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A high-performance observability data pipeline.
Uncomplicated Observability for Python and beyond! 🪵🔥
A curated list of engineering blogs
Test generation for Developers. Generate tests and stubs for your application that actually work!
🦔 PostHog provides open-source product analytics, session recording, feature flagging and A/B testing that you can self-host.
GritQL is a query language for searching, linting, and modifying code.
🪢 Langfuse Python SDK - Instrument your LLM app with decorators or low-level SDK and get detailed tracing/observability. Works with any LLM or framework
The fantastic ORM library for Golang, aims to be developer friendly
Community maintained clone of https://github.com/dgrijalva/jwt-go
Fully open source, End to End Encrypted alternative to Google Photos and Apple Photos
Open and extensible continuous delivery solution for Kubernetes. Powered by GitOps Toolkit.
High-Performance server for NATS.io, the cloud and edge native messaging system.
Get up and running with Llama 3, Mistral, Gemma 2, and other large language models.
This is a repo with links to everything you'd ever want to learn about data engineering
The high-performance database for modern applications
Examples and guides for using the Portkey APIs
Adding guardrails to large language models.
Build reliable, secure, and production-ready AI apps easily.
Build reliable, secure, and production-ready AI apps easily.
🔍 LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your d…
🦜🔗 Build context-aware reasoning applications
A Blazing Fast AI Gateway. Route to 200+ LLMs with 1 fast & friendly API.
Semantic cache for LLMs. Fully integrated with LangChain and llama_index.
LlamaIndex is a data framework for your LLM applications
Defining styles for creating an aesthetically pleasing command line experience
Add breakpoints to CI: pause, access the workflow with SSH, debug and resume.
Neon: Serverless Postgres. We separated storage and compute to offer autoscaling, code-like database branching, and scale to zero.