pezzo
đšī¸ Open-source, developer-first LLMOps platform designed to streamline prompt design, version management, instant delivery, collaboration, troubleshooting, observability and more.
Stars: 2266
Pezzo is a fully cloud-native and open-source LLMOps platform that allows users to observe and monitor AI operations, troubleshoot issues, save costs and latency, collaborate, manage prompts, and deliver AI changes instantly. It supports various clients for prompt management, observability, and caching. Users can run the full Pezzo stack locally using Docker Compose, with prerequisites including Node.js 18+, Docker, and a GraphQL Language Feature Support VSCode Extension. Contributions are welcome, and the source code is available under the Apache 2.0 License.
README:
Pezzo is a fully cloud-native and open-source LLMOps platform. Seamlessly observe and monitor your AI operations, troubleshoot issues, save up to 90% on costs and latency, collaborate and manage your prompts in one place, and instantly deliver AI changes.
Â
Â
Â
Click here to navigate to the Official Pezzo Documentation
In the documentation, you can find information on how to use Pezzo, its architecture, including tutorials and recipes for varius use cases and LLM providers.
Feature | Node.js âĸ Docs | Python âĸ Docs | LangChain |
---|---|---|---|
Prompt Management | â | â | â |
Observability | â | â | â |
Caching | â | â | â |
Looking for a client that's not listed here? Open an issue and let us know!
If you simplay want to run the full Pezzo stack locally, check out Running With Docker Compose in the documentation.
If you want to run Pezzo in development mode, continue reading.
- Node.js 18+
- Docker
- (Recommended) GraphQL Language Feature Support VSCode Extension
Install NPM dependencies by running:
npm install
Pezzo uses a .env file to store environment variables. When using docker, you should also create a .env.docker file.
See the .env.example file for reference.
Pezzo is entirely cloud-native and relies solely on open-source technologies such as PostgreSQL, ClickHouse, Redis and Supertokens.
You can run these dependencies via Docker Compose:
docker-compose -f docker-compose.infra.yaml up
Deploy Prisma migrations:
npx dotenv-cli -e apps/server/.env -- npx prisma migrate deploy --schema apps/server/prisma/schema.prisma
Run the server:
npx nx serve server
The server is now running. You can verify that by navigating to http://localhost:3000/api/healthz.
In development mode, you want to run codegen
in watch mode, so whenever you make changes to the schema, types are generated automatically. After running the server, run the following in a separate terminal Window:
npm run graphql:codegen:watch
This will connect codegen directly to the server and keep your GraphQL schema up-to-date as you make changes.
Finally, you are ready to run the Pezzo Console:
npx nx serve console
That's it! The Pezzo Console is now accessible at http://localhost:4200 đ
We welcome contributions from the community! Please feel free to submit pull requests or create issues for bugs or feature suggestions.
If you want to contribute but not sure how, join our Discord and we'll be happy to help you out!
Please check out CONTRIBUTING.md before contributing.
This repository's source code is available under the Apache 2.0 License.
For Tasks:
Click tags to check more tools for each tasksFor Jobs:
Alternative AI tools for pezzo
Similar Open Source Tools
pezzo
Pezzo is a fully cloud-native and open-source LLMOps platform that allows users to observe and monitor AI operations, troubleshoot issues, save costs and latency, collaborate, manage prompts, and deliver AI changes instantly. It supports various clients for prompt management, observability, and caching. Users can run the full Pezzo stack locally using Docker Compose, with prerequisites including Node.js 18+, Docker, and a GraphQL Language Feature Support VSCode Extension. Contributions are welcome, and the source code is available under the Apache 2.0 License.
vidur
Vidur is an open-source next-gen Recruiting OS that offers an intuitive and modern interface for forward-thinking companies to efficiently manage their recruitment processes. It combines advanced candidate profiles, team workspace, plugins, and one-click apply features. The project is under active development, and contributors are welcome to join by addressing open issues. To ensure privacy, security issues should be reported via email to [email protected].
InvokeAI
InvokeAI is a leading creative engine built to empower professionals and enthusiasts alike. Generate and create stunning visual media using the latest AI-driven technologies. InvokeAI offers an industry leading Web Interface, interactive Command Line Interface, and also serves as the foundation for multiple commercial products.
swirl-search
Swirl is an open-source software that allows users to simultaneously search multiple content sources and receive AI-ranked results. It connects to various data sources, including databases, public data services, and enterprise sources, and utilizes AI and LLMs to generate insights and answers based on the user's data. Swirl is easy to use, requiring only the download of a YML file, starting in Docker, and searching with Swirl. Users can add credentials to preloaded SearchProviders to access more sources. Swirl also offers integration with ChatGPT as a configured AI model. It adapts and distributes user queries to anything with a search API, re-ranking the unified results using Large Language Models without extracting or indexing anything. Swirl includes five Google Programmable Search Engines (PSEs) to get users up and running quickly. Key features of Swirl include Microsoft 365 integration, SearchProvider configurations, query adaptation, synchronous or asynchronous search federation, optional subscribe feature, pipelining of Processor stages, results stored in SQLite3 or PostgreSQL, built-in Query Transformation support, matching on word stems and handling of stopwords, duplicate detection, re-ranking of unified results using Cosine Vector Similarity, result mixers, page through all results requested, sample data sets, optional spell correction, optional search/result expiration service, easily extensible Connector and Mixer objects, and a welcoming community for collaboration and support.
buildel
Buildel is an AI automation platform that empowers users to create versatile workflows without writing code. It supports multiple providers and interfaces, offers pre-built use cases, and allows users to bring their own API keys. Ideal for AI-powered document retrieval, conversational interfaces, and data integration. Users can get started at app.buildel.ai or run Buildel locally with Node.js, Elixir/Erlang, Docker, Git, and JQ installed. Join the community on Discord for support and discussions.
ocular
Ocular is a set of modules and tools that allow you to build rich, reliable, and performant Generative AI-Powered Search Platforms without the need to reinvent Search Architecture. We help you build you spin up customized internal search in days not months.
chainlit
Chainlit is an open-source async Python framework which allows developers to build scalable Conversational AI or agentic applications. It enables users to create ChatGPT-like applications, embedded chatbots, custom frontends, and API endpoints. The framework provides features such as multi-modal chats, chain of thought visualization, data persistence, human feedback, and an in-context prompt playground. Chainlit is compatible with various Python programs and libraries, including LangChain, Llama Index, Autogen, OpenAI Assistant, and Haystack. It offers a range of examples and a cookbook to showcase its capabilities and inspire users. Chainlit welcomes contributions and is licensed under the Apache 2.0 license.
llm-app
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.
thread
Thread is an AI-powered Jupyter alternative that integrates an AI copilot into your editing experience. It offers a familiar Jupyter Notebook editing experience with features like natural language code edits, generating cells to answer questions, context-aware chat sidebar, and automatic error explanations or fixes. The tool aims to enhance code editing and data exploration by providing a more interactive and intuitive experience for users. Thread can be used for free with Ollama or your own API key, and it runs locally for convenience and privacy.
radicalbit-ai-monitoring
The Radicalbit AI Monitoring Platform provides a comprehensive solution for monitoring Machine Learning and Large Language models in production. It helps proactively identify and address potential performance issues by analyzing data quality, model quality, and model drift. The repository contains files and projects for running the platform, including UI, API, SDK, and Spark components. Installation using Docker compose is provided, allowing deployment with a K3s cluster and interaction with a k9s container. The platform documentation includes a step-by-step guide for installation and creating dashboards. Community engagement is encouraged through a Discord server. The roadmap includes adding functionalities for batch and real-time workloads, covering various model types and tasks.
FunClip
FunClip is an open-source, locally deployable automated video editing tool that utilizes the FunASR Paraformer series models from Alibaba DAMO Academy for speech recognition in videos. Users can select text segments or speakers from the recognition results and click the clip button to obtain the corresponding video segments. FunClip integrates advanced features such as the Paraformer-Large model for accurate Chinese ASR, SeACo-Paraformer for customized hotword recognition, CAM++ speaker recognition model, Gradio interactive interface for easy usage, support for multiple free edits with automatic SRT subtitles generation, and segment-specific SRT subtitles.
chatdev
ChatDev IDE is a tool for building your AI agent, Whether it's NPCs in games or powerful agent tools, you can design what you want for this platform. It accelerates prompt engineering through **JavaScript Support** that allows implementing complex prompting techniques.
embedchain
Embedchain is an Open Source Framework for personalizing LLM responses. It simplifies the creation and deployment of personalized AI applications by efficiently managing unstructured data, generating relevant embeddings, and storing them in a vector database. With diverse APIs, users can extract contextual information, find precise answers, and engage in interactive chat conversations tailored to their data. The framework follows the design principle of being 'Conventional but Configurable' to cater to both software engineers and machine learning engineers.
gradient-cli
Gradient CLI is a tool designed to facilitate the end-to-end MLOps process, allowing individuals and organizations to develop, train, and deploy Deep Learning models efficiently. It supports various ML/DL frameworks and provides features such as 1-click Jupyter Notebooks, scalable model training workflows, and model deployment as API endpoints. The tool can run on different infrastructures like AWS, GCP, on-premise, and Paperspace GPUs, offering automatic versioning, distributed training, hyperparameter search, and more.
admyral
Admyral is an open-source Cybersecurity Automation & Investigation Assistant that provides a unified console for investigations and incident handling, workflow automation creation, automatic alert investigation, and next step suggestions for analysts. It aims to tackle alert fatigue and automate security workflows effectively by offering features like workflow actions, AI actions, case management, alert handling, and more. Admyral combines security automation and case management to streamline incident response processes and improve overall security posture. The tool is open-source, transparent, and community-driven, allowing users to self-host, contribute, and collaborate on integrations and features.
toolmate
ToolMate AI is an advanced AI companion that integrates agents, tools, and plugins to excel in conversations, generative work, and task execution. It supports multi-step actions, allowing users to customize workflows for tackling complex projects with ease. The tool offers a wide range of AI backends and models, including Ollama, Llama.cpp, Groq Cloud API, OpenAI API, and Google Gemini via Vertex AI. Users can easily switch between backends and leverage AI models like wizardlm2 and mixtral. ToolMate AI stands out for its distinctive features such as tool calling for any LLMs, running multiple tools in one go, highly customizable plugins, and integration with popular AI tools. It also supports quick tool calling using '@' notation and enables the execution of computing tasks on demand. With features like multiple tools in one go, customizable plugins, system command and fabric integration, GPU offloading support, real-time data access, and device information retrieval, ToolMate AI offers a comprehensive solution for various tasks and content creation.
For similar tasks
pezzo
Pezzo is a fully cloud-native and open-source LLMOps platform that allows users to observe and monitor AI operations, troubleshoot issues, save costs and latency, collaborate, manage prompts, and deliver AI changes instantly. It supports various clients for prompt management, observability, and caching. Users can run the full Pezzo stack locally using Docker Compose, with prerequisites including Node.js 18+, Docker, and a GraphQL Language Feature Support VSCode Extension. Contributions are welcome, and the source code is available under the Apache 2.0 License.
airflow
Apache Airflow (or simply Airflow) is a platform to programmatically author, schedule, and monitor workflows. When workflows are defined as code, they become more maintainable, versionable, testable, and collaborative. Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command line utilities make performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress, and troubleshoot issues when needed.
tt-metal
TT-NN is a python & C++ Neural Network OP library. It provides a low-level programming model, TT-Metalium, enabling kernel development for Tenstorrent hardware.
Forza-Mods-AIO
Forza Mods AIO is a free and open-source tool that enhances the gaming experience in Forza Horizon 4 and 5. It offers a range of time-saving and quality-of-life features, making gameplay more enjoyable and efficient. The tool is designed to streamline various aspects of the game, improving user satisfaction and overall enjoyment.
openssa
OpenSSA is an open-source framework for creating efficient, domain-specific AI agents. It enables the development of Small Specialist Agents (SSAs) that solve complex problems in specific domains. SSAs tackle multi-step problems that require planning and reasoning beyond traditional language models. They apply OODA for deliberative reasoning (OODAR) and iterative, hierarchical task planning (HTP). This "System-2 Intelligence" breaks down complex tasks into manageable steps. SSAs make informed decisions based on domain-specific knowledge. With OpenSSA, users can create agents that process, generate, and reason about information, making them more effective and efficient in solving real-world challenges.
llm_qlora
LLM_QLoRA is a repository for fine-tuning Large Language Models (LLMs) using QLoRA methodology. It provides scripts for training LLMs on custom datasets, pushing models to HuggingFace Hub, and performing inference. Additionally, it includes models trained on HuggingFace Hub, a blog post detailing the QLoRA fine-tuning process, and instructions for converting and quantizing models. The repository also addresses troubleshooting issues related to Python versions and dependencies.
humanoid-gym
Humanoid-Gym is a reinforcement learning framework designed for training locomotion skills for humanoid robots, focusing on zero-shot transfer from simulation to real-world environments. It integrates a sim-to-sim framework from Isaac Gym to Mujoco for verifying trained policies in different physical simulations. The codebase is verified with RobotEra's XBot-S and XBot-L humanoid robots. It offers comprehensive training guidelines, step-by-step configuration instructions, and execution scripts for easy deployment. The sim2sim support allows transferring trained policies to accurate simulated environments. The upcoming features include Denoising World Model Learning and Dexterous Hand Manipulation. Installation and usage guides are provided along with examples for training PPO policies and sim-to-sim transformations. The code structure includes environment and configuration files, with instructions on adding new environments. Troubleshooting tips are provided for common issues, along with a citation and acknowledgment section.
transcriptionstream
Transcription Stream is a self-hosted diarization service that works offline, allowing users to easily transcribe and summarize audio files. It includes a web interface for file management, Ollama for complex operations on transcriptions, and Meilisearch for fast full-text search. Users can upload files via SSH or web interface, with output stored in named folders. The tool requires a NVIDIA GPU and provides various scripts for installation and running. Ports for SSH, HTTP, Ollama, and Meilisearch are specified, along with access details for SSH server and web interface. Customization options and troubleshooting tips are provided in the documentation.
For similar jobs
pezzo
Pezzo is a fully cloud-native and open-source LLMOps platform that allows users to observe and monitor AI operations, troubleshoot issues, save costs and latency, collaborate, manage prompts, and deliver AI changes instantly. It supports various clients for prompt management, observability, and caching. Users can run the full Pezzo stack locally using Docker Compose, with prerequisites including Node.js 18+, Docker, and a GraphQL Language Feature Support VSCode Extension. Contributions are welcome, and the source code is available under the Apache 2.0 License.
AirGo
AirGo is a front and rear end separation, multi user, multi protocol proxy service management system, simple and easy to use. It supports vless, vmess, shadowsocks, and hysteria2.
mosec
Mosec is a high-performance and flexible model serving framework for building ML model-enabled backend and microservices. It bridges the gap between any machine learning models you just trained and the efficient online service API. * **Highly performant** : web layer and task coordination built with Rust đĻ, which offers blazing speed in addition to efficient CPU utilization powered by async I/O * **Ease of use** : user interface purely in Python đ, by which users can serve their models in an ML framework-agnostic manner using the same code as they do for offline testing * **Dynamic batching** : aggregate requests from different users for batched inference and distribute results back * **Pipelined stages** : spawn multiple processes for pipelined stages to handle CPU/GPU/IO mixed workloads * **Cloud friendly** : designed to run in the cloud, with the model warmup, graceful shutdown, and Prometheus monitoring metrics, easily managed by Kubernetes or any container orchestration systems * **Do one thing well** : focus on the online serving part, users can pay attention to the model optimization and business logic
llm-code-interpreter
The 'llm-code-interpreter' repository is a deprecated plugin that provides a code interpreter on steroids for ChatGPT by E2B. It gives ChatGPT access to a sandboxed cloud environment with capabilities like running any code, accessing Linux OS, installing programs, using filesystem, running processes, and accessing the internet. The plugin exposes commands to run shell commands, read files, and write files, enabling various possibilities such as running different languages, installing programs, starting servers, deploying websites, and more. It is powered by the E2B API and is designed for agents to freely experiment within a sandboxed environment.
learn-generative-ai
Learn Cloud Applied Generative AI Engineering (GenEng) is a course focusing on the application of generative AI technologies in various industries. The course covers topics such as the economic impact of generative AI, the role of developers in adopting and integrating generative AI technologies, and the future trends in generative AI. Students will learn about tools like OpenAI API, LangChain, and Pinecone, and how to build and deploy Large Language Models (LLMs) for different applications. The course also explores the convergence of generative AI with Web 3.0 and its potential implications for decentralized intelligence.
gcloud-aio
This repository contains shared codebase for two projects: gcloud-aio and gcloud-rest. gcloud-aio is built for Python 3's asyncio, while gcloud-rest is a threadsafe requests-based implementation. It provides clients for Google Cloud services like Auth, BigQuery, Datastore, KMS, PubSub, Storage, and Task Queue. Users can install the library using pip and refer to the documentation for usage details. Developers can contribute to the project by following the contribution guide.
fluid
Fluid is an open source Kubernetes-native Distributed Dataset Orchestrator and Accelerator for data-intensive applications, such as big data and AI applications. It implements dataset abstraction, scalable cache runtime, automated data operations, elasticity and scheduling, and is runtime platform agnostic. Key concepts include Dataset and Runtime. Prerequisites include Kubernetes version > 1.16, Golang 1.18+, and Helm 3. The tool offers features like accelerating remote file accessing, machine learning, accelerating PVC, preloading dataset, and on-the-fly dataset cache scaling. Contributions are welcomed, and the project is under the Apache 2.0 license with a vendor-neutral approach.
aiges
AIGES is a core component of the Athena Serving Framework, designed as a universal encapsulation tool for AI developers to deploy AI algorithm models and engines quickly. By integrating AIGES, you can deploy AI algorithm models and engines rapidly and host them on the Athena Serving Framework, utilizing supporting auxiliary systems for networking, distribution strategies, data processing, etc. The Athena Serving Framework aims to accelerate the cloud service of AI algorithm models and engines, providing multiple guarantees for cloud service stability through cloud-native architecture. You can efficiently and securely deploy, upgrade, scale, operate, and monitor models and engines without focusing on underlying infrastructure and service-related development, governance, and operations.