Uploaded August 2025 | Updated September 2026, 3 hours ago
Hey everyone! Thanks so much for watching this video exploring DSPy's GEPA optimizer to train a Listwise Reranker! Here is the link to the notebook from the video to follow along with: github.com/weaviate/recipes/blob/main/integrations/llm-agent-frameworks/dspy/GEPA-Hands-On-Reranker.ipynb
Introduction to DSPy and Weaviate: youtube.com/watch?v=ickqCzFxWj0
Thanks so much for watching!
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Chapters
0:00 GEPA!
4:40 Step 1: DSPy Program
7:45 Step 2: Load Dataset
11:45 Step 3: Metric with Feedback
13:00 Step 4: Run Unoptimized Eval
13:40 Step 5: GEPA Optimization
23:16 Step 6: Run Optimized Eval
Hey everyone! Thanks so much for watching this video exploring DSPy's GEPA optimizer to train a Listwise Reranker! Here is the link to the notebook from the video to follow along with: github.com/weaviate/recipes/blob/main/integrations/llm-agent-frameworks/dspy/GEPA-Hands-On-Reranker.ipynb
Introduction to DSPy and Weaviate: youtube.com/watch?v=ickqCzFxWj0
Thanks so much for watching!
▬▬▬▬▬▬▬▬▬▬▬▬ CONNECT WITH US ▬▬▬▬▬▬▬▬▬▬▬▬
• Visit weaviate.io
• Star us on GitHub github.com/weaviate/weaviate
• Stay updated and subscribe to our newsletter: newsletter.weaviate.io
• Try out Weaviate Cloud Services for free here: https://console.weaviate.cloud/
Have questions?
• Forum: forum.weaviate.io
• Slack: weaviate.io/slack
Connect with us on:
• Twitter: twitter.com/weaviate_io
• LinkedIn: linkedin.com/company/weaviate-io
Chapters
0:00 GEPA!
4:40 Step 1: DSPy Program
7:45 Step 2: Load Dataset
11:45 Step 3: Metric with Feedback
13:00 Step 4: Run Unoptimized Eval
13:40 Step 5: GEPA Optimization
23:16 Step 6: Run Optimized Eval

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