generate responses in different media types. This architecture allows the model to convert between modalities, such as generating images from text descriptions or producing audio or video outputs based on textual prompts. ... -
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Fun Audio Chat
Large Audio Language Model built for natural interactions
...It combines speech recognition, audio processing, and AI generation so users can speak simply and receive spoken replies, enabling applications such as virtual assistants, voice bots, and hands-free chat interfaces. The system supports dynamic audio input and output, meaning it can handle different voices, tones, and conversational contexts without forcing users into typed interactions. With real-time streaming, it minimizes latency and delivers responses quickly, making it suitable for applications where responsiveness matters, such as interactive demos, accessibility tools, and conversational games. -
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Claude Code Tools
Practical productivity tools for Claude Code, Codex-CLI
...Some components enable Claude Code to interact with terminal multiplexers such as tmux so that it can run programs, debug applications, and interact with scripts that require user input. The toolkit also provides safety mechanisms that prevent potentially dangerous shell commands from being executed automatically by AI agents. -
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Qwen3-Omni
Qwen3-omni is a natively end-to-end, omni-modal LLM
...It uses a Thinker-Talker architecture with a Mixture-of-Experts (MoE) design, early text-first pretraining, and mixed multimodal training to support strong performance across all modalities without sacrificing text or image quality. The model supports 119 text languages, 19 speech input languages, and 10 speech output languages. It achieves state-of-the-art results: across 36 audio and audio-visual benchmarks, it hits open-source SOTA on 32 and overall SOTA on 22, outperforming or matching strong closed-source models such as Gemini-2.5 Pro and GPT-4o. To reduce latency, especially in audio/video streaming, Talker predicts discrete speech codecs via a multi-codebook scheme and replaces heavier diffusion approaches. -
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Qwen-2.5-VL
Qwen2.5-VL is the multimodal large language model series
Qwen2.5 is a series of large language models developed by the Qwen team at Alibaba Cloud, designed to enhance natural language understanding and generation across multiple languages. The models are available in various sizes, including 0.5B, 1.5B, 3B, 7B, 14B, 32B, and 72B parameters, catering to diverse computational requirements. Trained on a comprehensive dataset of up to 18 trillion tokens, Qwen2.5 models exhibit significant improvements in instruction following, long-text generation... -
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MarkPDFDown
A high-quality PDF to Markdown tool based on large language model
...By producing Markdown rather than raw text, the tool makes it easier to integrate documents into knowledge bases, documentation systems, or language model pipelines that rely on structured input. The software is particularly useful for developers working with technical documents, academic papers, or reports that need to be indexed, summarized, or processed by downstream AI systems. -
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OmniBox
Collect, organize, use, and share, all in OmniBox
Omnibox (mirror) is a SourceForge mirror of the Omnibox open-source project, which provides a software interface designed to simplify interaction with multiple tools and services through a unified command or search interface. The project focuses on creating a centralized input field where users can enter commands, queries, or shortcuts that trigger actions across different applications or services. Inspired by the omnibox concept used in modern browsers, the system combines search functionality with command execution so that users can access information and perform tasks without navigating complex menus. ... -
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CodeLlama
Inference code for CodeLlama models
Code Llama is a family of Llama-based code models optimized for programming tasks such as code generation, completion, and repair, with variants specialized for base coding, Python, and instruction following. The repo documents the sizes and capabilities (e.g., 7B, 13B, 34B) and highlights features like infilling and large input context to support real IDE workflows. It targets both general software synthesis and language-specific productivity, offering strong performance among open models at release time. Typical usage includes prompt-driven generation, function or class completion, and zero-shot adherence to natural-language instructions about code changes. ... -
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GLM-4-Voice
GLM-4-Voice | End-to-End Chinese-English Conversational Model
GLM-4-Voice is an open-source speech-enabled model from ZhipuAI, extending the GLM-4 family into the audio domain. It integrates advanced voice recognition and generation with the multimodal reasoning capabilities of GLM-4, enabling smooth natural interaction via spoken input and output. The model supports real-time speech-to-text transcription, spoken dialogue understanding, and text-to-speech synthesis, making it suitable for conversational AI, virtual assistants, and accessibility applications. GLM-4-Voice builds upon the bilingual strengths of the GLM architecture, supporting both Chinese and English, and is designed to handle long-form conversations with context retention. ... -
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Paper2Slides
From Paper to Presentation in One Click
...It is designed to replace the repetitive work of turning dense technical documents into presentation-friendly structure by extracting key points, figures, and data into a coherent visual narrative. The system supports multiple input formats, so you can process PDFs and common office documents rather than being locked to a single file type. It uses an extraction approach intended to capture critical insights comprehensively, including important visuals and data points that often get missed in naive summarization. A major focus is traceability: generated slide content is designed to remain linked back to the source material so you can verify accuracy and reduce information drift. ... -
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Qwen3-VL
Qwen3-VL, the multimodal large language model series by Alibaba Cloud
Qwen3-VL is the latest multimodal large language model series from Alibaba Cloud’s Qwen team, designed to integrate advanced vision and language understanding. It represents a major upgrade in the Qwen lineup, with stronger text generation, deeper visual reasoning, and expanded multimodal comprehension. The model supports dense and Mixture-of-Experts (MoE) architectures, making it scalable from edge devices to cloud deployments, and is available in both instruction-tuned and... -
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SimpleLLM
950 line, minimal, extensible LLM inference engine built from scratch
...Designed to run efficiently on high-end GPUs like NVIDIA H100 with support for models such as OpenAI/gpt-oss-120b, Simple-LLM implements continuous batching and event-driven inference loops to maximize hardware utilization and throughput. Its straightforward code structure allows anyone experimenting with custom kernels, new batching strategies, or inference optimizations to trace execution from input to output with minimal cognitive overhead. -
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MusicGPT
Generate music based on natural language prompts using LLMs
MusicGPT is an open-source application designed to generate music from natural language prompts using locally executed artificial intelligence models. The software allows users to run advanced music generation systems directly on their own devices without requiring heavy dependencies such as Python or full machine learning frameworks. Instead, it provides a lightweight environment capable of executing music generation models locally on CPUs or GPUs while maintaining strong performance across... -
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Slack MCP Server
The most powerful MCP Slack Server with no permission requirements
...Through this architecture, AI assistants can read message histories, interact with channels, and retrieve contextual information from Slack conversations in order to perform tasks such as automated analysis, collaboration assistance, or contextual code review. The server supports multiple communication transports, including standard input/output streams, HTTP, and Server-Sent Events, allowing flexible integration with different AI client environments. -
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GLM-V
GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning
GLM-V is an open-source vision-language model (VLM) series from ZhipuAI that extends the GLM foundation models into multimodal reasoning and perception. The repository provides both GLM-4.5V and GLM-4.1V models, designed to advance beyond basic perception toward higher-level reasoning, long-context understanding, and agent-based applications. GLM-4.5V builds on the flagship GLM-4.5-Air foundation (106B parameters, 12B active), achieving state-of-the-art results on 42 benchmarks across image,... -
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Chat UI
The open source codebase powering HuggingChat
...Chat UI connects to any service that exposes an OpenAI-compatible API endpoint, allowing it to work with a wide range of models and inference providers. The platform supports advanced capabilities such as multimodal input, tool integration through Model Context Protocol servers, and intelligent routing that selects the most appropriate model for each request. -
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Flock
Flock is a workflow-based low-code platform for building chatbots
Flock is a workflow-based low-code platform designed for building AI applications such as chatbots, retrieval-augmented generation systems, and multi-agent workflows. The platform uses a visual workflow architecture where different nodes represent processing steps such as input processing, model inference, retrieval operations, and tool execution. Developers can connect these nodes to create complex pipelines that orchestrate multiple language models and external services. Built on technologies such as LangChain, LangGraph, FastAPI, and Next.js, Flock combines a modern web interface with a flexible backend capable of supporting advanced AI workflows. ... -
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Gemma
Gemma open-weight LLM library, from Google DeepMind
...This repository provides the official implementation of the Gemma PyPI package, a JAX-based library that enables users to load, interact with, and fine-tune Gemma models. The framework supports both text and multi-modal input, allowing natural language conversations that incorporate visual content such as images. It includes APIs for conversational sampling, parameter management, and integration with fine-tuning methods like LoRA. The Gemma library can operate efficiently on CPUs, GPUs, or TPUs, with recommended configurations depending on model size. ... -
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Ring
Ring is a reasoning MoE LLM provided and open-sourced by InclusionAI
Ring is a reasoning Mixture-of-Experts (MoE) large language model (LLM) developed by inclusionAI. It is built from or derived from Ling. Its design emphasizes reasoning, efficiency, and modular expert activation. In its “flash” variant (Ring-flash-2.0), it optimizes inference by activating only a subset of experts. It applies reinforcement learning/reasoning optimization techniques. Its architectures and training approaches are tuned to enable efficient and capable reasoning performance.... -
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LlamaIndex
Central interface to connect your LLM's with external data
LlamaIndex (GPT Index) is a project that provides a central interface to connect your LLM's with external data. LlamaIndex is a simple, flexible interface between your external data and LLMs. It provides the following tools in an easy-to-use fashion. Provides indices over your unstructured and structured data for use with LLM's. These indices help to abstract away common boilerplate and pain points for in-context learning. Dealing with prompt limitations (e.g. 4096 tokens for Davinci) when...
