How we optimized Dash's relevance judge with DSPy
Dropbox used DSPy to turn prompt engineering for our relevance judge into a measurable, automated optimization loop, improving task performance, cost, and how reliably it works in production.
https://dropbox.tech/machine-learning/optimizing-dropbox-dash-relevance-judge-with-dspy
Dropbox used DSPy to turn prompt engineering for our relevance judge into a measurable, automated optimization loop, improving task performance, cost, and how reliably it works in production.
https://dropbox.tech/machine-learning/optimizing-dropbox-dash-relevance-judge-with-dspy
dropbox.tech
How we optimized Dash's relevance judge with DSPy
We used DSPy to turn prompt engineering for our relevance judge into a measurable, automated optimization loop, improving task performance, cost, and how reliably it works in production.
Would it have been better if Meta bought Astral.sh instead?
https://www.reddit.com/r/Python/comments/1ryglss/would_it_have_been_better_if_meta_bought_astralsh/
https://www.reddit.com/r/Python/comments/1ryglss/would_it_have_been_better_if_meta_bought_astralsh/
Reddit
From the Python community on Reddit
Explore this post and more from the Python community
Reinventing Python's AsyncIO
The post explores a redesign of Python’s async runtime, arguing that the current async/await and event-loop model adds unnecessary complexity, and proposing a simpler runtime where concurrency is handled automatically without explicit async syntax.The author experiments with a new runtime approach that can run async workloads 2–3.5× faster than traditional asyncio, suggesting Python’s co...
https://blog.baro.dev/p/reinventing-pythons-asyncio
The post explores a redesign of Python’s async runtime, arguing that the current async/await and event-loop model adds unnecessary complexity, and proposing a simpler runtime where concurrency is handled automatically without explicit async syntax.The author experiments with a new runtime approach that can run async workloads 2–3.5× faster than traditional asyncio, suggesting Python’s co...
https://blog.baro.dev/p/reinventing-pythons-asyncio
Fluxus by gi0baro
Reinventing Python's AsyncIO | Fluxus by gi0baro
My journey (so far) in rethinking Python's async code execution
Visitran
Build data transformation pipelines using Python with a visual IDE and AI assistant.
https://github.com/Zipstack/visitran
Build data transformation pipelines using Python with a visual IDE and AI assistant.
https://github.com/Zipstack/visitran
GitHub
GitHub - Zipstack/visitran: Modern, AI-native and agentic Pythonic data transformation platform.
Modern, AI-native and agentic Pythonic data transformation platform. - Zipstack/visitran
LiteLLM Python package compromised by supply-chain attack
https://github.com/BerriAI/litellm/issues/24512
https://github.com/BerriAI/litellm/issues/24512
GitHub
[Security]: CRITICAL: Malicious litellm_init.pth in litellm 1.82.8 — credential stealer · Issue #24512 · BerriAI/litellm
[LITELLM TEAM] - For updates from the team, please see: #24518 [Security]: CRITICAL: Malicious litellm_init.pth in litellm 1.82.8 PyPI package — credential stealer Summary The litellm==1.82.8 wheel...
The Hidden Mechanism Behind Clean Python APIs (Descriptor Deep Dive)
Descriptors define how Python resolves attribute access, explaining why values sometimes come from the instance, class, or elsewhere in non-obvious ways. Understanding descriptor rules enables cleaner, more reusable designs by giving you precise control over attribute behavior.
https://www.youtube.com/watch?v=7SUzTOkUVLY
Descriptors define how Python resolves attribute access, explaining why values sometimes come from the instance, class, or elsewhere in non-obvious ways. Understanding descriptor rules enables cleaner, more reusable designs by giving you precise control over attribute behavior.
https://www.youtube.com/watch?v=7SUzTOkUVLY
YouTube
The Hidden Mechanism Behind Clean Python APIs (Descriptor Deep Dive)
🧱 Build software that lasts. Join the Software Design Mastery waiting list → https://arjan.codes/mastery.
In this video, I explain what descriptors are, why attribute access in Python sometimes behaves in surprising ways, and how the descriptor rules determine…
In this video, I explain what descriptors are, why attribute access in Python sometimes behaves in surprising ways, and how the descriptor rules determine…
Build Your Own Openclaw - A step by step guide, using python
https://github.com/czl9707/build-your-own-openclaw
https://github.com/czl9707/build-your-own-openclaw
GitHub
GitHub - czl9707/build-your-own-openclaw: A step-by-step guide to build your own AI agent.
A step-by-step guide to build your own AI agent. Contribute to czl9707/build-your-own-openclaw development by creating an account on GitHub.
justx
A TUI command launcher built on top of just. Define recipes once, run them anywhere.
https://github.com/fpgmaas/justx
A TUI command launcher built on top of just. Define recipes once, run them anywhere.
https://github.com/fpgmaas/justx
GitHub
GitHub - fpgmaas/justx: A TUI command launcher built on top of just. Define recipes once, run them anywhere.
A TUI command launcher built on top of just. Define recipes once, run them anywhere. - fpgmaas/justx
agentscope-ai / ReMe
ReMe: Memory Management Kit for Agents - Remember Me, Refine Me.
https://github.com/agentscope-ai/ReMe
ReMe: Memory Management Kit for Agents - Remember Me, Refine Me.
https://github.com/agentscope-ai/ReMe
GitHub
GitHub - agentscope-ai/ReMe: ReMe: Memory Management Kit for Agents - Remember Me, Refine Me.
ReMe: Memory Management Kit for Agents - Remember Me, Refine Me. - agentscope-ai/ReMe
Pydantic AI - Intro to Agentic AI with Pydantic AI framework
We'll look at using Pydantic AI to build agent-based workflows, starting with simple fundamentals, and building up to more complex examples that use vector databases, RAG, multi-agent workflows and more.
https://www.youtube.com/playlist?list=PL-2EBeDYMIbSWGoDzOFm33_5W_ShO-VIi
We'll look at using Pydantic AI to build agent-based workflows, starting with simple fundamentals, and building up to more complex examples that use vector databases, RAG, multi-agent workflows and more.
https://www.youtube.com/playlist?list=PL-2EBeDYMIbSWGoDzOFm33_5W_ShO-VIi
Oxyde ORM
A type-safe, Pydantic-centric asynchronous ORM with a high-performance Rust core designed for clarity, speed, and reliability.
https://github.com/mr-fatalyst/oxyde
A type-safe, Pydantic-centric asynchronous ORM with a high-performance Rust core designed for clarity, speed, and reliability.
https://github.com/mr-fatalyst/oxyde
GitHub
GitHub - mr-fatalyst/oxyde: Oxyde ORM is a type-safe, Pydantic-centric asynchronous ORM with a high-performance Rust core designed…
Oxyde ORM is a type-safe, Pydantic-centric asynchronous ORM with a high-performance Rust core designed for clarity, speed, and reliability. - mr-fatalyst/oxyde