Building A Generative AI Platform
The article outlines the common components and architecture of a generative AI platform, discussing how to enhance context input, implement guardrails, add model routing and gateways, optimize with caching, and incorporate complex logic and write actions. It provides a comprehensive guide for building and scaling AI applications, emphasizing the importance of observability and orchestrat...
https://huyenchip.com//2024/07/25/genai-platform.html
The article outlines the common components and architecture of a generative AI platform, discussing how to enhance context input, implement guardrails, add model routing and gateways, optimize with caching, and incorporate complex logic and write actions. It provides a comprehensive guide for building and scaling AI applications, emphasizing the importance of observability and orchestrat...
https://huyenchip.com//2024/07/25/genai-platform.html
Chip Huyen
Building A Generative AI Platform
After studying how companies deploy generative AI applications, I noticed many similarities in their platforms. This post outlines the common components of a generative AI platform, what they do, and how they are implemented. I try my best to keep the architecture…
patchwork
Automate development gruntwork like code reviews, patching and documentation with LLM workflows.
https://github.com/patched-codes/patchwork
Automate development gruntwork like code reviews, patching and documentation with LLM workflows.
https://github.com/patched-codes/patchwork
GitHub
GitHub - patched-codes/patchwork: Agentic AI framework for enterprise workflow automation.
Agentic AI framework for enterprise workflow automation. - patched-codes/patchwork
❤1
Datoviz – Vulkan-based GPU scientific visualization (C/C++/Python)
https://github.com/datoviz/datoviz
https://github.com/datoviz/datoviz
GitHub
GitHub - datoviz/datoviz: ⚡ Datoviz: high-performance rendering for scientific data visualization
⚡ Datoviz: high-performance rendering for scientific data visualization - datoviz/datoviz
Debugging distributed database mysteries with Rust, packet capture and Polars
Unravel a mysterious network bandwidth issue in QuestDB's primary-replica replication was identified and resolved. Learn about the tools and techniques used, including Rust for packet capture and Python with Polars for data analysis, to optimize network performance.
https://questdb.io/blog/debugging-distributed-database-mysteries-with-rust-pcap-and-polars/
Unravel a mysterious network bandwidth issue in QuestDB's primary-replica replication was identified and resolved. Learn about the tools and techniques used, including Rust for packet capture and Python with Polars for data analysis, to optimize network performance.
https://questdb.io/blog/debugging-distributed-database-mysteries-with-rust-pcap-and-polars/
QuestDB
Debugging distributed database mysteries with Rust, packet capture and Polars | QuestDB
Unravel a mysterious network bandwidth issue in QuestDB's primary-replica replication was identified and resolved. Learn about the tools and techniques used, including Rust for packet capture and Python with Polars for data analysis, to optimize network performance.
A simply utility script which allows you to analyze your Python file
https://github.com/mraza007/python-file-analyzer
https://github.com/mraza007/python-file-analyzer
GitHub
GitHub - mraza007/python-file-analyzer: A simple utility script which allows you to analyze your python file
A simple utility script which allows you to analyze your python file - mraza007/python-file-analyzer
Dioptra
Dioptra is a software test platform for assessing the trustworthy characteristics of artificial intelligence (AI).
https://github.com/usnistgov/dioptra
Dioptra is a software test platform for assessing the trustworthy characteristics of artificial intelligence (AI).
https://github.com/usnistgov/dioptra
GitHub
GitHub - usnistgov/dioptra: Test Software for the Characterization of AI Technologies
Test Software for the Characterization of AI Technologies - GitHub - usnistgov/dioptra: Test Software for the Characterization of AI Technologies
Formy
Generate dynamic UI forms from text using OpenAI's structured output API.
https://github.com/deedy/formy
Generate dynamic UI forms from text using OpenAI's structured output API.
https://github.com/deedy/formy
GitHub
GitHub - deedy/formy: Generate dynamic UI forms from text using OpenAI's structured output API
Generate dynamic UI forms from text using OpenAI's structured output API - deedy/formy
MindSearch
An LLM-based Multi-agent Framework of Web Search Engine (like Perplexity.ai Pro and SearchGPT)
https://github.com/InternLM/MindSearch
An LLM-based Multi-agent Framework of Web Search Engine (like Perplexity.ai Pro and SearchGPT)
https://github.com/InternLM/MindSearch
GitHub
GitHub - InternLM/MindSearch: 🔍 An LLM-based Multi-agent Framework of Web Search Engine (like Perplexity.ai Pro and SearchGPT)
🔍 An LLM-based Multi-agent Framework of Web Search Engine (like Perplexity.ai Pro and SearchGPT) - InternLM/MindSearch
The trouble with __all__
This article discusses the limitations and pitfalls of using the all attribute in Python for defining public APIs, emphasizing how it fails to enforce module boundaries and can lead to tightly coupled codebases. The author proposes an alternative solution involving a custom import hook to ensure stricter module interface enforcement.
https://www.gauge.sh/blog/the-trouble-with-all
This article discusses the limitations and pitfalls of using the all attribute in Python for defining public APIs, emphasizing how it fails to enforce module boundaries and can lead to tightly coupled codebases. The author proposes an alternative solution involving a custom import hook to ensure stricter module interface enforcement.
https://www.gauge.sh/blog/the-trouble-with-all
www.gauge.sh
The trouble with __all__ - Gauge - Solving the monolith/microservices dilemma
The trouble with __all__. Gauge is solving the monolith/microservices dilemma. We’re building tools to untangle codebases through incremental modularization. Our open-source toolkit supports defining and enforcing rules for interfaces and dependencies. By…
FINALLY Python is Getting Rid of the GIL!
This video discusses how Python 3.13 is revolutionizing performance by making the Global Interpreter Lock (GIL) optional! Learn what the GIL is, why it exists, and the potential impacts of its removal on your Python projects.
https://www.youtube.com/watch?v=zWPe_CUR4yU
This video discusses how Python 3.13 is revolutionizing performance by making the Global Interpreter Lock (GIL) optional! Learn what the GIL is, why it exists, and the potential impacts of its removal on your Python projects.
https://www.youtube.com/watch?v=zWPe_CUR4yU
YouTube
How Much FASTER Is Python 3.13 Without the GIL?
👷 Review code better and faster with my 3-Factor Framework: https://arjan.codes/diagnosis.
In this video, I'll discuss how Python 3.13 is revolutionizing performance by making the Global Interpreter Lock (GIL) optional! Learn what the GIL is, why it exists…
In this video, I'll discuss how Python 3.13 is revolutionizing performance by making the Global Interpreter Lock (GIL) optional! Learn what the GIL is, why it exists…
👍2
Recent Performance Improvements in Function Calls in CPython
https://blog.codingconfessions.com/p/are-function-calls-still-slow-in-python
https://blog.codingconfessions.com/p/are-function-calls-still-slow-in-python
Codingconfessions
Are Function Calls Still Slow in Python? An Analysis of Recent Optimizations in CPython
How costly it is to call functions and builtins in your python code? Does inlining help? How have the recent CPython releases improved performance in these areas?
👍1
DCPerf
DCPerf benchmark suite for hyperscale cloud applications,
https://github.com/facebookresearch/DCPerf
DCPerf benchmark suite for hyperscale cloud applications,
https://github.com/facebookresearch/DCPerf
GitHub
GitHub - facebookresearch/DCPerf: DCPerf benchmark suite for hyperscale cloud applications
DCPerf benchmark suite for hyperscale cloud applications - facebookresearch/DCPerf
Talk to Django with natural language. Text to SQL and more.
The video demonstrates using Djeno database for natural language to SQL queries via embeddings, emphasizing semantic search, and integration with Django. It covers setting up PostgreSQL, creating Django models, embedding for efficient search, and caching for performance, while addressing bugs and customizing prompts in the SQL engine.
https://www.youtube.com/watch?v=GfDJ-Sxn4dE
The video demonstrates using Djeno database for natural language to SQL queries via embeddings, emphasizing semantic search, and integration with Django. It covers setting up PostgreSQL, creating Django models, embedding for efficient search, and caching for performance, while addressing bugs and customizing prompts in the SQL engine.
https://www.youtube.com/watch?v=GfDJ-Sxn4dE
YouTube
Talk to Django with natural language. Text to SQL and more.
⭐️ Sign up for Neon right now! https://neon.tech/cfe
Topics:
✅ Python web development with Django
✅ Talk to your database through Django and AI
✅ Adding AI to your Django Project
✅ Integrate Django and Jupyter for rapid analysis and prototyping
✅ Implementing…
Topics:
✅ Python web development with Django
✅ Talk to your database through Django and AI
✅ Adding AI to your Django Project
✅ Integrate Django and Jupyter for rapid analysis and prototyping
✅ Implementing…