AI tools for openmeter
Related Tools:
Open Interpreter Project
The Open Interpreter Project is an AI tool that enables users to run code on their computers to complete tasks. It offers a new way of interacting with computers by leveraging LLMs (Large Language Models). The project aims to simplify coding tasks and enhance productivity by providing a platform for executing code seamlessly.
openmeter
OpenMeter is a real-time and scalable usage metering tool for AI, usage-based billing, infrastructure, and IoT use cases. It provides a REST API for integrations and offers client SDKs in Node.js, Python, Go, and Web. OpenMeter is licensed under the Apache 2.0 License.
openshield
OpenShield is a firewall designed for AI models to protect against various attacks such as prompt injection, insecure output handling, training data poisoning, model denial of service, supply chain vulnerabilities, sensitive information disclosure, insecure plugin design, excessive agency granting, overreliance, and model theft. It provides rate limiting, content filtering, and keyword filtering for AI models. The tool acts as a transparent proxy between AI models and clients, allowing users to set custom rate limits for OpenAI endpoints and perform tokenizer calculations for OpenAI models. OpenShield also supports Python and LLM based rules, with upcoming features including rate limiting per user and model, prompts manager, content filtering, keyword filtering based on LLM/Vector models, OpenMeter integration, and VectorDB integration. The tool requires an OpenAI API key, Postgres, and Redis for operation.
beelzebub
Beelzebub is an advanced honeypot framework designed to provide a highly secure environment for detecting and analyzing cyber attacks. It offers a low code approach for easy implementation and utilizes virtualization techniques powered by OpenAI Generative Pre-trained Transformer. Key features include OpenAI Generative Pre-trained Transformer acting as Linux virtualization, SSH Honeypot, HTTP Honeypot, TCP Honeypot, Prometheus openmetrics integration, Docker integration, RabbitMQ integration, and kubernetes support. Beelzebub allows easy configuration for different services and ports, enabling users to create custom honeypot scenarios. The roadmap includes developing Beelzebub into a robust PaaS platform. The project welcomes contributions and encourages adherence to the Code of Conduct for a supportive and respectful community.
bee-agent-framework
The Bee Agent Framework is an open-source tool for building, deploying, and serving powerful agentic workflows at scale. It provides AI agents, tools for creating workflows in Javascript/Python, a code interpreter, memory optimization strategies, serialization for pausing/resuming workflows, traceability features, production-level control, and upcoming features like model-agnostic support and a chat UI. The framework offers various modules for agents, llms, memory, tools, caching, errors, adapters, logging, serialization, and more, with a roadmap including MLFlow integration, JSON support, structured outputs, chat client, base agent improvements, guardrails, and evaluation.
llm-colosseum
llm-colosseum is a tool designed to evaluate Language Model Models (LLMs) in real-time by making them fight each other in Street Fighter III. The tool assesses LLMs based on speed, strategic thinking, adaptability, out-of-the-box thinking, and resilience. It provides a benchmark for LLMs to understand their environment and take context-based actions. Users can analyze the performance of different LLMs through ELO rankings and win rate matrices. The tool allows users to run experiments, test different LLM models, and customize prompts for LLM interactions. It offers installation instructions, test mode options, logging configurations, and the ability to run the tool with local models. Users can also contribute their own LLM models for evaluation and ranking.
aituber-server
AITuberKit server-side is a tool that allows users to receive messages via WebSocket and obtain responses from Open Interpreter. Users can also send files to the server for storage and issue commands to Open Interpreter. The tool is designed for WebSocket operation and provides a default connection URL of `ws://127.0.0.1:8000/ws`. It supports debugging in VSCode with DEBUG_MODE=1. The tool is licensed under KillianLucas/open-interpreter and includes a guide on how to use Open Interpreter.
Code-Atlas
Code Atlas is a lightweight interpreter developed in C++ that supports the execution of multi-language code snippets and partial Markdown rendering. It consumes significantly lower resources compared to similar tools, making it suitable for resource-limited devices. It leverages llama.cpp for local large-model inference and supports cloud-based large-model APIs. The tool provides features for code execution, Markdown rendering, local AI inference, and resource efficiency.
awesome-mlops
Awesome MLOps is a curated list of tools related to Machine Learning Operations, covering areas such as AutoML, CI/CD for Machine Learning, Data Cataloging, Data Enrichment, Data Exploration, Data Management, Data Processing, Data Validation, Data Visualization, Drift Detection, Feature Engineering, Feature Store, Hyperparameter Tuning, Knowledge Sharing, Machine Learning Platforms, Model Fairness and Privacy, Model Interpretability, Model Lifecycle, Model Serving, Model Testing & Validation, Optimization Tools, Simplification Tools, Visual Analysis and Debugging, and Workflow Tools. The repository provides a comprehensive collection of tools and resources for individuals and teams working in the field of MLOps.
openmacro
Openmacro is a multimodal personal agent that allows users to run code locally. It acts as a personal agent capable of completing and automating tasks autonomously via self-prompting. The tool provides a CLI natural-language interface for completing and automating tasks, analyzing and plotting data, browsing the web, and manipulating files. Currently, it supports API keys for models powered by SambaNova, with plans to add support for other hosts like OpenAI and Anthropic in future versions.
AiTreasureBox
AiTreasureBox is a versatile AI tool that provides a collection of pre-trained models and algorithms for various machine learning tasks. It simplifies the process of implementing AI solutions by offering ready-to-use components that can be easily integrated into projects. With AiTreasureBox, users can quickly prototype and deploy AI applications without the need for extensive knowledge in machine learning or deep learning. The tool covers a wide range of tasks such as image classification, text generation, sentiment analysis, object detection, and more. It is designed to be user-friendly and accessible to both beginners and experienced developers, making AI development more efficient and accessible to a wider audience.
ollama
Ollama is a lightweight, extensible framework for building and running language models on the local machine. It provides a simple API for creating, running, and managing models, as well as a library of pre-built models that can be easily used in a variety of applications. Ollama is designed to be easy to use and accessible to developers of all levels. It is open source and available for free on GitHub.
ai-game-development-tools
Here we will keep track of the AI Game Development Tools, including LLM, Agent, Code, Writer, Image, Texture, Shader, 3D Model, Animation, Video, Audio, Music, Singing Voice and Analytics. π₯ * Tool (AI LLM) * Game (Agent) * Code * Framework * Writer * Image * Texture * Shader * 3D Model * Avatar * Animation * Video * Audio * Music * Singing Voice * Speech * Analytics * Video Tool
AIOS
AIOS, a Large Language Model (LLM) Agent operating system, embeds large language model into Operating Systems (OS) as the brain of the OS, enabling an operating system "with soul" -- an important step towards AGI. AIOS is designed to optimize resource allocation, facilitate context switch across agents, enable concurrent execution of agents, provide tool service for agents, maintain access control for agents, and provide a rich set of toolkits for LLM Agent developers.
Github-Ranking-AI
This repository provides a list of the most starred and forked repositories on GitHub. It is updated automatically and includes information such as the project name, number of stars, number of forks, language, number of open issues, description, and last commit date. The repository is divided into two sections: LLM and chatGPT. The LLM section includes repositories related to large language models, while the chatGPT section includes repositories related to the chatGPT chatbot.
awesome_ai_for_programmers
Π Π΅ΠΏΠΎΠ·ΠΈΡΠΎΡΠΈΠΉ ΡΠΎΠ΄Π΅ΡΠΆΠΈΡ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΡ ΠΎ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠΈ ΠΈΡΠΊΡΡΡΡΠ²Π΅Π½Π½ΠΎΠ³ΠΎ ΠΈΠ½ΡΠ΅Π»Π»Π΅ΠΊΡΠ° Π² ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠ΅ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ½ΠΎΠ³ΠΎ ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠ΅Π½ΠΈΡ. Π ΡΠ°ΡΡΠ½ΠΎΡΡΠΈ, ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°ΡΡΡΡ ΠΊΠ΅ΠΉΡΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΡ ChatGPT ΠΈ Π΄ΡΡΠ³ΠΈΡ ΡΠ·ΡΠΊΠΎΠ²ΡΡ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Π΄Π»Ρ Π°Π²ΡΠΎΠΌΠ°ΡΠΈΠ·Π°ΡΠΈΠΈ Π·Π°Π΄Π°Ρ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠΈ, ΡΠ°ΠΊΠΈΡ ΠΊΠ°ΠΊ Π½Π°ΠΏΠΈΡΠ°Π½ΠΈΠ΅ ΠΊΠΎΠ΄Π°, ΡΠ΅ΡΡΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅, ΡΠ΅ΡΠ°ΠΊΡΠΎΡΠΈΠ½Π³ ΠΈ Π³Π΅Π½Π΅ΡΠ°ΡΠΈΡ Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠ°ΡΠΈΠΈ.
awesome-LLM-game-agent-papers
This repository provides a comprehensive survey of research papers on large language model (LLM)-based game agents. LLMs are powerful AI models that can understand and generate human language, and they have shown great promise for developing intelligent game agents. This survey covers a wide range of topics, including adventure games, crafting and exploration games, simulation games, competition games, cooperation games, communication games, and action games. For each topic, the survey provides an overview of the state-of-the-art research, as well as a discussion of the challenges and opportunities for future work.
AITreasureBox
AITreasureBox is a comprehensive collection of AI tools and resources designed to simplify and accelerate the development of AI projects. It provides a wide range of pre-trained models, datasets, and utilities that can be easily integrated into various AI applications. With AITreasureBox, developers can quickly prototype, test, and deploy AI solutions without having to build everything from scratch. Whether you are working on computer vision, natural language processing, or reinforcement learning projects, AITreasureBox has something to offer for everyone. The repository is regularly updated with new tools and resources to keep up with the latest advancements in the field of artificial intelligence.
finagg
finagg is a Python package that provides implementations of popular and free financial APIs, tools for aggregating historical data from those APIs into SQL databases, and tools for transforming aggregated data into features useful for analysis and AI/ML. It offers documentation, installation instructions, and basic usage examples for exploring various financial APIs and features. Users can install recommended datasets from 3rd party APIs into a local SQL database, access Bureau of Economic Analysis (BEA) data, Federal Reserve Economic Data (FRED), Securities and Exchange Commission (SEC) filings, and more. The package also allows users to explore raw data features, install refined data features, and perform refined aggregations of raw data. Configuration options for API keys, user agents, and data locations are provided, along with information on dependencies and related projects.