Search Results for "framework python" - Page 14
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Showing 1500 open source projects for "framework python"
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WikiChat
WikiChat is an improved RAG
WikiChat is a chatbot framework designed to interactively retrieve and summarize Wikipedia information, allowing users to ask questions and get context-aware responses? -
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GPT Academic
Research-oriented chatbot framework
GPT Academic is a research-oriented chatbot framework designed to integrate large language models (LLMs) into academic workflows. It provides tools for structured document processing, citation management, and enhanced interaction with research papers. -
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Backtrack Sampler
An easy-to-understand framework for LLM samplers
Backtrack Sampler is a framework designed for experimenting with custom sampling strategies for language models (LLMs), enabling the ability to rewind and revise generated tokens. It allows developers to create and test their own token generation strategies by providing a base structure for manipulating logits and probabilities, making it a flexible tool for those interested in fine-tuning the behavior of LLMs. -
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embedchain
Framework to easily create LLM powered bots over any dataset
Embedchain is a framework to easily create LLM-powered bots over any dataset. If you want a javascript version, check out embedchain-js. Embedchain empowers you to create chatbot models similar to ChatGPT, using your own evolving dataset. Start building LLM powered bots under 30 seconds. -
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MiroFlow
Agent framework that enables tool-use agent tasks
MiroFlow is a high-performance open-source framework designed for building intelligent AI agents capable of solving complex reasoning and research tasks. The system introduces a hierarchical architecture that organizes components into control, agent, and foundation layers, allowing developers to manage agent orchestration and tool interactions in a structured manner. One of the core innovations of MiroFlow is its use of agent graphs, which enable flexible orchestration of multiple sub-agents... -
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WFGY 3.0
A tension reasoning engine over 131 S-class problems
WFGY is an experimental open-source reasoning framework designed to improve the reliability and interpretability of large language model outputs through structured reasoning layers. The project introduces a conceptual reasoning engine that analyzes complex problems by identifying semantic compression errors and residual assumptions within a system’s reasoning process. Its architecture treats reasoning failures as measurable signals that can be detected and analyzed rather than simply... -
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Agents 2.0
An Open-source Framework for Data-centric Language Agents
Agents is an open-source framework designed to build and train autonomous language agents through a data-centric and learning-oriented architecture. The project introduces a concept known as agent symbolic learning, which treats an agent pipeline similarly to a neural network computational graph. In this framework, each node in the pipeline represents a step in the reasoning or action process, while prompts and tools act as adjustable parameters analogous to neural network weights. During... -
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Lingvo
Framework for building neural networks
Lingvo is a TensorFlow based framework focused on building and training sequence models, especially for language and speech tasks. It was originally developed for internal research and later open sourced to support reproducible experiments and shared model implementations. The framework provides a structured way to define models, input pipelines, and training configurations using a common interface for layers, which encourages reuse across different tasks. It has been used to implement state... -
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RWARE
MuA multi-agent reinforcement learning environment
robotic-warehouse is a simulation environment and framework for robotic warehouse automation, enabling research and development of AI and robotic agents to manage warehouse logistics, such as item picking and transport. -
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TensorFlow
TensorFlow is an open source library for machine learning
...Nodes take tensors—multidimensional arrays—as input and produce tensors as output. The framework allows for these algorithms to be run in C++ for better performance, while the multiple levels of APIs let the user determine how high or low they wish the level of abstraction to be in the models produced. Tensorflow can also be used for research and production with TensorFlow Extended. -
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fairseq2
FAIR Sequence Modeling Toolkit 2
fairseq2 is a modern, modular sequence modeling framework developed by Meta AI Research as a complete redesign of the original fairseq library. Built from the ground up for scalability, composability, and research flexibility, fairseq2 supports a broad range of language, speech, and multimodal content generation tasks, including instruction fine-tuning, reinforcement learning from human feedback (RLHF), and large-scale multilingual modeling. Unlike the original fairseq—which evolved into a... -
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Lambda Builders
Python library to compile, build & package AWS Lambda functions
...Build Actions could be implemented in any programming language. Preferably in the language that they are building. Some build actions simply execute a binary (like Golang) without writing a Go script. We provide a generic Python runner to implement such build actions. A build action is a module that knows how to build for a particular programming language & framework (ex: Python+PIP). Build actions can be implemented in Python or in the native programming language. Each build action has its own design document. -
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TorchDistill
A coding-free framework built on PyTorch
torchdistill (formerly kdkit) offers various state-of-the-art knowledge distillation methods and enables you to design (new) experiments simply by editing a declarative yaml config file instead of Python code. Even when you need to extract intermediate representations in teacher/student models, you will NOT need to reimplement the models, which often change the interface of the forward, but instead specify the module path(s) in the yaml file. In addition to knowledge distillation, this framework helps you design and perform general deep learning experiments (WITHOUT coding) for reproducible deep learning studies. i.e., it enables you to train models without teachers simply by excluding teacher entries from a declarative yaml config file. -
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PySINDy
A package for the sparse identification of nonlinear dynamical systems
PySINDy is a Python library that implements the Sparse Identification of Nonlinear Dynamics (SINDy) method for discovering mathematical models of dynamical systems from data. The framework focuses on identifying governing equations that describe the behavior of complex physical systems by selecting sparse combinations of candidate functions. Instead of fitting a purely predictive machine learning model, PySINDy attempts to recover interpretable differential equations that explain how a system evolves over time. ... -
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wxWidgets
Cross-Platform C++ GUI Library
wxWidgets is a C++ library that lets developers create applications for Windows, macOS, Linux, and other platforms with a single code base. It has popular language bindings for Python, Ruby, Lua, Perl, and several other languages, and unlike other cross-platform toolkits, wxWidgets gives applications a truly native look and feel because it uses the platform's native API rather than emulating the GUI. It's also extensive, free, open-source, and mature. -
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Prometheus-Eval
Evaluate your LLM's response with Prometheus and GPT4
...The repository includes a Python package that provides a straightforward interface for running evaluations and integrating them into model development pipelines. It also provides training data and utilities for fine-tuning evaluator models so they can assess outputs according to custom scoring rubrics such as helpfulness, accuracy, or style. -
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LLM-Pruner
On the Structural Pruning of Large Language Models
LLM-Pruner is an open-source framework designed to compress large language models through structured pruning techniques while maintaining their general capabilities. Large language models often require enormous computational resources, making them expensive to deploy and inefficient for many practical applications. LLM-Pruner addresses this issue by identifying and removing non-essential components within transformer architectures, such as redundant attention heads or feed-forward... -
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KVCache-Factory
Unified KV Cache Compression Methods for Auto-Regressive Models
KVCache-Factory is an open-source research framework designed to explore and implement unified key-value cache compression techniques for autoregressive transformer models. In large language models, the key-value cache stores intermediate attention states that enable efficient token generation during inference, but these caches can consume large amounts of GPU memory when handling long contexts. KVCache-Factory provides a platform for implementing and evaluating multiple compression... -
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Twisted
Event-driven networking engine written in Python
Twisted is an event-based framework for internet applications, supporting Python 3.6+. It includes modules for many different purposes. Twisted supports all major system event loops, select (all platforms), poll (most POSIX platforms), epoll (Linux), kqueue (FreeBSD, macOS), IOCP (Windows), and various GUI event loops (GTK+2/3, Qt, wxWidgets). Third-party reactors can plug into Twisted, and provide support for additional event loops. -
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caveman
Why use many token when few token do trick
Caveman is a lightweight and experimental project focused on simplifying backend or full-stack development workflows through minimalistic abstractions and rapid prototyping principles. It is designed to reduce the complexity of modern frameworks by offering a stripped-down approach that prioritizes speed, clarity, and ease of use. The project often serves as a foundation for developers who want to build applications quickly without being constrained by heavy conventions or extensive... -
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Distributed Transactions Manager
A distributed transaction framework that supports multiple languages
Support HTTP and GRPC, provide easy-to-use interfaces, lower substantially the barrier of getting started with distributed transactions, and newcomers can adapt quickly. Developers no longer worry about suspension, null compensation, idempotent transaction, and other tricky problems, the framework layer handles them all. Suitable for companies with the multi-language stack. Easy for go, python, php, nodejs, ruby and so forth. The only external dependence is the database server, easy to deploy, cluster, and scale horizontally. Supports TCC, SAGA, XA, and transaction messages. DTM is a distributed transaction framework that provides cross-service eventual data consistency. ... -
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OpenHarness
Open Agent Harness with a built-in personal agent, Ohmo
OpenHarness is an open-source framework developed to support large-scale machine learning workflows, particularly in the context of training, evaluating, and benchmarking AI models. It provides a structured environment for orchestrating experiments, managing datasets, and standardizing evaluation processes across different models. The project focuses on reproducibility and scalability, allowing researchers and engineers to run consistent experiments while tracking results effectively. It... -
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Cognita
Open source RAG framework for building scalable modular AI apps
Cognita is an open source framework designed to help developers build, organize, and deploy Retrieval-Augmented Generation (RAG) applications in a structured and production-ready way. It addresses the gap between quick experimentation in notebooks and the complexity of deploying scalable AI systems by introducing a modular and API-driven architecture. Cognita provides reusable components such as parsers, data loaders, embedders, retrievers, and query controllers, allowing teams to customize... -
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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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OSRFramework
OSRFramework, the Open Sources Research Framework is a AGPLv3+ project
OSRFramework is a GNU AGPLv3+ set of libraries developed by i3visio to perform Open Source Intelligence collection tasks. They include references to a bunch of different applications related to username checking, DNS lookups, information leaks research, deep web search, regular expressions extraction and many others. At the same time, by means of ad-hoc Maltego transforms, OSRFramework provides a way of making these queries graphically as well as several interfaces to interact with like...
