Best AI tools for< Observe Code Behavior >

Camel AGI is a groundbreaking platform that revolutionizes the way artificial intelligence is utilized to solve complex tasks by employing a unique role-playing method inspired by loop architecture, similar to that of BabyAGI and AutoGPT. At its core, CamelAGI facilitates the collaboration between two autonomous AI agents, each assigned specific roles, to work synergistically towards accomplishing a designated task. This innovative approach allows users to observe as the agents, equipped with distinct capabilities and perspectives, engage in a dynamic and context-aware dialogue, effectively mirroring the collaborative efforts seen in human interactions.

Observe.AI is a conversation intelligence software designed for contact centers, offering a suite of AI-powered tools to enhance customer interactions, support agents in real-time, and improve overall customer satisfaction. The platform combines advanced analytics, automation, and real-time assistance to drive continuous improvement and boost operational efficiency. Trusted by over 350 enterprises worldwide, Observe.AI helps businesses transform customer conversations into actionable insights, leading to measurable results such as increased sales conversions, improved compliance adherence, and enhanced customer sentiment.

Wallaroo.AI is an AI inference platform that offers production-grade AI inference microservices optimized on OpenVINO for cloud and Edge AI application deployments on CPUs and GPUs. It provides hassle-free AI inferencing for any model, any hardware, anywhere, with ultrafast turnkey inference microservices. The platform enables users to deploy, manage, observe, and scale AI models effortlessly, reducing deployment costs and time-to-value significantly.

Spreadsite is an AI-powered platform that turns spreadsheets into interactive web dashboards without the need for coding. It utilizes AI to transform data into visually appealing and interactive dashboards, offering features like agent-powered workflows, interactive data visualization, seamless sharing, and endless possibilities for data exploration. Spreadsite caters to various industries such as finance, marketing, and energy, providing users with the ability to create custom websites from their spreadsheet data effortlessly.

Radicalbit is an MLOps and AI Observability platform that helps businesses deploy, serve, observe, and explain their AI models. It provides a range of features to help data teams maintain full control over the entire data lifecycle, including real-time data exploration, outlier and drift detection, and model monitoring in production. Radicalbit can be seamlessly integrated into any ML stack, whether SaaS or on-prem, and can be used to run AI applications in minutes.

Sanctuary Cognitive Systems Corporation is a company that develops and manufactures general-purpose robots. Their flagship product, Phoenix™, is the world's first humanoid general-purpose robot powered by Carbon™, their pioneering AI control system. Phoenix™ is designed for work and is the only general-purpose robot featured in TIME's Best Inventions 2023. Sanctuary's robots are remotely piloted or supervised by people and are designed to both train and work alongside them. When instructed to do so, their robots will use their own built-in autonomous control system to observe, assess, and act on tasks in an efficient and prosperous manner.

MagicForm is an AI-powered lead generation tool that supercharges the top of your sales funnel with a 24/7 AI assistant. It learns about your business, follows up with leads, and helps increase conversions by providing personalized interactions. MagicForm is easy to train, instruct, trust, deploy, observe, integrate, and follow up with. It offers features like scanning websites, extracting facts, easy customization of conversation flow, and automation setup. The tool is powered by GPT-4 and offers different pricing plans to cater to solopreneurs, small businesses, and large companies.

Observer is a news and media website that covers a wide range of topics, including business, finance, technology, media, lifestyle, arts, entertainment, and power lists. The website features articles, reviews, interviews, and videos from a team of experienced journalists and critics.

Privacy Observer is an AI-powered tool that makes privacy accessible by scanning and analyzing privacy policies of websites. It helps users understand when websites request excessive personal information without the need to read lengthy policies. The tool provides a detailed score for each website, ensuring users can make informed decisions about their online privacy. With features like unlimited background scans, anonymous checks by humans, and a user-friendly browser extension, Privacy Observer aims to empower users to protect their privacy online.

Revisor is a neural network-based software package designed for monitoring electoral procedures and counting the number of actual voters. It utilizes AI-enabled monitoring to provide fast, reliable, and cost-effective election observation missions with high precision in voter counting. The system is trainable and can work with different types of voting procedures and electoral systems in any country. Revisor operates based on video recordings, allowing immediate results post-election and detection of violations.

Langfuse Python SDK is a software development kit that provides tools and functionalities for integrating with Langfuse's language processing services. It offers decorators for observing code behavior, low-level SDK for tracing, and wrappers for accessing Langfuse's public API. The SDK was recently rewritten in version 2, released on December 17, 2023, with detailed documentation available on the official website. It also supports integrations with OpenAI SDK, LlamaIndex, and LangChain for enhanced language processing capabilities.

Reinforcement Learning from AI Feedback (RLAIF) is a concept that describes a type of machine learning approach where **an AI agent learns by receiving feedback or guidance from another AI system**. This concept is closely related to the field of Reinforcement Learning (RL), which is a type of machine learning where an agent learns to make a sequence of decisions in an environment to maximize a cumulative reward. In traditional RL, an agent interacts with an environment and receives feedback in the form of rewards or penalties based on the actions it takes. It learns to improve its decision-making over time to achieve its goals. In the context of Reinforcement Learning from AI Feedback, the AI agent still aims to learn optimal behavior through interactions, but **the feedback comes from another AI system rather than from the environment or human evaluators**. This can be **particularly useful in situations where it may be challenging to define clear reward functions or when it is more efficient to use another AI system to provide guidance**. The feedback from the AI system can take various forms, such as: - **Demonstrations** : The AI system provides demonstrations of desired behavior, and the learning agent tries to imitate these demonstrations. - **Comparison Data** : The AI system ranks or compares different actions taken by the learning agent, helping it to understand which actions are better or worse. - **Reward Shaping** : The AI system provides additional reward signals to guide the learning agent's behavior, supplementing the rewards from the environment. This approach is often used in scenarios where the RL agent needs to learn from **limited human or expert feedback or when the reward signal from the environment is sparse or unclear**. It can also be used to **accelerate the learning process and make RL more sample-efficient**. Reinforcement Learning from AI Feedback is an area of ongoing research and has applications in various domains, including robotics, autonomous vehicles, and game playing, among others.

This repository contains the implementation of Self-Play of Adversarial Language Game (SPAG) as described in the paper 'Self-playing Adversarial Language Game Enhances LLM Reasoning'. The SPAG involves training Language Models (LLMs) in an adversarial language game called Adversarial Taboo. The repository provides tools for imitation learning, self-play episode collection, and reinforcement learning on game episodes to enhance LLM reasoning abilities. The process involves training models using GPUs, launching imitation learning, conducting self-play episodes, assigning rewards based on outcomes, and learning the SPAG model through reinforcement learning. Continuous improvements on reasoning benchmarks can be observed by repeating the episode-collection and SPAG-learning processes.

Godot RL Agents is an open-source package that facilitates the integration of Machine Learning algorithms with games created in the Godot Engine. It provides interfaces for popular RL frameworks, support for memory-based agents, 2D and 3D games, AI sensors, and is licensed under MIT. Users can train agents in the Godot editor, create custom environments, export trained agents in ONNX format, and utilize advanced features like different RL training frameworks.

STORM is a LLM system that writes Wikipedia-like articles from scratch based on Internet search. While the system cannot produce publication-ready articles that often require a significant number of edits, experienced Wikipedia editors have found it helpful in their pre-writing stage. **Try out our [live research preview](https://storm.genie.stanford.edu/) to see how STORM can help your knowledge exploration journey and please provide feedback to help us improve the system 🙏!**

This repository contains a collection of papers and resources related to Large Language Models (LLMs), including their applications in various domains such as text generation, translation, question answering, and dialogue systems. The repository also includes discussions on the ethical and societal implications of LLMs. **Description** This repository is a collection of papers and resources related to Large Language Models (LLMs). LLMs are a type of artificial intelligence (AI) that can understand and generate human-like text. They have a wide range of applications, including text generation, translation, question answering, and dialogue systems. **For Jobs** - **Content Writer** - **Copywriter** - **Editor** - **Journalist** - **Marketer** **AI Keywords** - **Large Language Models** - **Natural Language Processing** - **Machine Learning** - **Artificial Intelligence** - **Deep Learning** **For Tasks** - **Generate text** - **Translate text** - **Answer questions** - **Engage in dialogue** - **Summarize text**

The LLM course is divided into three parts: 1. 🧩 **LLM Fundamentals** covers essential knowledge about mathematics, Python, and neural networks. 2. 🧑‍🔬 **The LLM Scientist** focuses on building the best possible LLMs using the latest techniques. 3. 👷 **The LLM Engineer** focuses on creating LLM-based applications and deploying them. For an interactive version of this course, I created two **LLM assistants** that will answer questions and test your knowledge in a personalized way: * 🤗 **HuggingChat Assistant**: Free version using Mixtral-8x7B. * 🤖 **ChatGPT Assistant**: Requires a premium account. ## 📝 Notebooks A list of notebooks and articles related to large language models. ### Tools | Notebook | Description | Notebook | |----------|-------------|----------| | 🧐 LLM AutoEval | Automatically evaluate your LLMs using RunPod |  | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. |  | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. |  | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. |  | | 🌳 Model Family Tree | Visualize the family tree of merged models. |  | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. |  |

Simulator Controller is a modular administration and controller application for Sim Racing, featuring a comprehensive plugin automation framework for external controller hardware. It includes voice chat capable Assistants like Virtual Race Engineer, Race Strategist, Race Spotter, and Driving Coach. The tool offers features for setup, strategy development, monitoring races, and more. Developed in AutoHotkey, it supports various simulation games and integrates with third-party applications for enhanced functionality.

Fairlearn is a Python package designed to help developers assess and mitigate fairness issues in artificial intelligence (AI) systems. It provides mitigation algorithms and metrics for model assessment. Fairlearn focuses on two types of harms: allocation harms and quality-of-service harms. The package follows the group fairness approach, aiming to identify groups at risk of experiencing harms and ensuring comparable behavior across these groups. Fairlearn consists of metrics for assessing model impacts and algorithms for mitigating unfairness in various AI tasks under different fairness definitions.

ControlFlow is a Python framework designed for building agentic AI workflows. It provides a structured approach for defining tasks, assigning specialized AI agents, and orchestrating complex behaviors. By balancing AI autonomy with precise oversight, users can create sophisticated AI-powered applications with confidence. ControlFlow offers a task-centric architecture, structured results with type-safe outputs, specialized agents for efficient problem-solving, ecosystem integration with LangChain models, flexible control over workflows, multi-agent orchestration, and native observability and debugging capabilities.

Non-interactive, silent GPT.

上帝视角观察、探索和影响一个末日丧尸灾难后的人类社会。Observe, explore and influence human society after the apocalyptic zombie disaster from a God's perspective. Sponsor：小红书“ ItsJoe就出行 ”

Guides on outdoor activities, with an informative and adventure-oriented tone.

Monitoring tools expert with brief responses and guiding hints.