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Showing 992 open source projects for "python ai"
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Gen AI apps are built with MongoDB AtlasMongoDB Atlas provides built-in vector search and a flexible document model so developers can build, scale, and run gen AI apps without stitching together multiple databases. From LLM integration to semantic search, Atlas simplifies your AI architecture—and it’s free to get started.
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lightning AI
The most intuitive, flexible, way for researchers to build models
Build in days not months with the most intuitive, flexible framework for building models and Lightning Apps (ie: ML workflow templates) which "glue" together your favorite ML lifecycle tools. Build models and build/publish end-to-end ML workflows that "glue" your favorite tools together. Models are “easy”, the “glue” work is hard. Lightning Apps are community-built templates that stitch together your favorite ML lifecycle tools into cohesive ML workflows that can run on your laptop or any... -
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CAMEL AI
Finding the Scaling Law of Agents. A multi-agent framework
The rapid advancement of conversational and chat-based language models has led to remarkable progress in complex task-solving. However, their success heavily relies on human input to guide the conversation, which can be challenging and time-consuming. This paper explores the potential of building scalable techniques to facilitate autonomous cooperation among communicative agents and provide insight into their "cognitive" processes. To address the challenges of achieving autonomous... -
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Lepton AI
A Pythonic framework to simplify AI service building
A Pythonic framework to simplify AI service building. Cutting-edge AI inference and training, unmatched cloud-native experience, and top-tier GPU infrastructure. Ensure 99.9% uptime with comprehensive health checks and automatic repairs. -
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HexStrike AI MCP Agents
HexStrike AI MCP Agents is an advanced MCP server
HexStrike AI is an MCP server that lets LLM agents autonomously operate a large catalog of offensive-security tools. Its goal is to bridge “language models” and practical pentest workflows—enumeration, exploitation, vulnerability discovery, and bug bounty reconnaissance—under safe, auditable controls. The server exposes typed tools and guardrails so agent prompts translate to concrete, parameterized actions rather than brittle shell strings. It ships with curated tool adapters, task... -
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Pruna AI
Pruna is a model optimization framework built for developers
Pruna is an open-source, self-hostable AI inference engine designed to help teams deploy and manage large language models (LLMs) efficiently across private or hybrid infrastructures. Built with performance and developer ergonomics in mind, Pruna simplifies inference workflows by enabling multi-model orchestration, autoscaling, GPU resource allocation, and compatibility with popular open-source models. It is ideal for companies or teams looking to reduce reliance on external APIs while... -
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Generative AI Docs
Documentation for Google's Gen AI site - including Gemini API & Gemma
Generative AI Docs is Google’s official documentation repository for Gemini, Vertex AI, and related generative AI APIs. It contains guides, API references, and examples for developers building applications using Google’s large language models, text-to-image models, embeddings, and multimodal capabilities. The repository includes markdown source files that power the Google AI developer documentation site, as well as sample code snippets in Python, JavaScript, and other languages that demonstrate... -
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TorchMetrics AI
Machine learning metrics for distributed, scalable PyTorch application
TorchMetrics is a collection of 100+ PyTorch metrics implementations and an easy-to-use API to create custom metrics. -
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AI Chatbot Framework
Python chatbot framework with Natural Language Understanding
Building a chatbot can sound daunting, but it’s totally doable. AI Chatbot Framework is an AI powered conversational dialog interface built in Python. With this tool, it’s easy to create Natural Language conversational scenarios with no coding efforts whatsoever. The smooth UI makes it effortless to create and train conversations to the bot and it continuously gets smarter as it learns from conversations it has with people. AI Chatbot Framework can live on any channel of your choice... -
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Klavis AI
Open Source MCP integration for AI applications
Klavis AI is an open-source platform that simplifies the integration of Model Context Protocols (MCPs) into AI applications. It provides hosted, secure MCP servers with built-in OAuth support, eliminating the need for complex authentication management and client-side code. Klavis AI enables developers to connect AI agents to various tools and services efficiently, facilitating scalable and secure AI deployments. -
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Arcade AI
Arcade Tool Development Kit (TDK), Worker, Evals, and CLI
Arcade AI Platform is a developer-oriented toolkit for building, deploying, and managing tools tailored to AI agents, structured as modular Python packages for flexibility and extensibility. Core platform functionality and schemas. This repository contains the core Arcade libraries, organized as separate packages for maximum flexibility and modularity. Evaluation framework for testing tool performance. Test your MCP server's tools, resources, prompts, elicitation, and OAuth 2. MCPJam... -
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AI Hedge Fund
An AI Hedge Fund Team
This repository demonstrates how to build a simplified, automated hedge fund strategy powered by AI/ML. It integrates financial data collection, preprocessing, feature engineering, and predictive modeling to simulate decision-making in trading. The code shows workflows for pulling stock or market data, applying machine learning algorithms to forecast trends, and generating buy/sell/hold signals based on the predictions. Its structure is educational: intended more as a proof-of-concept than... -
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Ludwig AI
Low-code framework for building custom LLMs, neural networks
Declarative deep learning framework built for scale and efficiency. Ludwig is a low-code framework for building custom AI models like LLMs and other deep neural networks. Declarative YAML configuration file is all you need to train a state-of-the-art LLM on your data. Support for multi-task and multi-modality learning. Comprehensive config validation detects invalid parameter combinations and prevents runtime failures. Automatic batch size selection, distributed training (DDP, DeepSpeed... -
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Colossal-AI
Making large AI models cheaper, faster and more accessible
..., distributed training, especially model parallelism, often requires domain expertise in computer systems and architecture. It remains a challenge for AI researchers to implement complex distributed training solutions for their models. Colossal-AI provides a collection of parallel components for you. We aim to support you to write your distributed deep learning models just like how you write your model on your laptop. -
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README-AI
README file generator, powered by AI
README-AI is an automated documentation generator that creates structured README files for GitHub repositories using AI-powered analysis. -
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Generative AI for Beginners (Version 3)
21 Lessons, Get Started Building with Generative AI
Generative AI for Beginners is a 21-lesson course by Microsoft Cloud Advocates that teaches the fundamentals of building generative AI applications in a practical, project-oriented way. Lessons are split into “Learn” modules for core concepts and “Build” modules with hands-on code in Python and TypeScript, so you can jump in at any point that matches your goals. The course covers everything from model selection, prompt engineering, and chat/text/image app patterns to secure development... -
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AIQuant
AI-powered platform for quantitative trading
ai_quant_trade is an AI-powered, one-stop open-source platform for quantitative trading—ranging from learning and simulation to actual trading. It consolidates stock trading knowledge, strategy examples, factor discovery, traditional rules-based strategies, various machine learning and deep learning methods, reinforcement learning, graph neural networks, high-frequency trading, C++ deployment, and Jupyter Notebook examples for practical hands-on use. Stock trading strategies: large models... -
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llama.cpp Python Bindings
Python bindings for llama.cpp
llama-cpp-python provides Python bindings for llama.cpp, enabling the integration of LLaMA (Large Language Model Meta AI) language models into Python applications. This facilitates the use of LLaMA's capabilities in natural language processing tasks within Python environments. -
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OpenAI Python
The official Python library for the OpenAI API
The OpenAI Python library provides convenient access to the OpenAI REST API from any Python 3.7+ application. The library includes type definitions for all request params and response fields, and offers both synchronous and asynchronous clients powered by httpx. -
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Python Client For NLP Cloud
NLP Cloud serves high performance pre-trained or custom models for NER
NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, dialogue summarization, paraphrasing, intent classification, product description and ad generation, chatbot, grammar and spelling correction, keywords and keyphrases extraction, text generation, image generation, blog post generation, source code generation, question answering, automatic speech recognition, machine translation, language detection, semantic search,... -
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Ollama Python
Ollama Python library
ollama-python is an open-source Python SDK that wraps the Ollama CLI, allowing seamless interaction with local large language models (LLMs) managed by Ollama. Developers use it to load models, send prompts, manage sessions, and stream responses directly from Python code. It simplifies integration of Ollama-based models into applications, supporting synchronous and streaming modes. This tool is ideal for those building AI-driven apps with local model deployment. -
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State of Open Source AI
Clarity in the current fast-paced mess of Open Source innovation
This repository is the source for a book (or large written work) titled “The State of Open Source AI”. The goal of the project is to bring clarity to the rapidly evolving open-source AI ecosystem by documenting trends, models, tools, standards, deployment practices, and challenges. It acts as both a snapshot and a guide: readers can see what’s “hot now” in open AI infrastructure, what open licensing or governance issues are emerging, how deployment options compare, and what gaps remain. Because... -
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Sweep AI
Sweep: AI-powered Junior Developer for small features and bug fixes
Let Sweep handle your tech debt so you can focus on the exciting problems. Sweep is an AI junior developer that transforms bug reports & feature requests into code changes. Describe bugs, small features, and refactors like you would to a junior developer and Sweep. -
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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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Super Easy AI Installer Tool
Application that simplifies the installation of AI-related projects
"Super Easy AI Installer Tool" is a user-friendly application that simplifies the installation process of AI-related repositories for users. The tool is designed to provide an easy-to-use solution for accessing and installing AI repositories with minimal technical hassle to none the tool will automatically handle the installation process, making it easier for users to access and use AI tools. "Super Easy AI Installer Tool" is currently in early development phase and may have a few bugs... -
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Anthropic SDK Python
Provides convenient access to the Anthropic REST API from any Python 3
The anthropic-sdk-python repository is the official Python client library for interacting with the Anthropic (Claude) REST API. It is designed to provide a user-friendly, type-safe, and asynchronous/synchronous capable interface for making chat/completion requests to models like Claude. The library includes definitions for all request and response parameters using Python typed objects, automatically handles serialization and deserialization, and wraps HTTP logic (timeouts, retries, error...
