Resources¶
This is the list of tutorials and blog posts on DSPy. If you would like to add your own tutorial, please make a PR.
A Few Blogs & Videos on using DSPy¶
Blogs¶
| Name | Link |
|---|---|
| Why I bet on DSPy | Blog |
| Not Your Average Prompt Engineering | Blog |
| Why I'm excited about DSPy | Blog |
| Achieving GPT-4 Performance at Lower Cost | Link |
| Prompt engineering is a task best left to AI models | Link |
| What makes DSPy a valuable framework for developing complex language model pipelines? | Link |
| DSPy: A new framework to program your foundation models just by prompting | Link |
| Intro to DSPy: Goodbye Prompting, Hello Programming | Link |
| DSPyGen: Revolutionizing AI | Link |
| Building an AI Assistant with DSPy | Link |
| Building Self-improving Agents in Production with DSPy | Link |
Videos¶
| Name | Link |
|---|---|
| DSPy Explained! (60K views) | Link |
| DSPy Intro from Sephora (25K views) | Link |
| Structured Outputs with DSPy | Link |
| DSPy and ColBERT - Weaviate Podcast | Link |
| SBTB23 DSPy | Link |
| Optimization with DSPy and LangChain | Link |
| Automated Prompt Engineering + Visualization | Link |
| Transforming LM Calls into Pipelines | Link |
| NeurIPS Hacker Cup: DSPy for Code Gen | Link |
| MIPRO and DSPy - Weaviate Podcast | Link |
| Getting Started with RAG in DSPy | Link |
| Adding Depth to DSPy Programs | Link |
| Programming Foundation Models with DSPy | Link |
| DSPy End-to-End: SF Meetup | Link |
| Monitoring & Tracing DSPy with Langtrace | Link |
| Teaching chat models to solve chess puzzles using DSPy + Finetuning | Link |
| Build Self-Improving AI Agents with DSPy (No Code) | Link |
| DSPy 3.0 and DSPy at Databricks | Link |
| Context Engineering with DSPy | Link |
Slides¶
| Name | Link |
|---|---|
| Context Engineering with DSPy | Link |
Podcasts¶
Weaviate has a directory of 10 amazing notebooks and 6 podcasts! Huge shoutout to them for the massive support ❤️. See the Weaviate DSPy directory.
This list represents a curated selection of DSPy resources. We continuously add new content as it becomes available in the community.
Credit: Some of these resources were originally compiled in the Awesome DSPy repo.