Pinned Repositories
animated_horizontal_calendar
brick
An intuitive way to work with persistent data in Dart
Cheatsheets-1
Penetration Testing/Security Cheatsheets
dspy
DSPy: The framework for programming—not prompting—foundation models
dspy-docs
Official Documentation for DSPy Library
litellm
Python SDK, Proxy Server (LLM Gateway) to call 100+ LLM APIs in OpenAI format - [Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, HuggingFace, Replicate, Groq]
search_fundamentals_course
Public repository for the Search Fundamentals course taught by Daniel Tunkelang and Grant Ingersoll. Available at https://corise.com/course/search-fundamentals?utm_source=daniel
search_with_machine_learning_course
Public repository for the Search with Machine Learning course taught by Daniel Tunkelang and Grant Ingersoll. Available at https://corise.com/course/search-with-machine-learning?utm_source=daniel.
tetrisai
A Tetris AI written in Javascript
Haknt's Repositories
Haknt/brick
An intuitive way to work with persistent data in Dart
Haknt/tetrisai
A Tetris AI written in Javascript
Haknt/animated_horizontal_calendar
Haknt/Cheatsheets-1
Penetration Testing/Security Cheatsheets
Haknt/dspy
DSPy: The framework for programming—not prompting—foundation models
Haknt/dspy-docs
Official Documentation for DSPy Library
Haknt/litellm
Python SDK, Proxy Server (LLM Gateway) to call 100+ LLM APIs in OpenAI format - [Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, HuggingFace, Replicate, Groq]
Haknt/search_fundamentals_course
Public repository for the Search Fundamentals course taught by Daniel Tunkelang and Grant Ingersoll. Available at https://corise.com/course/search-fundamentals?utm_source=daniel
Haknt/search_with_machine_learning_course
Public repository for the Search with Machine Learning course taught by Daniel Tunkelang and Grant Ingersoll. Available at https://corise.com/course/search-with-machine-learning?utm_source=daniel.
Haknt/uvicorn-gunicorn-docker
Docker image with Uvicorn managed by Gunicorn for high-performance web applications in Python 3.6 with performance auto-tuning. Optionally with Alpine Linux.