HunxByts / GhostTrack
Useful tool to track location or mobile number
https://github.com/HunxByts/GhostTrack
Useful tool to track location or mobile number
https://github.com/HunxByts/GhostTrack
GitHub
GitHub - HunxByts/GhostTrack: Useful tool to track location or mobile number
Useful tool to track location or mobile number. Contribute to HunxByts/GhostTrack development by creating an account on GitHub.
Add Agents to your Web Applications with Pydantic AI and Django
The video demonstrates how to integrate Pydantic AI with Django to add agent-like features to web applications, allowing developers to enrich chatbots with app-specific context and tools such as real-time weather services and database interactionsattached file. It showcases building customizable agents that can use dependencies, execute functions, and securely manipulate database recor...
https://www.youtube.com/watch?v=Z33IBfgVbxI
The video demonstrates how to integrate Pydantic AI with Django to add agent-like features to web applications, allowing developers to enrich chatbots with app-specific context and tools such as real-time weather services and database interactionsattached file. It showcases building customizable agents that can use dependencies, execute functions, and securely manipulate database recor...
https://www.youtube.com/watch?v=Z33IBfgVbxI
YouTube
Pydantic AI and Django: Add Agents to your Web Applications
This video gives an overview of Pydantic AI and shows how you can use it to add agentic functionality to your web applications.
Pydantic AI: https://ai.pydantic.dev/
SaaS Pegasus: https://www.saaspegasus.com/
Weather agent demo (requires login): https:/…
Pydantic AI: https://ai.pydantic.dev/
SaaS Pegasus: https://www.saaspegasus.com/
Weather agent demo (requires login): https:/…
IBM / mcp-context-forge
A Model Context Protocol (MCP) Gateway & Registry. Serves as a central management point for tools, resources, and prompts that can be accessed by MCP-compatible LLM applications. Converts REST API endpoints to MCP, composes virtual MCP servers with added security and observability, and converts between protocols (stdio, SSE, Streamable HTTP).
https://github.com/IBM/mcp-context-forge
A Model Context Protocol (MCP) Gateway & Registry. Serves as a central management point for tools, resources, and prompts that can be accessed by MCP-compatible LLM applications. Converts REST API endpoints to MCP, composes virtual MCP servers with added security and observability, and converts between protocols (stdio, SSE, Streamable HTTP).
https://github.com/IBM/mcp-context-forge
GitHub
GitHub - IBM/mcp-context-forge: A Model Context Protocol (MCP) Gateway & Registry. Serves as a central management point for tools…
A Model Context Protocol (MCP) Gateway & Registry. Serves as a central management point for tools, resources, and prompts that can be accessed by MCP-compatible LLM applications. Converts R...
wall-x
Building General-Purpose Robots Based on Embodied Foundation Model.
https://github.com/X-Square-Robot/wall-x
Building General-Purpose Robots Based on Embodied Foundation Model.
https://github.com/X-Square-Robot/wall-x
GitHub
GitHub - X-Square-Robot/wall-x: Building General-Purpose Robots Based on Embodied Foundation Model
Building General-Purpose Robots Based on Embodied Foundation Model - X-Square-Robot/wall-x
I decoupled FastAPI dependency injection system in pure python, no dependencies.
https://www.reddit.com/r/Python/comments/1ndj5vz/i_decoupled_fastapi_dependency_injection_system/
https://www.reddit.com/r/Python/comments/1ndj5vz/i_decoupled_fastapi_dependency_injection_system/
Reddit
From the Python community on Reddit: I decoupled FastAPI dependency injection system in pure python, no dependencies.
Explore this post and more from the Python community
TensorRT-Model-Optimizer
A unified library of state-of-the-art model optimization techniques like quantization, pruning, distillation, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM or TensorRT to optimize inference speed.
https://github.com/NVIDIA/TensorRT-Model-Optimizer
A unified library of state-of-the-art model optimization techniques like quantization, pruning, distillation, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM or TensorRT to optimize inference speed.
https://github.com/NVIDIA/TensorRT-Model-Optimizer
GitHub
GitHub - NVIDIA/TensorRT-Model-Optimizer: A unified library of state-of-the-art model optimization techniques like quantization…
A unified library of state-of-the-art model optimization techniques like quantization, pruning, distillation, speculative decoding, etc. It compresses deep learning models for downstream deployment...
datalab-to / marker
Convert PDF to markdown + JSON quickly with high accuracy
https://github.com/datalab-to/marker
Convert PDF to markdown + JSON quickly with high accuracy
https://github.com/datalab-to/marker
GitHub
GitHub - datalab-to/marker: Convert PDF to markdown + JSON quickly with high accuracy
Convert PDF to markdown + JSON quickly with high accuracy - datalab-to/marker
Jaxformer Scaling Modern Transformers
This is a zero-to-one guide on scaling modern transformers with n-dimensional parallelism. Transformers have driven much of the deep learning revolution, yet no practical guide reflects SOTA architectures and the complexities of large-scale language modelling. While excellent resources such as DeepMind’s How to Scale Your Model and HuggingFace’s Ultra Scale Playbook exist, a gap remains ...
https://jaxformer.com/
This is a zero-to-one guide on scaling modern transformers with n-dimensional parallelism. Transformers have driven much of the deep learning revolution, yet no practical guide reflects SOTA architectures and the complexities of large-scale language modelling. While excellent resources such as DeepMind’s How to Scale Your Model and HuggingFace’s Ultra Scale Playbook exist, a gap remains ...
https://jaxformer.com/
Jaxformer
JAXformer: Scaling Modern Transformers
A zero-to-one guide on scaling modern transformers with n-dimensional parallelism.
Post-training 101
A hitchhiker's guide into LLM post-training.
https://tokens-for-thoughts.notion.site/post-training-101
A hitchhiker's guide into LLM post-training.
https://tokens-for-thoughts.notion.site/post-training-101
tokens-for-thoughts on Notion
Post-training 101 | Tokens for Thoughts
A hitchhiker's guide into LLM post-training, by Han Fang and Karthik A Sankararaman
Nvmath-Python: Nvidia Math Libraries for the Python Ecosystem
https://github.com/NVIDIA/nvmath-python
https://github.com/NVIDIA/nvmath-python
GitHub
GitHub - NVIDIA/nvmath-python: NVIDIA Math Libraries for the Python Ecosystem
NVIDIA Math Libraries for the Python Ecosystem. Contribute to NVIDIA/nvmath-python development by creating an account on GitHub.
Python 3.13 is 10% slower than 3.12 for my file parser
https://www.reddit.com/r/Python/comments/1nmuy7t/python_313_is_10_slower_than_312_for_my_file/
https://www.reddit.com/r/Python/comments/1nmuy7t/python_313_is_10_slower_than_312_for_my_file/
Reddit
From the Python community on Reddit: Python 3.13 is 10% slower than 3.12 for my file parser
Explore this post and more from the Python community
List of 87 Programming Ideas for Beginners (with Python implementations)
https://www.reddit.com/r/Python/comments/1nitzoz/list_of_87_programming_ideas_for_beginners_with/
https://www.reddit.com/r/Python/comments/1nitzoz/list_of_87_programming_ideas_for_beginners_with/
Reddit
From the Python community on Reddit
Explore this post and more from the Python community
Mini-o3
Scaling Up Reasoning Patterns and Interaction Turns for Visual Search.
https://mini-o3.github.io/
Scaling Up Reasoning Patterns and Interaction Turns for Visual Search.
https://mini-o3.github.io/
Sphinx Docs Instantly in Your Browser (MyST Markdown + reStructuredText)
Edit and preview reStructuredText or MyST Markdown instantly in a Sphinx running in a browser. Runs entirely in Python using WebAssembly, so it’s private, fast, and ideal for learning markup.
https://snippets.documatt.com
Edit and preview reStructuredText or MyST Markdown instantly in a Sphinx running in a browser. Runs entirely in Python using WebAssembly, so it’s private, fast, and ideal for learning markup.
https://snippets.documatt.com
Documatt
Sphinx reStucturedText and Markdown online preview and editor
Preview and edit reStructuredText or Markdown (MyST) documents online with Sphinx and Docutils without installing it.
Just for fun: animating a mosaic of 90s GIFs
The post describes an experiment in animating a mosaic of vintage 90s GIFs collected from the GeoCities archive, using HTML Canvas for random, lively playback. It celebrates the playful aesthetics of early web graphics and highlights the technical and nostalgic joy of reintroducing these classic GIFs into a modern browser setting.
https://alexplescan.com/posts/2025/09/15/gifs/
The post describes an experiment in animating a mosaic of vintage 90s GIFs collected from the GeoCities archive, using HTML Canvas for random, lively playback. It celebrates the playful aesthetics of early web graphics and highlights the technical and nostalgic joy of reintroducing these classic GIFs into a modern browser setting.
https://alexplescan.com/posts/2025/09/15/gifs/
Alex Plescan
Just for fun: animating a mosaic of 90s GIFs
How I built a scrolling GIF mosaic for Battle of the Tech Bands: p5.js/WebGL, CRT shader, perceptual hashing, and NSFW filtering on GeoCities classics
JiraTUI
A Textual User Interface for interacting with Atlassian Jira from your shell.
https://github.com/whyisdifficult/jiratui
A Textual User Interface for interacting with Atlassian Jira from your shell.
https://github.com/whyisdifficult/jiratui
GitHub
GitHub - whyisdifficult/jiratui: A Textual User Interface for interacting with Atlassian Jira from your shell
A Textual User Interface for interacting with Atlassian Jira from your shell - whyisdifficult/jiratui
Tiny LLM - LLM Serving in a Week
A course of learning LLM inference serving on Apple Silicon for systems engineers: build a tiny vLLM + Qwen.
https://skyzh.github.io/tiny-llm/
A course of learning LLM inference serving on Apple Silicon for systems engineers: build a tiny vLLM + Qwen.
https://skyzh.github.io/tiny-llm/