@julien_c: Today I'm launching a new project called SynthTraces It is a minimal codebase to generate synthetic coding agent sessio…

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Summary

Julien Chaumond launches SynthTraces, a minimal codebase that generates synthetic coding agent session traces by having an open model (via HF Inference Providers) interact with a small local model (via llama.cpp) on real open-source codebases, producing over 2,000 Pi session traces for training and fine-tuning LLMs.

Today I'm launching a new project called SynthTraces It is a minimal codebase to generate synthetic coding agent session traces using Pi (from @badlogicgames) I wanted a large number of coding-agent traces, so I built a tiny harness where two models talk to each other: - an open model (served via HF Inference Providers) plays the coding agent. It gets read + bash access to a real open source codebase (the huggingface OSS projects) - a small local model (llama.cpp) plays the human user, asking simple questions like "how do I run this?" or "how is CI set up?" The result is more than 2,000 Pi session traces which can be used to train or fine-tune LLMs, and optimize them for Pi And ofc everything is published on @huggingface
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Cached at: 06/05/26, 07:11 AM

Today I’m launching a new project called SynthTraces

It is a minimal codebase to generate synthetic coding agent session traces using Pi (from @badlogicgames)

I wanted a large number of coding-agent traces, so I built a tiny harness where two models talk to each other:

  • an open model (served via HF Inference Providers) plays the coding agent. It gets read + bash access to a real open source codebase (the huggingface OSS projects)
  • a small local model (llama.cpp) plays the human user, asking simple questions like “how do I run this?” or “how is CI set up?”

The result is more than 2,000 Pi session traces which can be used to train or fine-tune LLMs, and optimize them for Pi

And ofc everything is published on @huggingface

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