feat: integrate CodeDebug (HumanEvalFix) environment and core server stabilization

[RUFFY-369]

Note

Research Context: This PR provides the underlying CodeDebugEnv backend required for the agentic reasoning and vLLM stabilization benchmarks in hermes-agent (PR #3448).

PR Type

• RL Environment PR - Complete Environment Snapshot & Zero-Training sections
• Non-Environment PR - Complete Description, Related Issues & Type of Change sections

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📝 General Information

Description

This pull request introduces the CodeDebug environment for standardized debugging benchmarks and includes critical stabilization for the core server handling layer.

• New Environment: Integrated environments/community/code_debug_env/ based on HumanEvalFix.
• Server Stabilization: Refactored openai_server.py to use structured logging and robust completion handling, removing legacy debug prints and emojis.
• Safe Execution: Added code_executor.py for isolated, execution-based scoring of code fixes.

Related Issues

Closes (No specific issue linked, new feature/env)

Type of Change

• New feature (non-breaking change which adds functionality)
• Code refactor (no functional changes)
• Documentation update

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🔖 Environment Snapshot

Field	Your Entry
Environment Name	CodeDebug-v0
Short Description	Standardized debugging benchmark based on HumanEvalFix.
Category	Verifiable-Reasoning
Dataset Needed?	Yes (bigcode/humanevalpack)
External Deps	datasets, tqdm
Environmental Variables	N/A
Compute Footprint Estimate	<1 GB RAM, <2 sec per verification

🧪 Zero-Training Test Results

Details

W&B Link: N/A (Initial Integration)

Examples of the Environment scoring:

• Good Fix (Score 1.0): Correctly identifies a syntax error or logic flaw and provides a passing implementation.
• Partial Improvement (Score Variable): Provides code that passes more tests than the original buggy version but does not yet satisfy the full suite.
• Failure (Score -1.0): Code fails to compile or makes the logic worse.

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✅ Developer & Reviewer Checklist

• Code follows project style (black, ruff pass)
• I have performed a self-review of my own code
• I have commented my code appropriately
• My changes generate no new warnings
• New and existing unit tests pass locally (test_code_debug.py)
• Docstrings added for all new public classes / functions

cc @dmahan93 @teknium1