Search Results for "ai coding model"
Sort By:
Showing 45 open source projects for "ai coding model"
View related business solutions-
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
1
RuoYi AI
Enterprise AI platform for building, deploying, and managing apps
RuoYi AI is a full-stack enterprise-oriented AI development platform designed to help developers rapidly build, deploy, and manage intelligent applications using modern large language models and AI ecosystems. It provides a unified framework for integrating multiple AI models from different providers, allowing teams to switch or combine models through a consistent interface without vendor lock-in. RuoYi AI includes built-in support for retrieval-augmented generation, enabling organizations... -
2
JADX-AI-MCP
Plugin for JADX to integrate MCP server
JADX-AI-MCP is an open-source plugin that integrates large language models into the JADX Android decompiler to assist with reverse engineering and code analysis tasks. The project connects JADX with AI assistants through the Model Context Protocol, enabling language models to interact directly with decompiled Android application code. Through this integration, AI systems can inspect classes, analyze methods, retrieve application manifests, and examine other elements of Android packages in real time. ... -
3
Spring AI Alibaba Examples
Spring AI Alibaba examples for building and testing AI apps
...Each module focuses on a specific use case such as chat, image processing, audio handling, graph workflows, and retrieval-augmented generation. The examples highlight how to integrate AI models, manage prompts, handle memory, and build multi-model or multi-agent workflows. Developers can explore individual project folders for detailed instructions and implementation guidance. Spring AI Alibaba Examples also supports experimentation through playground modules and encourages contributions to expand real-world AI use cases and improve development practices. -
4
Ghidra MCP
Socket based MCP Server for Ghidra
GhidraMCP is a Ghidra plugin implementing the Model Context Protocol, bridging Ghidra's reverse engineering capabilities with AI assistants to enhance binary analysis tasks. -
Forever Free Full-Stack Observability | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
-
5
Wanaku
Wanaku MCP Router
Wanaku is an MCP Router designed to connect AI-enabled applications using the Model Context Protocol. Built on top of Apache Camel and Quarkus, it offers unmatched connectivity, speed, and reliability for AI agents, facilitating seamless integration across various services and platforms. -
6
JAI Workflow
Build programmatically custom agentic workflows, AI Agents, RAG system
JAI-Workflow is a framework for building and managing machine learning workflows, streamlining the process from data ingestion to model deployment. -
7
DevoxxGenie
DevoxxGenie is a plugin for IntelliJ IDEA that uses local LLM's
Devoxx Genie is a fully Java-based LLM Code Assistant plugin for IntelliJ IDEA, designed to integrate with local LLM providers such as Ollama, LMStudio, GPT4All, Llama.cpp, and Exo but also cloud-based LLMs such as OpenAI, Anthropic, Mistral, Groq, Gemini, DeepInfra, DeepSeek, OpenRouter and Azure OpenAI. -
8
Wren Engine
The Semantic Engine for Model Context Protocol(MCP)
Wren Engine is a semantic engine designed to empower Model Context Protocol (MCP) clients and AI agents by providing accurate, contextual, and governed access to business data. It serves as a bridge between large language models (LLMs) and enterprise systems, facilitating seamless integration and interaction. -
9
FIT Framework
An enterprise-level AI development framework
FIT Framework is an open-source infrastructure designed to support the development, training, and evaluation of machine learning and AI models through a modular and scalable architecture. It aims to streamline the lifecycle of AI systems by providing standardized components for data processing, model training, evaluation, and deployment. The framework is particularly useful for research and production environments where reproducibility and consistency are critical, as it enforces structured workflows and configurable pipelines. ... -
Try Google Cloud Risk-Free With $300 in CreditUse your credit across every product. Compute, storage, AI, analytics. When it runs out, 20+ products stay free. You only pay when you choose to.
-
10
Brokk
Brokk brings code intelligence to AI
Brokk is a code intelligence assistant framework designed to let large language models (LLMs) understand code semantically (not just as raw text) so that they can work effectively on large codebases that don’t fit wholly in a prompt context. It helps bridge the gap between LLMs and real-world engineering code by offering tooling to index, analyze, query, and augment code context, so that AI can meaningfully reason about existing code, suggest edits, and navigate across projects. Modular... -
11
Astron Agent
Enterprise platform for building and orchestrating AI agent workflows
Astron Agent is an enterprise-grade platform designed for building and managing intelligent AI agent workflows in production environments. It provides a development environment that combines workflow orchestration, model management, and integration with various AI tools and services. Astron Agent enables organizations to design complex agent-driven processes that coordinate models, automation tools, and enterprise systems. It also integrates robotic process automation capabilities so agents can execute tasks across digital systems instead of only generating responses. ... -
12
Azure CLI MCP
Talk with Azure using MCP
An MCP server that enables AI assistants to interact with Microsoft Azure via the Azure CLI, allowing tasks such as listing resources, checking configurations, fixing issues, and creating new resources through conversational commands. -
13
Agent Development Kit (ADK) for Java
An open-source, code-first Java toolkit
...ADK is designed to be flexible and modular so that developers can build simple automation agents or large distributed agent systems depending on their needs. While it integrates well with Google’s AI ecosystem, the framework is designed to remain model-agnostic and compatible with different machine learning platforms. -
14
Solon
Java enterprise application development framework
Solon is a full-scenario Java enterprise application framework that positions itself as a lean, high-performance alternative to heavy stacks. It advertises large concurrency gains, lower memory use, much faster startup, and dramatically smaller packages while remaining compatible from Java 8 through Java 24. The framework focuses on restrained APIs and an open ecosystem, with modules that cover web, data, cloud, and microservice patterns. Its messaging emphasizes “replaceable Spring”... -
15
LangChain for Java
LangChain4j is an open-source Java library
LangChain for Java is an open-source Java framework designed to simplify the development of applications powered by large language models. The library provides a unified API that allows developers to connect Java applications to multiple AI providers and embedding databases without having to implement separate integrations for each service. Its architecture includes abstractions for prompts, chat interactions, document processing, embeddings, and vector storage, enabling developers to build... -
16
Jlama
Jlama is a modern LLM inference engine for Java
...Unlike frameworks that require external APIs or remote services, Jlama performs inference directly on a machine using pre-trained models. This allows organizations to integrate generative AI features into their systems while maintaining full control over data privacy and infrastructure. The engine supports a wide range of open-source model architectures and formats, including variants of Llama, Mistral, and other transformer-based models. It provides tools for running chat interactions, completing prompts, or exposing an OpenAI-compatible REST API for applications that expect standard LLM endpoints. ... -
17
PC_Workman_HCK
AI-powered PC monitoring that explains. Not shows numbers/spikes.
PC_Workman is what 680 hours of coding after warehouse shifts looks like. Built on a laptop hitting 94°C, this AI-powered monitoring tool does what Task Manager can't: it understands your system, not just measures it. Features: - Time travel monitoring - debug issues from hours ago - AI diagnostics with HCK_GPT - Custom fan curves with profiles - Floating always-on-top widget - 2D system map - Cross-GPU support (NVIDIA/AMD/Intel) Four complete rebuilds. 29 features killed. 24,000 lines of optimized code. ... -
18
ChatGPT Java
A Java client for the ChatGPT API
ChatGPT Java is a Java client for the ChatGPT API. Use official API with model gpt-3.5-turbo. -
19
elevenlabs-api
elevenlabs-api is an open source Java wrapper around the ElevenLabs
...To set up your ElevenLabs API key, you must register it with the ElevenLabsAPI Java API. For any public repository security, you should store your API key in an environment variable, or external from your source code. The most realistic and versatile AI speech software, ever. Eleven brings the most compelling, rich and lifelike voices to creators and publishers seeking the ultimate tools for storytelling. Generate top-quality spoken audio in any voice and style with the most advanced and multipurpose AI speech tool out there. Our deep learning model renders human intonation and inflections with unprecedented fidelity and adjusts delivery based on context. -
20
Intelligent Java
Integrate with the latest language models, image generation and speech
...The library provides an intuitive functions for sending input to models like ChatGPT and DALL·E, and receiving generated text, speech or images. With just a few lines of code, you can easily access the power of cutting-edge AI models to enhance your projects. Access ChatGPT, GPT3 to generate text and DALL·E to generate images. OpenAI is preferred for quality results without tuning. Generate text; Cohere allows you to generate a language model to suit your specific needs. Generate audio from text; Access DeepMind’s speech models. The only dependencies is GSON. ... -
21
DeepCode for Visual Studio Code
DeepCode extension for Visual Studio Code
DeepCode AI has always been the backbone of Snyk code, which is why it's the fastest, most accurate SAST on the market. DeepCode AI, powering the Snyk platform, utilizes multiple AI models, is trained on security-specific data, and is all curated by top security researchers to give you all the power of AI without any of the drawbacks. With 11 supported languages, and multiple AI models, Snyk's DeepCode AI was designed to find and fix vulnerabilities and manage tech debt. DeepCode AI powers... -
22
commit-autosuggestions
A tool that AI automatically recommends commit messages
This is implementation of CommitBERT: Commit Message Generation Using Pre-Trained Programming Language Model. CommitBERT is accepted in ACL workshop : NLP4Prog. Have you ever hesitated to write a commit message? Now get a commit message from Artificial Intelligence! CodeBERT: A Pre-Trained Model for Programming and Natural Languages introduces a pre-trained model in a combination of Program Language and Natural Language(PL-NL). It also introduces the problem of converting code into natural... -
23
SQLFlow
SQL compiler bridging databases and machine learning workflows
...By embedding machine learning operations into SQL, it removes the need for users to switch between programming languages such as Python or R, simplifying the overall workflow. SQLFlow also supports model training, prediction, and explanation tasks, allowing data practitioners to work entirely within a familiar query interface. -
24
The MCAPL Project provides a tool for prototyping BDI agent programming languages and model checking programs written in these languages via an interface to the JavaPathfinder model checker.
-
25
This project develops a Java API and tools to specify and execute organisations for multiagent systems based on Moise model. This model is built upon concepts like groups, roles, global goals and plans, and obligations.
