Search Results for "input-output model"
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Showing 778 open source projects for "input-output model"
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Output
TypeScript framework for building AI workflows and agents
...The framework is built specifically to work with AI coding agents, enabling them to read, modify, and execute workflows directly from structured project folders. It eliminates reliance on fragmented SaaS tools by providing all necessary components locally, ensuring better transparency and control over data and processes. Output includes built-in evaluation systems, such as LLM-as-a-judge scoring, and integrates workflow orchestration tools like Temporal to handle retries, parallel execution, and state management. It also supports multiple model providers through a unified API. -
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MCP Shell Server
Shell command execution server implementing the Model Context Protocol
A secure shell command execution server implementing the Model Context Protocol (MCP), allowing remote execution of whitelisted shell commands with support for standard input. -
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ModelContextProtocol.NET
A C# SDK implementation of the Model Context Protocol (MCP)
ModelContextProtocol.NET is a C# SDK that implements the Model Context Protocol (MCP), allowing developers to build MCP servers on the .NET platform. It supports standard input/output communication and provides a framework for tool integration. The SDK is compatible with Native AOT, enhancing performance and deployment flexibility. A calculator demo implementation is included to demonstrate its capabilities. -
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voice-input-src
Documents and exposes generated source for menu-bar workflows
...A floating capsule displays a live waveform and expanding transcription text while recording. Clipboard restoration and temporary input-method switching make text injection safer for CJK users. An optional OpenAI-compatible model can conservatively correct obvious recognition errors before the final text is inserted. -
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MCPTools
A command-line interface for interacting with MCP
mcptools is a command-line interface designed for interacting with Model Context Protocol (MCP) servers using both standard input/output and HTTP transport methods. It allows users to discover and call tools, list resources, and interact with MCP-compatible servers. The tool supports various output formats and includes features like an interactive shell, project scaffolding, and server alias management. -
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MuseBot
Supports Telegram, Discord, Slack, Lark, compatible with LLMs
MuseBot is a multi-platform AI chatbot designed to connect popular messaging apps with large language model APIs. It supports Telegram, Discord, Slack, Lark, DingTalk, WeCom, QQ, WeChat, and a Web API for custom integrations. The bot can generate AI responses, stream output, understand images, process voice input, and use function-calling workflows. It supports model providers such as OpenAI, Gemini, DeepSeek, OpenRouter, Doubao, Qwen, and other compatible services. ... -
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EduCDM
The Model Zoo of cognitive diagnosis models
The Model Zoo of Cognitive Diagnosis Models, including classic Item Response Ranking (IRT), Multidimensional Item Response Ranking (MIRT), Deterministic Input, Noisy "And" model(DINA), and advanced Fuzzy Cognitive Diagnosis Framework (FuzzyCDF), Neural Cognitive Diagnosis Model (NCDM), Item Response Ranking framework (IRR), Incremental Cognitive Diagnosis (ICD) and Knowledge-association baesd extension of NeuralCD (KaNCD). -
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Guardrails
Framework for validating and controlling LLM outputs in AI apps
...Guardrails also supports generating structured data from language models, allowing developers to enforce schemas or type constraints on responses. A companion ecosystem known as a hub provides reusable validators that can be combined into input and output guards to address different reliability and safety concerns. -
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iTerm MCP
A Model Context Protocol server that executes commands
A Model Context Protocol server that executes commands in the current iTerm session, providing AI assistants with the ability to interact with REPL environments and command-line interfaces. -
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Strata
Qwen3.8-Flash-Next on any consumer hardware
...Strata provides a local chat interface and exposes OpenAI- and Anthropic-compatible APIs for other applications. Optional image input and several quantized model sizes allow users to balance memory use, speed, and quality. -
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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. ... -
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Bytewax
Python Stream Processing
...Connect data sources, run stateful transformations, and write to various downstream systems with built-in connectors or existing Python libraries. Bytewax is a Python framework and Rust distributed processing engine that uses a dataflow computational model to provide parallelizable stream processing and event processing capabilities similar to Flink, Spark, and Kafka Streams. You can use Bytewax for a variety of workloads from moving data à la Kafka Connect style all the way to advanced online machine learning workloads. Bytewax is not limited to streaming applications but excels anywhere that data can be distributed at the input and output. -
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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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LatentSync
Taming Stable Diffusion for Lip Sync
LatentSync is an open-source framework from ByteDance that produces high-quality lip-synchronization for video by using an audio-conditioned latent diffusion model, bypassing traditional intermediate motion representations. In effect, given a source video (with masked or reference frames) and an audio track, LatentSync directly generates frames whose lip motions and expressions align with the audio, producing convincing talking-head or animated lip-sync output. The system leverages a U-Net diffusion backbone, with cross-attention of audio embeddings (via an audio encoder) and reference video frames to guide generation, and applies a set of loss functions (temporal, perceptual, sync-net based) to enforce lip-sync accuracy, visual fidelity, and temporal consistency. ... -
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Dia2
TTS model capable of streaming conversational audio in realtime
Dia2 is a streaming dialogue text-to-speech model created by Nari Labs for generating conversational audio in real time. It is designed to begin producing speech before receiving the entire input text, which makes it useful for interactive voice applications. The model supports audio conditioning, allowing generated speech to follow a reference voice or conversational style more naturally. -
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Actors MCP Server
Model Context Protocol (MCP) Server for Apify's Actors
The Apify Actors MCP Server is a Model Context Protocol (MCP) server that enables AI assistants to interact with Apify Actors. This integration allows AI models to utilize various web scraping and automation tools provided by Apify, facilitating tasks such as data extraction and web automation. -
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AlphaFold 3
AlphaFold 3 inference pipeline
AlphaFold 3, developed by Google DeepMind, is an advanced deep learning system for predicting biomolecular structures and interactions with exceptional accuracy. This repository provides the complete inference pipeline for running AlphaFold 3, though access to the model parameters is restricted and must be obtained directly from Google under specific terms of use. The system is designed for scientific research applications in structural biology, biochemistry, and bioinformatics, enabling accurate modeling of proteins, ligands, and covalent modifications. Users can perform local predictions via Docker containers, integrating AlphaFold 3’s inference process with provided JSON input configurations. ... -
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WASTE
Run the full 2.78-trillion-parameter Kimi K3 model
WASTE is an embeddable C inference engine for running extremely large mixture-of-experts models when the weights exceed available RAM. It keeps the shared model trunk in memory and streams only the experts selected for each token from fast NVMe storage. A bounded cache reuses recently needed experts, while lookahead routing begins disk reads before the next layer requires them. Its main target is the full 2.78-trillion-parameter Kimi K3 model, including multimodal image input. The engine has no third-party runtime dependency on its CPU inference path and exposes both a CLI and C library. ... -
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Hunyuan3D 2.0
High-Resolution 3D Assets Generation with Large Scale Diffusion Models
...Hunyuan3D-2 supports various enhancements and is available for deployment through tools like Blender and Hugging Face. Includes a user-friendly production/studio tool (Hunyuan3D-Studio) to manipulate/animate meshes. Condition-aligned shape generation via the DiT model, so generated mesh is influenced by input images or prompts. -
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SageMaker TensorFlow Training Toolkit
Toolkit for running TensorFlow training scripts on SageMaker
...A Batch Transform job runs an offline-inference job using your TensorFlow Serving model. Input data in S3 is converted to HTTP requests, and responses are saved to an output bucket in S3. -
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MiniMind-O
A 0.1B Omni model trained from scratch
MiniMind-O is an educational open-source project for building a small end-to-end Omni model from scratch. It extends the MiniMind family by exploring a model that can handle text, audio, and image inputs while producing text and streaming speech outputs. The project is designed to make multimodal AI training more accessible by keeping the model size small enough for ordinary personal hardware. It includes both mini and full training data paths, allowing learners to run a complete workflow... -
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SHAP
A game theoretic approach to explain the output of ml models
...To understand how a single feature effects the output of the model we can plot the SHAP value of that feature vs. the value of the feature for all the examples in a dataset. Since SHAP values represent a feature's responsibility for a change in the model output, the plot below represents the change in predicted house price as RM (the average number of rooms per house in an area) changes. -
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Template MCP Server
Template to quickly set up your own MCP server
The template-mcp-server is a TypeScript-based template designed to expedite the setup of Model Context Protocol (MCP) servers. It provides a basic server configuration with options for both standard input/output and HTTP transport using FastMCP. The template includes a structured framework for defining MCP tools, resources, and prompts, along with TypeScript configuration and development scripts. -
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Persona
Create agentic front-end experiences for the web in VanillaJS
...It is written in TypeScript and renders with Vanilla JavaScript, so it can work alongside React, Vue, Svelte, static HTML, or other front-end stacks. The widget is backend-agnostic and connects to any SSE-capable agent or model backend through the Persona streaming protocol. It supports streaming chat, multimodal attachments, voice input and output, WebMCP page tools, local client tools, approval gates, tool call visualization, artifact rendering, and safe markdown or HTML output. It also includes configurable layouts such as floating, docked, fullscreen, and inline experiences. ... -
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Qwen-Image-2.1
Qwen's most powerful open-source image generation model
...Local edits can be guided with circles, painted annotations, or separate masks. It supports native 2K output across multiple aspect ratios while improving typography, portrait lighting, textures, and fine details. Efficient inference features include mixed-granularity attention, prefix KV caching, model offloading, and integrations with Diffusers, ComfyUI, vLLM, SGLang, and LightX2V.
