Logtriage Sre Agent

--- license: apache-2.0 base_model: Qwen/Qwen2.5-72B-Instruct datasets: - OpenEnv task_ids: - reinforcement-learning library_name: transformers tags: - reinforcement-learning - qwen2 - incident-triage - grpo - sre - production-incidents - trl - amd-mi300x - openenv language: - en --- # LogTriageEnv SRE Agent An LLM agent trained with GRPO (Group Relative Policy Optimization) on **AMD MI300X (192GB VRAM)** to triage production incidents through multi-hop causal reasoning. This model learns to trace root causes backward through microservice dependency graphs — a task where even frontier LLMs struggle. > **Meta × PyTorch × Scaler OpenEnv Grand Finale 2026** --- ## Model Details | Property | Value | |---|---| | Base Model | Qwen/Qwen2.5-72B-Instruct | | Training Algorithm | GRPO (Group Relative Policy Optimization) | | Training Framework | HuggingFace TRL 1.2.0 | | Training Hardware | AMD MI300X — 192GB VRAM | | Episodes | 100 per task (300 total) | | Environment | LogTriageEnv (OpenEnv compliant) | | License | Apache 2.0 | --- ## The Problem This Solves Every on-call SRE faces this at 2AM: ``` api-gateway → ERROR: upstream timeout (30002ms) ← visible symptom auth-service → WARNING: db connection pool exhausted payment-service → TIMEOUT errors cascading payment-db → [silent, no logs] ← actual root cause ``` Standard LLMs pattern-match on keywords and page whoever logged first. **The root cause is 3 hops downstream and never logs an ERROR.** LogTriageEnv trains agents to reason backward through dependency graphs instead of reacting to surface symptoms. --- ## Environment — LogTriageEnv ``` [api-gateway] ├── [auth-service] ──→ [user-db] ├── [payment-service] ──→ [payment-db] └── [notification-service] ──→ [email-queue] ``` **Three Tasks:** | Task | Difficulty | Max Steps | Challenge | |---|---|---|---| | single_crash | Easy | 8 | One service fails — classify and remediate | | cascading_failure | Medium | 12 | Root cause never logs first — trace backward | | silent_degradation | Hard | 15 | 60% log noise + temporal reasoning | **Structured Action Space:** ```python classify_severity → P1 (outage) | P2 (degradation) | P3 (warning) identify_root_cause → one of 7 services escalate → sre-team | backend-team | dba-team | security-team remediate → restart | rollback | scale | flush-cache | kill-query request_more_logs → <service> or all resolve →...

Source context: 14 downloads · 0 likes · Pipeline reinforcement-learning · Library transformers · Repo OGrohit/logtriage-sre-agent

Source context: 85 downloads · 0 likes · Pipeline reinforcement-learning · Library transformers · Repo OGrohit/logtriage-sre-agent