Search Results for "basic-ro" - Page 2
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Showing 290 open source projects for "basic-ro"
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ChatOllama
ChatOllama is an open-source AI chatbot
ChatOllama is an open-source chatbot platform built with Nuxt 3 and designed to provide a private, extensible interface for working with multiple modern language model providers. It goes beyond a basic chat UI by supporting a broad model ecosystem that includes OpenAI, Azure OpenAI, Anthropic, Google Gemini, Groq, Moonshot, Ollama, and other OpenAI-compatible services. The platform also includes higher-level capabilities such as AI agents, document-backed knowledge bases, real-time voice chat, and Model Context Protocol integration for external tools. ... -
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OpenAI Quickstart Node
Node.js example app from the OpenAI API quickstart tutorial
...The repository provides structured sample code for a variety of API endpoints, including chat completions, assistants, embeddings, fine-tuning, moderation, batch processing, and image generation. Each folder contains runnable scripts that demonstrate both basic usage and more advanced scenarios. By following the examples, developers can quickly understand how to authenticate with an API key, send requests, and handle responses within a Node.js environment. The project is a practical starting point for building AI-powered applications, serving as a foundation for experimentation and integration into larger projects. ... -
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Freqtrade
Free, open source crypto trading bot
...Always start by running a trading bot in Dry-run and do not engage money before you understand how it works and what profit/loss you should expect. We strongly recommend you have basic coding skills and Python knowledge. Do not hesitate to read the source code and understand the mechanisms of this bot, algorithms, and techniques implemented in it. Write your strategy in python, using pandas. Example strategies to inspire you are available in the strategy repository. Download historical data of the exchange and the markets you may want to trade with. ... -
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Glowby
Glowby Basic helps you create your own voice-based AI assistants
Glowby is an open-source platform designed to assist users in creating and sharing interactive educational content, enabling collaborative learning experiences. -
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Ditto
The simplest self-building coding agent
Ditto is a simple self-building coding agent that generates multi-file Flask applications from natural language descriptions. Users describe the app they want, and the system attempts to plan and create routes, templates, static assets, and supporting files. It uses an LLM loop with basic tools to automate part of the coding process. The project is intentionally lightweight and experimental, making it easier to understand than larger agentic coding platforms. Its modular structure separates generated Flask components into cleaner directories for routes, templates, and static files. It is best suited for prototyping, learning, and exploring how natural-language app generation can work in a small local project. -
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Hindsight
Hindsight: Agent Memory That Learns
...It addresses one of the core limitations of modern AI agents, which is their inability to retain and meaningfully use past experiences over time, by introducing a structured, biomimetic memory architecture inspired by how human memory works. Instead of relying solely on vector similarity or basic retrieval techniques, Hindsight organizes information into distinct categories such as facts, experiences, beliefs, and observations, allowing agents to differentiate between raw data and inferred knowledge. The system operates through three core mechanisms—retain, recall, and reflect—which respectively handle storing information, retrieving relevant context, and generating new insights based on accumulated experience. -
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Advanced + Agentic RAG Cookbooks
Advanced RAG cookbooks for building accurate LLM applications
Athina AI’s RAG Cookbooks is a GitHub repository that showcases advanced and agentic Retrieval-Augmented Generation techniques for building more accurate AI applications. It provides ready-to-use notebooks, implementations, and explanations that help developers move from basic RAG setups to more sophisticated workflows. Athina AI’s RAG Cookbooks covers the full RAG pipeline, including indexing, retrieval, augmentation, and generation, while also addressing evaluation to measure accuracy and relevance. It includes multiple approaches such as hybrid search, contextual compression, and agent-based retrieval strategies, allowing users to experiment and compare methods. ... -
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Kong
The Cloud-Native API Gateway
Kong is a next generation cloud-native API platform for multi-cloud and hybrid organizations. When building for the web, mobile, or Internet of Things, you’ll need a common functionality to run your software, and Kong is that solution. Kong acts as a gateway, connecting microservices requests and APIs natively while also providing load balancing, logging, monitoring, authentication, rate-limiting, and so much more through plugins. Kong is highly extensible as well as platform agnostic,... -
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MCP OpenAI
Chat with OpenAI models from Claude Desktop
The MCP OpenAI Server is a Model Context Protocol server that allows seamless interaction with OpenAI's models directly from applications like Claude Desktop. It simplifies the integration of OpenAI's language models into various workflows. -
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LiteMultiAgent
The Library for LLM-based multi-agent applications
LiteMultiAgent is a lightweight and extensible multi-agent reinforcement learning (MARL) platform designed for rapid experimentation. It allows researchers to design and test coordination, competition, and collaboration scenarios in simulated environments. -
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Prompt Engineering Techniques
Collection of tutorials for Prompt Engineering techniques
Prompt Engineering Techniques is a focused companion repository that teaches prompt engineering systematically, from fundamentals to advanced strategies. It contains around twenty-plus hands-on Jupyter notebooks, each dedicated to a specific technique such as basic prompt structures, prompt templates and variables, zero-shot prompting, few-shot prompting, chain-of-thought, self-consistency, constrained generation, role prompting, task decomposition, and more. The tutorials are designed to be practical; you can run them directly, examine the prompts, and see how small changes affect model behavior and quality. ... -
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GLM-V
GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning
GLM-V is an open-source vision-language model (VLM) series from ZhipuAI that extends the GLM foundation models into multimodal reasoning and perception. The repository provides both GLM-4.5V and GLM-4.1V models, designed to advance beyond basic perception toward higher-level reasoning, long-context understanding, and agent-based applications. GLM-4.5V builds on the flagship GLM-4.5-Air foundation (106B parameters, 12B active), achieving state-of-the-art results on 42 benchmarks across image, video, document, GUI, and grounding tasks. It introduces hybrid training for broad-spectrum reasoning and a Thinking Mode switch to balance speed and depth of reasoning. ... -
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DataFrame
C++ DataFrame for statistical, Financial, and ML analysis
...You can multi-column sort, custom pick, and delete the data. DataFrame also includes a large collection of analytical algorithms in the form of visitors. These are from basic stats such as Mean, and Std Deviation and return, … to more involved analysis such as Affinity Propagation, Polynomial Fit, and Fast Fourier transform of arbitrary length … including a good collection of trading indicators. You can also easily add your own algorithms. -
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Pedalboard
A Python library for audio
pedalboard is a Python library for working with audio: reading, writing, rendering, adding effects, and more. It supports the most popular audio file formats and a number of common audio effects out of the box and also allows the use of VST3® and Audio Unit formats for loading third-party software instruments and effects. pedalboard was built by Spotify’s Audio Intelligence Lab to enable using studio-quality audio effects from within Python and TensorFlow. Internally at Spotify, pedalboard... -
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Amazing-Python-Scripts
Curated collection of Amazing Python scripts
Amazing-Python-Scripts is a collaborative repository that collects a wide variety of Python scripts designed to demonstrate practical programming techniques and automation tasks. The project includes scripts ranging from beginner-level utilities to more advanced applications involving machine learning, data processing, and system automation. Its goal is to provide developers with useful coding examples that can solve everyday problems, automate repetitive tasks, or serve as learning... -
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Learn PyTorch for Deep Learning
Materials for the Learn PyTorch for Deep Learning
Learn PyTorch for Deep Learning is an open-source educational repository that provides the full learning materials for the “Learn PyTorch for Deep Learning: Zero to Mastery” course created by Daniel Bourke. The project is designed to teach beginners how to build deep learning models using PyTorch through a hands-on, code-first learning approach. Instead of focusing heavily on theory alone, the repository encourages learners to experiment with code and develop practical machine learning... -
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Lecca.io
Lecca.io | AI Agents & Automations
Lecca.io is an AI platform that allows you to configure and deploy Large Language Models (LLMs) equipped with powerful tools and workflows. Build, customize, and automate your AI agents with ease. -
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PaddlePaddle
PArallel Distributed Deep LEarning: Machine Learning Framework
...It is the only independent R&D deep learning platform in China, and has been widely adopted in various sectors including manufacturing, agriculture and enterprise service. PaddlePaddle covers core deep learning frameworks, basic model libraries, end-to-end development kits and more, with support for both dynamic and static graphs. -
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llm_interview_note
Mainly record the knowledge and interview questions
...The repository also explores practical engineering concerns including distributed training strategies, dataset construction, model parameters, and scaling techniques used in large-scale machine learning systems. By organizing topics in a hierarchical documentation format, it enables readers to progress from basic NLP concepts to advanced topics like mixture-of-experts architectures and large-scale training frameworks. -
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Optax
Optax is a gradient processing and optimization library for JAX
...It is designed to facilitate research by providing building blocks that can be recombined in custom ways in order to optimize parametric models such as, but not limited to, deep neural networks. We favor focusing on small composable building blocks that can be effectively combined into custom solutions. Others may build upon these basic components in more complicated abstractions. Whenever reasonable, implementations prioritize readability and structuring code to match standard equations, over code reuse. -
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NeuroMatch Academy (NMA)
NMA Computational Neuroscience course
...We have curated a curriculum that spans most areas of computational neuroscience (a hard task in an increasingly big field!). We will expose you to both theoretical modeling and more data-driven analyses. The Neuro Video Series is a series of 12 videos that covers basic neuroscience concepts and neuroscience methods. These videos are completely optional and do not need to be watched in a fixed order so you can pick and choose which videos will help you brush up on your knowledge. The pre-reqs refresher days are asynchronous, so you can go through the material on your own time. You will learn how to code in Python from scratch using a simple neural model, the leaky integrate-and-fire model, as a motivation. ... -
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IP as Logo
Compact Agent Skill for simplified neo-skeuomorphic IP mascot logos
...It treats each result as a logo first, emphasizing bold rounded silhouettes, restrained detail, and subtle neo-skeuomorphic shading. The skill limits designs to a small number of basic shapes and normally uses three semantic colors. It proposes three design directions before generating six independent candidate images after approval. Composition rules favor large lower-corner crops, clear identifying features, and opaque square output. The skill follows the open Agent Skills format and can work across supported agents rather than depending on one specific AI product. -
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micrograd
A tiny scalar-valued autograd engine and a neural net library
...The repository is intentionally compact and readable, prioritizing clarity over performance so learners can follow every step of gradient flow and parameter updates. It is commonly used as a learning bridge between basic calculus intuition and full-scale deep learning frameworks, helping developers understand why autodiff libraries behave the way they do. -
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Reader 3
Quick illustration of how one can easily read books together with LLMs
...It was created primarily as a simple demonstration of how to combine local book reading with LLM workflows without heavy dependencies or complicated setup, and it runs with just a small Python script and a basic HTTP server. The interface focuses on clarity and ease of use, offering straightforward navigation of book chapters rather than full-featured e-reading capabilities. While it lacks advanced features like built-in annotations or rich media support, its simplicity is intentional, enabling users to quickly load EPUBs, view them in a browser, and even repurpose text for downstream tasks. -
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video2robot
End-to-end pipeline converting generative videos
...This workflow allows users to generate robot motion files that specify joint angles, root positions, and orientations that can be deployed on supported robot platforms (e.g., Unitree models). Video2robot includes scripts for each stage of the pipeline (generation, extraction, conversion, visualization) and can run as a CLI or through a basic web UI.
