Search Results for "self-extracing" - Page 3
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Showing 159 open source projects for "self-extracing"
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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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Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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LazyLLM
Easiest and laziest way for building multi-agent LLMs applications
LazyLLM is an optimized, lightweight LLM server designed for easy and fast deployment of large language models. It is fully compatible with the OpenAI API specification, enabling developers to integrate their own models into applications that normally rely on OpenAI’s endpoints. LazyLLM emphasizes low resource usage and fast inference while supporting multiple models. -
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video-use
Edit videos with Claude Code
Video Use is an open-source AI-powered video editing tool that allows users to transform raw footage into polished videos using natural language commands. Designed to work with Claude Code, it automates the entire editing process—from cutting clips to rendering the final output—without requiring manual timelines or complex software interfaces. The system intelligently analyzes audio transcripts and visual cues to make precise, context-aware editing decisions. It supports a wide range of... -
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AgentHandover
AgentHandover observes, learns and teaches agents with skills
AgentHandover is a Mac-focused system that observes how a user works and converts repeated workflows into reusable, self-improving skills for AI agents. It is designed for tools such as Claude Code, OpenClaw, Codex, Hermes, Cursor, Windsurf, and other MCP-compatible environments. Instead of asking users to manually write long prompts or static automation instructions, it records real actions, infers decision logic, and produces skills that include steps, strategy, guardrails, selection criteria, and writing style. ... -
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Lyra 2
Project Lyra: Open Generative 3D World Models
The Lyra 2 project is a research-driven framework developed by NVIDIA that focuses on building open generative 3D world models using advanced diffusion-based techniques. It enables the creation of fully explorable 3D environments from minimal inputs such as a single image or video, leveraging self-distillation methods to generate consistent spatial representations. The system evolves across versions, with newer iterations introducing long-horizon generation and improved 3D consistency across frames. It combines elements of computer vision, generative modeling, and spatial intelligence to produce dynamic and navigable virtual worlds. ... -
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Pika Skills
A collection of open-source skills for AI coding agents
Pika Skills is an open-source framework designed to extend the capabilities of AI coding agents by introducing modular, reusable “skills” that can be dynamically invoked during development workflows. Each skill acts as a self-contained unit composed of structured instructions, executable scripts, and dependency definitions, enabling agents to autonomously perform complex tasks without requiring manual configuration or orchestration. The system is tightly integrated with the Pika Developer API, allowing developers to plug advanced functionalities such as automation, integrations, or real-time interactions directly into their AI-assisted coding environments. ... -
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Omnilingual ASR
Omnilingual ASR Open-Source Multilingual SpeechRecognition
Omnilingual-ASR is a research codebase exploring automatic speech recognition that generalizes across a very large number of languages using shared modeling and training recipes. It focuses on leveraging self-supervised audio pretraining and scalable fine-tuning so low-resource languages can benefit from high-resource data. The project provides data preparation pipelines, training scripts, decoding utilities, and evaluation tools so researchers can reproduce results and extend to new language sets. It emphasizes modularity: acoustic modeling, language modeling, tokenization, and decoding are separable pieces you can swap or ablate. ... -
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MoCo (Momentum Contrast)
Self-supervised visual learning using momentum contrast in PyTorch
MoCo is an open source PyTorch implementation developed by Facebook AI Research (FAIR) for the papers “Momentum Contrast for Unsupervised Visual Representation Learning” (He et al., 2019) and “Improved Baselines with Momentum Contrastive Learning” (Chen et al., 2020). It introduces Momentum Contrast (MoCo), a scalable approach to self-supervised learning that enables visual representation learning without labeled data. The core idea of MoCo is to maintain a dynamic dictionary with a momentum-updated encoder, allowing efficient contrastive learning across large batches. The repository includes implementations for both MoCo v1 and MoCo v2, the latter improving training stability and performance through architectural and augmentation enhancements. ... -
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MemMachine
Universal memory layer for AI Agents
MemMachine is a universal memory layer designed for AI agents that provides persistent, rich memory storage and retrieval capabilities so autonomous agent systems can recall context, personal preferences, and long-term interaction history across sessions, models, and use cases. Unlike ephemeral LLM prompt state, MemMachine supports distinct memory types—short-term conversational context, long-term persistent knowledge, and profile memory for personalized facts—persisted in optimized stores... -
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EPUB to Audiobook Converter
EPUB to audiobook converter, optimized for Audiobookshelf
...The project supports multiple TTS providers, including Microsoft Azure TTS, EdgeTTS, OpenAI TTS, local Piper, and Kokoro via an OpenAI-compatible endpoint, allowing users to choose between cloud and self-hosted voices. A recent addition is a Gradio-based WebUI, which wraps all configuration options in a graphical interface for users who prefer not to work with the command line. The tool offers advanced options such as controlling chapter ranges, handling paragraph detection via newline modes, removing endnote markers, and using regex-based search-and-replace files to tweak pronunciations. ... -
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Vanna
Chat with your SQL database
Vanna.AI is an AI-powered tool for natural language database querying, enabling users to interact with databases using simple English queries. It converts natural language questions into SQL queries, making data access more intuitive for non-technical users. -
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DSPy
DSPy: The framework for programming—not prompting—language models
Developed by the Stanford NLP Group, DSPy (Declarative Self-improving Python) is a framework that enables developers to program language models through compositional Python code rather than relying solely on prompt engineering. It facilitates the construction of modular AI systems and provides algorithms for optimizing prompts and weights, enhancing the quality and reliability of language model outputs. -
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Aim
An easy-to-use & supercharged open-source experiment tracker
...The Aim standard package comes with all integrations. If you'd like to modify the integration and make it custom, create a new integration package and share with others. Aim is an open-source, self-hosted AI Metadata tracking tool designed to handle 100,000s of tracked metadata sequences. The two most famous AI metadata applications are: experiment tracking and prompt engineering. Aim provides a performant and beautiful UI for exploring and comparing training runs, and prompt sessions. -
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Databend
Cloud-native open source data warehouse for analytics and AI queries
...Databend supports SQL-based workflows and enables real-time data ingestion, transformation, and analysis through streaming and task orchestration features. With its cloud-native design and distributed architecture, Databend can run both as a self-hosted system or within managed environments to power data analytics, AI workloads, and large-scale data. -
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claude-obsidian
Claude + Obsidian knowledge companion
claude-obsidian is an AI-powered knowledge engine that transforms an Obsidian vault into a self-organizing, continuously evolving wiki. Instead of acting as a simple chat assistant, it autonomously creates, links, and maintains structured knowledge based on user inputs and external sources. The system follows the LLM Wiki pattern, where information is stored as persistent markdown files that grow richer over time through cross-referencing and synthesis. -
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Scikit-LLM
Seamlessly integrate LLMs into scikit-learn
...Note: unlike in a typical supervised setting, the performance of a zero-shot classifier greatly depends on how the label itself is structured. It has to be expressed in natural language, descriptive, and self-explanatory. -
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Acontext
Context data platform for building observable, self-learning AI agents
...The platform observes agent tasks and user feedback in real time, offering robust observability into workflows and helping teams understand how agents perform over time. Acontext also supports agent self-learning by distilling structured skills and experiences from previously completed tasks, which can later be reused or searched to improve future performance. It includes tools to interact with session data, background agents that monitor progress, and a dashboard that visualizes success rates, artifacts, and learned skills. By combining persistent storage, observability, and learning capabilities, Acontext aims to make AI agents more scalable, reliable, and capable. -
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MaxKB
Open-source platform for building enterprise-grade agents
...It’s backed by an active org that also builds adjacent ops tooling, and there’s a dedicated documentation repo for configuration and contribution. Community posts describe “self-host your ChatGPT-style assistant” positioning, with integrations and workflows to move from demo to production. Security advisories are tracked publicly, with upgrade guidance when issues arise. -
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Ollama RAG Chatbot
Chat with multiple PDFs locally
...With Docker support, script-based setup, optional ngrok exposure, and a clear local run path, it serves as a compact starter project for people who want a hands-on, self-hosted PDF chat system. -
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Mistral Vibe CLI
Minimal CLI coding agent by Mistral
Mistral Vibe is an AI-powered “vibe-coding” command-line interface (CLI) and coding-assistant framework built by Mistral AI to let developers write, refactor, search, and manage code through natural language and context-aware automation, rather than manual typing only. It aims to take developers out of repetitive boilerplate and let them stay “in the flow”: you can ask the tool to generate functions, refactor code, search across the codebase, manipulate files, commit changes via Git, or run... -
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Khoj
An AI personal assistant for your digital brain
...So that you can stay focused on doing what matters. Khoj started with the founding principle that a personal assistant be understandable, accessible and hackable. This means you can always customize and self-host your Khoj on your own machines. -
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cognee
Deterministic LLMs Outputs for AI Applications and AI Agents
Cognee implements scalable, modular data pipelines that allow for creating the LLM-enriched data layer using graph and vector stores. Cognee acts a semantic memory layer, unveiling hidden connections within your data and infusing it with your company's language and principles. This self-optimizing process ensures ultra-relevant, personalized, and contextually aware LLM retrievals. Any kind of data works; unstructured text or raw media files, PDFs, tables, presentations, JSON files, and so many more. Add small or large files, or many files at once. We map out a knowledge graph from all the facts and relationships we extract from your data. ... -
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Red Discord Bot
A multi-function Discord bot
Red is a fully modular bot, meaning all features and commands can be enabled/disabled to your liking, making it completely customizable. This is a self-hosted bot, meaning you will need to host and maintain your own instance. You can turn Red into an admin bot, music bot, trivia bot, new best friend or all of these together! CustomCommands allows you to create simple commands for your bot without requiring you to code your own cog for Red. If the command you attempt to create shares a name with an already loaded command, you cannot overwrite it with this cog. ... -
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Artificial Intelligence for Beginners
12 Weeks, 24 Lessons, AI for All
...The curriculum is intentionally beginner-friendly while still exposing learners to widely used frameworks such as TensorFlow and PyTorch. It also supports many languages, making the material accessible to a global audience. Overall, the project functions as a complete self-paced learning pathway for students, educators, and developers who want a practical introduction to modern AI concepts. -
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AWorld
Build, evaluate and train General Multi-Agent Assistance with ease
AWorld (Agent World) is an agent runtime/framework. It supports building, evaluating, and training self-improving intelligent agents and multi-agent systems (MAS). It is designed to provide infrastructure for agent orchestration, iterative learning, and environment interaction at scale. Scalable training across environments and distributed setups. Support for multi-agent collaboration/orchestration (MAS). The system is intended to help agents evolve via experience. -
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Hamilton DAGWorks
Helps scientists define testable, modular, self-documenting dataflow
Hamilton is a lightweight Python library for directed acyclic graphs (DAGs) of data transformations. Your DAG is portable; it runs anywhere Python runs, whether it's a script, notebook, Airflow pipeline, FastAPI server, etc. Your DAG is expressive; Hamilton has extensive features to define and modify the execution of a DAG (e.g., data validation, experiment tracking, remote execution). To create a DAG, write regular Python functions that specify their dependencies with their parameters. As...