Search Results for "x-windows" - Page 31
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Showing 14905 open source projects for "x-windows"
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TreeQuest
A Tree Search Library with Flexible API for LLM Inference-Time Scaling
TreeQuest, developed by SakanaAI, is a versatile Python library implementing adaptive tree search algorithms—such as AB‑MCTS—for enhancing inference-time performance of large language models (LLMs). It allows developers to define custom state-generation and scoring functions (e.g., via LLMs), and then efficiently explores possible answer trees during runtime. With support for multi-LLM collaboration, checkpointing, and mixed policies, TreeQuest enables smarter, trial‑and‑error question... -
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OpenAI Agents (Python)
A lightweight, powerful framework for multi-agent workflows
openai-agents-python is a library developed by OpenAI to simplify the process of creating and running agents that interact with tools and APIs using OpenAI models. It provides abstractions for tool usage, memory management, and agent workflows, enabling developers to define function-calling agents that reason through multi-step tasks. Ideal for building custom AI workflows, the library supports dynamic tool definitions and contextual memory handling. -
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FastAPI Python
FastAPI framework, high performance, easy to learn, fast to code
FastAPI framework, high performance, easy to learn, fast to code, ready for production. FastAPI is a modern, fast (high-performance), web framework for building APIs with Python based on standard Python type hints. -
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Advanced Alchemy
A carefully crafted, thoroughly tested, optimized companion library
advanced-alchemy is an opinionated ORM toolkit built on SQLAlchemy and designed for integration with the Litestar web framework. It simplifies common ORM patterns such as CRUD, pagination, and async support while providing extensibility and best practices out of the box. It’s designed to accelerate backend development for modern Python web apps. -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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asyncpg
A fast PostgreSQL Database Client Library for Python/asyncio
asyncpg is a high-performance PostgreSQL client library designed for Python's asyncio framework. It offers a clean and efficient implementation of the PostgreSQL server binary protocol, enabling developers to execute database operations asynchronously. This approach allows for scalable and responsive applications that can handle numerous concurrent database connections. -
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Airweave
Airweave lets agents search any app
Airweave is an open-source platform that enables agents to semantically search across various applications, databases, and APIs. By transforming disparate data sources into a unified, searchable knowledge base, Airweave facilitates intelligent information retrieval through REST APIs or the MCP protocol. It's particularly useful for building AI agents that require access to structured and unstructured data across multiple platforms. -
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RL Games
RL implementations
rl_games is a high-performance reinforcement learning framework optimized for GPU-based training, particularly in environments like robotics and continuous control tasks. It supports advanced algorithms and is built with PyTorch. -
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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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PaperAI
Semantic search and workflows for medical/scientific papers
PaperAI is an open-source framework for searching and analyzing scientific papers, particularly useful for researchers looking to extract insights from large-scale document collections. -
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FastRAG
Efficient Retrieval Augmentation and Generation Framework
fastRAG is a research framework for efficient and optimized retrieval augmented generative pipelines, incorporating state-of-the-art LLMs and Information Retrieval. fastRAG is designed to empower researchers and developers with a comprehensive tool set for advancing retrieval augmented generation. -
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STORM
An LLM-powered knowledge curation system that researches topics
STORM is an open-source virtual assistant framework developed by Stanford's OVAL lab. It is designed for creating natural language interfaces and assistants that can interact with APIs, databases, and services in a modular way. -
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Trame
Weave various components and technologies into a Web App
Developed by Kitware, trame is a Python-based framework that allows developers to create web applications with desktop-like functionality. It enables the integration of various components and technologies, such as VTK and ParaView, into web applications written entirely in Python. With best-in-class platforms at its core, trame provides complete control of 3D visualizations and data processing. Developers benefit from a write-once environment from trame. trame is an open source project... -
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Ragas
Supercharge Your LLM Application Evaluations
Objective metrics, intelligent test generation, and data-driven insights for LLM apps. Ragas is your ultimate toolkit for evaluating and optimizing Large Language Model (LLM) applications. Say goodbye to time-consuming, subjective assessments and hello to data-driven, efficient evaluation workflows. Don't have a test dataset ready? We also do production-aligned test set generation. -
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ArchiveBox
Open source self-hosted web archiving
ArchiveBox is a powerful, self-hosted internet archiving solution to collect, save, and view websites offline. Without active preservation effort, everything on the internet eventually disappears or degrades. Archive.org does a great job as a centralized service, but saved URLs have to be public, and they can't save every type of content. ArchiveBox is an open source tool that lets organizations & individuals archive both public & private web content while retaining control over their data.... -
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PaperQA2
High accuracy RAG for answering questions from scientific documents
PaperQA2 is a package for doing high-accuracy retrieval augmented generation (RAG) on PDFs or text files, with a focus on the scientific literature. See our recent 2024 paper to see examples of PaperQA2's superhuman performance in scientific tasks like question answering, summarization, and contradiction detection. In this example we take a folder of research paper PDFs, magically get their metadata - including citation counts and a retraction check, then parse and cache PDFs into a... -
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Taipy
Turns Data and AI algorithms into production-ready web applications
From simple pilots to production-ready web applications in no time. No more compromise on performance, customization, and scalability. Taipy enhances performance with caching control of graphical events, optimizing rendering by selectively updating graphical components only upon interaction. Effortlessly manage massive datasets with Taipy's built-in decimator for charts, intelligently reducing the number of data points to save time and memory without losing the essence of your data's shape.... -
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magentic
Seamlessly integrate LLMs as Python functions
Easily integrate Large Language Models into your Python code. Simply use the @prompt and @chatprompt decorators to create functions that return structured output from the LLM. Mix LLM queries and function calling with regular Python code to create complex logic. -
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Bytewax
Python Stream Processing
Bytewax is a Python framework that simplifies event and stream processing. Because Bytewax couples the stream and event processing capabilities of Flink, Spark, and Kafka Streams with the friendly and familiar interface of Python, you can re-use the Python libraries you already know and love. 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... -
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Metarget
Framework for automatic construction of vulnerable infrastructures
Metarget = meta- + target, a framework providing automatic constructions of vulnerable infrastructures, used to deploy simple or complicated vulnerable cloud native targets swiftly and automatically. During security research, we might find that the deployment of a vulnerable environment often takes much time, while the time spent on testing PoC or ExP is comparatively short. In the field of cloud-native security, thanks to the complexity of cloud-native systems, this issue is more terrible.... -
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GemGIS
Spatial data processing for geomodeling
GemGIS is a Python-based, open-source geographic information processing library. It is capable of preprocessing spatial data such as vector data (shape files, geojson files, geopackages,…), raster data (tif, png,…), data obtained from online services (WCS, WMS, WFS) or XML/KML files (soon). Preprocessed data can be stored in a dedicated Data Class to be passed to the geomodeling package GemPy in order to accelerate the model-building process. Postprocessing of model results will allow export... -
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Stock prediction deep neural learning
Predicting stock prices using a TensorFlow LSTM
Predicting stock prices can be a challenging task as it often does not follow any specific pattern. However, deep neural learning can be used to identify patterns through machine learning. One of the most effective techniques for series forecasting is using LSTM (long short-term memory) networks, which are a type of recurrent neural network (RNN) capable of remembering information over a long period of time. This makes them extremely useful for predicting stock prices. Predicting stock... -
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borb
borb is a library for reading, creating and manipulating PDF files
borb is a library for creating and manipulating PDF files in python. borb is a pure python library to read, write, and manipulate PDF documents. It represents a PDF document as a JSON-like data structure of nested lists, dictionaries and primitives (numbers, string, booleans, etc) This is currently a one-man project, so the focus will always be to support those use-cases that are more common in favor of those that are rare. -
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LLaMA Efficient Tuning
Easy-to-use LLM fine-tuning framework (LLaMA-2, BLOOM, Falcon
Easy-to-use LLM fine-tuning framework (LLaMA-2, BLOOM, Falcon, Baichuan, Qwen, ChatGLM2) -
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proxy.py
Utilize all available CPU cores for accepting new client connections
proxy.py is made with performance in mind. By default, proxy.py will try to utilize all available CPU cores to it for accepting new client connections. This is achieved by starting AcceptorPool which listens on configured server port. Then, AcceptorPool starts Acceptor processes (--num-acceptors) to accept incoming client connections. Alongside, if --threadless is enabled, ThreadlessPool is setup which starts Threadless processes (--num-workers) to handle the incoming client connections.... -
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Open Source Vizier
Python-based research interface for blackbox
Open Source (OSS) Vizier is a Python-based interface for blackbox optimization and research, based on Google’s original internal Vizier, one of the first hyperparameter tuning services designed to work at scale. Allows a user to setup an OSS Vizier Server, which can host black-box optimization algorithms to serve multiple clients simultaneously in a fault-tolerant manner to tune their objective functions. Defines abstractions and utilities for implementing new optimization algorithms for...
