Search Results for "language processing" - Page 8
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Showing 519 open source projects for "language processing"
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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NeMo Curator
Scalable data pre processing and curation toolkit for LLMs
NeMo Curator is a Python library specifically designed for fast and scalable dataset preparation and curation for large language model (LLM) use-cases such as foundation model pretraining, domain-adaptive pretraining (DAPT), supervised fine-tuning (SFT) and paramter-efficient fine-tuning (PEFT). It greatly accelerates data curation by leveraging GPUs with Dask and RAPIDS, resulting in significant time savings. The library provides a customizable and modular interface, simplifying pipeline... -
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SimpleMem
SimpleMem: Efficient Lifelong Memory for LLM Agents
SimpleMem is a lightweight memory-augmented model framework that helps developers build AI applications that retain long-term context and recall relevant information without overloading model context windows. It provides easy-to-use APIs for storing structured memory entries, querying those memories using semantic search, and retrieving context to augment prompt inputs for downstream processing. Unlike monolithic systems where memory management is ad-hoc, SimpleMem formalizes a memory... -
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gensim
Topic Modelling for Humans
Gensim is a Python library for topic modeling, document indexing, and similarity retrieval with large corpora. The target audience is the natural language processing (NLP) and information retrieval (IR) community. -
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MiniCPM4
Ultra-Efficient LLMs on End Device
MiniCPM4 is part of the MiniCPM family of ultra-efficient large language models designed specifically for high performance on edge devices and resource-constrained environments. Unlike traditional large-scale models that require extensive computational resources, MiniCPM4 focuses on delivering competitive reasoning and language capabilities while maintaining significantly lower latency and higher efficiency. It achieves this through optimized architectures, scalable training strategies, and... -
Stop vibe-debugging.AppSignal's MCP server hands Claude, Cursor, or Zed your real errors, traces, and the deploy that shipped them. AI writes the fix; you review the diff.
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LLM Scraper
Extract structured data from webpages using LLM-powered scraping
...LLM Scraper integrates browser automation through Playwright, allowing it to load webpages and process their content before sending it to a language model for interpretation. Multiple content processing modes are supported, including raw HTML, cleaned HTML, Markdown, extracted text, screenshots, and custom inputs, making it adaptable to a wide range of scraping scenarios. LLM Scraper also provides streaming output and code generation capabilities that help developers build reusable scraping workflows. -
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React Native AI
Full stack framework for building cross-platform mobile AI apps
React Native AI is a full-stack framework designed to simplify the development of AI-powered mobile applications using React Native. The project provides a ready-to-use infrastructure for building cross-platform apps that integrate large language models and other AI services. It supports real-time streaming responses from multiple AI providers and enables developers to build chat interfaces, AI-driven image generation tools, and natural language features within mobile apps. The framework... -
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TEN Framework
TEN, a voice agent framework to create conversational AI.
TEN (Transformative Extensions Network) is a voice agent framework for creating conversational AI applications, focusing on high performance and modularity. -
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Transformer Explainer
Learn How LLM Transformer Models Work with Interactive Visualization
Transformer Explainer is an interactive visualization tool created to help users understand how transformer-based language models operate internally. The platform runs a lightweight GPT-2 model directly in the user’s browser and allows users to experiment with text prompts while observing the model’s internal operations. Through visual diagrams and interactive interfaces, the tool reveals how tokens are processed through layers such as embeddings, attention mechanisms, and feed-forward... -
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Handy STT
A free, open source, and extensible speech-to-text application
Handy is a free, open-source, offline speech-to-text application built for privacy, accessibility, and extensibility. Developed using Tauri (Rust + React/TypeScript), it runs natively across Windows, macOS, and Linux while performing local speech recognition without sending any audio to cloud servers. Handy allows users to start transcription instantly using a configurable keyboard shortcut—press to record, release to transcribe—and automatically pastes the resulting text into any active... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Text2Code for Jupyter notebook
A proof-of-concept jupyter extension which converts english queries
...The system uses natural language processing techniques to identify the intent of the query, extract relevant variables, and map the request to predefined code templates. Technologies such as sentence embeddings and named entity recognition are used to interpret user instructions and construct appropriate code outputs. -
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Fun Audio Chat
Large Audio Language Model built for natural interactions
Fun Audio Chat is an interactive voice-first conversational AI platform designed to let users engage in natural spoken dialogue with large language models in real time, turning speech into context-aware responses while maintaining a smooth back-and-forth experience. 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. ... -
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AIGC-Interview-Book
AIGC algorithm engineer interview secrets
...The project compiles knowledge from industry practitioners and researchers into a structured reference covering the AI ecosystem. Topics included in the repository span large language models, generative AI systems, traditional deep learning methods, reinforcement learning, computer vision, natural language processing, and machine learning theory. In addition to technical concepts, the repository also contains interview preparation materials such as practice questions, hiring insights, and career advice for AI engineers. ... -
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Fulling
Full-stack Engineer Agent. Built with Next.js, Claude, shadcn/ui
...Instead of manually configuring development environments, the system automatically provisions the required infrastructure including a Linux environment, database services, and development tools. It integrates an AI pair programmer that can generate code, implement features, and assist with debugging tasks through natural language instructions. The environment also includes web-based terminals, file management tools, and version control capabilities to support collaborative software development workflows. Developers can connect external services by simply providing API credentials, allowing the AI system to automatically integrate features such as authentication or payment processing. -
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Pipecat
Framework for building real-time voice and multimodal AI agents
Pipecat is an open source Python framework designed for building real-time voice and multimodal conversational AI agents. It provides developers with tools to orchestrate complex pipelines that combine speech recognition, language models, audio processing, and speech synthesis into a cohesive conversational system. Pipecat focuses on low-latency interactions so voice conversations with AI feel natural and responsive during live use. Pipecat allows applications to integrate multiple AI services and transports, enabling flexible deployment across different environments and communication channels. ... -
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Agent SOP
Natural language workflows for AI agents
Agent SOP is a framework that implements structured operational procedures (SOPs) for autonomous agents so that they can carry out complex multi-step tasks reliably and in a defined order. Instead of relying solely on broad language model reasoning, this project enforces explicit step sequences with checkpoints, conditional transitions, and rollback logic, making agent workflows more predictable and auditable. It defines reusable SOP templates that agents can instantiate with context-specific parameters, allowing organizations to codify best practices for customer support, data processing, document workflows, or incident response. ... -
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FastAgency
The fastest way to bring multi-agent workflows to production
FastAgency is a framework that simplifies the creation and deployment of AI-driven automation agents. It provides a structured environment for developing AI assistants capable of handling various business and technical tasks. -
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RuoYi AI
Enterprise AI platform for building, deploying, and managing apps
RuoYi AI is a full-stack enterprise-oriented AI development platform designed to help developers rapidly build, deploy, and manage intelligent applications using modern large language models and AI ecosystems. It provides a unified framework for integrating multiple AI models from different providers, allowing teams to switch or combine models through a consistent interface without vendor lock-in. RuoYi AI includes built-in support for retrieval-augmented generation, enabling organizations... -
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Claude Code Video Vision
Give Claude the ability to watch and understand videos
...The system dynamically adapts how much data it extracts based on the user’s query, adjusting frame rate, resolution, and time windows to optimize both performance and token efficiency. It supports multiple backends for audio processing, including local and cloud-based options, enabling flexible deployment depending on privacy or performance requirements. -
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GalTransl
Automated translation solution for visual novels
GalTransl is an automated translation system specifically designed for visual novels, particularly those in the “galgame” genre, leveraging large language models to streamline and enhance the translation process. It integrates support for multiple advanced LLM providers such as GPT-4, Claude, DeepSeek, and other models, enabling high-quality, context-aware translations that go beyond traditional machine translation approaches. The platform is built to handle the unique structure of visual... -
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Rivet
Visual AI IDE for building agents with prompt chains and graphs
...Its architecture emphasizes composability, where different components like prompts, APIs, and data processing steps can be combined into reusable pipelines. -
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kg-gen
Knowledge Graph Generation from Any Text
kg-gen is an open-source framework developed by the STAIR Lab that automatically generates knowledge graphs from unstructured text using large language models. The system is designed to transform plain text sources such as documents, articles, or conversation transcripts into structured graphs composed of entities and relationships. Instead of relying on traditional rule-based extraction techniques, KG-Gen uses language models to identify entities and their relationships, producing... -
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RAG Web UI
RAG Web UI is an intelligent dialogue system based on RAG
RAG Web UI is an open-source intelligent dialogue system built on retrieval-augmented generation technology, designed to enable users to create AI-powered question answering systems grounded in their own knowledge bases. It combines document retrieval with large language models to provide accurate, context-aware responses based on indexed data rather than generic model knowledge. The platform supports ingestion of multiple document formats, including PDFs, Word files, Markdown, and plain text, automatically processing and vectorizing them for efficient retrieval. It features a multi-turn conversational interface that maintains context across interactions, allowing users to engage in more natural and continuous dialogues with their data. ... -
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Kaggle Solutions
Collection of Kaggle Solutions and Ideas
...Each competition entry typically includes information about the dataset, evaluation metrics, modeling strategies, and techniques used by high-ranking competitors. The repository also highlights important machine learning concepts such as feature engineering, cross-validation strategies, ensemble modeling, and post-processing methods commonly used in winning solutions. Because the content is organized by competition categories such as computer vision, natural language processing, tabular data, and time-series forecasting, users can explore techniques relevant to specific problem types. -
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Readest
Readest is a modern, feature-rich ebook reader
Readest is a project meant to facilitate reading, studying, or consuming content by integrating reading tools with AI-powered assistance. Although the repository is not as widely documented or popular as some, the idea is that Readest supports features to help with reading comprehension — likely combining OCR / text retrieval, translation, note-taking, or summarization for reading materials (eBooks, articles, PDFs). The goal appears to be to let users feed in arbitrary reading material and... -
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ESPnet
End-to-end speech processing toolkit
ESPnet is a comprehensive end-to-end speech processing toolkit covering a wide spectrum of tasks, including automatic speech recognition (ASR), text-to-speech (TTS), speech translation (ST), speech enhancement, speaker diarization, and spoken language understanding. It uses PyTorch as its deep learning engine and adopts a Kaldi-style data processing pipeline for features, data formats, and experimental recipes.
