Best AI tools for< Llm App Developer >

Inductor is a developer tool for evaluating, ensuring, and improving the quality of your LLM applications – both during development and in production. It provides a fantastic workflow for continuous testing and evaluation as you develop, so that you always know your LLM app’s quality. Systematically improve quality and cost-effectiveness by actionably understanding your LLM app’s behavior and quickly testing different app variants. Rigorously assess your LLM app’s behavior before you deploy, in order to ensure quality and cost-effectiveness when you’re live. Easily monitor your live traffic: detect and resolve issues, analyze usage in order to improve, and seamlessly feed back into your development process. Inductor makes it easy for engineering and other roles to collaborate: get critical human feedback from non-engineering stakeholders (e.g., PM, UX, or subject matter experts) to ensure that your LLM app is user-ready.

Backmesh is an AI tool that serves as a proxy on edge CDN servers, enabling secure and direct access to LLM APIs without the need for a backend or SDK. It allows users to call LLM APIs from their apps, ensuring protection through JWT verification and rate limits. Backmesh also offers user analytics for LLM API calls, helping identify usage patterns and enhance user satisfaction within AI applications.

Reprompt is a prompt testing tool designed to help developers save time and make data-driven decisions about their prompts. It allows users to analyze more data in less time, easily identify anomalies, and speed up debugging by testing multiple scenarios at once. With Reprompt, users can have confidence in their changes by comparing with previous versions. The tool also offers real-time trading, < 1 sec operations, no commissions, built-in enterprise encryption and security, 256-bit AES encryption, and advanced security standards.

Private LLM is a secure, local, and private AI chatbot designed for iOS and macOS devices. It operates offline, ensuring that user data remains on the device, providing a safe and private experience. The application offers a range of features for text generation and language assistance, utilizing state-of-the-art quantization techniques to deliver high-quality on-device AI experiences without compromising privacy. Users can access a variety of open-source LLM models, integrate AI into Siri and Shortcuts, and benefit from AI language services across macOS apps. Private LLM stands out for its superior model performance and commitment to user privacy, making it a smart and secure tool for creative and productive tasks.

The LLM Token Counter is a sophisticated tool designed to help users effectively manage token limits for various Language Models (LLMs) like GPT-3.5, GPT-4, Claude-3, Llama-3, and more. It utilizes Transformers.js, a JavaScript implementation of the Hugging Face Transformers library, to calculate token counts client-side. The tool ensures data privacy by not transmitting prompts to external servers.

Lore macOS GPT-LLM Playground is an AI tool designed for macOS users, offering a Multi-Model Time Travel Versioning Combinatorial Runs Variants Full-Text Search Model-Cost Aware API & Token Stats Custom Endpoints Local Models Tables. It provides a user-friendly interface with features like Syntax, LaTeX Notes Export, Shortcuts, Vim Mode, and Sandbox. The tool is built with Cocoa, SwiftUI, and SQLite, ensuring privacy and offering support & feedback.

Empower is a serverless fine-tuned LLM hosting platform that offers a developer platform for fine-tuned LLMs. It provides prebuilt task-specific base models with GPT4 level response quality, enabling users to save up to 80% on LLM bills with just 5 lines of code change. Empower allows users to own their models, offers cost-effective serving with no compromise on performance, and charges on a per-token basis. The platform is designed to be user-friendly, efficient, and cost-effective for deploying and serving fine-tuned LLMs.

RecurseChat is a personal AI chat that is local, offline, and private. It allows users to chat with a local LLM, import ChatGPT history, chat with multiple models in one chat session, and use multimodal input. RecurseChat is also secure and private, and it is customizable to the core.

Flowise is an open-source, low-code tool that enables developers to build customized LLM orchestration flows and AI agents. It provides a drag-and-drop interface, pre-built app templates, conversational agents with memory, and seamless deployment on cloud platforms. Flowise is backed by Combinator and trusted by teams around the globe.

Faraday.dev is an offline-first, zero-configuration, desktop app that supports chatting with AI Characters. With Faraday.dev, you can run over 100 different open-source LLMs all on your machine without needing to touch the command line. Faraday.dev also supports Llama 2 models and GPU acceleration.

LangChain is an AI tool that offers a suite of products supporting developers in the LLM application lifecycle. It provides a framework to construct LLM-powered apps easily, visibility into app performance, and a turnkey solution for serving APIs. LangChain enables developers to build context-aware, reasoning applications and future-proof their applications by incorporating vendor optionality. LangSmith, a part of LangChain, helps teams improve accuracy and performance, iterate faster, and ship new AI features efficiently. The tool is designed to drive operational efficiency, increase discovery & personalization, and deliver premium products that generate revenue.

LM Studio is an AI tool designed for discovering, downloading, and running local LLMs (Large Language Models). Users can run LLMs on their laptops offline, use models through an in-app Chat UI or a local server, download compatible model files from HuggingFace repositories, and discover new LLMs. The tool ensures privacy by not collecting data or monitoring user actions, making it suitable for personal and business use. LM Studio supports various models like ggml Llama, MPT, and StarCoder on Hugging Face, with minimum hardware/software requirements specified for different platforms.

Faune is an anonymous AI chat app that brings the power of large language models (LLMs) like GPT-3, GPT-4, and Mistral directly to users. It prioritizes privacy and offers unique features such as a dynamic prompt editor, support for multiple LLMs, and a built-in image processor. With Faune, users can engage in rich and engaging AI conversations without the need for user accounts or complex setups.

Portkey is a monitoring and improvement tool for Gen AI apps, helping teams enhance cost, performance, and accuracy. It integrates quickly, monitors LLM requests, and boosts app resilience, security, performance, and accuracy. The tool offers a product walkthrough and easy integration with OpenAI Python and Node libraries.

Wordware is an AI toolkit that empowers cross-functional teams to build reliable high-quality agents through rapid iteration. It combines the best aspects of software with the power of natural language, freeing users from traditional no-code tool constraints. With advanced technical capabilities, multiple LLM providers, one-click API deployment, and multimodal support, Wordware offers a seamless experience for AI app development and deployment.

KoppieOS is an AI copilot that helps you with productivity and personalization. It offers features such as AI chat, quick ask, easy-to-recheck notes, app launcher, and 3D wallpapers. KoppieOS is free to use and works on Windows and MacOS.

Narada is an AI application designed for busy professionals to streamline their work processes. It leverages cutting-edge AI technology to automate tasks, connect favorite apps, and enhance productivity through intelligent automation. Narada's LLM Compiler routes text and voice commands to the right tools in real time, offering seamless app integration and time-saving features.

Allganize Japan Blog is an AI tool that provides information and updates about Allganize, a company offering AI solutions for enterprises. The blog covers topics such as AI applications, events, partnerships, and technical explanations related to AI technologies like LLM (Large Language Model). It serves as a platform to showcase the company's products, services, and industry insights.

Notification Harbor is an email marketing platform that uses Large Language Models (LLMs) to help businesses create and send more effective email campaigns. With Notification Harbor, businesses can use LLMs to generate personalized email content, optimize subject lines, and even create entire email campaigns from scratch. Notification Harbor is designed to make email marketing easier and more effective for businesses of all sizes.

Keymate.AI is an AI application that allows users to build GPTs with advanced search, browse, and long-term memory capabilities. It offers a personalized long-term memory on ChatGPT, parallel search functionality, and privacy features using Google API. Keymate.AI aims to elevate research, projects, and daily tasks by providing efficient AI memory management and real-time data retrieval from the web.

Data Prep Kit is a community project aimed at democratizing and speeding up unstructured data preparation for LLM app developers. It provides high-level APIs and modules for transforming data (code, language, speech, visual) to optimize LLM performance across different use cases. The toolkit supports Python, Ray, Spark, and Kubeflow Pipelines runtimes, offering scalability from laptop to datacenter-scale processing. Developers can contribute new custom modules and leverage the data processing library for building data pipelines. Automation features include workflow automation with Kubeflow Pipelines for transform execution.

Promptic is a tool designed for LLM app development, providing a productive and pythonic way to build LLM applications. It leverages LiteLLM, allowing flexibility to switch LLM providers easily. Promptic focuses on building features by providing type-safe structured outputs, easy-to-build agents, streaming support, automatic prompt caching, and built-in conversation memory.

This repository contains separate packages for Grafana LLM Plugin and the @grafana/llm package for interfacing with it. The packages are tightly coupled and developed together with identical dependencies. The repository provides instructions for developing the packages, including backend and frontend development, testing, and release processes.

Pathway's LLM (Large Language Model) Apps provide a platform to quickly deploy AI applications using the latest knowledge from data sources. The Python application examples in this repository are Docker-ready, exposing an HTTP API to the frontend. These apps utilize the Pathway framework for data synchronization, API serving, and low-latency data processing without the need for additional infrastructure dependencies. They connect to document data sources like S3, Google Drive, and Sharepoint, offering features like real-time data syncing, easy alert setup, scalability, monitoring, security, and unification of application logic.

LLM App Stack, also known as Emerging Architectures for LLM Applications, is a comprehensive list of available tools, projects, and vendors at each layer of the LLM app stack. It covers various categories such as Data Pipelines, Embedding Models, Vector Databases, Playgrounds, Orchestrators, APIs/Plugins, LLM Caches, Logging/Monitoring/Eval, Validators, LLM APIs (proprietary and open source), App Hosting Platforms, Cloud Providers, and Opinionated Clouds. The repository aims to provide a detailed overview of tools and projects for building, deploying, and maintaining enterprise data solutions, AI models, and applications.

Awesome LLM Courses is a curated list of online courses focused on Large Language Models (LLMs). The repository aims to provide a comprehensive collection of free available courses covering various aspects of LLMs, including fundamentals, engineering, and applications. The courses are suitable for individuals interested in natural language processing, AI development, and machine learning. The list includes courses from reputable platforms such as Hugging Face, Udacity, DeepLearning.AI, Cohere, DataCamp, and more, offering a wide range of topics from pretraining LLMs to building AI applications with LLMs. Whether you are a beginner looking to understand the basics of LLMs or an intermediate developer interested in advanced topics like prompt engineering and generative AI, this repository has something for everyone.

LLM-PowerHouse is a comprehensive and curated guide designed to empower developers, researchers, and enthusiasts to harness the true capabilities of Large Language Models (LLMs) and build intelligent applications that push the boundaries of natural language understanding. This GitHub repository provides in-depth articles, codebase mastery, LLM PlayLab, and resources for cost analysis and network visualization. It covers various aspects of LLMs, including NLP, models, training, evaluation metrics, open LLMs, and more. The repository also includes a collection of code examples and tutorials to help users build and deploy LLM-based applications.

IPEX-LLM is a PyTorch library for running Large Language Models (LLMs) on Intel CPUs and GPUs with very low latency. It provides seamless integration with various LLM frameworks and tools, including llama.cpp, ollama, Text-Generation-WebUI, HuggingFace transformers, and more. IPEX-LLM has been optimized and verified on over 50 LLM models, including LLaMA, Mistral, Mixtral, Gemma, LLaVA, Whisper, ChatGLM, Baichuan, Qwen, and RWKV. It supports a range of low-bit inference formats, including INT4, FP8, FP4, INT8, INT2, FP16, and BF16, as well as finetuning capabilities for LoRA, QLoRA, DPO, QA-LoRA, and ReLoRA. IPEX-LLM is actively maintained and updated with new features and optimizations, making it a valuable tool for researchers, developers, and anyone interested in exploring and utilizing LLMs.

Langroid is a Python framework that makes it easy to build LLM-powered applications. It uses a multi-agent paradigm inspired by the Actor Framework, where you set up Agents, equip them with optional components (LLM, vector-store and tools/functions), assign them tasks, and have them collaboratively solve a problem by exchanging messages. Langroid is a fresh take on LLM app-development, where considerable thought has gone into simplifying the developer experience; it does not use Langchain.

This repository showcases how to build a simple LLM-based chatbot for answering questions based on documents using retrieval augmented generation (RAG) technique. It also provides guidance on deploying the chatbot using Podman or on the OpenShift Container Platform. The workshop associated with this repository introduces participants to LLMs & RAG concepts and demonstrates how to customize the chatbot for specific purposes. The software stack relies on open-source tools like streamlit, LlamaIndex, and local open LLMs via Ollama, making it accessible for GPU-constrained environments.

Langfuse is a powerful tool that helps you develop, monitor, and test your LLM applications. With Langfuse, you can: * **Develop:** Instrument your app and start ingesting traces to Langfuse, inspect and debug complex logs, and manage, version, and deploy prompts from within Langfuse. * **Monitor:** Track metrics (cost, latency, quality) and gain insights from dashboards & data exports, collect and calculate scores for your LLM completions, run model-based evaluations, collect user feedback, and manually score observations in Langfuse. * **Test:** Track and test app behaviour before deploying a new version, test expected in and output pairs and benchmark performance before deploying, and track versions and releases in your application. Langfuse is easy to get started with and offers a generous free tier. You can sign up for Langfuse Cloud or deploy Langfuse locally or on your own infrastructure. Langfuse also offers a variety of integrations to make it easy to connect to your LLM applications.

This repository is a curated list of open-source, actively maintained web applications that leverage large language models (LLMs) for various use cases, including chatbots, natural language interfaces, assistants, and question answering systems. The projects are evaluated based on key criteria such as licensing, maintenance status, complexity, and features, to help users select the most suitable starting point for their LLM-based applications. The repository welcomes contributions and encourages users to submit projects that meet the criteria or suggest improvements to the existing list.

Firebase Genkit (beta) is a framework with powerful tooling to help app developers build, test, deploy, and monitor AI-powered features with confidence. Genkit is cloud optimized and code-centric, integrating with many services that have free tiers to get started. It provides unified API for generation, context-aware AI features, evaluation of AI workflow, extensibility with plugins, easy deployment to Firebase or Google Cloud, observability and monitoring with OpenTelemetry, and a developer UI for prototyping and testing AI features locally. Genkit works seamlessly with Firebase or Google Cloud projects through official plugins and templates.

A comprehensive repository of resources for Chinese large language models (LLMs), including data processing tools, fine-tuning frameworks, inference libraries, evaluation platforms, RAG engines, agent frameworks, books, courses, tutorials, and tips. The repository covers a wide range of tools and resources for working with LLMs, from data labeling and processing to model fine-tuning, inference, evaluation, and application development. It also includes resources for learning about LLMs through books, courses, and tutorials, as well as insights and strategies from building with LLMs.

This repository is a curated list of open-source libraries for production large language models. It includes tools for data preprocessing, training/finetuning, evaluation/benchmarking, serving/inference, application/RAG, testing/monitoring, and guardrails/security. The repository also provides a new category called LLM Cookbook/Examples for showcasing examples and guides on using various LLM APIs.

Awesome-LLM-Eval: a curated list of tools, benchmarks, demos, papers for Large Language Models (like ChatGPT, LLaMA, GLM, Baichuan, etc) Evaluation on Language capabilities, Knowledge, Reasoning, Fairness and Safety.

The awesome-langchain-zh repository is a collection of resources related to LangChain, a framework for building AI applications using large language models (LLMs). The repository includes sections on the LangChain framework itself, other language ports of LangChain, tools for low-code development, services, agents, templates, platforms, open-source projects related to knowledge management and chatbots, as well as learning resources such as notebooks, videos, and articles. It also covers other LLM frameworks and provides additional resources for exploring and working with LLMs. The repository serves as a comprehensive guide for developers and AI enthusiasts interested in leveraging LangChain and LLMs for various applications.

Awesome-LLM is a curated list of resources related to large language models, focusing on papers, projects, frameworks, tools, tutorials, courses, opinions, and other useful resources in the field. It covers trending LLM projects, milestone papers, other papers, open LLM projects, LLM training frameworks, LLM evaluation frameworks, tools for deploying LLM, prompting libraries & tools, tutorials, courses, books, and opinions. The repository provides a comprehensive overview of the latest advancements and resources in the field of large language models.

mllm is a fast and lightweight multimodal LLM inference engine for mobile and edge devices. It is a Plain C/C++ implementation without dependencies, optimized for multimodal LLMs like fuyu-8B, and supports ARM NEON and x86 AVX2. The engine offers 4-bit and 6-bit integer quantization, making it suitable for intelligent personal agents, text-based image searching/retrieval, screen VQA, and various mobile applications without compromising user privacy.

Expert on LLM security risks, providing detailed, accurate advice.

Specializes in summarizing LLM news and papers from the past week.

An LLM specialist aiding in learning and understanding LLMs.

Daily updates on LLM news and trends

I explain AI papers in Chinese.

Advisor for safe LLM integration using OWASP guidelines

Translates and provides responses in Comanche

Download and Run Open Source LLMs Locally.

This GPT generates the best possible LLM-agents for your system prompts. You can also specify the model size, like 3B, 33B, 70B, etc.

Specialized LLM in computer security, acting as a CISO with 20 years of experience, providing precise, data-driven technical responses to enhance organizational security.

I imitate GPT-5 LLM, with advanced reasoning, personalization, and higher emotional intelligence

A guide for ML & LLM bootcamp with a bioengineering background.

Expert in hacking and programming queries on LLM V 1.1

Using OpenLLMLeaderboard data to answer your questions about LLM. For Currently!

Premier AI Prompt Engineer for Advanced LLM Optimization, Enhancing AI-to-AI Interaction and Comprehension. Create -> Optimize -> Revise iteratively

专门优化和翻译不同LLM的提示词的专家，基于用户选择和LLM特性。

EmotionPrompt手法に基づいて作成していますが、本来の理論とは反対に人間に対してLLMがPromptを投げます。本来の手法の詳細：https://ai-data-base.com/archives/58158

Hack Me if you can - I can only talk to you about computer security, software security and LLM security @JacquesGariepy

Helps you build logic security into your GPTs custom instructions. Documentation: https://github.com/infotrix/SSLLMs---Semantic-Secuirty-for-LLM-GPTs

🪄Prompt一键强化,快速、精准对齐需求，与AI对话更高效。 🧙‍♂️解锁LLM潜力，让ChatGPT、Claude更懂你，工作快人一步。 🧸你的AI对话伙伴，定制专属需求，轻松开启高品质对话体验