Alternatives to PromptLayer

Fully managed ML tools allow you to build, deploy and scale machine-learning (ML) models quickly, for any use case. Vertex AI Workbench is natively integrated with BigQuery Dataproc and Spark. You can use BigQuery to create and execute machine-learning models in BigQuery by using standard SQL queries and spreadsheets or you can export datasets directly from BigQuery into Vertex AI Workbench to run your models there. Vertex Data Labeling can be used to create highly accurate labels for data collection. Vertex AI Agent Builder empowers developers to design and deploy advanced generative AI applications for enterprise use. It supports both no-code and code-driven development, enabling users to create AI agents through natural language prompts or by integrating with frameworks like LangChain and LlamaIndex.

Google AI Studio is a user-friendly, web-based workspace that offers a streamlined environment for exploring and applying cutting-edge AI technology. It acts as a powerful launchpad for diving into the latest developments in AI, making complex processes more accessible to developers of all levels. The platform provides seamless access to Google's advanced Gemini AI models, creating an ideal space for collaboration and experimentation in building next-gen applications. With tools designed for efficient prompt crafting and model interaction, developers can quickly iterate and incorporate complex AI capabilities into their projects. The flexibility of the platform allows developers to explore a wide range of use cases and AI solutions without being constrained by technical limitations. Google AI Studio goes beyond basic testing by enabling a deeper understanding of model behavior, allowing users to fine-tune and enhance AI performance. This comprehensive platform unlocks the full potential of AI, facilitating innovation and improving efficiency in various fields by lowering the barriers to AI development. By removing complexities, it helps users focus on building impactful solutions faster.

Lunary serves as a platform for AI developers, facilitating the management, enhancement, and safeguarding of Large Language Model (LLM) chatbots. It encompasses a suite of features, including tracking conversations and feedback, analytics for costs and performance, debugging tools, and a prompt directory that supports version control and team collaboration. The platform is compatible with various LLMs and frameworks like OpenAI and LangChain and offers SDKs compatible with both Python and JavaScript. Additionally, Lunary incorporates guardrails designed to prevent malicious prompts and protect against sensitive data breaches. Users can deploy Lunary within their VPC using Kubernetes or Docker, enabling teams to evaluate LLM responses effectively. The platform allows for an understanding of the languages spoken by users, experimentation with different prompts and LLM models, and offers rapid search and filtering capabilities. Notifications are sent out when agents fail to meet performance expectations, ensuring timely interventions. With Lunary's core platform being fully open-source, users can choose to self-host or utilize cloud options, making it easy to get started in a matter of minutes. Overall, Lunary equips AI teams with the necessary tools to optimize their chatbot systems while maintaining high standards of security and performance.

Langtail is a cloud-based development tool designed to streamline the debugging, testing, deployment, and monitoring of LLM-powered applications. The platform provides a no-code interface for debugging prompts, adjusting model parameters, and conducting thorough LLM tests to prevent unexpected behavior when prompts or models are updated. Langtail is tailored for LLM testing, including chatbot evaluations and ensuring reliable AI test prompts. Key features of Langtail allow teams to: • Perform in-depth testing of LLM models to identify and resolve issues before production deployment. • Easily deploy prompts as API endpoints for smooth integration into workflows. • Track model performance in real-time to maintain consistent results in production environments. • Implement advanced AI firewall functionality to control and protect AI interactions. Langtail is the go-to solution for teams aiming to maintain the quality, reliability, and security of their AI and LLM-based applications.

Literal AI is a collaborative platform crafted to support engineering and product teams in the creation of production-ready Large Language Model (LLM) applications. It features an array of tools focused on observability, evaluation, and analytics, which allows for efficient monitoring, optimization, and integration of different prompt versions. Among its noteworthy functionalities are multimodal logging, which incorporates vision, audio, and video, as well as prompt management that includes versioning and A/B testing features. Additionally, it offers a prompt playground that allows users to experiment with various LLM providers and configurations. Literal AI is designed to integrate effortlessly with a variety of LLM providers and AI frameworks, including OpenAI, LangChain, and LlamaIndex, and comes equipped with SDKs in both Python and TypeScript for straightforward code instrumentation. The platform further facilitates the development of experiments against datasets, promoting ongoing enhancements and minimizing the risk of regressions in LLM applications. With these capabilities, teams can not only streamline their workflows but also foster innovation and ensure high-quality outputs in their projects.

Maxim is a enterprise-grade stack that enables AI teams to build applications with speed, reliability, and quality. Bring the best practices from traditional software development to your non-deterministic AI work flows. Playground for your rapid engineering needs. Iterate quickly and systematically with your team. Organise and version prompts away from the codebase. Test, iterate and deploy prompts with no code changes. Connect to your data, RAG Pipelines, and prompt tools. Chain prompts, other components and workflows together to create and test workflows. Unified framework for machine- and human-evaluation. Quantify improvements and regressions to deploy with confidence. Visualize the evaluation of large test suites and multiple versions. Simplify and scale human assessment pipelines. Integrate seamlessly into your CI/CD workflows. Monitor AI system usage in real-time and optimize it with speed.

AI engineering can be transparent rather than opaque. With a suite of tools for tracing, assessment, prompt management, and more, HoneyHive emerges as a comprehensive platform for AI observability and evaluation, aimed at helping teams create dependable generative AI applications. This platform equips users with resources for model evaluation, testing, and monitoring, promoting effective collaboration among engineers, product managers, and domain specialists. By measuring quality across extensive test suites, teams can pinpoint enhancements and regressions throughout the development process. Furthermore, it allows for the tracking of usage, feedback, and quality on a large scale, which aids in swiftly identifying problems and fostering ongoing improvements. HoneyHive is designed to seamlessly integrate with various model providers and frameworks, offering the necessary flexibility and scalability to accommodate a wide range of organizational requirements. This makes it an ideal solution for teams focused on maintaining the quality and performance of their AI agents, delivering a holistic platform for evaluation, monitoring, and prompt management, ultimately enhancing the overall effectiveness of AI initiatives. As organizations increasingly rely on AI, tools like HoneyHive become essential for ensuring robust performance and reliability.

LangChain provides a comprehensive framework that empowers developers to build and scale intelligent applications using large language models (LLMs). By integrating data and APIs, LangChain enables context-aware applications that can perform reasoning tasks. The suite includes LangGraph, a tool for orchestrating complex workflows, and LangSmith, a platform for monitoring and optimizing LLM-driven agents. LangChain supports the full lifecycle of LLM applications, offering tools to handle everything from initial design and deployment to post-launch performance management. Its flexibility makes it an ideal solution for businesses looking to enhance their applications with AI-powered reasoning and automation.

Collaborate effectively on prompts and assess LLM applications with assurance using Agenta, a versatile platform that empowers teams to swiftly develop powerful LLM applications. Build an interactive playground linked to your code, allowing the entire team to engage in experimentation and collaboration seamlessly. Methodically evaluate various prompts, models, and embeddings prior to launching into production. Share a link to collect valuable human feedback from team members, fostering a collaborative environment. Agenta is compatible with all frameworks, such as Langchain and Lama Index, as well as model providers, including OpenAI, Cohere, Huggingface, and self-hosted models. Additionally, the platform offers insights into the costs, latency, and chain of calls associated with your LLM application. Users can create straightforward LLM apps right from the user interface, but for those seeking to develop more tailored applications, coding in Python is necessary. Agenta stands out as a model-agnostic tool that integrates with a wide variety of model providers and frameworks, though it currently only supports an SDK in Python. This flexibility ensures that teams can adapt Agenta to their specific needs while maintaining a high level of functionality.

Parea is a prompt engineering platform designed to allow users to experiment with various prompt iterations, assess and contrast these prompts through multiple testing scenarios, and streamline the optimization process with a single click, in addition to offering sharing capabilities and more. Enhance your AI development process by leveraging key functionalities that enable you to discover and pinpoint the most effective prompts for your specific production needs. The platform facilitates side-by-side comparisons of prompts across different test cases, complete with evaluations, and allows for CSV imports of test cases, along with the creation of custom evaluation metrics. By automating the optimization of prompts and templates, Parea improves the outcomes of large language models, while also providing users the ability to view and manage all prompt versions, including the creation of OpenAI functions. Gain programmatic access to your prompts, which includes comprehensive observability and analytics features, helping you determine the costs, latency, and overall effectiveness of each prompt. Embark on the journey to refine your prompt engineering workflow with Parea today, as it empowers developers to significantly enhance the performance of their LLM applications through thorough testing and effective version control, ultimately fostering innovation in AI solutions.

LMOps is a stack that allows you to launch production-ready applications for monitoring, model management and more. Portkey is a replacement for OpenAI or any other provider APIs. Portkey allows you to manage engines, parameters and versions. Switch, upgrade, and test models with confidence. View aggregate metrics for your app and users to optimize usage and API costs Protect your user data from malicious attacks and accidental exposure. Receive proactive alerts if things go wrong. Test your models in real-world conditions and deploy the best performers. We have been building apps on top of LLM's APIs for over 2 1/2 years. While building a PoC only took a weekend, bringing it to production and managing it was a hassle! We built Portkey to help you successfully deploy large language models APIs into your applications. We're happy to help you, regardless of whether or not you try Portkey!

CometLLM serves as a comprehensive platform for recording and visualizing your LLM prompts and chains. By utilizing CometLLM, you can discover effective prompting techniques, enhance your troubleshooting processes, and maintain consistent workflows. It allows you to log not only your prompts and responses but also includes details such as prompt templates, variables, timestamps, duration, and any necessary metadata. The user interface provides the capability to visualize both your prompts and their corresponding responses seamlessly. You can log chain executions with the desired level of detail, and similarly, visualize these executions through the interface. Moreover, when you work with OpenAI chat models, the tool automatically tracks your prompts for you. It also enables you to monitor and analyze user feedback effectively. The UI offers the feature to compare your prompts and chain executions through a diff view. Comet LLM Projects are specifically designed to aid in conducting insightful analyses of your logged prompt engineering processes. Each column in the project corresponds to a specific metadata attribute that has been recorded, meaning the default headers displayed can differ based on the particular project you are working on. Thus, CometLLM not only simplifies prompt management but also enhances your overall analytical capabilities.

Pezzo serves as an open-source platform for LLMOps, specifically designed for developers and their teams. With merely two lines of code, users can effortlessly monitor and troubleshoot AI operations, streamline collaboration and prompt management in a unified location, and swiftly implement updates across various environments. This efficiency allows teams to focus more on innovation rather than operational challenges.

Langfuse is a free and open-source LLM engineering platform that helps teams to debug, analyze, and iterate their LLM Applications. Observability: Incorporate Langfuse into your app to start ingesting traces. Langfuse UI : inspect and debug complex logs, user sessions and user sessions Langfuse Prompts: Manage versions, deploy prompts and manage prompts within Langfuse Analytics: Track metrics such as cost, latency and quality (LLM) to gain insights through dashboards & data exports Evals: Calculate and collect scores for your LLM completions Experiments: Track app behavior and test it before deploying new versions Why Langfuse? - Open source - Models and frameworks are agnostic - Built for production - Incrementally adaptable - Start with a single LLM or integration call, then expand to the full tracing for complex chains/agents - Use GET to create downstream use cases and export the data

Klu.ai, a Generative AI Platform, simplifies the design, deployment, and optimization of AI applications. Klu integrates your Large Language Models and incorporates data from diverse sources to give your applications unique context. Klu accelerates the building of applications using language models such as Anthropic Claude (Azure OpenAI), GPT-4 (Google's GPT-4), and over 15 others. It allows rapid prompt/model experiments, data collection and user feedback and model fine tuning while cost-effectively optimising performance. Ship prompt generation, chat experiences and workflows in minutes. Klu offers SDKs for all capabilities and an API-first strategy to enable developer productivity. Klu automatically provides abstractions to common LLM/GenAI usage cases, such as: LLM connectors and vector storage, prompt templates, observability and evaluation/testing tools.

DagsHub serves as a collaborative platform tailored for data scientists and machine learning practitioners to effectively oversee and optimize their projects. By merging code, datasets, experiments, and models within a cohesive workspace, it promotes enhanced project management and teamwork among users. Its standout features comprise dataset oversight, experiment tracking, a model registry, and the lineage of both data and models, all offered through an intuitive user interface. Furthermore, DagsHub allows for smooth integration with widely-used MLOps tools, which enables users to incorporate their established workflows seamlessly. By acting as a centralized repository for all project elements, DagsHub fosters greater transparency, reproducibility, and efficiency throughout the machine learning development lifecycle. This platform is particularly beneficial for AI and ML developers who need to manage and collaborate on various aspects of their projects, including data, models, and experiments, alongside their coding efforts. Notably, DagsHub is specifically designed to handle unstructured data types, such as text, images, audio, medical imaging, and binary files, making it a versatile tool for diverse applications. In summary, DagsHub is an all-encompassing solution that not only simplifies the management of projects but also enhances collaboration among team members working across different domains.

Explore the prompts available in ChatGPT tailored for SEO, marketing, copywriting, and more. With the AIPRM extension, you gain access to a collection of carefully curated prompt templates designed specifically for ChatGPT. Take advantage of this opportunity to enhance your productivity—it's available for free! Prompt Engineers share their most effective prompts, providing a platform for experts to gain visibility and increase traffic to their websites. AIPRM serves as your comprehensive AI prompt toolkit, equipping you with everything necessary to effectively prompt ChatGPT. Covering a wide array of subjects such as SEO, sales, customer support, marketing strategies, and even guitar playing, AIPRM ensures you won’t waste any more time grappling with prompt creation. Allow the AIPRM ChatGPT Prompts extension to streamline the process for you! These prompts are not only designed to optimize your website for better search engine rankings but also assist in researching innovative product strategies and enhancing sales and support for your SaaS offerings. Ultimately, AIPRM is the AI prompt manager you’ve always desired, ready to elevate your creative and strategic endeavors to new heights.

The use of prompts has emerged as a potent method for programming AI models such as DALL·E, Midjourney, and GPT, yet discovering high-quality prompts online can be quite a challenge. For those skilled in prompt engineering, monetizing this expertise is often unclear. PromptBase addresses this gap by providing a marketplace that allows users to buy and sell effective prompts that yield superior results while minimizing API costs. Users can access top-notch prompts, enhance their output, and profit by selling their own creations. As an innovative marketplace tailored for DALL·E, Midjourney, Stable Diffusion, and GPT prompts, PromptBase offers a straightforward way for individuals to sell their prompts and earn from their creative talents. In just two minutes, you can upload your prompt, link to Stripe, and start selling. PromptBase also facilitates instant prompt engineering with Stable Diffusion, enabling users to craft and market their prompts efficiently. Additionally, users benefit from receiving five free generation credits every day, making it an enticing platform for budding prompt engineers. This unique opportunity not only cultivates creativity but also fosters a community of prompt enthusiasts eager to share and improve their skills.

Relying solely on a few examples is insufficient for thorough evaluation. To gain actionable insights for enhancing your models, it’s essential to gather extensive end-user feedback. With the improvement engine designed for GPT, you can effortlessly conduct A/B tests on models and prompts. While prompts serve as a starting point, achieving superior results necessitates fine-tuning on your most valuable data—no coding expertise or data science knowledge is required. Integrate with just a single line of code and seamlessly experiment with various language model providers like Claude and ChatGPT without needing to revisit the setup. By leveraging robust APIs, you can create innovative and sustainable products, provided you have the right tools to tailor the models to your clients’ needs. Copy AI fine-tunes models using their best data, leading to cost efficiencies and a competitive edge. This approach fosters enchanting product experiences that captivate over 2 million active users, highlighting the importance of continuous improvement and adaptation in a rapidly evolving landscape. Additionally, the ability to iterate quickly on user feedback ensures that your offerings remain relevant and engaging.

Enhance and maintain your prompts using version control techniques. Implement an auto-generated API to access your prompts seamlessly. Conduct comprehensive end-to-end testing of your LLM before deploying any updates to production prompts. Facilitate collaboration between industry experts and engineers on a unified platform. Allow your industry specialists and prompt engineers to experiment and refine their prompts without needing programming expertise. Our testing suite enables you to design and execute an unlimited number of test cases, ensuring the optimal quality of your prompts. Evaluate for hallucinations, potential issues, edge cases, and more. This suite represents the pinnacle of prompt complexity. Utilize Git-like functionalities to oversee your prompts effectively. Establish a repository for each specific project, allowing for the creation of multiple branches to refine your prompts. You can commit changes and evaluate them in an isolated environment, with the option to revert to any previous version effortlessly. With our real-time APIs, a single click can update and deploy your prompt instantly, ensuring that your latest revisions are always live and accessible to users. This streamlined process not only improves efficiency but also enhances the overall reliability of your prompt management.

Introducing Ape, the pioneering AI prompt engineer, designed with advanced capabilities such as tracing, dataset curation, batch testing, and evaluations. Achieving a remarkable 93% score on the GSM8K benchmark, Ape outperforms both DSPy, which scores 86%, and traditional LLMs, which only reach 70%. It employs real-world data to continually refine prompts and integrates CI/CD to prevent any decline in performance. By incorporating a human-in-the-loop approach featuring scoring and feedback, Ape enhances its effectiveness. Furthermore, the integration with the Weavel SDK allows for automatic logging and incorporation of LLM outputs into your dataset as you interact with your application. This ensures a smooth integration process and promotes ongoing enhancement tailored to your specific needs. In addition to these features, Ape automatically generates evaluation code and utilizes LLMs as impartial evaluators for intricate tasks, which simplifies your assessment workflow and guarantees precise, detailed performance evaluations. With Ape's reliable functionality, your guidance and feedback help it evolve further, as you can contribute scores and suggestions for improvement. Equipped with comprehensive logging, testing, and evaluation tools for LLM applications, Ape stands out as a vital resource for optimizing AI-driven tasks. Its adaptability and continuous learning mechanism make it an invaluable asset in any AI project.

Entry Point AI serves as a cutting-edge platform for optimizing both proprietary and open-source language models. It allows users to manage prompts, fine-tune models, and evaluate their performance all from a single interface. Once you hit the ceiling of what prompt engineering can achieve, transitioning to model fine-tuning becomes essential, and our platform simplifies this process. Rather than instructing a model on how to act, fine-tuning teaches it desired behaviors. This process works in tandem with prompt engineering and retrieval-augmented generation (RAG), enabling users to fully harness the capabilities of AI models. Through fine-tuning, you can enhance the quality of your prompts significantly. Consider it an advanced version of few-shot learning where key examples are integrated directly into the model. For more straightforward tasks, you have the option to train a lighter model that can match or exceed the performance of a more complex one, leading to reduced latency and cost. Additionally, you can configure your model to avoid certain responses for safety reasons, which helps safeguard your brand and ensures proper formatting. By incorporating examples into your dataset, you can also address edge cases and guide the behavior of the model, ensuring it meets your specific requirements effectively. This comprehensive approach ensures that you not only optimize performance but also maintain control over the model's responses.

Introduce features powered by LLMs into production using tools designed for prompt engineering, semantic search, version control, quantitative testing, and performance tracking, all of which are compatible with the leading LLM providers. Expedite the process of developing a minimum viable product by testing various prompts, parameters, and different LLM providers to quickly find the optimal setup for your specific needs. Vellum serves as a fast, dependable proxy to LLM providers, enabling you to implement version-controlled modifications to your prompts without any coding requirements. Additionally, Vellum gathers model inputs, outputs, and user feedback, utilizing this information to create invaluable testing datasets that can be leveraged to assess future modifications before deployment. Furthermore, you can seamlessly integrate company-specific context into your prompts while avoiding the hassle of managing your own semantic search infrastructure, enhancing the relevance and precision of your interactions.

Ignite your imagination with PromptPal, the premier platform designed for exploring and exchanging top-notch AI prompts. Spark fresh ideas and enhance your efficiency as you tap into the potential of artificial intelligence through PromptPal's extensive collection of over 3,400 complimentary AI prompts. Delve into our impressive library of suggestions and find the inspiration you need to elevate your productivity today. Peruse our vast array of ChatGPT prompts, fueling your motivation and efficiency even further. Additionally, you can monetize your creativity by contributing prompts and showcasing your prompt engineering expertise within the dynamic PromptPal community. This is not just a platform; it's a thriving hub for collaboration and innovation.

Introducing PromptPerfect, an innovative tool specifically crafted for enhancing prompts used with large language models (LLMs), large models (LMs), and LMOps. Crafting the ideal prompt can present challenges, yet it is essential for generating exceptional AI-driven content. Fortunately, PromptPerfect is here to assist you! This advanced tool simplifies the process of prompt engineering by automatically refining your prompts for various models, including ChatGPT, GPT-3.5, DALLE, and StableDiffusion. Regardless of whether you are a prompt engineer, a content creator, or a developer in the AI field, PromptPerfect ensures that prompt optimization is straightforward and user-friendly. Equipped with an easy-to-navigate interface and robust features, PromptPerfect empowers users to harness the complete capabilities of LLMs and LMs, consistently producing outstanding results. Embrace the shift from mediocre AI-generated content to the pinnacle of prompt optimization with PromptPerfect, and experience the difference in quality you can achieve!

DoCoreAI is a platform focused on optimizing AI prompts and telemetry, catering to product teams, SaaS companies, and developers who engage with large language models (LLMs) such as those from OpenAI and Groq (Infra). Featuring a local-first Python client along with a secure telemetry engine, DoCoreAI allows teams to gather metrics on LLM usage while safeguarding original prompts to ensure data confidentiality. Highlighted Features: - Prompt Optimization → Enhance the effectiveness and dependability of LLM prompts. - LLM Usage Monitoring → Observe token usage, response times, and performance trends. - Cost Analytics → Evaluate and optimize expenses related to LLM usage across teams. - Developer Productivity Dashboards → Pinpoint time savings and identify usage bottlenecks. - AI Telemetry → Gather comprehensive insights while prioritizing user privacy. By utilizing DoCoreAI, organizations can reduce token expenses, elevate AI model performance, and provide developers with a centralized platform to analyze prompt behavior in production, ultimately fostering a more efficient workflow. This all-encompassing approach not only boosts productivity but also promotes informed decision-making based on actionable data insights.

Phoenix serves as a comprehensive open-source observability toolkit tailored for experimentation, evaluation, and troubleshooting purposes. It empowers AI engineers and data scientists to swiftly visualize their datasets, assess performance metrics, identify problems, and export relevant data for enhancements. Developed by Arize AI, the creators of a leading AI observability platform, alongside a dedicated group of core contributors, Phoenix is compatible with OpenTelemetry and OpenInference instrumentation standards. The primary package is known as arize-phoenix, and several auxiliary packages cater to specialized applications. Furthermore, our semantic layer enhances LLM telemetry within OpenTelemetry, facilitating the automatic instrumentation of widely-used packages. This versatile library supports tracing for AI applications, allowing for both manual instrumentation and seamless integrations with tools like LlamaIndex, Langchain, and OpenAI. By employing LLM tracing, Phoenix meticulously logs the routes taken by requests as they navigate through various stages or components of an LLM application, thus providing a clearer understanding of system performance and potential bottlenecks. Ultimately, Phoenix aims to streamline the development process, enabling users to maximize the efficiency and reliability of their AI solutions.

Latitude is a comprehensive platform for prompt engineering, helping product teams design, test, and optimize AI prompts for large language models (LLMs). It provides a suite of tools for importing, refining, and evaluating prompts using real-time data and synthetic datasets. The platform integrates with production environments to allow seamless deployment of new prompts, with advanced features like automatic prompt refinement and dataset management. Latitude’s ability to handle evaluations and provide observability makes it a key tool for organizations seeking to improve AI performance and operational efficiency.

Introducing Narrow AI: Eliminating the Need for Prompt Engineering by Engineers Narrow AI seamlessly generates, oversees, and fine-tunes prompts for any AI model, allowing you to launch AI functionalities ten times quicker and at significantly lower costs. Enhance quality while significantly reducing expenses - Slash AI expenditures by 95% using more affordable models - Boost precision with Automated Prompt Optimization techniques - Experience quicker responses through models with reduced latency Evaluate new models in mere minutes rather than weeks - Effortlessly assess prompt effectiveness across various LLMs - Obtain benchmarks for cost and latency for each distinct model - Implement the best-suited model tailored to your specific use case Deliver LLM functionalities ten times faster - Automatically craft prompts at an expert level - Adjust prompts to accommodate new models as they become available - Fine-tune prompts for optimal quality, cost efficiency, and speed while ensuring a smooth integration process for your applications.

Streamline your prompt testing, collaboration, versioning, and deployment all in one location with PromptHub. Eliminate the hassle of constant copy and pasting by leveraging variables for easier prompt creation. Bid farewell to cumbersome spreadsheets and effortlessly compare different outputs side-by-side while refining your prompts. Scale your testing with batch processing to effectively manage your datasets and prompts. Ensure the consistency of your prompts by testing across various models, variables, and parameters. Simultaneously stream two conversations and experiment with different models, system messages, or chat templates to find the best fit. You can commit prompts, create branches, and collaborate without any friction. Our system detects changes to prompts, allowing you to concentrate on analyzing outputs. Facilitate team reviews of changes, approve new versions, and keep everyone aligned. Additionally, keep track of requests, associated costs, and latency with ease. PromptHub provides a comprehensive solution for testing, versioning, and collaborating on prompts within your team, thanks to its GitHub-style versioning that simplifies the iterative process and centralizes your work. With the ability to manage everything in one place, your team can work more efficiently and effectively than ever before.

Enhance your team's prompt engineering capabilities by guaranteeing top-notch outputs from LLMs through automated testing and thorough evaluation. Streamline the creation and organization of your prompts, allowing for easy templating, saving, and structuring of prompt settings. Conduct automated tests and receive detailed results within seconds, which will help you save valuable time and boost your productivity. Organize your prompt settings meticulously, and deploy them instantly for integration into your own software solutions. Design, test, and implement prompts with remarkable speed and efficiency. Empower your entire team and effectively reconcile technical execution with practical applications. With PromptPoint’s intuitive no-code platform, every team member can effortlessly create and evaluate prompt configurations. Adapt with ease in a diverse model landscape by seamlessly interfacing with a multitude of large language models available. This approach not only enhances collaboration but also fosters innovation across your projects.

Streamline your prompt edits, version control, and SDK integration all in one centralized location. Say goodbye to the chaos of multiple tools and the delays of waiting for deployments to implement changes. Discover features specifically designed to enhance your workflow and boost your prompt engineering capabilities. Organize your prompts and projects systematically, utilizing tools that ensure everything remains structured and easy to access. Adapt your prompts on the fly to suit the specific context of your application, significantly improving user interactions with customized experiences. Effortlessly integrate prompt management into your existing development environment with our intuitive SDK, which prioritizes minimal disruption while maximizing productivity. Utilize comprehensive analytics to gain insights into prompt effectiveness, user interaction, and potential areas for enhancement, all based on solid data. Foster collaboration by inviting team members to work within a shared framework, allowing everyone to contribute, evaluate, and improve prompts collectively. Additionally, manage access and permissions among team members to ensure smooth and efficient collaboration. Ultimately, this cohesive approach empowers teams to achieve their goals more effectively.

Promptologer is dedicated to empowering the upcoming wave of prompt engineers, entrepreneurs, business leaders, and everyone in between. Showcase your array of prompts and GPTs, easily publish and disseminate content through our blog integration, and take advantage of shared SEO traffic within the Promptologer network. This is your comprehensive toolkit for managing products, enhanced by AI technology. UserTale simplifies the process of planning and executing your product strategy, from generating product specifications to developing detailed user personas and business model canvases, thereby reducing uncertainty. Yippity’s AI-driven question generator can automatically convert text into various formats such as multiple choice, true/false, or fill-in-the-blank quizzes. The diversity in prompts can result in a wide range of outputs. We offer a unique platform for deploying AI web applications that are exclusive to your team, allowing members to collaboratively create, share, and use company-approved prompts, thus ensuring consistency and high-quality results. Additionally, this approach fosters innovation and teamwork across your organization, ultimately driving success.

DeepEval offers an intuitive open-source framework designed for the assessment and testing of large language model systems, similar to what Pytest does but tailored specifically for evaluating LLM outputs. It leverages cutting-edge research to measure various performance metrics, including G-Eval, hallucinations, answer relevancy, and RAGAS, utilizing LLMs and a range of other NLP models that operate directly on your local machine. This tool is versatile enough to support applications developed through methods like RAG, fine-tuning, LangChain, or LlamaIndex. By using DeepEval, you can systematically explore the best hyperparameters to enhance your RAG workflow, mitigate prompt drift, or confidently shift from OpenAI services to self-hosting your Llama2 model. Additionally, the framework features capabilities for synthetic dataset creation using advanced evolutionary techniques and integrates smoothly with well-known frameworks, making it an essential asset for efficient benchmarking and optimization of LLM systems. Its comprehensive nature ensures that developers can maximize the potential of their LLM applications across various contexts.

OpenPipe offers an efficient platform for developers to fine-tune their models. It allows you to keep your datasets, models, and evaluations organized in a single location. You can train new models effortlessly with just a click. The system automatically logs all LLM requests and responses for easy reference. You can create datasets from the data you've captured, and even train multiple base models using the same dataset simultaneously. Our managed endpoints are designed to handle millions of requests seamlessly. Additionally, you can write evaluations and compare the outputs of different models side by side for better insights. A few simple lines of code can get you started; just swap out your Python or Javascript OpenAI SDK with an OpenPipe API key. Enhance the searchability of your data by using custom tags. Notably, smaller specialized models are significantly cheaper to operate compared to large multipurpose LLMs. Transitioning from prompts to models can be achieved in minutes instead of weeks. Our fine-tuned Mistral and Llama 2 models routinely exceed the performance of GPT-4-1106-Turbo, while also being more cost-effective. With a commitment to open-source, we provide access to many of the base models we utilize. When you fine-tune Mistral and Llama 2, you maintain ownership of your weights and can download them whenever needed. Embrace the future of model training and deployment with OpenPipe's comprehensive tools and features.

Unexpected outcomes are a common occurrence in software development. With complete insight into the entire sequence of calls, developers can pinpoint the origins of errors and unexpected results in real time with remarkable accuracy. The discipline of software engineering heavily depends on unit testing to create efficient and production-ready software solutions. LangSmith offers similar capabilities tailored specifically for LLM applications. You can quickly generate test datasets, execute your applications on them, and analyze the results without leaving the LangSmith platform. This tool provides essential observability for mission-critical applications with minimal coding effort. LangSmith is crafted to empower developers in navigating the complexities and leveraging the potential of LLMs. We aim to do more than just create tools; we are dedicated to establishing reliable best practices for developers. You can confidently build and deploy LLM applications, backed by comprehensive application usage statistics. This includes gathering feedback, filtering traces, measuring costs and performance, curating datasets, comparing chain efficiencies, utilizing AI-assisted evaluations, and embracing industry-leading practices to enhance your development process. This holistic approach ensures that developers are well-equipped to handle the challenges of LLM integrations.

Introducing a user-friendly right-hand side panel for AI models like ChatGPT, Google Gemini, Claude.ai, Mistral, Groq, and Pi.ai, allowing you to access your prompt library effortlessly with just a click. The PI Prompts Chrome extension is a robust tool that significantly improves your interaction with AI by streamlining your workflow and removing the hassle of repetitive copy-pasting of prompts. With features that enable you to download and upload prompts in JSON format, sharing your collection with others or curating task-specific sets is a breeze. As you begin typing your prompt in the input box, the extension intelligently filters and displays relevant prompts in the right panel. You also have the flexibility to manage your prompt list by adding external JSON prompt lists, as well as editing or deleting prompts directly from the panel. Your prompt collections will automatically sync across all devices using Chrome, ensuring seamless access wherever you are. Additionally, the panel is designed to accommodate both light and dark themes, making it visually versatile for any user preference. This extension not only enhances productivity but also fosters collaboration by making it easy to share and manage prompts with friends and colleagues.

Leverage cutting-edge NLP advancements by utilizing Haystack's pipeline architecture on your own datasets. You can create robust solutions for semantic search, question answering, summarization, and document ranking, catering to a diverse array of NLP needs. Assess various components and refine models for optimal performance. Interact with your data in natural language, receiving detailed answers from your documents through advanced QA models integrated within Haystack pipelines. Conduct semantic searches that prioritize meaning over mere keyword matching, enabling a more intuitive retrieval of information. Explore and evaluate the latest pre-trained transformer models, including OpenAI's GPT-3, BERT, RoBERTa, and DPR, among others. Develop semantic search and question-answering systems that are capable of scaling to accommodate millions of documents effortlessly. The framework provides essential components for the entire product development lifecycle, such as file conversion tools, indexing capabilities, model training resources, annotation tools, domain adaptation features, and a REST API for seamless integration. This comprehensive approach ensures that you can meet various user demands and enhance the overall efficiency of your NLP applications.

Flowise is a versatile open-source platform that simplifies the creation of tailored Large Language Model (LLM) applications using an intuitive drag-and-drop interface designed for low-code development. This platform accommodates connections with multiple LLMs, such as LangChain and LlamaIndex, and boasts more than 100 integrations to support the building of AI agents and orchestration workflows. Additionally, Flowise offers a variety of APIs, SDKs, and embedded widgets that enable smooth integration into pre-existing systems, ensuring compatibility across different platforms, including deployment in isolated environments using local LLMs and vector databases. As a result, developers can efficiently create and manage sophisticated AI solutions with minimal technical barriers.

Promptimize AI is a browser extension designed to help users elevate their interactions with AI effortlessly. By entering a prompt and clicking "enhance," users can upgrade their initial submissions into more powerful prompts, which leads to a significant improvement in the quality of AI-generated content. The extension provides various features, including immediate enhancements, dynamic variables for maintaining consistent context, a library for saving favorite prompts, and support for all leading AI platforms such as ChatGPT, Claude, and Gemini. This tool is perfect for anyone who wishes to simplify their prompt creation journey, uphold brand consistency, and enhance their skills in prompt engineering without needing extensive knowledge. With Promptimize, users can avoid the complexity of becoming prompt engineers, allowing the extension to handle the hard work. Customized prompts yield more accurate, engaging, and influential AI outputs. By utilizing this tool, you can streamline your prompt creation process, which not only saves time but also conserves valuable resources, ultimately making your AI interactions more efficient and effective. Embrace the ease of using Promptimize and transform the way you work with AI technology.

ChainForge serves as an open-source visual programming platform aimed at enhancing prompt engineering and evaluating large language models. This tool allows users to rigorously examine the reliability of their prompts and text-generation models, moving beyond mere anecdotal assessments. Users can conduct simultaneous tests of various prompt concepts and their iterations across different LLMs to discover the most successful combinations. Additionally, it assesses the quality of responses generated across diverse prompts, models, and configurations to determine the best setup for particular applications. Evaluation metrics can be established, and results can be visualized across prompts, parameters, models, and configurations, promoting a data-driven approach to decision-making. The platform also enables the management of multiple conversations at once, allows for the templating of follow-up messages, and supports the inspection of outputs at each interaction to enhance communication strategies. ChainForge is compatible with a variety of model providers, such as OpenAI, HuggingFace, Anthropic, Google PaLM2, Azure OpenAI endpoints, and locally hosted models like Alpaca and Llama. Users have the flexibility to modify model settings and leverage visualization nodes for better insights and outcomes. Overall, ChainForge is a comprehensive tool tailored for both prompt engineering and LLM evaluation, encouraging innovation and efficiency in this field.

SpellPrints allows creators to create and monetize generative AI-powered apps. The platform provides access to over 1,000 AI models and UI elements, as well as payments and prompt chaining interfaces. This makes it easy for prompt engineers turn their knowledge into a business. The creator can transform prompts or AI models into monetizable apps that can be distributed via UI and API. We are creating both a platform for developers and a marketplace where users can find and use these apps.

Athina functions as a collaborative platform for AI development, empowering teams to efficiently create, test, and oversee their AI applications. It includes a variety of features such as prompt management, evaluation tools, dataset management, and observability, all aimed at facilitating the development of dependable AI systems. With the ability to integrate various models and services, including custom solutions, Athina also prioritizes data privacy through detailed access controls and options for self-hosted deployments. Moreover, the platform adheres to SOC-2 Type 2 compliance standards, ensuring a secure setting for AI development activities. Its intuitive interface enables seamless collaboration between both technical and non-technical team members, significantly speeding up the process of deploying AI capabilities. Ultimately, Athina stands out as a versatile solution that helps teams harness the full potential of artificial intelligence.

Orq.ai stands out as the leading platform tailored for software teams to effectively manage agentic AI systems on a large scale. It allows you to refine prompts, implement various use cases, and track performance meticulously, ensuring no blind spots and eliminating the need for vibe checks. Users can test different prompts and LLM settings prior to launching them into production. Furthermore, it provides the capability to assess agentic AI systems within offline environments. The platform enables the deployment of GenAI features to designated user groups, all while maintaining robust guardrails, prioritizing data privacy, and utilizing advanced RAG pipelines. It also offers the ability to visualize all agent-triggered events, facilitating rapid debugging. Users gain detailed oversight of costs, latency, and overall performance. Additionally, you can connect with your preferred AI models or even integrate your own. Orq.ai accelerates workflow efficiency with readily available components specifically designed for agentic AI systems. It centralizes the management of essential phases in the LLM application lifecycle within a single platform. With options for self-hosted or hybrid deployment, it ensures compliance with SOC 2 and GDPR standards, thereby providing enterprise-level security. This comprehensive approach not only streamlines operations but also empowers teams to innovate and adapt swiftly in a dynamic technological landscape.

Automated voice testing, monitoring and more. Test your AI voice agent with 1000s of simulated users within minutes. It's hard to get AI voice agents right. LLM outputs can be affected by a small change in the prompts, function calls or model providers. We are the only platform that can support you from development through to production. Hamming allows you to store, manage, update and sync your prompts with voice infra provider. This is 1000x faster than testing voice agents manually. Use our prompt playground for testing LLM outputs against a dataset of inputs. Our LLM judges quality of generated outputs. Save 80% on manual prompt engineering. Monitor your app in more than one way. We actively track, score and flag cases where you need to pay attention. Convert calls and traces to test cases, and add them to the golden dataset.