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DSPyWeekly Issue No #2
Published on September 11, 2025
📚 Articles
Exploring GEPA and DSPy for AI system optimization
GEPA, or Genetic-Pareto, is a sample-efficient optimizer based on three principles: Genetic evolution, Pareto filtering, and Reflection using natural language feedback.
Manual Tool Handling
For more control over the tool calling process, you can manually handle tools using DSPy's tool types.
DSRs, @DSPyOSS for Rust
Happy to finally announce the stable release of DSRs. Over the past few months, I’ve been building DSRs with incredible support and contributions from folks Maguire Papay, @tech_optimist, and @joshmo_dev. A big shout out to @lateinteraction and @ChenMoneyQ who were the first people to hear my frequent rants on this!! Couldn't have done this without all of them.
@DSPyOSS module which lets you wrap another module and make it stateful - allowing multi-turn conversations
Created a little custom @DSPyOSS module which lets you wrap another module and make it stateful - allowing multi-turn conversations.
Where are DSPy users from?
GA analytics shared by DSPy team.
🎥 Video
No metric? No problem. Optimizing Dspy programs with human in the loop
Getting started with Dspy can be difficult because we often don't see great performance out of the box without using an optimizer. | Channel: Skylar Payne
Accelerate End-to-End Multi-Agents on Databricks and DSPy
A production-ready GenAI application is more than the framework itself. Like ML, you need a unified platform to create an ... | Channel: Databricks
Context Engineering: Isaac Miller on Context Engineering with DSPy
Context engineering is rising in popularity because prompting alone isn't enough—we're still figuring out how to build reliable AI ... | Channel: Chroma
DSPy 3.0 — and DSPy at Databricks
The DSPy OSS team at Databricks and beyond is excited to present DSPy 3.0, targeted for release close to DAIS 2025. We will ... | Channel: Databricks
Context Engineering with DSPy - the fully hands-on Basics to Pro course!
This comprehensive guide to Context Engineering shows how to build powerful and reliable applications with Large Language ... | Channel: Neural Breakdown with AVB
🚀 Projects
KarelDO/xmc.dspy
In-Context Learning for eXtreme Multi-Label Classification (XMC) using only a handful of examples. | Language: Python | License: MIT License
ganarajpr/awesome-dspy
An Awesome list of curated DSPy resources.
XiaoConstantine/maestro
Local AI code review assistant built on dspy-go. | Language: Go | License: MIT License
sachink1729/DSPy-Multi-Hop-Chain-of-Thought-RAG
Discover advanced AI techniques in my repository combining Multi-Hop Chain of Thought (CoT) and Retrieval-Augmented Generation (RAG) using DSPy and Indexify. Enhance complex problem-solving with multi-step reasoning and external knowledge integration. Perfect for AI enthusiasts and researchers. | Language: Jupyter Notebook | License: Apache License 2.0
kuzudb/dspy-kuzu-demo
Intro to using DSPy with Kuzu to enrich the data within the Nobel Laureate mentorship network | Language: Python | License: MIT License
dleerdefi/llm-security-auditor
Universal LLM security auditor with automated jailbreak testing, DSPy optimization, and OWASP 2025-aligned attack patterns | Language: Python | License: MIT License
sachink1729/SQL-Agents-Using-RAG-DSPy-Groq
Exploring advanced prompting tools to query SQL database with multiple tables in natural language using LLMs | Language: Jupyter Notebook | License: Apache License 2.0
ganarajpr/sanskrit-translator-dspy
Using DSPy and LLM's to translate Sanskrit verses | Language: Python
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