Best AI tools for< Manage Llm Models >

Chatty is an AI-powered chat application that utilizes cutting-edge models to provide efficient and personalized responses to user queries. The application is designed to optimize VRAM usage by employing models with specific suffixes, resulting in reduced memory requirements. Users can expect a slight delay in the initial response due to model downloading. Chatty aims to enhance user experience through its advanced AI capabilities.

Labellerr is a data labeling software that helps AI teams prepare high-quality labels 99 times faster for Vision, NLP, and LLM models. The platform offers automated annotation, advanced analytics, and smart QA to process millions of images and thousands of hours of videos in just a few weeks. Labellerr's powerful analytics provides full control over output quality and project management, making it a valuable tool for AI labeling partners.

Athina AI is a comprehensive platform designed to monitor, debug, analyze, and improve the performance of Large Language Models (LLMs) in production environments. It provides a suite of tools and features that enable users to detect and fix hallucinations, evaluate output quality, analyze usage patterns, and optimize prompt management. Athina AI supports integration with various LLMs and offers a range of evaluation metrics, including context relevancy, harmfulness, summarization accuracy, and custom evaluations. It also provides a self-hosted solution for complete privacy and control, a GraphQL API for programmatic access to logs and evaluations, and support for multiple users and teams. Athina AI's mission is to empower organizations to harness the full potential of LLMs by ensuring their reliability, accuracy, and alignment with business objectives.

Medical Chat is an advanced AI assistant designed for healthcare professionals, providing instant and accurate medical answers for both human and veterinary medicine. Its capabilities include diagnosing medical conditions, generating differential diagnosis reports, creating patient-specific clinic plans, and offering comprehensive drug information. Medical Chat utilizes the latest LLM models, including ChatGPT 3.5 and 4.0, to deliver reliable and up-to-date medical knowledge. The platform also features a vast database of professional medical textbooks, veterinary books, and PubMed articles, ensuring evidence-based responses. With its HIPAA compliance and commitment to data privacy, Medical Chat empowers healthcare providers to enhance their diagnostic capabilities and improve patient outcomes.

LexEdge is an AI-powered legal practice management solution that revolutionizes how legal professionals handle their responsibilities. It offers advanced features like case tracking, client communications, AI chatbot assistance, document automation, task management, and detailed reporting and analytics. LexEdge enhances productivity, accuracy, and client satisfaction by leveraging technologies such as AI, large language models (LLM), retrieval-augmented generation (RAG), fine-tuning, and custom model training. It caters to solo practitioners, small and large law firms, and corporate legal departments, providing tailored solutions to meet their unique needs.

GoCharlie is a leading Generative AI company specializing in developing cognitive agents and models optimized for businesses. Its AI technology enables professionals and businesses to amplify their productivity and create high-performing content tailored to their needs. GoCharlie's AI assistant, Charlie, automates repetitive tasks, allowing teams to focus on more strategic and creative work. It offers a suite of proprietary LLM and multimodal models, a Memory Vault to build an AI Brain for businesses, and Agent AI to deliver the full power of AI to operations. GoCharlie can automate mundane tasks, drive complex workflows, and facilitate instant, precise data retrieval.

Langtail is a platform that helps developers build, test, and deploy AI-powered applications. It provides a suite of tools to help developers debug prompts, run tests, and monitor the performance of their AI models. Langtail also offers a community forum where developers can share tips and tricks, and get help from other users.

Vellum AI is an AI platform that supports using Microsoft Azure hosted OpenAI models. It offers tools for prompt engineering, semantic search, prompt chaining, evaluations, and monitoring. Vellum enables users to build AI systems with features like workflow automation, document analysis, fine-tuning, Q&A over documents, intent classification, summarization, vector search, chatbots, blog generation, sentiment analysis, and more. The platform is backed by top VCs and founders of well-known companies, providing a complete solution for building LLM-powered applications.

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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.

AiPlus is an AI tool designed to serve as a cost-efficient model gateway. It offers users a platform to access and utilize various AI models for their projects and tasks. With AiPlus, users can easily integrate AI capabilities into their applications without the need for extensive development or resources. The tool aims to streamline the process of leveraging AI technology, making it accessible to a wider audience.

Datasaur is an advanced text and audio data labeling platform that offers customizable solutions for various industries such as LegalTech, Healthcare, Financial, Media, e-Commerce, and Government. It provides features like configurable annotation, quality control automation, and workforce management to enhance the efficiency of NLP and LLM projects. Datasaur prioritizes data security with military-grade practices and offers seamless integrations with AWS and other technologies. The platform aims to streamline the data labeling process, allowing engineers to focus on creating high-quality models.

FinetuneDB is an AI fine-tuning platform that allows users to easily create and manage datasets to fine-tune LLMs, evaluate outputs, and iterate on production data. It integrates with open-source and proprietary foundation models, and provides a collaborative editor for building datasets. FinetuneDB also offers a variety of features for evaluating model performance, including human and AI feedback, automated evaluations, and model metrics tracking.

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.

Mirage is a custom AI platform that builds custom LLMs to accelerate productivity. It is backed by Sequoia and offers a variety of features, including the ability to create custom AI models, train models on your own data, and deploy models to the cloud or on-premises.

Pontus is an AI tool that enables users to build AI models with trust, manage risk, and ensure compliance effortlessly. It offers features like smart anonymization, rapid audit, and liability reduction, along with privacy-enhancing technology. Pontus allows for on-premise deployment, role-based access controls, and toxicity checking to prevent inappropriate content. The application is designed to work seamlessly with common LLM providers, making it a valuable asset for industries like healthcare, finance, and research.

StandardNodeAI is an AI application that offers end-to-end sales systems utilizing AI to help businesses scale without huge costs. It provides bespoke AI solutions, AI chat agents, and tools to optimize operations, streamline workflows, and automate tasks. The application also offers AI models to gain actionable insights, custom solutions to save time and increase revenue, and LLM's to improve work productivity. StandardNodeAI replaces manual staff timings with 24/7 customer support and lead qualification, making it easier for clients to manage leads effectively. The application aims to revolutionize businesses by harnessing the efficiency of AI and providing tailored solutions for startups and businesses.

Legalysis is a powerful tool for analyzing and summarizing legal documents. It is designed to save time and reduce complexity in legal processes. The tool uses advanced AI technology to examine contracts and other legal documents in depth, detecting potential risks and issues with impressive accuracy. It also converts dense, lengthy legal documents into brief, one-page summaries, making them easier to understand. Legalysis is a valuable tool for law firms, corporate legal departments, and individuals dealing with legal documents.

Deuz GPT is an AI tool that offers a range of AI models such as ChatGPT, Claude, and Gemini. It provides features like accurate translations, smart search capabilities, and text-to-speech functionality. The platform aims to simplify users' lives by providing a one-stop solution for various AI-related tasks. Join Deuz GPT to explore the world of AI and leverage its powerful capabilities.

LLM Price Check is an AI tool designed to compare and calculate the latest prices for Large Language Models (LLM) APIs from leading providers such as OpenAI, Anthropic, Google, and more. Users can use the streamlined tool to optimize their AI budget efficiently by comparing pricing, sorting by various parameters, and searching for specific models. The tool provides a comprehensive overview of pricing information to help users make informed decisions when selecting an LLM API provider.

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.

Log10 is a one-line Python integration to manage your LLM data. It helps you log both closed and open-source LLM calls, compare and identify the best models and prompts, store feedback for fine-tuning, collect performance metrics such as latency and usage, and perform analytics and monitor compliance for LLM powered applications. Log10 offers various integration methods, including a python LLM library wrapper, the Log10 LLM abstraction, and callbacks, to facilitate its use in both existing production environments and new projects. Pick the one that works best for you. Log10 also provides a copilot that can help you with suggestions on how to optimize your prompt, and a feedback feature that allows you to add feedback to your completions. Additionally, Log10 provides prompt provenance, session tracking and call stack functionality to help debug prompt chains. With Log10, you can use your data and feedback from users to fine-tune custom models with RLHF, and build and deploy more reliable, accurate and efficient self-hosted models. Log10 also supports collaboration, allowing you to create flexible groups to share and collaborate over all of the above features.

COMFYUI LLM PARTY is a node library designed for LLM workflow development in ComfyUI, an extremely minimalist UI interface primarily used for AI drawing and SD model-based workflows. The project aims to provide a complete set of nodes for constructing LLM workflows, enabling users to easily integrate them into existing SD workflows. It features various functionalities such as API integration, local large model integration, RAG support, code interpreters, online queries, conditional statements, looping links for large models, persona mask attachment, and tool invocations for weather lookup, time lookup, knowledge base, code execution, web search, and single-page search. Users can rapidly develop web applications using API + Streamlit and utilize LLM as a tool node. Additionally, the project includes an omnipotent interpreter node that allows the large model to perform any task, with recommendations to use the 'show_text' node for display output.

QA-Pilot is an interactive chat project that leverages online/local LLM for rapid understanding and navigation of GitHub code repository. It allows users to chat with GitHub public repositories using a git clone approach, store chat history, configure settings easily, manage multiple chat sessions, and quickly locate sessions with a search function. The tool integrates with `codegraph` to view Python files and supports various LLM models such as ollama, openai, mistralai, and localai. The project is continuously updated with new features and improvements, such as converting from `flask` to `fastapi`, adding `localai` API support, and upgrading dependencies like `langchain` and `Streamlit` to enhance performance.

PySpur is a graph-based editor designed for LLM (Large Language Models) workflows. It offers modular building blocks, node-level debugging, and performance evaluation. The tool is easy to hack, supports JSON configs for workflow graphs, and is lightweight with minimal dependencies. Users can quickly set up PySpur by cloning the repository, creating a .env file, starting docker services, and accessing the portal. PySpur can also work with local models served using Ollama, with steps provided for configuration. The roadmap includes features like canvas, async/batch execution, support for Ollama, new nodes, pipeline optimization, templates, code compilation, multimodal support, and more.

Clipboard Conqueror is a multi-platform omnipresent copilot alternative. Currently requiring a kobold united or openAI compatible back end, this software brings powerful LLM based tools to any text field, the universal copilot you deserve. It simply works anywhere. No need to sign in, no required key. Provided you are using local AI, CC is a data secure alternative integration provided you trust whatever backend you use. *Special thank you to the creators of KoboldAi, KoboldCPP, llamma, openAi, and the communities that made all this possible to figure out.

The Keras-llm-robot Web UI project is an open-source tool designed for offline deployment and testing of various open-source models from the Hugging Face website. It allows users to combine multiple models through configuration to achieve functionalities like multimodal, RAG, Agent, and more. The project consists of three main interfaces: chat interface for language models, configuration interface for loading models, and tools & agent interface for auxiliary models. Users can interact with the language model through text, voice, and image inputs, and the tool supports features like model loading, quantization, fine-tuning, role-playing, code interpretation, speech recognition, image recognition, network search engine, and function calling.

ChatBook provides a one-stop AI service, including basic AI dialogue, AI role agents, AI customer service, AI knowledge base, AI mind map generation, and AI PPTX generation. Users can define AI workflows freely to handle more complex business scenarios. The backend uses serverless functions with data stored in the ./data directory. The tool allows administrators to manage knowledge bases, configure keys, and review user registrations. Normal users can directly use AI models and knowledge bases after registration. The technology stack includes LLM models like Langchain, Pinecone, OpenAi, Gemini, Baidu Wenxin, Node Express for backend, and React, NextJS, MUI for frontend.

The OpenAI Completion plugin for Sublime Text provides first-class code assistant support within the editor. It utilizes LLM models to manipulate code, engage in chat mode, and perform various tasks. The plugin supports OpenAI, llama.cpp, and ollama models, allowing users to customize their AI assistant experience. It offers separated chat histories and assistant settings for different projects, enabling context-specific interactions. Additionally, the plugin supports Markdown syntax with code language syntax highlighting, server-side streaming for faster response times, and proxy support for secure connections. Users can configure the plugin's settings to set their OpenAI API key, adjust assistant modes, and manage chat history. Overall, the OpenAI Completion plugin enhances the Sublime Text editor with powerful AI capabilities, streamlining coding workflows and fostering collaboration with AI assistants.

A Rust based tool to evaluate LLM models, prompts and model params. It automates the process of selecting the best model parameters, given an LLM model and a prompt, iterating over the possible combinations and letting the user visually inspect the results. The tool assumes the user has Ollama installed and serving endpoints, either in `localhost` or in a remote server. Key features include: * Automatically fetches models from local or remote Ollama servers * Iterates over different models and params to generate inferences * A/B test prompts on different models simultaneously * Allows multiple iterations for each combination of parameters * Makes synchronous inference calls to avoid spamming servers * Optionally outputs inference parameters and response metadata (inference time, tokens and tokens/s) * Refetching of individual inference calls * Model selection can be filtered by name * List experiments which can be downloaded in JSON format * Configurable inference timeout * Custom default parameters and system prompts can be defined in settings

Groq Cloud runs LLM models fast and cheap. Llama 3, Mixtrel, Gemma, and more at hundreds of tokens per second, at cents per million tokens.

OmniSteward is an AI-powered steward system based on large language models that can interact with users through voice or text to help control smart home devices and computer programs. It supports multi-turn dialogue, tool calling for complex tasks, multiple LLM models, voice recognition, smart home control, computer program management, online information retrieval, command line operations, and file management. The system is highly extensible, allowing users to customize and share their own tools.

BentoVLLM is an example project demonstrating how to serve and deploy open-source Large Language Models using vLLM, a high-throughput and memory-efficient inference engine. It provides a basis for advanced code customization, such as custom models, inference logic, or vLLM options. The project allows for simple LLM hosting with OpenAI compatible endpoints without the need to write any code. Users can interact with the server using Swagger UI or other methods, and the service can be deployed to BentoCloud for better management and scalability. Additionally, the repository includes integration examples for different LLM models and tools.

AgentForge is a low-code framework tailored for the rapid development, testing, and iteration of AI-powered autonomous agents and Cognitive Architectures. It is compatible with a range of LLM models and offers flexibility to run different models for different agents based on specific needs. The framework is designed for seamless extensibility and database-flexibility, making it an ideal playground for various AI projects. AgentForge is a beta-testing ground and future-proof hub for crafting intelligent, model-agnostic autonomous agents.

Unofficial HuggingChat Python API for creating chatbots, supporting features like image generation, web search, memorizing context, and changing LLMs. Users can log in, chat with the ChatBot, perform web searches, create new conversations, manage conversations, switch models, get conversation info, use assistants, and delete conversations. The API also includes a CLI mode with various commands for interacting with the tool. Users are advised not to use the application for high-stakes decisions or advice and to avoid high-frequency requests to preserve server resources.

GPT Academic is a powerful tool that leverages the capabilities of large language models (LLMs) to enhance academic research and writing. It provides a user-friendly interface that allows researchers, students, and professionals to interact with LLMs and utilize their abilities for various academic tasks. With GPT Academic, users can access a wide range of features and functionalities, including: * **Summarization and Paraphrasing:** GPT Academic can summarize complex texts, articles, and research papers into concise and informative summaries. It can also paraphrase text to improve clarity and readability. * **Question Answering:** Users can ask GPT Academic questions related to their research or studies, and the tool will provide comprehensive and well-informed answers based on its knowledge and understanding of the relevant literature. * **Code Generation and Explanation:** GPT Academic can generate code snippets and provide explanations for complex coding concepts. It can also help debug code and suggest improvements. * **Translation:** GPT Academic supports translation of text between multiple languages, making it a valuable tool for researchers working with international collaborations or accessing resources in different languages. * **Citation and Reference Management:** GPT Academic can help users manage their citations and references by automatically generating citations in various formats and providing suggestions for relevant references based on the user's research topic. * **Collaboration and Note-Taking:** GPT Academic allows users to collaborate on projects and take notes within the tool. They can share their work with others and access a shared workspace for real-time collaboration. * **Customizable Interface:** GPT Academic offers a customizable interface that allows users to tailor the tool to their specific needs and preferences. They can choose from a variety of themes, adjust the layout, and add or remove features to create a personalized workspace. Overall, GPT Academic is a versatile and powerful tool that can significantly enhance the productivity and efficiency of academic research and writing. It empowers users to leverage the capabilities of LLMs and unlock new possibilities for academic exploration and knowledge creation.

QMedia is an open-source multimedia AI content search engine designed specifically for content creators. It provides rich information extraction methods for text, image, and short video content. The tool integrates unstructured text, image, and short video information to build a multimodal RAG content Q&A system. Users can efficiently search for image/text and short video materials, analyze content, provide content sources, and generate customized search results based on user interests and needs. QMedia supports local deployment for offline content search and Q&A for private data. The tool offers features like content cards display, multimodal content RAG search, and pure local multimodal models deployment. Users can deploy different types of models locally, manage language models, feature embedding models, image models, and video models. QMedia aims to spark new ideas for content creation and share AI content creation concepts in an open-source manner.

Cognita is an open-source framework to organize your RAG codebase along with a frontend to play around with different RAG customizations. It provides a simple way to organize your codebase so that it becomes easy to test it locally while also being able to deploy it in a production ready environment. The key issues that arise while productionizing RAG system from a Jupyter Notebook are: 1. **Chunking and Embedding Job** : The chunking and embedding code usually needs to be abstracted out and deployed as a job. Sometimes the job will need to run on a schedule or be trigerred via an event to keep the data updated. 2. **Query Service** : The code that generates the answer from the query needs to be wrapped up in a api server like FastAPI and should be deployed as a service. This service should be able to handle multiple queries at the same time and also autoscale with higher traffic. 3. **LLM / Embedding Model Deployment** : Often times, if we are using open-source models, we load the model in the Jupyter notebook. This will need to be hosted as a separate service in production and model will need to be called as an API. 4. **Vector DB deployment** : Most testing happens on vector DBs in memory or on disk. However, in production, the DBs need to be deployed in a more scalable and reliable way. Cognita makes it really easy to customize and experiment everything about a RAG system and still be able to deploy it in a good way. It also ships with a UI that makes it easier to try out different RAG configurations and see the results in real time. You can use it locally or with/without using any Truefoundry components. However, using Truefoundry components makes it easier to test different models and deploy the system in a scalable way. Cognita allows you to host multiple RAG systems using one app. ### Advantages of using Cognita are: 1. A central reusable repository of parsers, loaders, embedders and retrievers. 2. Ability for non-technical users to play with UI - Upload documents and perform QnA using modules built by the development team. 3. Fully API driven - which allows integration with other systems. > If you use Cognita with Truefoundry AI Gateway, you can get logging, metrics and feedback mechanism for your user queries. ### Features: 1. Support for multiple document retrievers that use `Similarity Search`, `Query Decompostion`, `Document Reranking`, etc 2. Support for SOTA OpenSource embeddings and reranking from `mixedbread-ai` 3. Support for using LLMs using `Ollama` 4. Support for incremental indexing that ingests entire documents in batches (reduces compute burden), keeps track of already indexed documents and prevents re-indexing of those docs.

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

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

Advisor for safe LLM integration using OWASP guidelines

Download and Run Open Source LLMs Locally.

ChatGPT Detector quickly finds AI writing from ChatGPT, LLMs, Bard, and GPT-4. It's easy and fast to use!

Dietician that helps those with IBS manage their symptoms via FODMAPs. FODMAP stands for fermentable oligosaccharides, disaccharides, monosaccharides and polyols. These are the chemical names of 5 naturally occurring sugars that are not well absorbed by your small intestine.

Provides cognitive-behavioral and emotional therapy guidance, helping users understand and manage their thoughts, behaviors, and emotions.

Cross-cultural management. Useful for those who relocate to another country or manage cross-cultural teams.

I manage finances securely with encryption and user authentication.

Expert project manager, I can help you manage IT projects

Helps developers manage state using StateAdapt

Recognize, manage, cope. Works well with GPT-Voice.

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I manage your grocery lists to help you stay organized. *1/ Tell me what to add to a list. 2/ Ask me to add all ingredients for a receipe. 3/ Upload a receipt to remove items from your lists 4/ Add an item by simply uploading a picture. 5/ Ask me what items I would recommend you add to your lists.*

Helps create and manage local clubs based on shared interests.

Helps users manage and preserve family heirlooms with empathy and practical advice.

Use me to manage your contents.

Give me your syptoms and I will provide instructions for how to manage your illness.

Your AI Google Slides assistant! Effortlessly locate, manage, and summarize your presentations!

A simulation game where players learn grow medicinal plants, craft remedies, and manage a herbal healing garden. Another AI Tiny Game by Dave Lalande