Search Results for "llm for java developers" - Page 2
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Showing 714 open source projects for "llm for java developers"
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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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Gemma
Gemma open-weight LLM library, from Google DeepMind
...Through included tutorials and Colab notebooks, users can explore examples covering sampling, multi-modal interactions, and fine-tuning workflows. By providing accessible open-weight models, Gemma enables researchers and developers to experiment with state-of-the-art LLM architectures. -
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garak
Developers and anyone seeking an LLM solution to scan for vulnerabilit
garak checks if an LLM can be made to fail in a way we don't want. garak probes for hallucination, data leakage, prompt injection, misinformation, toxicity generation, jailbreaks, and many other weaknesses. garak's a free tool, we love developing it and are always interested in adding functionality to support applications. garak is a command-line tool, it's developed in Linux and OSX. Just grab it from PyPI and you should be good to go. The standard pip version of garak is updated... -
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Instructor
Structured outputs for llms
Instructor is a tool that enables developers to extract structured data from natural language using Large Language Models (LLMs). Integrating with Python's Pydantic library allows users to define desired output structures through type hints, facilitating schema validation and seamless integration with IDEs. Instructor supports various LLM providers, including OpenAI, Anthropic, Litellm, and Cohere, offering flexibility in implementation. -
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Sagify
LLMs and Machine Learning done easily
Sagify is a tool designed to simplify the process of deploying and managing machine learning models, including Large Language Models (LLMs), on AWS SageMaker. It abstracts the complexities involved in setting up and managing SageMaker resources, allowing developers to focus on building and fine-tuning models. Sagify provides a command-line interface (CLI) and supports various machine-learning frameworks, making it accessible for a wide range of users. -
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langrocks
Tools like web browser, computer access and code runner for LLMs
Langrocks is a programming language experimentation toolkit that enables developers to create, test, and optimize custom programming languages. -
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LangChain.js
Building applications with LLMs through composability
Building applications with LLMs through composability. Large language models (LLMs) are emerging as a transformative technology, enabling developers to build applications that they previously could not. But using these LLMs in isolation is often not enough to create a truly powerful app - the real power comes when you can combine them with other sources of computation or knowledge. This library is aimed at assisting in the development of those types of applications. This is built to... -
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codename goose
AI coding agent that's more than suggestions - install, execute, edit+
...By leveraging Goose, developers can improve productivity and code quality through advanced AI-driven assistance. -
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MCP Go
A Go implementation of the Model Context Protocol (MCP)
mcp-go is a Go implementation of the Model Context Protocol (MCP), designed to enable seamless integration between Large Language Model (LLM) applications and external data sources and tools. It abstracts the complexities of the protocol and server management, allowing developers to focus on building robust tools. The library is high-level and user-friendly, facilitating the development of MCP servers in Go. -
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Beta9
Run serverless GPU workloads with fast cold starts on bare-metal
beta9 is a platform that enables running serverless GPU workloads with fast cold starts on bare-metal servers globally. It allows developers to deploy and scale GPU-accelerated applications without managing underlying infrastructure, offering flexibility and efficiency for AI and high-performance computing tasks. beta9 supports various frameworks and provides tools for monitoring and managing deployments effectively. -
Keep company data safe with Chrome EnterpriseMake AI work your way with Chrome Enterprise. Block unapproved sites and set custom data controls that align with your company's policies.
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Helicone
Open source LLM-Observability Platform for Developers
Open source LLM-Observability Platform for Developers. One-line integration for monitoring, metrics, evals, agent tracing, prompt management, playground, etc. Supports OpenAI SDK, Vercel AI SDK, Anthropic SDK, LiteLLM, LLamaIndex, LangChain, and more. -
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Gitleaks
Protect and discover secrets using Gitleaks
Gitleaks is a fast, lightweight, portable, and open-source secret scanner for git repositories, files, and directories. With over 6.8 million docker downloads, 11.2k GitHub stars, 1.7 million GitHub Downloads, thousands of weekly clones, and over 400k homebrew installs, gitleaks is the most trusted secret scanner among security professionals, enterprises, and developers. Gitleaks-Action is our official GitHub Action. You can use it to automatically run a gitleaks scan on all your team's pull... -
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cognee
Deterministic LLMs Outputs for AI Applications and AI Agents
We build for developers who need a reliable, production-ready data layer for AI applications. 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. -
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Superduper
Superduper: Integrate AI models and machine learning workflows
Superduper is a Python-based framework for building end-2-end AI-data workflows and applications on your own data, integrating with major databases. It supports the latest technologies and techniques, including LLMs, vector-search, RAG, and multimodality as well as classical AI and ML paradigms. Developers may leverage Superduper by building compositional and declarative objects that out-source the details of deployment, orchestration versioning, and more to the Superduper engine. This... -
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Qwen
The official repo of Qwen chat & pretrained large language model
Qwen is a series of large language models developed by Alibaba Cloud, consisting of various pretrained versions like Qwen-1.8B, Qwen-7B, Qwen-14B, and Qwen-72B. These models, which range from smaller to larger configurations, are designed for a wide range of natural language processing tasks. They are openly available for research and commercial use, with Qwen's code and model weights shared on GitHub. Qwen's capabilities include text generation, comprehension, and conversation, making it a... -
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CodeGeeX
CodeGeeX: An Open Multilingual Code Generation Model (KDD 2023)
CodeGeeX is a large-scale multilingual code generation model with 13 billion parameters, trained on 850B tokens across more than 20 programming languages. Developed with MindSpore and later made PyTorch-compatible, it is capable of multilingual code generation, cross-lingual code translation, code completion, summarization, and explanation. It has been benchmarked on HumanEval-X, a multilingual program synthesis benchmark introduced alongside the model, and achieves state-of-the-art... -
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MagicAPI AI Gateway
Built for demanding AI workflows
The world's fastest AI Gateway proxy, written in Rust and optimized for maximum performance. This high-performance API gateway routes requests to various AI providers (OpenAI, GROQ) with streaming support, making it perfect for developers who need reliable and blazing-fast AI API access. -
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ExecuTorch
On-device AI across mobile, embedded and edge for PyTorch
ExecuTorch is an end-to-end solution for enabling on-device inference capabilities across mobile and edge devices including wearables, embedded devices and microcontrollers. It is part of the PyTorch Edge ecosystem and enables efficient deployment of PyTorch models to edge devices. -
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ncnn
High-performance neural network inference framework for mobile
ncnn is a high-performance neural network inference computing framework designed specifically for mobile platforms. It brings artificial intelligence right at your fingertips with no third-party dependencies, and speeds faster than all other known open source frameworks for mobile phone cpu. ncnn allows developers to easily deploy deep learning algorithm models to the mobile platform and create intelligent APPs. It is cross-platform and supports most commonly used CNN networks, including... -
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Groq Python
The official Python Library for the Groq API
Groq Python is the official Python SDK for the Groq REST API, giving Python developers straightforward access to Groq’s LLM, chat, audio, and other AI services. Through this library, you can call Groq’s models from Python code — for example to request chat completions, code generation, transcription, or any supported endpoint — using idiomatic Python syntax. The SDK handles authentication (via environment variable or parameter), defines proper type-safe request/response data types, and supports both synchronous and asynchronous usage patterns depending on your application needs. ... -
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Adversarial Robustness Toolbox
Adversarial Robustness Toolbox (ART) - Python Library for ML security
Adversarial Robustness Toolbox (ART) is a Python library for Machine Learning Security. ART provides tools that enable developers and researchers to evaluate, defend, certify and verify Machine Learning models and applications against the adversarial threats of Evasion, Poisoning, Extraction, and Inference. ART supports all popular machine learning frameworks (TensorFlow, Keras, PyTorch, MXNet, sci-kit-learn, XGBoost, LightGBM, CatBoost, GPy, etc.), all data types (images, tables, audio,... -
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Secret Llama
Fully private LLM chatbot that runs entirely with a browser
Secret Llama is a privacy-first large-language-model chatbot that runs entirely inside your web browser, meaning no server is required and your conversation data never leaves your device. It focuses on open-source model support, letting you load families like Llama and Mistral directly in the client for fully local inference. Because everything happens in-browser, it can work offline once models are cached, which is helpful for air-gapped environments or travel. The interface mirrors the... -
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ModelScope
Bring the notion of Model-as-a-Service to life
ModelScope is built upon the notion of “Model-as-a-Service” (MaaS). It seeks to bring together most advanced machine learning models from the AI community, and streamlines the process of leveraging AI models in real-world applications. The core ModelScope library open-sourced in this repository provides the interfaces and implementations that allow developers to perform model inference, training and evaluation. In particular, with rich layers of API abstraction, the ModelScope library offers... -
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bolt.diy
Prompt, run, edit, & deploy full-stack web applications using any LLM
bolt.diy is an open-source platform that allows you to easily create, run, edit, and deploy full-stack web applications using a variety of large language models (LLMs). It supports popular models like OpenAI, Anthropic, Ollama, OpenRouter, Gemini, LMStudio, Mistral, xAI, HuggingFace, DeepSeek, and Groq, and provides the flexibility to integrate additional models through the Vercel AI SDK. Whether you’re experimenting with pre-built models or developing custom AI-driven applications, bolt.diy... -
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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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FastMCP
The fast, Pythonic way to build Model Context Protocol servers
FastMCP is a Pythonic framework designed to simplify the creation of MCP servers. It allows developers to build servers that provide context and tools to Large Language Models (LLMs) using clean and intuitive Python code, streamlining the integration process between AI models and external resources.
