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We present an experimental evaluation that assesses the robustness of four open source LLMs claiming function-calling capabilities against three...
In this video Prashanth Rao talks about his contribution to DSPy codebase and in the course of doing so gives us a walkthrough of BAML, it's...
Worth knowing why someone wouldn't like DSPy and see the conversation underneath.
In this conversation, Herumb Shandilya, a core maintainer of DSPy and developer of its Rust variant DSRS, discusses his journey with DSPy, the Rust...
Vicente Reig creator of DSPy.rb talking at ruby conference on DSPy.
We present Artemis, a no-code evolutionary optimization platform that jointly optimizes agent configurations through semantically-aware genetic...
DSPy’s built-in usage tracking gives you aggregate token counts after a program runs. That’s fine for simple pipelines. But when you’re debugging...
Quick Primer on GEPA# GEPA (Genetic-Pareto) is a reflective optimizer. It evolves prompts by having an LLM critique failures and propose...
New technical example: @cocoindex_io plau @DSPyOSS for structured extraction from intake forms. This demo shows how to build a fully-typed,...
Compounding Engineering is a philosophy where every task you complete makes the next one easier. This isn't just about reusing code—it's about...
In this work, we introduce agent symbolic learning, a systematic framework that enables language agents to optimize themselves on their own in a...
Comparing DSPy, GEPA-AI, and Synth AI on the LangProBe benchmark suite
Building production AI agents with DSPy is straightforward—until you need multiple specialized submodules, each with its own tools and behaviors. At...
Building reliable LLM systems isn’t about chasing a “magic prompt” — it’s about a disciplined, iterative development cycle. DSPy treats LLM pipelines...
Building a research agent with CodeAct where the LLM generates Ruby code on the fly.
In complex agent systems, you might have chained multiple prompts together. You can provide all these prompts together for GEPA to consider and...
This paper reformulates prompt engineering as a classical state-space search, treating prompts as "states" and edits as "transitions." By using...
A tool that serves DSPy programs as HTTP APIs with Docker config, OpenAPI specs, MCP support, and more.
DSPy Pune meetup, December 13, 2025, 4 p.m. and DSPy Bengaluru - Quarterly Meetup, December 20, 2025, 10 a.m.
Show a video on integrated output with claude desktop.