feat(env): integrate CodeDebug environment and vLLM inference stabilization

[RUFFY-369]

Note

Research Context: This PR integrates the physical environment provided in atropos (PR #421) and establishes the foundation for the MT-GRPO reward infrastructure in PR #3451.

What does this PR do?

This PR integrates the CodeDebug environment for agentic reasoning and introduces a Universal Tool Strategy to stabilize inference on vLLM backends.

It solves two primary problems:

1. Lack of Agentic Debugging Benchmarks
   Provides a high-fidelity sandbox where agents iteratively debug code using real terminal and file tools.

2. vLLM Tool Parsing Bugs
   Implements a robust client-side tool parsing fallback in model_tools.py and environments/agent_loop.py to bypass known bugs in vLLM 0.6.5 that cause 400/500 errors during complex tool-use sessions.

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Related Issue

Fixes # (Initial integration of debugging environment)

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Type of Change

• 🐛 Bug fix (non-breaking change that fixes an issue)
• ✨ New feature (non-breaking change that adds functionality)
• 🔒 Security fix
• 📝 Documentation update
• ✅ Tests (adding or improving test coverage)
• ♻️ Refactor (no behavior change)
• 🎯 New skill (bundled or hub)

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Changes Made

• environments/agent_loop.py: Added client-side tool parsing loop and atropos_inhibit_tools support
• model_tools.py: Added parse_tool_calls_from_text (regex-based fallback parser)
• environments/code_debug_env/code_debug_env.py: Environment logic based on HumanEvalFix
• environments/code_debug_env/default.yaml: Configuration for agent prompts and tool inhibition
• environments/code_debug_env/README.md: Usage and stabilization documentation

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How to Test

1. Rollout Verification

   python environments/code_debug_env/code_debug_env.py process

2. vLLM Stability

   • Verify that complex tool calls are correctly extracted from <tool_code> tags
   • Confirm fallback parsing works when server-side parsing fails

3. Mock Trajectories

   • Verify that tool calls (terminal/file) are correctly dispatched to the sandbox
   • Ensure multi-step debugging runs complete without errors

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Checklist

Code

• I've read the Contributing Guide
• My commit messages follow Conventional Commits (fix(scope):, feat(scope):, etc.)
• I searched for existing PRs to make sure this isn't a duplicate
• My PR contains only changes related to this fix/feature (no unrelated commits)
• I've run pytest tests/ -q and all tests pass (Note: system-level version conflict in env, but rollout verified)
• I've added tests for my changes (required for bug fixes, strongly encouraged for features)
• I've tested on my platform: Ubuntu 22.04

Documentation & Housekeeping

• I've updated relevant documentation (README, docs/, docstrings)
• I've updated cli-config.yaml.example — or N/A
• I've updated CONTRIBUTING.md or AGENTS.md — or N/A
• I've considered cross-platform impact (Windows, macOS) — or N/A
• I've updated tool descriptions/schemas if I changed tool behavior — or N/A

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For New Skills

N/A — This is an RL training environment integration.

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Screenshots / Logs

• Environment successfully executes multi-turn debugging sessions
• Real terminal feedback verified
• Running on Port 9001

cc @teknium1