
fastserve-ai
Machine Learning Serving focused on GenAI with simplicity as the top priority.
Stars: 56

FastServe-AI is a machine learning serving tool focused on GenAI & LLMs with simplicity as the top priority. It allows users to easily serve custom models by implementing the 'handle' method for 'FastServe'. The tool provides a FastAPI server for custom models and can be deployed using Lightning AI Studio. Users can install FastServe-AI via pip and run it to serve their own GPT-like LLM models in minutes.
README:
Machine Learning Serving focused on GenAI & LLMs with simplicity as the top priority.
Stable:
pip install FastServeAI
Latest:
pip install git+https://github.com/gradsflow/fastserve-ai.git@main
YouTube: How to serve your own GPT like LLM in 1 minute with FastServe.
To serve a custom model, you will have to implement handle
method for FastServe
that processes a batch of inputs and
returns the response as a list.
from fastserve import FastServe
class MyModelServing(FastServe):
def __init__(self):
super().__init__(batch_size=2, timeout=0.1)
self.model = create_model(...)
def handle(self, batch: List[BaseRequest]) -> List[float]:
inputs = [b.request for b in batch]
response = self.model(inputs)
return response
app = MyModelServing()
app.run_server()
You can run the above script in terminal, and it will launch a FastAPI server for your custom model.
python fastserve.deploy.lightning --filename main.py \
--user LIGHTNING_USERNAME \
--teamspace LIGHTNING_TEAMSPACE \
--machine "CPU" # T4, A10G or A10G_X_4
Install in editable mode:
git clone https://github.com/gradsflow/fastserve-ai.git
cd fastserve
pip install -e .
Create a new branch
git checkout -b <new-branch>
Make your changes, commit and create a PR.
For Tasks:
Click tags to check more tools for each tasksFor Jobs:
Alternative AI tools for fastserve-ai
Similar Open Source Tools

fastserve-ai
FastServe-AI is a machine learning serving tool focused on GenAI & LLMs with simplicity as the top priority. It allows users to easily serve custom models by implementing the 'handle' method for 'FastServe'. The tool provides a FastAPI server for custom models and can be deployed using Lightning AI Studio. Users can install FastServe-AI via pip and run it to serve their own GPT-like LLM models in minutes.

llama-assistant
Llama Assistant is an AI-powered assistant that helps with daily tasks, such as voice recognition, natural language processing, summarizing text, rephrasing sentences, answering questions, and more. It runs offline on your local machine, ensuring privacy by not sending data to external servers. The project is a work in progress with regular feature additions.

obsei
Obsei is an open-source, low-code, AI powered automation tool that consists of an Observer to collect unstructured data from various sources, an Analyzer to analyze the collected data with various AI tasks, and an Informer to send analyzed data to various destinations. The tool is suitable for scheduled jobs or serverless applications as all Observers can store their state in databases. Obsei is still in alpha stage, so caution is advised when using it in production. The tool can be used for social listening, alerting/notification, automatic customer issue creation, extraction of deeper insights from feedbacks, market research, dataset creation for various AI tasks, and more based on creativity.

AutoRAG
AutoRAG is an AutoML tool designed to automatically find the optimal RAG pipeline for your data. It simplifies the process of evaluating various RAG modules to identify the best pipeline for your specific use-case. The tool supports easy evaluation of different module combinations, making it efficient to find the most suitable RAG pipeline for your needs. AutoRAG also offers a cloud beta version to assist users in running and optimizing the tool, along with building RAG evaluation datasets for a starting price of $9.99 per optimization.

auto-subs
Auto-subs is a tool designed to automatically transcribe editing timelines using OpenAI Whisper and Stable-TS for extreme accuracy. It generates subtitles in a custom style, is completely free, and runs locally within Davinci Resolve. It works on Mac, Linux, and Windows, supporting both Free and Studio versions of Resolve. Users can jump to positions on the timeline using the Subtitle Navigator and translate from any language to English. The tool provides a user-friendly interface for creating and customizing subtitles for video content.

Learn_Prompting
Learn Prompting is a platform offering free resources, courses, and webinars to master prompt engineering and generative AI. It provides a Prompt Engineering Guide, courses on Generative AI, workshops, and the HackAPrompt competition. The platform also offers AI Red Teaming and AI Safety courses, research reports on prompting techniques, and welcomes contributions in various forms such as content suggestions, translations, artwork, and typo fixes. Users can locally develop the website using Visual Studio Code, Git, and Node.js, and run it in development mode to preview changes.

WilliamButcherBot
WilliamButcherBot is a Telegram Group Manager Bot and Userbot written in Python using Pyrogram. It provides features for managing Telegram groups and users, with ready-to-use methods available. The bot requires Python 3.9, Telegram API Key, Telegram Bot Token, and MongoDB URI. Users can install it locally or on a VPS, run it directly, generate Pyrogram session for Heroku, or use Docker for deployment. Additionally, users can write new modules to extend the bot's functionality by adding them to the wbb/modules/ directory.

wzry_ai
This is an open-source project for playing the game King of Glory with an artificial intelligence model. The first phase of the project has been completed, and future upgrades will be built upon this foundation. The second phase of the project has started, and progress is expected to proceed according to plan. For any questions, feel free to join the QQ exchange group: 687853827. The project aims to learn artificial intelligence and strictly prohibits cheating. Detailed installation instructions are available in the doc/README.md file. Environment installation video: (bilibili) Welcome to follow, like, tip, comment, and provide your suggestions.

yolo-flutter-app
Ultralytics YOLO for Flutter is a Flutter plugin that allows you to integrate Ultralytics YOLO computer vision models into your mobile apps. It supports both Android and iOS platforms, providing APIs for object detection and image classification. The plugin leverages Flutter Platform Channels for seamless communication between the client and host, handling all processing natively. Before using the plugin, you need to export the required models in `.tflite` and `.mlmodel` formats. The plugin provides support for tasks like detection and classification, with specific instructions for Android and iOS platforms. It also includes features like camera preview and methods for object detection and image classification on images. Ultralytics YOLO thrives on community collaboration and offers different licensing paths for open-source and commercial use cases.

ebook2audiobook
ebook2audiobook is a CPU/GPU converter tool that converts eBooks to audiobooks with chapters and metadata using tools like Calibre, ffmpeg, XTTSv2, and Fairseq. It supports voice cloning and a wide range of languages. The tool is designed to run on 4GB RAM and provides a new v2.0 Web GUI interface for user-friendly interaction. Users can convert eBooks to text format, split eBooks into chapters, and utilize high-quality text-to-speech functionalities. Supported languages include Arabic, Chinese, English, French, German, Hindi, and many more. The tool can be used for legal, non-DRM eBooks only and should be used responsibly in compliance with applicable laws.

duolingo-clone
Lingo is an interactive platform for language learning that provides a modern UI/UX experience. It offers features like courses, quests, and a shop for users to engage with. The tech stack includes React JS, Next JS, Typescript, Tailwind CSS, Vercel, and Postgresql. Users can contribute to the project by submitting changes via pull requests. The platform utilizes resources from CodeWithAntonio, Kenney Assets, Freesound, Elevenlabs AI, and Flagpack. Key dependencies include @clerk/nextjs, @neondatabase/serverless, @radix-ui/react-avatar, and more. Users can follow the project creator on GitHub and Twitter, as well as subscribe to their YouTube channel for updates. To learn more about Next.js, users can refer to the Next.js documentation and interactive tutorial.

Notate
Notate is a powerful desktop research assistant that combines AI-driven analysis with advanced vector search technology. It streamlines research workflow by processing, organizing, and retrieving information from documents, audio, and text. Notate offers flexible AI capabilities with support for various LLM providers and local models, ensuring data privacy. Built for researchers, academics, and knowledge workers, it features real-time collaboration, accessible UI, and cross-platform compatibility.

claude-code.nvim
Claude Code Neovim Plugin is a seamless integration between Claude Code AI assistant and Neovim. It allows users to toggle Claude Code in a terminal window with a single key press, automatically detect and reload files modified by Claude Code, provide real-time buffer updates when files are changed externally, offer customizable window position and size, integrate with which-key, use git project root as working directory, maintain a modular code structure, provide type annotations with LuaCATS for better IDE support, offer configuration validation, and include a testing framework for reliability. The plugin creates a terminal buffer running the Claude Code CLI, sets up autocommands to detect file changes on disk, automatically reloads files modified by Claude Code, provides keymaps and commands for toggling the terminal, and detects git repositories to set the working directory to the git root.

ollama4j
Ollama4j is a Java library that serves as a wrapper or binding for the Ollama server. It facilitates communication with the Ollama server and provides models for deployment. The tool requires Java 11 or higher and can be installed locally or via Docker. Users can integrate Ollama4j into Maven projects by adding the specified dependency. The tool offers API specifications and supports various development tasks such as building, running unit tests, and integration tests. Releases are automated through GitHub Actions CI workflow. Areas of improvement include adhering to Java naming conventions, updating deprecated code, implementing logging, using lombok, and enhancing request body creation. Contributions to the project are encouraged, whether reporting bugs, suggesting enhancements, or contributing code.

ChatGPT-Next-Web
ChatGPT Next Web is a well-designed cross-platform ChatGPT web UI tool that supports Claude, GPT4, and Gemini Pro models. It allows users to deploy their private ChatGPT applications with ease. The tool offers features like one-click deployment, compact client for Linux/Windows/MacOS, compatibility with self-deployed LLMs, privacy-first approach with local data storage, markdown support, responsive design, fast loading speed, prompt templates, awesome prompts, chat history compression, multilingual support, and more.
For similar tasks

fastserve-ai
FastServe-AI is a machine learning serving tool focused on GenAI & LLMs with simplicity as the top priority. It allows users to easily serve custom models by implementing the 'handle' method for 'FastServe'. The tool provides a FastAPI server for custom models and can be deployed using Lightning AI Studio. Users can install FastServe-AI via pip and run it to serve their own GPT-like LLM models in minutes.
For similar jobs

weave
Weave is a toolkit for developing Generative AI applications, built by Weights & Biases. With Weave, you can log and debug language model inputs, outputs, and traces; build rigorous, apples-to-apples evaluations for language model use cases; and organize all the information generated across the LLM workflow, from experimentation to evaluations to production. Weave aims to bring rigor, best-practices, and composability to the inherently experimental process of developing Generative AI software, without introducing cognitive overhead.

LLMStack
LLMStack is a no-code platform for building generative AI agents, workflows, and chatbots. It allows users to connect their own data, internal tools, and GPT-powered models without any coding experience. LLMStack can be deployed to the cloud or on-premise and can be accessed via HTTP API or triggered from Slack or Discord.

VisionCraft
The VisionCraft API is a free API for using over 100 different AI models. From images to sound.

kaito
Kaito is an operator that automates the AI/ML inference model deployment in a Kubernetes cluster. It manages large model files using container images, avoids tuning deployment parameters to fit GPU hardware by providing preset configurations, auto-provisions GPU nodes based on model requirements, and hosts large model images in the public Microsoft Container Registry (MCR) if the license allows. Using Kaito, the workflow of onboarding large AI inference models in Kubernetes is largely simplified.

PyRIT
PyRIT is an open access automation framework designed to empower security professionals and ML engineers to red team foundation models and their applications. It automates AI Red Teaming tasks to allow operators to focus on more complicated and time-consuming tasks and can also identify security harms such as misuse (e.g., malware generation, jailbreaking), and privacy harms (e.g., identity theft). The goal is to allow researchers to have a baseline of how well their model and entire inference pipeline is doing against different harm categories and to be able to compare that baseline to future iterations of their model. This allows them to have empirical data on how well their model is doing today, and detect any degradation of performance based on future improvements.

tabby
Tabby is a self-hosted AI coding assistant, offering an open-source and on-premises alternative to GitHub Copilot. It boasts several key features: * Self-contained, with no need for a DBMS or cloud service. * OpenAPI interface, easy to integrate with existing infrastructure (e.g Cloud IDE). * Supports consumer-grade GPUs.

spear
SPEAR (Simulator for Photorealistic Embodied AI Research) is a powerful tool for training embodied agents. It features 300 unique virtual indoor environments with 2,566 unique rooms and 17,234 unique objects that can be manipulated individually. Each environment is designed by a professional artist and features detailed geometry, photorealistic materials, and a unique floor plan and object layout. SPEAR is implemented as Unreal Engine assets and provides an OpenAI Gym interface for interacting with the environments via Python.

Magick
Magick is a groundbreaking visual AIDE (Artificial Intelligence Development Environment) for no-code data pipelines and multimodal agents. Magick can connect to other services and comes with nodes and templates well-suited for intelligent agents, chatbots, complex reasoning systems and realistic characters.