Best AI tools for< Trace Code Execution >

BIASafe is an AI-driven platform that revolutionizes institutional portfolio management by leveraging artificial intelligence to drive unbiased, efficient, and scalable investment decisions. The platform offers a comprehensive suite of tools, including Soteria AI for data analytics, research and development capabilities, and portfolio management solutions. BIASafe empowers users with AI-powered intelligence for data-driven decision-making, predictive analytics, and uncovering hidden opportunities across portfolio strategies. The platform features a no-code R&D ecosystem for rapid design and strategy deployment, along with fully automated portfolio operations. With a focus on bias-free decisions and accelerated innovation, BIASafe sets a new standard in institutional-grade investment tools.

Lunary is an AI developer platform designed to bring AI applications to production. It offers a comprehensive set of tools to manage, improve, and protect LLM apps. With features like Logs, Metrics, Prompts, Evaluations, and Threads, Lunary empowers users to monitor and optimize their AI agents effectively. The platform supports tasks such as tracing errors, labeling data for fine-tuning, optimizing costs, running benchmarks, and testing open-source models. Lunary also facilitates collaboration with non-technical teammates through features like A/B testing, versioning, and clean source-code management.

CursorLens is an open-source dashboard designed to provide insights for AI-assisted coding within the Cursor.sh IDE. It allows users to log AI code generations, track usage, and control AI models, including local ones. Users can run CursorLens locally or utilize the upcoming hosted version for enhanced convenience and efficiency.

ReleasesNotes is an AI-powered release notes generator that helps developers create comprehensive and informative release notes with ease. It simplifies the process of compiling release notes by automatically fetching commit messages from version control systems like GitHub and GitLab. With ReleasesNotes, developers can save time, improve productivity, and enhance collaboration within their teams.

QRBTF is an AI-powered QR code generator that allows users to create QR codes from text, images, or even other QR codes. It offers a variety of customization options, including the ability to add logos, change colors, and set the size and shape of the QR code. QRBTF also provides a bulk QR code generation feature, making it easy to create multiple QR codes at once.

MyQRCode.com™ is an advanced QR code generator that empowers businesses and individuals to create, customize, and track QR codes for various purposes. With its user-friendly interface and powerful features, MyQRCode.com™ simplifies the process of generating QR codes, making it accessible to anyone. The platform offers a wide range of QR code types, including website URLs, vCards, PDFs, images, social media profiles, videos, simple text, business pages, Facebook pages, Wi-Fi networks, and app downloads. MyQRCode.com™ also provides advanced customization options, allowing users to add their company logos, change colors, and select from a variety of designs to create visually appealing QR codes that align with their brand identity. Additionally, the platform offers comprehensive analytics, enabling users to track the performance of their QR codes, including the number of scans, scan locations, and the devices used to scan the codes. This data provides valuable insights into the effectiveness of QR code campaigns and helps businesses optimize their marketing strategies.

Quick QR Art is a free QR Code AI Art Generator that allows users to create, customize, and track stunning QR Codes Art. With Quick QR Art, users can easily generate QR Codes Art that are fully customizable, dynamic, and trackable. Quick QR Art also offers a comprehensive suite of link management tools, making it easy to manage and track all of your links in one place. Whether you're looking to create QR Codes Art for marketing, branding, or personal use, Quick QR Art has you covered.

Sheety is a spreadsheet-like database that lets you build powerful apps without writing any code. It's perfect for teams who need to track data, manage projects, and collaborate on documents.

GitHub is a collaborative platform for building and shipping software that offers various features such as GitHub Copilot for AI-powered coding assistance, security tools for finding and fixing vulnerabilities, automation of workflows, instant development environments, project management, code review, and collaboration tools. It aims to simplify the software development process and improve developer productivity by leveraging AI technology.

Thentic is a no-code automation platform for Web3. It allows users to automate tasks such as receiving market analysis, airdropping free NFTs, setting coin price alerts, tracking new transactions, analyzing DeFi data, getting paid and notified, creating AI-generated NFTs, receiving crypto news, randomizing NFT attributes, and developing Web3 APIs. Thentic supports hundreds of blockchains with prebuilt integrations.

GitGab is a collaborative platform for developers to share code, collaborate on projects, and build software together. It provides a centralized space for version control, issue tracking, and code review, making it easier for teams to work together efficiently. With GitGab, developers can easily manage their codebase, track changes, and collaborate with team members in real-time. The platform supports integration with popular development tools and services, streamlining the development process and enhancing productivity.

TextIt is a leading bot platform that allows users to easily build scalable, interactive chatbots on any channel without writing any code. It offers a robust suite of features, including a drag-and-drop flow designer, custom contact database, automated campaigns, omni-channel support, ticketing system, and integrations with Zapier, Wit.ai, and custom webhooks. TextIt is trusted by organizations large and small and is free to try with friendly pricing even at massive scale.

Valyr is a tool that helps you track usage, costs, and latency metrics for your GPT-3 logs with just one line of code. It's easy to get started and can be up and running in less than 3 minutes.

Fenado AI is an AI-powered platform that allows users to build apps and websites in minutes without the need for coding. Users can describe their ideas to the AI, chat with it to refine, and then publish with just one click. The platform offers instant prototypes, AI-powered creation, design assistance, business dashboard, and scalability for users to launch their startups quickly and efficiently.

AddisChat is a no-code custom AI chatbot platform that allows businesses to create and integrate AI-powered chatbots directly on their websites. With full control over data and no coding required, AddisChat offers powerful features such as customization options, training data capabilities, user analytics dashboard, and integration capabilities. The platform simplifies chatbot creation and optimization to enhance customer experience and fuel business growth.

Fenado AI is an AI-powered platform that enables users to build apps and websites in minutes without the need for coding. Users can describe their ideas to the AI, chat with it to refine the designs, and then publish with just one click. The platform offers instant prototypes, AI-powered creation, design assistance, business dashboard, and scalability for users to launch their startups quickly and efficiently.

Alta is a no-code AI-powered application builder that allows users to quickly and easily create AI chatbots, websites, and mobile apps. With Alta, users can design their app using drag-and-drop components, connect their data from various sources, and personalize their app with their own branding. Alta also provides real-time insights on all channels, allowing users to track their app's performance and optimize the user experience.

Airtable is a next-gen app-building platform that enables teams to create custom business apps without the need for coding. It offers features like AI integration, connected data, automations, interface design, and data visualization. Airtable allows users to manage security, permissions, and data protection at scale. The platform also provides integrations with popular tools like Slack, Google Drive, and Salesforce, along with an extension marketplace for additional templates and apps. Users can streamline workflows, automate processes, and gain insights through reporting and analytics.

QR Diffusion is an AI-powered QR code art generator that allows users to transform their QR codes into visually stunning works of art in seconds. The website offers a variety of templates and customization options to create unique and eye-catching QR codes. With features like dynamic QR data, editable artwork templates, and analytics dashboard, QR Diffusion provides a user-friendly platform for generating artistic QR codes. Users can easily grab attention and increase scan rates with the help of this innovative tool.

PracticeCraft.AI is an innovative AI-powered platform designed to help users enhance their skills and knowledge in various fields through interactive practice sessions and personalized feedback. The platform leverages advanced algorithms to create tailored learning experiences that adapt to individual learning styles and preferences. With a user-friendly interface and a wide range of practice exercises, PracticeCraft.AI aims to make learning engaging, effective, and enjoyable for users of all levels.

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.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

Invariant Analyzer is an open-source scanner designed for LLM-based AI agents to find bugs, vulnerabilities, and security threats. It scans agent execution traces to identify issues like looping behavior, data leaks, prompt injections, and unsafe code execution. The tool offers a library of built-in checkers, an expressive policy language, data flow analysis, real-time monitoring, and extensible architecture for custom checkers. It helps developers debug AI agents, scan for security violations, and prevent security issues and data breaches during runtime. The analyzer leverages deep contextual understanding and a purpose-built rule matching engine for security policy enforcement.

AgentNeo is a Python package that provides functionalities for project, trace, dataset, experiment management. It allows users to authenticate, create projects, trace agents and LangGraph graphs, manage datasets, and run experiments with metrics. The tool aims to streamline AI project management and analysis by offering a comprehensive set of features.

AgentNeo is an advanced, open-source Agentic AI Application Observability, Monitoring, and Evaluation Framework designed to provide deep insights into AI agents, Large Language Model (LLM) calls, and tool interactions. It offers robust logging, visualization, and evaluation capabilities to help debug and optimize AI applications with ease. With features like tracing LLM calls, monitoring agents and tools, tracking interactions, detailed metrics collection, flexible data storage, simple instrumentation, interactive dashboard, project management, execution graph visualization, and evaluation tools, AgentNeo empowers users to build efficient, cost-effective, and high-quality AI-driven solutions.

RagaAI Catalyst is a comprehensive platform designed to enhance the management and optimization of LLM projects. It offers features such as project management, dataset management, evaluation management, trace management, prompt management, synthetic data generation, and guardrail management. These functionalities enable efficient evaluation and safeguarding of LLM applications.

Trace is a new AutoDiff-like tool for training AI systems end-to-end with general feedback. It generalizes the back-propagation algorithm by capturing and propagating an AI system's execution trace. Implemented as a PyTorch-like Python library, users can write Python code directly and use Trace primitives to optimize certain parts, similar to training neural networks.

CodeCompanion.nvim is a Neovim plugin that provides a Copilot Chat experience, adapter support for various LLMs, agentic workflows, inline code creation and modification, built-in actions for language prompts and error fixes, custom actions creation, async execution, and more. It supports Anthropic, Ollama, and OpenAI adapters. The plugin is primarily developed for personal workflows with no guarantees of regular updates or support. Users can customize the plugin to their needs by forking the project.

tinyllm is a lightweight framework designed for developing, debugging, and monitoring LLM and Agent powered applications at scale. It aims to simplify code while enabling users to create complex agents or LLM workflows in production. The core classes, Function and FunctionStream, standardize and control LLM, ToolStore, and relevant calls for scalable production use. It offers structured handling of function execution, including input/output validation, error handling, evaluation, and more, all while maintaining code readability. Users can create chains with prompts, LLM models, and evaluators in a single file without the need for extensive class definitions or spaghetti code. Additionally, tinyllm integrates with various libraries like Langfuse and provides tools for prompt engineering, observability, logging, and finite state machine design.

Vidur is a high-fidelity and extensible LLM inference simulator designed for capacity planning, deployment configuration optimization, testing new research ideas, and studying system performance of models under different workloads and configurations. It supports various models and devices, offers chrome trace exports, and can be set up using mamba, venv, or conda. Users can run the simulator with various parameters and monitor metrics using wandb. Contributions are welcome, subject to a Contributor License Agreement and adherence to the Microsoft Open Source Code of Conduct.

Phoenix is a tool that provides MLOps and LLMOps insights at lightning speed with zero-config observability. It offers a notebook-first experience for monitoring models and LLM Applications by providing LLM Traces, LLM Evals, Embedding Analysis, RAG Analysis, and Structured Data Analysis. Users can trace through the execution of LLM Applications, evaluate generative models, explore embedding point-clouds, visualize generative application's search and retrieval process, and statistically analyze structured data. Phoenix is designed to help users troubleshoot problems related to retrieval, tool execution, relevance, toxicity, drift, and performance degradation.

Nous is an open-source TypeScript platform for autonomous AI agents and LLM based workflows. It aims to automate processes, support requests, review code, assist with refactorings, and more. The platform supports various integrations, multiple LLMs/services, CLI and web interface, human-in-the-loop interactions, flexible deployment options, observability with OpenTelemetry tracing, and specific agents for code editing, software engineering, and code review. It offers advanced features like reasoning/planning, memory and function call history, hierarchical task decomposition, and control-loop function calling options. Nous is designed to be a flexible platform for the TypeScript community to expand and support different use cases and integrations.

Sophia is an open-source TypeScript platform designed for autonomous AI agents and LLM based workflows. It aims to automate processes, review code, assist with refactorings, and support various integrations. The platform offers features like advanced autonomous agents, reasoning/planning inspired by Google's Self-Discover paper, memory and function call history, adaptive iterative planning, and more. Sophia supports multiple LLMs/services, CLI and web interface, human-in-the-loop interactions, flexible deployment options, observability with OpenTelemetry tracing, and specific agents for code editing, software engineering, and code review. It provides a flexible platform for the TypeScript community to expand and support various use cases and integrations.

This is a development tutorial for eBPF based on CO-RE (Compile Once, Run Everywhere). It provides practical eBPF development practices from beginner to advanced, including basic concepts, code examples, and real-world applications. The tutorial focuses on eBPF examples in observability, networking, security, and more. It aims to help eBPF application developers quickly grasp eBPF development methods and techniques through examples in languages such as C, Go, and Rust. The tutorial is structured with independent eBPF tool examples in each directory, covering topics like kprobes, fentry, opensnoop, uprobe, sigsnoop, execsnoop, exitsnoop, runqlat, hardirqs, and more. The project is based on libbpf and frameworks like libbpf, Cilium, libbpf-rs, and eunomia-bpf for development.

ENOVA is an open-source service for Large Language Model (LLM) deployment, monitoring, injection, and auto-scaling. It addresses challenges in deploying stable serverless LLM services on GPU clusters with auto-scaling by deconstructing the LLM service execution process and providing configuration recommendations and performance detection. Users can build and deploy LLM with few command lines, recommend optimal computing resources, experience LLM performance, observe operating status, achieve load balancing, and more. ENOVA ensures stable operation, cost-effectiveness, efficiency, and strong scalability of LLM services.

The 'gritlm' repository provides all materials for the paper Generative Representational Instruction Tuning. It includes code for inference, training, evaluation, and known issues related to the GritLM model. The repository also offers models for embedding and generation tasks, along with instructions on how to train and evaluate the models. Additionally, it contains visualizations, acknowledgements, and a citation for referencing the work.

LangChain Decorators is a layer on top of LangChain that provides syntactic sugar for writing custom langchain prompts and chains. It offers a more pythonic way of writing code, multiline prompts without breaking code flow, IDE support for hinting and type checking, leveraging LangChain ecosystem, support for optional parameters, and sharing parameters between prompts. It simplifies streaming, automatic LLM selection, defining custom settings, debugging, and passing memory, callback, stop, etc. It also provides functions provider, dynamic function schemas, binding prompts to objects, defining custom settings, and debugging options. The project aims to enhance the LangChain library by making it easier to use and more efficient for writing custom prompts and chains.

The 'llm-strategy' repository implements the Strategy Pattern using Large Language Models (LLMs) like OpenAI’s GPT-3. It provides a decorator 'llm_strategy' that connects to an LLM to implement abstract methods in interface classes. The package uses doc strings, type annotations, and method/function names as prompts for the LLM and can convert the responses back to Python data. It aims to automate the parsing of structured data by using LLMs, potentially reducing the need for manual Python code in the future.

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