JR
Jokke Ruokolainen
@jruokola
Model Context Protocol development prompt
Prompt for developing RAG based systems and features in GenAI applications
Prompt for developing agent based GenAI applications
Prompt for the LLM to generate better prompts for given tasks and problems
Prompt for defining good practices around LLM application data pipeline development
Prompt for assistants to develop production grade deployment architecures for GenAI applications
Prompt for assistants to develop comprehensive evaluation strategies for GenAI applications
Prompt for the assistant to develop sound and relevant fine-tuning code
Documentation for Langgraph
Documentation for FastAPI
Documentation for Uvicorn
Polars is a blazingly fast DataFrame library for manipulating structured data. The core is written in Rust, and available for Python, R and NodeJS.
Documentation for Microsoft Autogen
Documentation for Model Context Protocol
Documentation for Llama-Index
Documentation for Langchain
ONNX can be compared to a programming language specialized in mathematical functions. It defines all the necessary operations a machine learning model needs to implement its inference function with this language.
MLX is a NumPy-like array framework designed for efficient and flexible machine learning on Apple silicon, brought to you by Apple machine learning research.
PydanticAI is a Python Agent Framework designed to make it less painful to build production grade applications with Generative AI.
NVIDIA TensorRT is an SDK that facilitates high-performance machine learning inference. It complements training frameworks such as TensorFlow, PyTorch, and MXNet. It focuses on running an already-trained network quickly and efficiently on NVIDIA hardware.
DSPy is the framework for programming—rather than prompting—language models. It allows you to iterate fast on building modular AI systems and offers algorithms for optimizing their prompts and weights, whether you're building simple classifiers, sophisticated RAG pipelines, or Agent loops.
JAX is a Python library for accelerator-oriented array computation and program transformation, designed for high-performance numerical computing and large-scale machine learning.
An extremely fast Python linter and code formatter, written in Rust.
An extremely fast Python package and project manager, written in Rust.
MLflow is an open-source platform, purpose-built to assist machine learning practitioners and teams in handling the complexities of the machine learning process. MLflow focuses on the full lifecycle for machine learning projects, ensuring that each phase is manageable, traceable, and reproducible.
Ragas is a library that provides tools to supercharge the evaluation of Large Language Model (LLM) applications. It is designed to help you evaluate your LLM applications with ease and confidence.
OpenAI Proxy Server (LLM Gateway) to call 100+ LLMs in a unified interface & track spend, set budgets per virtual key/user
Infrastrucuture as code
Containerize applications
Kubernetes is an open source container orchestration engine for automating deployment, scaling, and management of containerized applications. The open source project is hosted by the Cloud Native Computing Foundation (CNCF).
OpenTelemetry, also known as OTel, is a vendor-neutral open source Observability framework for instrumenting, generating, collecting, and exporting telemetry data such as traces, metrics, and logs. As an industry-standard, OpenTelemetry is supported by more than 40 observability vendors, integrated by many libraries, services, and apps, and adopted by numerous end users.
Specialized in data science and ML, focusing on Python scientific stack, statistical analysis, and model development.
Specialized in developing GenAI applications in Python, fluent in best practices related to: MPC Tool Design RAG Pipeline Desing Multi-Agent System Design Prompt Template Development Training Data Pipeline Design for LLMs GenAI Production System Design GenAI Evaluation Framework Design Custom Model Development and Fine-Tuning Strategies
