Princeton group open sources "SWE-agent", with 12.3% fix rate for GitHub issues

• SWE-agent

  6 10,247 9.6 Python

  SWE-agent takes a GitHub issue and tries to automatically fix it, using GPT-4, or your LM of choice. It solves 12.29% of bugs in the SWE-bench evaluation set and takes just 1.5 minutes to run.

  

Very neat. Uses the langchain method, here are some of the prompts:

https://github.com/princeton-nlp/SWE-agent/blob/main/config/...

• dspy

  22 10,820 9.9 Python

  DSPy: The framework for programming—not prompting—foundation models

  

DSPy is the best tool for optimizing prompts [0]: https://github.com/stanfordnlp/dspy

Think of it as a meta-prompt optimizer, it uses a LLM to optimize your prompts, to optimize your LLM.

• InfluxDB

  www.influxdata.com featured

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

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