Search Results for "simple ai"
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Showing 17 open source projects for "simple ai"
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LLPhant
A comprehensive PHP Generative AI Framework
LLPhant is a PHP-based generative AI framework designed to bring large language model capabilities into modern PHP applications with a structure inspired by frameworks like LangChain. It provides developers with a set of abstractions for building AI-powered features such as chat systems, retrieval pipelines, and automated workflows while remaining simple enough to integrate into existing Symfony or Laravel projects. -
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PromptingTools.jl
Streamline your life using PromptingTools.jl
...It focuses on reducing the complexity of prompt creation by introducing templating systems, macros, and reusable functions that standardize how prompts are constructed and executed. The library provides a family of ai* functions that handle tasks such as generation, embeddings, classification, and data extraction, all following a consistent structure. It supports multiple backends, including OpenAI-compatible APIs and local models such as those served through Ollama, allowing users to switch providers without rewriting prompts. The toolkit also includes advanced capabilities such as asynchronous execution, routing, OCR, and experimental agent workflows, making it suitable for both simple and complex AI applications. -
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Groq TypeScript / Node.s
The official Node.js / Typescript library for the Groq API
Groq TypeScript / Node.s (also often referred to as “groq-sdk” on npm) is the official Node.js / TypeScript client library for Groq’s REST API, enabling JavaScript/TypeScript developers to integrate LLM and AI-powered services into web backends, serverless functions, or frontend apps. It exports strongly-typed interfaces for models, chat completions, file uploads (e.g. for audio transcription), and other endpoints, allowing for better type safety and developer experience when using Groq from... -
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Writer Framework
No-code in the front, Python in the back. An open-source framework
Writer Framework is an open source platform designed to help developers build AI-powered applications by combining a visual interface builder with a Python-based backend architecture. It follows a hybrid approach where user interfaces are created using a drag-and-drop editor while business logic is implemented in Python, allowing teams to balance speed and flexibility without sacrificing control. The framework is particularly focused on AI use cases, enabling developers to integrate large... -
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5
Google Cloud Platform Go Samples
Sample apps and code written for Google Cloud
...Each sample is designed to be easily reusable, allowing developers to copy code directly into their own projects as a starting point for development. The repository includes both simple quickstart examples and more advanced application patterns, often accompanied by documentation guides that explain how to deploy and run them in different environments. It also showcases integrations with services such as Pub/Sub, BigQuery, Cloud Functions, and Vertex AI, helping developers understand how to orchestrate distributed systems in Go. -
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Ollama-rs
A simple and easy-to-use library for interacting with the Ollama API
Ollama-rs is a Rust library designed to provide a simple and efficient interface for interacting with the Ollama API, enabling developers to integrate local large language models into Rust applications. It follows the official Ollama API closely, ensuring compatibility while offering an idiomatic Rust experience with strong typing and asynchronous execution. The library supports a wide range of operations, including text generation, chat interactions, embeddings, and model management, making it suitable for both simple applications and more advanced AI workflows. ... -
7
Ollama-Laravel Package
Ollama-Laravel is a Laravel package providing seamless integration
...It abstracts the Ollama API into a developer-friendly facade, allowing Laravel developers to interact with models using familiar patterns such as service containers, configuration files, and fluent method chaining. The package supports a wide range of AI capabilities including text generation, chat-based interactions, embeddings, and multimodal vision analysis, making it suitable for both simple features and complex AI-driven systems. It also includes support for reasoning models and function calling, enabling developers to build more advanced workflows where models can trigger tools or structured actions. ... -
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Google Kubernetes Engine (GKE) Samples
Sample applications for Google Kubernetes Engine (GKE)
...It serves as a practical companion to official GKE tutorials, providing real, runnable code that illustrates how containerized applications are packaged, deployed, and scaled within Kubernetes clusters. The repository is organized into multiple categories such as AI and machine learning, autoscaling, networking, observability, security, and cost optimization, allowing developers to explore specific use cases and architectural patterns. It includes both simple quickstart examples, like basic “hello world” applications, and more advanced scenarios such as migrating monolithic applications to microservices, implementing service meshes, and configuring custom autoscaling metrics. -
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kagglehub
Python library to access Kaggle resources
...Its main value is making Kaggle assets easier to consume programmatically in Python-first data science and AI development workflows. -
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10
Public Image Mirror
Many images are hosted overseas, such as GCR
...This project solves the problem by offering mirrored registries with consistent image hashes and real-time synchronization. It uses a lazy-loading mechanism, caching image layers in third-party object storage, ensuring that frequently used images are delivered faster. The system is simple to use, requiring only a prefix replacement to pull images from the mirror instead of the original registry. By reducing latency and improving reliability, the service supports developers in accelerating Kubernetes, Docker, Containerd, and AI model image downloads in production environments. -
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Karpathy-Inspired Claude Code Guidelines
A single CLAUDE.md file to improve Claude Code behavior
Karpathy-Inspired Claude Code Guidelines is a curated learning and experimentation repository inspired by the work and teaching philosophy of Andrej Karpathy, designed to help learners build practical competence in deep learning, neural networks, and AI infrastructure. The project organizes a progressive path through exercises, notebooks, code examples, and practical mini-projects that echo Karpathy’s approach to “learning by doing,” where students build core concepts from first principles rather than consuming superficial abstractions. It covers topics like implementing backpropagation from scratch, understanding convolutional and recurrent networks, building simple training loops, and exploring real datasets with hands-on code. ... -
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Ollama4j
A simple Java library for interacting with Ollama server
...The library supports a wide range of core capabilities, including chat-based interactions, text generation, embeddings, and model management, making it suitable for both simple applications and more advanced AI-driven systems. It integrates seamlessly into Java ecosystems through Maven or Gradle dependencies, and it works with standard Java environments starting from JDK 11 and above. Ollama4j also includes support for advanced features such as tool or function calling, enabling models to interact with external systems and execute more complex workflows. -
13
EKS Best Practices
A best practices guide for day 2 operations
The Amazon EKS Best Practices Guide is a public repository containing comprehensive documentation and guidance for operating production-grade Kubernetes clusters on AWS’s managed service, Amazon EKS. Rather than a code library, it serves as a reference catalogue of patterns, anti-patterns, checklists and architectures across domains such as security, reliability, scalability, networking, cost optimization and hybrid cloud deployments. The repository is maintained by AWS but open to... -
14
GenAI Processors
GenAI Processors is a lightweight Python library
GenAI Processors is a lightweight Python library for building modular, asynchronous, and composable AI pipelines around Gemini. Its central abstraction is the Processor, a unit of work that consumes an asynchronous stream of parts (text, images, audio, JSON) and produces another stream, making it natural to chain operations and keep everything streaming end-to-end. Processors can be composed sequentially (to build multi-step flows) or in parallel (to fan-out work and merge results), which makes sophisticated agent behaviors easy to express with simple operators. ... -
15
Flashlight library
A C++ standalone library for machine learning
Flashlight is a fast, flexible machine learning library written entirely in C++ by Facebook AI Research and the creators of Torch, TensorFlow, Eigen, and Deep Speech. Native support in C++ and simple extensibility make Flashlight a powerful research framework that's hackable to its core and enables fast iteration on new experimental setups and algorithms with little unopinionated and without sacrificing performance. In a single repository, Flashlight provides apps for research across multiple domains. ... -
16
avldb
Simple struct storage system, database library and engine.
Very simple struct storage system, AVL and red-black tree based database library - database engine. You can define indexes over C struct. -
17
Java framework for agent based application development
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