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    <title>article Optimizing Databricks LLM Pipelines with DSPy in Databricks TV</title>
    <link>https://community.databricks.com/t5/databricks-tv/optimizing-databricks-llm-pipelines-with-dspy/ba-p/72533</link>
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    <pubDate>Fri, 14 Jun 2024 17:25:14 GMT</pubDate>
    <dc:creator>lara_rachidi</dc:creator>
    <dc:date>2024-06-14T17:25:14Z</dc:date>
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      <title>Optimizing Databricks LLM Pipelines with DSPy</title>
      <link>https://community.databricks.com/t5/databricks-tv/optimizing-databricks-llm-pipelines-with-dspy/ba-p/72533</link>
      <description>&lt;P&gt;&lt;SPAN&gt;In October 2023, researchers working in Databricks co-founder Matei Zaharia’s Stanford research lab released DSPy, a library for compiling declarative language model calls into self-improving pipelines. The key component of DSPy is self-improving pipelines. In a complex, multi-stage LLM pipeline, there are often multiple prompts along the way that require tuning. We discuss a blog post that dives into how to build a custom, multi-tool LLM agent using readily available Databricks Marketplace models in DSPy and how to deploy the resulting chain to Databricks Model Serving. Link to blog: &lt;A href="https://www.databricks.com/blog/optimizing-databricks-llm-pipelines-dspy" target="_blank"&gt;https://www.databricks.com/blog/optimizing-databricks-llm-pipelines-dspy&lt;/A&gt;&lt;/SPAN&gt;&lt;/P&gt;</description>
      <pubDate>Fri, 14 Jun 2024 17:25:14 GMT</pubDate>
      <guid>https://community.databricks.com/t5/databricks-tv/optimizing-databricks-llm-pipelines-with-dspy/ba-p/72533</guid>
      <dc:creator>lara_rachidi</dc:creator>
      <dc:date>2024-06-14T17:25:14Z</dc:date>
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