# Trenches - JERRY(Jerry needs to be removed from host) & Alazar

- **Event:** [OpenEnv Hackathon SF](https://cerebralvalley.ai/e/openenv-hackathon-sf)
- **When:** Mar 7 at 9:00 AM – Mar 8 at 12:00 AM (PST)
- **Where:** Shack15, San Francisco, CA
- **Team:** [Jerry Xiao](https://cerebralvalley.ai/u/foresee), [Alazar Manakelew](https://cerebralvalley.ai/u/AlazerM)
- **GitHub:** https://github.com/shlawgathon/trenches
- **Website:** https://colab.research.google.com/drive/1GS_EIi7FcNEo5Q7TKoLsrikfd5P8J4mH?usp=sharing
- **Demo video:** https://www.loom.com/share/d300db2a727b4a85883ed68146b42641
- **Hugging Face:** https://huggingface.co/spaces/AlazarM/trenches-us-qwen3-8b-chat
- **Gallery:** https://cerebralvalley.ai/e/openenv-hackathon-sf/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/openenv-hackathon-sf/hackathon/gallery/94

Trenches is a multi-agent geopolitical crisis simulator and command interface built around six separately finetuned Qwen/Qwen3-8B models representing the US, Israel, Iran, Hezbollah, the Gulf, and an
  Oversight entity, all operating inside a shared fog-of-war world. Training was done by collecting
  historically aligned data from 2025-01-01 to 2026-01-01 using GDELT and entity-relevant source feeds, formatting it into the same structured observation/output schemas used at runtime, and post-training
  each model with Hugging Face TRL and GRPO on top of an OpenEnv-compatible environment, with the serious runs executed on Modal. The final inference stack serves one model per entity on Modal L40 GPUs, with checkpoints stored under @AlazarM on Hugging Face, and the overall result is a live, replayable simulation where doctrine-specific agents take structured actions, predict outcomes, and interact through a stateful world rather than a simple chat interface.

JERRY & ALAZAR

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Markdown version of https://cerebralvalley.ai/e/openenv-hackathon-sf/hackathon/gallery/94. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt