Day 6: inference.py (renamed from baseline.py), HF_TOKEN/API_BASE_URL/MODEL_NAME env vars, pyproject.toml for openenv validate

DAY3_STATUS.md

@@ -1,290 +0,0 @@
-# 🎯 DAY 3 STATUS — LogTriageEnv Complete
-
-**Status: ✅ 100% COMPLETE (Days 1-2-3 now complete!)**  
-**Last Updated:** March 27, 2026  
-**Overall Progress:** ▓▓▓░░ (60% of total project)
-
----
-
-## 📊 Quick Status
-
-| Component | Status | Details |
-|-----------|--------|---------|
-| **Day 1 Work** | ✅ 100% | Models, API scaffold, config, docs |
-| **Day 2 Work** | ✅ 100% | Environment, log gen, Task 1 wired |
-| **Day 3 Work** | ✅ 100% | Tasks 2 & 3 scenarios + wiring |
-| **Task 1 (Easy)** | ✅ 100% | Single crash - FULLY PLAYABLE |
-| **Task 2 (Medium)** | ✅ 100% | Cascading failures - FULLY PLAYABLE |
-| **Task 3 (Hard)** | ✅ 100% | Silent degradation - FULLY PLAYABLE |
-| **Graders** | ⏳ 0% | Day 4 - not started |
-| **Baseline Agent** | ⏳ 0% | Day 5 - not started |
-
----
-
-## ✅ What Was Completed in Day 3
-
-### 1. **Task 2: Cascading Failure (Medium Difficulty)**
-**File:** `server/scenarios/cascading.py` (171 lines)
-
-✅ **Scenario Definition:**
-- Database slowdown in user-db → exhausts auth-service connection pool → cascade to api-gateway
-- Surface logs show gateway errors loudly (symptom), but root cause is hidden (user-db)
-- Agent must trace backward through the cascade chain, not treat symptoms
-
-✅ **Ground Truth:**
-```
-Severity:    P1
-Root Cause:  user-db (NOT auth-service, NOT api-gateway)
-Remediation: kill-query:user-db OR restart:user-db
-Teams:       dba-team, sre-team
-Max Steps:   12
-Noise:       30%
-```
-
-✅ **Step-by-Step Signal Plan (12 stages):**
-- Step 0-1: Gateway errors appear (symptoms only)
-- Step 2-3: Auth-service DB pressure becomes visible
-- Step 4-5: user-db slow queries exposed; circuit breaker opens
-- Step 6-7: Full cascade; all 3 services degraded/down
-- Step 8-11: Escalating alerts; root cause becomes unmistakable
-
-✅ **System State Modeling:**
-- api-gateway: degrades from 8% error → 99% error
-- auth-service: degrades from healthy → down by step 6
-- user-db: shows latency increase from 2847ms → 10000ms
-
-✅ **Integration:**
-- Wired to environment.py as `cascading_failure` task
-- Accessible via `/reset?task=cascading_failure`
-- Returns realistic logs with 30% noise injected
-
----
-
-### 2. **Task 3: Silent Degradation (Hard Difficulty)**
-**File:** `server/scenarios/silent_degrade.py` (185 lines)
-
-✅ **Scenario Definition:**
-- payment-db query latency slowly increases over time
-- No service crashes; error rate stays below P1 threshold (5%)
-- 60% of logs are irrelevant noise from other services
-- Agent must filter noise, identify subtle signal, and classify as P2 (not P1, not P3)
-
-✅ **Ground Truth:**
-```
-Severity:    P2 (NOT P1, NOT P3 — nuanced judgment required)
-Root Cause:  payment-db
-Remediation: flush-cache:payment-db OR kill-query:payment-db
-Teams:       dba-team
-Max Steps:   15
-Noise:       60% (hardest noise ratio of all tasks)
-```
-
-✅ **Step-by-Step Signal Plan (15 stages):**
-- Step 0-2: Very subtle signals (payment-db latency 450ms → 890ms)
-- Step 3-5: Buffer cache degradation visible; error rate at 2.1%
-- Step 6-8: Latency 2200ms → 3100ms; still well below P1 threshold
-- Step 9-12: Approaching but not breaching timeout (4200ms → 4600ms)
-- Step 13-14: P1 breach imminent/breached (4950ms → payment error 5.1%)
-
-✅ **Noise Characteristics:**
-- Most logs are from unrelated services (api-gateway, auth-service, etc.)
-- Signal is sparse — only 1-2 relevant logs per step
-- Requires agent to carefully read logs and filter signal from noise
-
-✅ **System State Modeling:**
-- payment-db: latency increases 450ms → 4950ms, status stays "up" until step 3
-- payment-service: becomes slightly degraded from step 4 onward
-- All other services: remain in healthy state
-
-✅ **Integration:**
-- Wired to environment.py as `silent_degradation` task
-- Accessible via `/reset?task=silent_degradation`
-- Returns realistic logs with 60% noise injected
-
----
-
-### 3. **Environment Wiring (Updated)**
-**File:** `server/environment.py` (updated)
-
-✅ **Imports Added:**
-```python
-from server.scenarios import cascading
-from server.scenarios import silent_degrade
-```
-
-✅ **Task Registry Updated:**
-```python
-TASK_MAX_STEPS = {
-    "single_crash":      8,
-    "cascading_failure": 12,
-    "silent_degradation": 15,
-}
-```
-
-✅ **reset() Method Wired All 3 Tasks:**
-```python
-if task_id == "single_crash":
-    self._ground_truth = single_crash.GROUND_TRUTH
-elif task_id == "cascading_failure":
-    self._ground_truth = cascading.GROUND_TRUTH
-elif task_id == "silent_degradation":
-    self._ground_truth = silent_degrade.GROUND_TRUTH
-```
-
-✅ **_get_step_data() Extracts Scenario Data:**
-- Calls `scenario.get_step_data(step, base_time, rng)` for real logs
-- Calls `scenario.get_system_state(step, base_time)` for service status
-- All 3 tasks return deterministic logs based on ground truth
-
-✅ **_get_alerts() Returns Scenario-Specific Alerts:**
-- Each scenario defines its own alert progression
-- Alerts evolve as cascade/degradation unfolds
-
----
-
-## 🎮 All 3 Tasks Now Playable End-to-End
-
-### **Task 1: Single Service Crash (Easy)**
-```bash
-curl -X POST "http://localhost:7860/reset?task=single_crash&seed=42"
-curl -X POST "http://localhost:7860/step" \
-  -H "Content-Type: application/json" \
-  -d '{"action_type":"classify_severity","value":"P1","confidence":0.95}'
-# Expected: +0.30 reward for correct severity
-```
-
-### **Task 2: Cascading Failure (Medium)**
-```bash
-curl -X POST "http://localhost:7860/reset?task=cascading_failure&seed=42"
-curl -X POST "http://localhost:7860/step" \
-  -H "Content-Type: application/json" \
-  -d '{"action_type":"request_more_logs","value":"system_state","confidence":0.9}'
-# Agent must trace: gateway errors → auth-service → user-db (root cause)
-# Expected: +0.35 reward for identifying user-db (not gateway/auth-service)
-```
-
-### **Task 3: Silent Degradation (Hard)**
-```bash
-curl -X POST "http://localhost:7860/reset?task=silent_degradation&seed=42"
-curl -X POST "http://localhost:7860/step" \
-  -H "Content-Type: application/json" \
-  -d '{"action_type":"classify_severity","value":"P2","confidence":0.85}'
-# Nuanced judgment: error rate is 2.1% (below P1 @ 5%) but trending toward breach
-# Expected: +0.30 reward for correct P2 (not P1, not P3)
-```
-
----
-
-## 📈 Scoring Distribution
-
-Each task has different difficulty → different expected agent score ranges:
-
-| Task | Difficulty | Max Score | Expected Range | Key Challenge |
-|------|-----------|-----------|-----------------|---------------|
-| **Single Crash** | Easy | 1.00 | 0.75–0.85 | Simple identification |
-| **Cascading** | Medium | 1.00 | 0.45–0.60 | Trace root cause, not symptoms |
-| **Silent Degrade** | Hard | 1.00 | 0.20–0.40 | Filter 60% noise, nuanced P2 judgment |
-
----
-
-## 🔍 Key Metrics
-
-### Code
-- **Total lines written (Days 1-3):** ~1,500 lines of Python
-- **Scenario files:** 3 complete (single_crash + cascading + silent_degrade)
-- **Scenario logic:** ~500 lines of step-by-step signal planning + system state modeling
-
-### Documentation
-- **Status files:** Now consolidated (DAY1_STATUS, DAY2_STATUS, DAY3_STATUS merged → use this file + DAYS_1-2_SUMMARY)
-- **Total doc lines:** ~2,000+ across remaining guides
-
-### Testing
-- **Endpoints wired:** 7/7 (all endpoints can now be called)
-- **Tasks playable:** 3/3 ✅
-- **Test cases needed:** Day 4 (grader logic tests)
-
----
-
-## 📋 Files in Play
-
-### **Core Code (Keep)**
-```
-✅ server/models.py (218 lines)
-✅ server/app.py (7 endpoints)
-✅ server/environment.py (environment logic)
-✅ server/log_generator.py (synthetic logs)
-✅ server/scenarios/single_crash.py (Task 1)
-✅ server/scenarios/cascading.py (Task 2)
-✅ server/scenarios/silent_degrade.py (Task 3)
-```
-
-### **Configuration (Keep)**
-```
-✅ openenv.yaml
-✅ requirements.txt
-✅ Dockerfile
-```
-
-### **Documentation (Use These)**
-```
-✅ README.md (main spec)
-✅ EXECUTIVE_SUMMARY.md (overview for judges)
-✅ DAYS_1-2_SUMMARY_FINAL.md (technical deep-dive, Days 1-2)
-✅ STATUS.md (quick progress matrix)
-✅ START_HERE_DAY2.md (navigation guide)
-✅ FILE_INVENTORY.md (file listing)
-✅ TEST_ENDPOINTS.md (curl examples)
-✅ VISUAL_SUMMARY.md (architecture diagrams)
-✅ DAY3_STATUS.md (this file — complete Day 3 status)
-```
-
-### **Removed Files (No Longer Needed)**
-```
-❌ DAY1.md (consolidated)
-❌ DAY1_STATUS.md (consolidated)
-❌ DAY2.md (consolidated)
-❌ ANALYSIS_SUMMARY.md (redundant)
-❌ COMPLETE_SUMMARY.md (redundant)
-❌ etc.
-```
-
----
-
-## 🎯 What's Next (Day 4-5)
-
-### **Day 4: Graders**
-- [ ] Implement grader logic (evaluation of agent actions)
-- [ ] Wire `/grader` endpoint
-- [ ] Validate scoring across all 3 tasks
-
-### **Day 5: Baseline Agent**
-- [ ] Implement simple baseline agent
-- [ ] Wire `/baseline` endpoint
-- [ ] Deployment to Hugging Face
-
----
-
-## 💡 Summary
-
-**Days 1-3 Complete:** All 3 tasks are now fully playable end-to-end with realistic scenario data.
-
-✅ **Single Service Crash (Easy):** One service crashes → clear logs → straightforward triage  
-✅ **Cascading Failure (Medium):** DB slowdown cascades upstream → must trace root cause, not symptoms  
-✅ **Silent Degradation (Hard):** Slow creeping problem in 60% noise → nuanced P2 judgment required  
-
-**Completion Status:**
-- 60% of total project complete (Days 1-3 of 5)
-- 3/3 tasks playable
-- All endpoints wired and functional
-- Ready for Day 4 grader implementation
-
----
-
-**Next Action:** Create Day 4 grader logic to evaluate agent performance across all 3 tasks.
-
----
-
-Generated: March 27, 2026  
-Project: LogTriageEnv (Meta × PyTorch Hackathon)  
-Deadline: April 7, 2026, 11:59 PM IST  
-Status: **ON TRACK** ✅ (60% complete)

DAYS_1-2-3-4_FINAL_STATUS.md

@@ -1,484 +0,0 @@
-# 🎯 DAYS 1-4 FINAL STATUS — LogTriageEnv Complete
-
-**Status: ✅ 100% COMPLETE (Days 1-4 now complete!)**  
-**Last Updated:** March 28, 2026  
-**Overall Progress:** ▓▓▓▓░ (80% of total project)
-
----
-
-## 📊 Quick Status Summary
-
-| Component | Status | Details |
-|-----------|--------|---------|
-| **Day 1 Work** | ✅ 100% | Models, API scaffold, config, docs |
-| **Day 2 Work** | ✅ 100% | Environment, log gen, Task 1 wired |
-| **Day 3 Work** | ✅ 100% | Tasks 2 & 3 scenarios + wiring |
-| **Day 4 Work** | ✅ 100% | Graders, /grader endpoint, CLI tool |
-| **Task 1 (Easy)** | ✅ 100% | Single crash - FULLY PLAYABLE & GRADED |
-| **Task 2 (Medium)** | ✅ 100% | Cascading failures - FULLY PLAYABLE & GRADED |
-| **Task 3 (Hard)** | ✅ 100% | Silent degradation - FULLY PLAYABLE & GRADED |
-| **Baseline Agent** | ⏳ 0% | Day 5 - not started |
-| **Final Deployment** | ⏳ 0% | Day 5 - not started |
-
----
-
-## ✅ What Was Completed in Day 4
-
-### 1. **Grader Infrastructure**
-**Files Created:**
-- `server/graders/base_grader.py` (195 lines) — Abstract base interface
-- `server/graders/crash_grader.py` (330 lines) — Task 1 grader
-- `server/graders/cascade_grader.py` (360 lines) — Task 2 grader
-- `server/graders/noise_grader.py` (320 lines) — Task 3 grader
-- `server/graders/__init__.py` — Registry + scoring interface
-
-**Key Features:**
-✅ Abstract `BaseGrader` class with helper methods for action evaluation  
-✅ Task-specific graders inherit from BaseGrader  
-✅ Each grader implements deterministic scoring logic  
-✅ Grader registry automatically dispatches to correct grader by task_id  
-✅ Helper methods: `_get_actions_of_type()`, `_was_action_taken()`, `_get_first_value()`, etc.
-
----
-
-### 2. **Model Updates**
-**File:** `server/models.py`
-
-✅ **Added to EpisodeState:**
-```python
-action_history: list[dict] = Field(
-    default_factory=list,
-    description="Full action objects taken this episode (for grader evaluation)"
-)
-```
-
-**Purpose:** Tracks complete action data (type, value, confidence, reasoning) for grader evaluation
-
----
-
-### 3. **Environment Updates**
-**File:** `server/environment.py`
-
-✅ **In step() method:**
-```python
-self._state.action_history.append(action.model_dump())
-```
-
-**Purpose:** Records full action object for each step taken
-
----
-
-### 4. **API Endpoint: /grader**
-**File:** `server/app.py`
-
-✅ **Endpoint Signature:**
-```python
-@app.post("/grader")
-def grader():
-    from server.graders import score_episode
-    state = env.state
-    result = score_episode(state.task_id, state)
-    return result
-```
-
-**Returns:**
-```json
-{
-  "score": 0.95,
-  "task_id": "single_crash",
-  "steps_taken": 4,
-  "max_steps": 8,
-  "resolved": true,
-  "breakdown": {
-    "severity": "+0.30 (correct: P1)",
-    "root_cause": "+0.35 (correct: payment-service)",
-    "remediation": "+0.25 (correct: restart:payment-service)",
-    "speed": "+0.10 (resolved in 4 steps)"
-  }
-}
-```
-
----
-
-### 5. **Grader Scoring Logic**
-
-#### **Task 1 (Single Crash) — CrashGrader**
-**Ground Truth:**
-- Severity: P1
-- Root Cause: payment-service
-- Remediation: restart:payment-service
-- Max Steps: 8
-
-**Scoring Breakdown:**
-- Correct severity (P1) → +0.30
-- Correct root cause (payment-service) → +0.35
-- Correct remediation (restart:payment-*) → +0.25
-- Speed bonus (resolved ≤ 5 steps) → +0.10
-- **Max Score:** 1.00
-
-**Penalties:**
-- Partial credit for close answers (P2 severity = +0.10, service family = +0.10)
-- Never resolved → -0.10
-
----
-
-#### **Task 2 (Cascading Failure) — CascadeGrader**
-**Ground Truth:**
-- Severity: P1
-- Root Cause: user-db (NOT api-gateway, NOT auth-service)
-- Remediation: kill-query:user-db OR restart:user-db
-- Max Steps: 12
-
-**Scoring Breakdown:**
-- Correct severity (P1) → +0.25
-- Correct root cause (user-db) → +0.40 (higher difficulty)
-- Correct remediation → +0.20
-- Speed bonus (resolved ≤ 7 steps) → +0.10
-- Avoiding symptom confusion → +0.05 (partial bonus)
-- **Max Score:** 1.00
-
-**Key Challenge:** Must trace root cause through cascade chain, not misidentify symptoms
-
----
-
-#### **Task 3 (Silent Degradation) — NoiseGrader**
-**Ground Truth:**
-- Severity: P2 (NOT P1, NOT P3)
-- Root Cause: payment-db
-- Remediation: flush-cache:payment-db OR kill-query:payment-db
-- Max Steps: 15
-- Noise Ratio: 60%
-
-**Scoring Breakdown:**
-- Correct severity (P2) → +0.35 (nuanced judgment)
-- Correct root cause (payment-db) → +0.30
-- Correct remediation → +0.20
-- Speed bonus (resolved ≤ 10 steps) → +0.10
-- Noise tolerance → +0.05 (partial bonus)
-- **Max Score:** 1.00
-
-**Key Challenge:** Filter 60% irrelevant logs; classify subtle P2 (not obvious P1/P3)
-
----
-
-### 6. **Grader Validation CLI Tool**
-**File:** `scripts/run_grader.py` (133 lines)
-
-✅ **Features:**
-- Simulates correct and wrong agents for each task
-- Runs full episode and calls official grader
-- Displays score breakdown and variance analysis
-- Proves grader returns VARYING scores
-
-**Usage Examples:**
-```bash
-# Test single task with correct agent
-python scripts/run_grader.py --task single_crash --agent correct
-
-# Test single task with wrong agent
-python scripts/run_grader.py --task cascading_failure --agent wrong
-
-# Test all 3 tasks with both correct/wrong agents
-python scripts/run_grader.py --all
-```
-
-**Expected Output:**
-```
-============================================================
-Task:     single_crash
-Agent:    correct
-Score:    0.95   [====================]
-Steps:    4/8
-Resolved: True
-
-Breakdown:
-  severity             +0.30 (correct: P1)
-  root_cause           +0.35 (correct: payment-service)
-  remediation          +0.25 (correct: restart:payment-service)
-  speed                +0.10 (resolved in 4 steps)
-============================================================
-```
-
----
-
-## 🎮 All 3 Tasks Now Fully Playable & Graded
-
-### **Complete Flow Example: Task 1**
-
-```bash
-# 1. Reset episode
-curl -X POST "http://localhost:7860/reset?task=single_crash&seed=42"
-
-# 2. Step 1: Classify severity
-curl -X POST "http://localhost:7860/step" \
-  -H "Content-Type: application/json" \
-  -d '{
-    "action_type": "classify_severity",
-    "value": "P1",
-    "confidence": 0.95
-  }'
-
-# 3. Step 2: Identify root cause
-curl -X POST "http://localhost:7860/step" \
-  -H "Content-Type: application/json" \
-  -d '{
-    "action_type": "identify_root_cause",
-    "value": "payment-service",
-    "confidence": 0.90
-  }'
-
-# 4. Step 3: Remediate
-curl -X POST "http://localhost:7860/step" \
-  -H "Content-Type: application/json" \
-  -d '{
-    "action_type": "remediate",
-    "value": "restart:payment-service",
-    "confidence": 0.85
-  }'
-
-# 5. Step 4: Resolve
-curl -X POST "http://localhost:7860/step" \
-  -H "Content-Type: application/json" \
-  -d '{
-    "action_type": "resolve",
-    "value": "resolved",
-    "confidence": 1.00
-  }'
-
-# 6. Get official grade
-curl -X POST "http://localhost:7860/grader"
-
-# Response:
-{
-  "score": 0.95,
-  "task_id": "single_crash",
-  "steps_taken": 4,
-  "max_steps": 8,
-  "resolved": true,
-  "breakdown": {
-    "severity": "+0.30 (correct: P1)",
-    "root_cause": "+0.35 (correct: payment-service)",
-    "remediation": "+0.25 (correct: restart:payment-service)",
-    "speed": "+0.10 (resolved in 4 steps)"
-  }
-}
-```
-
----
-
-## 🔍 Verified: Graders Return VARYING Scores
-
-**Test Results (from run_grader.py --all):**
-
-| Task | Correct Agent | Wrong Agent | Variance | Status |
-|------|---------------|-------------|----------|--------|
-| Single Crash | **0.95** | 0.10 | 0.85 | ✅ GOOD |
-| Cascading Failure | **0.85** | 0.15 | 0.70 | ✅ GOOD |
-| Silent Degradation | **0.80** | 0.20 | 0.60 | ✅ GOOD |
-
-**Key Verification:**
-✅ Graders DO NOT always return same score  
-✅ Correct agents score 0.80-0.95  
-✅ Wrong agents score 0.10-0.20  
-✅ Variance is high (0.60-0.85) — good discrimination  
-✅ No disqualification conditions triggered  
-
----
-
-## 📈 Scoring Distribution Summary
-
-| Task | Difficulty | Max | Range | Key Challenge |
-|------|-----------|-----|-------|---------------|
-| Single Crash | Easy | 1.00 | 0.75–0.95 | Simple identification |
-| Cascading | Medium | 1.00 | 0.45–0.85 | Trace root cause, not symptoms |
-| Silent Degrade | Hard | 1.00 | 0.20–0.80 | Filter 60% noise, nuanced P2 |
-
----
-
-## 🏗️ Architecture Now Complete (Days 1-4)
-
-```
-LogTriageEnv
-├── server/
-│   ├── app.py (123 lines) — 8 endpoints
-│   │   ├── GET /health ✅
-│   │   ├── POST /reset ✅
-│   │   ├── POST /step ✅
-│   │   ├── GET /state ✅
-│   │   ├── GET /tasks ✅
-│   │   ├── POST /grader ✅ (NEW Day 4)
-│   │   ├── POST /baseline ⏳ (Day 5)
-│   │   └── + more...
-│   │
-│   ├── models.py (250+ lines)
-│   │   ├── LogLine ✅
-│   │   ├── ServiceStatus ✅
-│   │   ├── TriageAction ✅
-│   │   ├── Observation ✅
-│   │   └── EpisodeState ✅ (updated with action_history)
-│   │
-│   ├── environment.py (400+ lines)
-│   │   ├── LogTriageEnvironment class ✅
-│   │   ├── reset() — all 3 tasks ✅
-│   │   ├── step() — action processing ✅ (with action_history)
-│   │   ├── state() — current state ✅
-│   │   └── _get_alerts() ✅
-│   │
-│   ├── log_generator.py (280+ lines)
-│   │   ├── Synthetic log generation ✅
-│   │   ├── Scenario-aware logs ✅
-│   │   └── Noise injection ✅
-│   │
-│   ├── scenarios/ (3 files, 500+ lines total)
-│   │   ├── single_crash.py ✅
-│   │   ├── cascading.py ✅
-│   │   └── silent_degrade.py ✅
-│   │
-│   └── graders/ (5 files, 1200+ lines total) ✅ NEW Day 4
-│       ├── base_grader.py (195 lines)
-│       ├── crash_grader.py (330 lines)
-│       ├── cascade_grader.py (360 lines)
-│       ├── noise_grader.py (320 lines)
-│       └── __init__.py (registry)
-│
-├── scripts/
-│   ├── run_grader.py (133 lines) ✅ NEW Day 4
-│   └── baseline.py ⏳ (Day 5)
-│
-├── requirements.txt ✅
-├── Dockerfile ✅
-├── openenv.yaml ✅
-└── README.md + docs ✅
-```
-
----
-
-## 📋 Files Complete (Days 1-4)
-
-### **Core Code (✅ Complete)**
-```
-✅ server/models.py (250+ lines)
-✅ server/app.py (123 lines, 8 endpoints)
-✅ server/environment.py (400+ lines)
-✅ server/log_generator.py (280+ lines)
-✅ server/scenarios/single_crash.py (Task 1)
-✅ server/scenarios/cascading.py (Task 2)
-✅ server/scenarios/silent_degrade.py (Task 3)
-✅ server/graders/base_grader.py (Day 4)
-✅ server/graders/crash_grader.py (Day 4)
-✅ server/graders/cascade_grader.py (Day 4)
-✅ server/graders/noise_grader.py (Day 4)
-✅ server/graders/__init__.py (Day 4)
-✅ scripts/run_grader.py (Day 4)
-```
-
-### **Configuration (✅ Complete)**
-```
-✅ openenv.yaml
-✅ requirements.txt
-✅ Dockerfile
-```
-
-### **Documentation (✅ Complete)**
-```
-✅ README.md (main spec)
-✅ EXECUTIVE_SUMMARY.md (overview)
-✅ DAYS_1-2_SUMMARY_FINAL.md (technical deep-dive)
-✅ DAY3_STATUS.md (Day 3 completion)
-✅ DAYS_1-2-3-4_FINAL_STATUS.md (this file)
-✅ START_HERE_DAY2.md (navigation)
-✅ FILE_INVENTORY.md (file listing)
-✅ TEST_ENDPOINTS.md (curl examples)
-✅ VISUAL_SUMMARY.md (architecture)
-```
-
----
-
-## 🎯 What's Next (Day 5)
-
-### **Remaining Work:**
-- [ ] Implement baseline agent (`scripts/baseline.py`)
-- [ ] Wire `/baseline` endpoint in `app.py`
-- [ ] Deploy to Hugging Face Spaces
-- [ ] Final validation and submission
-
-### **Day 5 Success Criteria:**
-✅ Baseline agent achieves ≥0.50 avg score across all 3 tasks  
-✅ Deployed to HF Spaces with working API  
-✅ All 3 tasks playable via hosted endpoint  
-✅ Grader working live  
-
----
-
-## 💡 Key Achievements (Days 1-4)
-
-### **Codebase:**
-- ~3,000 lines of Python written
-- 3 complete, deterministic task scenarios
-- 3 sophisticated graders with nuanced scoring
-- All 8 endpoints implemented and tested
-
-### **Architecture:**
-- Fully functional OpenEnv-compliant environment
-- Modular scenario system
-- Pluggable grader registry
-- Deterministic reproducibility (seeded RNG)
-
-### **Testing:**
-- Grader validation script with correct/wrong agent simulation
-- Verified: graders return VARYING scores (0.10-0.95)
-- All 3 tasks playable end-to-end
-- No disqualification conditions triggered
-
-### **Documentation:**
-- Comprehensive status files
-- Technical deep-dives
-- Curl examples for all endpoints
-- Architecture diagrams
-
----
-
-## 📊 Progress Timeline
-
-| Day | Deliverable | Status | Files |
-|-----|-------------|--------|-------|
-| **Day 1** | Models, API scaffold, Task 1 config | ✅ 100% | 5 files |
-| **Day 2** | Environment, log generator, Task 1 wired | ✅ 100% | +3 files |
-| **Day 3** | Tasks 2 & 3 complete, all wired | ✅ 100% | +2 files |
-| **Day 4** | Graders, /grader endpoint, validation CLI | ✅ 100% | +5 files |
-| **Day 5** | Baseline agent, deployment | ⏳ Pending | +2 files |
-| **Total** | Full submission-ready environment | ⏳ 80% | ~20 files |
-
----
-
-## 🚀 Ready for Day 5
-
-**All prerequisites for Day 5 complete:**
-✅ 3 tasks fully playable  
-✅ Graders fully functional  
-✅ /grader endpoint live  
-✅ Scoring proven to vary  
-
-**Day 5 can proceed immediately to:**
-1. Implement simple baseline agent
-2. Wire to /baseline endpoint
-3. Deploy to HF Spaces
-
----
-
-## ✅ Disqualification Checks (All Passed)
-
-- ✅ Graders DO NOT always return same score
-- ✅ Graders HAVE logic (3 different graders, 3 different scoring)
-- ✅ Scores ALWAYS in [0.0, 1.0] range
-- ✅ /grader endpoint returns proper response
-- ✅ No external dependencies violated
-- ✅ Reproducible (seed support)
-
----
-
-Generated: March 28, 2026  
-Project: LogTriageEnv (Meta × PyTorch Hackathon)  
-Deadline: April 7, 2026, 11:59 PM IST  
-Status: **ON TRACK** ✅ (80% complete, Day 5 ready)
-Estimated Completion: March 28, 2026 (Day 5)

DAYS_1-2_SUMMARY_FINAL.md

@@ -1,282 +0,0 @@
-# FINAL SUMMARY — Days 1-2 Complete
-
-**Status:** ✅ **40% of Project Complete (Days 1-2 Done)**  
-**Date:** March 27, 2026  
-**Next:** Day 3 (Scenarios 2 & 3)
-
----
-
-## Quick Summary
-
-### ✅ What You've Built (Days 1-2)
-
-**Day 1:**
-- ✅ 5 Pydantic models (fully typed)
-- ✅ 7 FastAPI endpoints (all registered)
-- ✅ Configuration (openenv.yaml, requirements.txt)
-- ✅ Docker setup
-- ✅ Comprehensive documentation
-
-**Day 2:**
-- ✅ LogTriageEnvironment class (environment management)
-- ✅ Synthetic log generation engine (realistic logs)
-- ✅ Task 1 scenario (single_crash - easy task)
-- ✅ Wired 3/7 endpoints to real logic (/reset, /step, /state)
-- ✅ Full Task 1 playable end-to-end
-
-**Total:** ~1,100 lines of core code + 1,900 lines of documentation
-
----
-
-## 📋 Files Created/Modified
-
-### Day 1 (Skeleton)
-| File | Lines | Purpose |
-|------|-------|---------|
-| `server/models.py` | 218 | 5 Pydantic classes |
-| `server/app.py` | 101 | FastAPI app |
-| `openenv.yaml` | 38 | Environment spec |
-| `requirements.txt` | 6 | Dependencies |
-| `Dockerfile` | 16 | Containerization |
-| `README.md` | 533 | Documentation |
-
-### Day 2 (Brain)
-| File | Lines | Purpose |
-|------|-------|---------|
-| `server/environment.py` | 250 | Core environment class |
-| `server/log_generator.py` | 400 | Synthetic log generation |
-| `server/scenarios/single_crash.py` | 150 | Task 1 scenario |
-| `server/app.py` | +50 | Wired endpoints |
-
----
-
-## 🎯 What's Working Now
-
-### Fully Playable
-✅ **Task 1: Single Service Crash (Easy)**
-- Agent can reset, observe, act, and resolve
-- Full episode: 5 steps minimum to win
-- Reward calculation working
-- Episode state tracking
-
-### Partially Working
-✅ **3/7 Endpoints Wired:**
-- `/reset` - creates real episodes ✅
-- `/step` - processes actions & returns rewards ✅
-- `/state` - returns episode state ✅
-- `/health` - health check ✅
-- `/tasks` - task definitions ✅
-
-❌ **4/7 Endpoints Still TODO:**
-- `/grader` - grading logic (Day 4)
-- `/baseline` - LLM baseline (Day 5)
-
----
-
-## 📊 Progress Breakdown
-
-```
-Day 1: Scaffold (40%)
-  ├─ Models: ✅ 100%
-  ├─ API endpoints: ✅ 100% (stubbed)
-  ├─ Config: ✅ 100%
-  └─ Docs: ✅ 100%
-
-Day 2: Environment & Task 1 (40%)
-  ├─ Environment class: ✅ 100%
-  ├─ Log generator: ✅ 100%
-  ├─ Task 1 scenario: ✅ 100%
-  ├─ Endpoints wired: ✅ 3/7 (42.8%)
-  └─ Task 1 playable: ✅ 100%
-
-Day 3: Scenarios 2 & 3 (20%)
-  ├─ Task 2 scenario: ⏳ 0%
-  ├─ Task 3 scenario: ⏳ 0%
-  └─ All 3 tasks playable: ⏳ 0%
-
-Days 4-5: Graders & Baseline (TODO)
-  ├─ Graders: ⏳ 0%
-  └─ Baseline agent: ⏳ 0%
-
-TOTAL: ✅ 40% Complete (Days 1-2)
-```
-
----
-
-## 🎮 How to Play Task 1
-
-### Quick Test
-```bash
-# Terminal 1: Start server
-python -m uvicorn server.app:app --port 7860
-
-# Terminal 2: Play episode
-curl -X POST "http://localhost:7860/reset?task=single_crash&seed=42"
-curl -X POST "http://localhost:7860/step" \
-  -H "Content-Type: application/json" \
-  -d '{"action_type":"classify_severity","value":"P1","confidence":0.95}'
-curl -X POST "http://localhost:7860/step" \
-  -H "Content-Type: application/json" \
-  -d '{"action_type":"identify_root_cause","value":"payment-service","confidence":0.9}'
-curl -X POST "http://localhost:7860/step" \
-  -H "Content-Type: application/json" \
-  -d '{"action_type":"remediate","value":"restart:payment-service","confidence":0.95}'
-curl -X POST "http://localhost:7860/step" \
-  -H "Content-Type: application/json" \
-  -d '{"action_type":"resolve","value":"resolved"}'
-```
-
-### What Happens
-1. `/reset` returns initial observation with crash logs
-2. Each `/step` returns:
-   - New logs (scenario escalates)
-   - Reward (0.30 for severity, 0.35 for root cause, 0.25 for fix, 0.10 for speed)
-   - Feedback ("Correct severity!" etc)
-   - Cumulative score
-3. Final episode score: 1.0 (perfect play)
-
----
-
-## ✨ Key Features
-
-### Log Generation
-- ✅ 7 services (api-gateway, auth, dbs, payment, notification, email)
-- ✅ Noise templates (realistic but irrelevant)
-- ✅ Signal templates (error patterns)
-- ✅ Step-by-step injection (escalating scenario)
-- ✅ Deterministic (reproducible with seed)
-
-### Environment Management
-- ✅ Episode initialization
-- ✅ State tracking (step count, score, done)
-- ✅ Action validation
-- ✅ Reward calculation
-- ✅ Feedback generation
-
-### Task 1 Scenario
-- ✅ Ground truth (correct answers)
-- ✅ 8-step episode maximum
-- ✅ 20% noise ratio
-- ✅ Single service crash
-- ✅ Clear error signals
-
----
-
-## 📈 Code Quality
-
-| Aspect | Status |
-|--------|--------|
-| Type Safety | ✅ 100% (all typed) |
-| Validation | ✅ Full action validation |
-| Error Handling | ✅ Proper HTTP status codes |
-| Documentation | ✅ Comprehensive guides |
-| Testing | ✅ Manual tests pass |
-| Architecture | ✅ Clean separation |
-| Extensibility | ✅ Easy to add scenarios |
-
----
-
-## 📚 Documentation Updated
-
-| Document | Status | Purpose |
-|----------|--------|---------|
-| DAY1_STATUS.md | 🔄 Renamed | Day 1 reference |
-| DAY2_STATUS.md | ✅ Created | Day 2 detailed guide |
-| DAYS_1-2_SUMMARY.md | ✅ Created | Days 1-2 overview |
-| EXECUTIVE_SUMMARY.md | ✅ Updated | Current progress |
-| README.md | ✅ Still valid | Official spec |
-
----
-
-## 🚀 Next Steps (Day 3)
-
-### Build Two More Scenarios
-1. **cascading.py** (Task 2 - Medium)
-   - Database slowdown → upstream cascade
-   - 12 steps max
-   - 30% noise
-   - Agent must trace backward
-
-2. **silent_degrade.py** (Task 3 - Hard)
-   - Slow degradation in heavy noise
-   - 15 steps max
-   - 60% noise
-   - Nuanced P2 judgment required
-
-### Effort: ~3-4 hours (similar to Day 2)
-
----
-
-## 💡 Architecture
-
-```
-curl /reset?task=single_crash
-    ↓
-app.py: reset() endpoint
-    ↓
-environment.reset("single_crash")
-    ↓
-scenarios/single_crash.py: Load ground truth
-    ↓
-log_generator.py: Generate logs + state
-    ↓
-Return: TriageObservation
-
----
-
-curl /step -d '{"action_type":"...","value":"..."}'
-    ↓
-app.py: step() endpoint
-    ↓
-action.is_valid() - Validate
-    ↓
-environment.step(action)
-    ├─ Check if correct (vs ground truth)
-    ├─ Calculate reward
-    ├─ Generate next logs (step N+1)
-    └─ Update state
-    ↓
-Return: TriageObservation + reward + feedback
-```
-
----
-
-## ✅ Verification Checklist
-
-- [x] server/models.py — 5 classes, fully typed
-- [x] server/app.py — 7 endpoints, 3 wired
-- [x] server/environment.py — Complete class implementation
-- [x] server/log_generator.py — Synthetic logs working
-- [x] server/scenarios/single_crash.py — Task 1 defined
-- [x] /reset endpoint — Returns real observations
-- [x] /step endpoint — Returns real rewards
-- [x] /state endpoint — Returns real state
-- [x] Task 1 playable — Full episode works
-- [x] Documentation — DAY2_STATUS.md created
-- [x] Code pushed — Committed to GitHub
-
----
-
-## 🎯 Summary
-
-**Days 1-2: ✅ 100% Complete**
-
-What's done:
-- Skeleton (Day 1): ✅
-- Environment (Day 2): ✅
-- Task 1 (Day 2): ✅
-- Endpoints wired (3/7): ✅
-
-What's next:
-- Tasks 2 & 3 (Day 3): ⏳
-- Graders (Day 4): ⏳
-- Baseline agent (Day 5): ⏳
-
-**Total Progress: 40% (2 of 5 days)**
-
----
-
-Generated: 2026-03-27  
-Project: LogTriageEnv (Meta × PyTorch Hackathon)  
-Deadline: April 7, 2026, 11:59 PM IST  
-Status: ON TRACK ✅

EXECUTIVE_SUMMARY.md

@@ -1,347 +0,0 @@
-~# 🚀 EXECUTIVE SUMMARY — LogTriageEnv Days 1-3
-
-**Status: ✅ 100% COMPLETE (Days 1-3) — ALL 3 TASKS FULLY PLAYABLE**
-
----
-
-## What You've Built
-
-**LogTriageEnv** — An OpenEnv environment that teaches AI agents to be on-call SREs.
-
-**Days 1-3 Complete:** All 3 tasks (Single Crash, Cascading Failure, Silent Degradation) are now fully playable end-to-end!
-
-```
-Agent receives → System logs from 7-service cluster
-Agent analyzes → Identifies root cause, severity, remediation
-Agent acts → Takes triage actions with confidence & reasoning
-Agent learns → Gets reward signal + feedback
-```
-
----
-
-## 📊 By The Numbers
-
-| Metric | Value |
-|--------|-------|
-| **Files Created** | 30+ |
-| **Folders Created** | 5 |
-| **Code Written** | ~1,100 lines (models + API + environment) |
-| **Documentation** | ~1,900 lines (README + guides) |
-| **Tests Written** | ~200 lines |
-| **Data Models** | 5 (all fully typed) |
-| **API Endpoints** | 7 (3 wired & working, 4 TODO) |
-| **Tasks Playable** | 3/3 (ALL COMPLETE) |
-| **Supporting Guides** | 9 reference documents |
-| **Completion %** | **60% (Days 1-3 Complete)** |
-
----
-
-## ✅ What's Complete
-
-### Core Files (Ready to Use)
-- ✅ `openenv.yaml` — Environment specification
-- ✅ `requirements.txt` — All dependencies
-- ✅ `Dockerfile` — Container definition
-- ✅ `server/models.py` — 5 Pydantic models, fully validated
-- ✅ `server/app.py` — FastAPI with 7 working endpoints
-- ✅ `README.md` — 533-line comprehensive guide
-
-### Testing & Validation
-- ✅ `test_day1.py` — Automated validation (11 test cases)
-- ✅ `test_all.bat` — Windows batch runner
-- ✅ `TEST_ENDPOINTS.md` — 17 curl examples
-
-### Documentation Suite
-- ✅ `DAY1_STATUS.md` — Detailed status report
-- ✅ `COMPLETE_SUMMARY.md` — Quick reference
-- ✅ `README_EXPLAINED.md` — README breakdown
-- ✅ `VISUAL_SUMMARY.md` — Diagrams and examples
-- ✅ `FILE_INVENTORY.md` — Complete file listing
-
----
-
-## 🎯 Key Features Implemented
-
-### 1. **Fully Typed Models** (218 lines)
-```python
-✅ LogLine           — Single log entry
-✅ ServiceStatus     — Service health snapshot
-✅ TriageAction      — Agent decision (with validation!)
-✅ TriageObservation — What agent sees after step
-✅ EpisodeState      — Episode tracking
-```
-
-### 2. **Smart Action Validation** ⭐ CRITICAL
-```python
-TriageAction.is_valid() method:
-✅ Validates severity (P1, P2, P3 only)
-✅ Validates service names (7 valid services)
-✅ Validates team names (4 valid teams)
-✅ Validates remediation format (action:service)
-✅ Returns proper error messages
-✅ Used by /step endpoint to return 422 on invalid input
-```
-
-### 3. **FastAPI Server** (101 lines)
-```
-✅ /health           Returns status
-✅ /tasks            Returns all 3 task definitions
-✅ /step             Validates action, returns 422 on error
-✅ /reset            Skeleton (wire Day 2)
-✅ /state            Skeleton (wire Day 2)
-✅ /grader           Skeleton (wire Day 4)
-✅ /baseline         Skeleton (wire Day 5)
-```
-
-### 4. **Three Escalating Tasks**
-```
-✅ Task 1: Single Service Crash (Easy)
-   - One service down, clear logs
-   - Expected score: 0.75–0.85
-
-✅ Task 2: Cascading Failure (Medium)
-   - DB slowdown → upstream cascade
-   - Must trace to root, not symptoms
-   - Expected score: 0.45–0.60
-
-✅ Task 3: Silent Degradation (Hard)
-   - Slow creeping problem in 60% noise
-   - Nuanced P2 judgment required
-   - Expected score: 0.20–0.40
-```
-
----
-
-## 📝 Documentation Provided
-
-Your hackathon judges will find:
-
-1. **README.md** (533 lines)
-   - Clear problem statement (why SRE triage matters)
-   - Environment architecture (microservice topology)
-   - Detailed action/observation spaces
-   - Reward function with scoring table
-   - All 3 tasks with success criteria
-   - Complete API documentation
-   - Setup and deployment instructions
-   - Pre-submission checklist
-
-2. **7 Supporting Guides**
-   - Status report (what's done, what's left)
-   - Summary reference (quick overview)
-   - README explanation (section breakdown)
-   - Visual guide (diagrams and examples)
-   - File inventory (complete listing)
-   - Test endpoints (copy-paste curl commands)
-   - Original plan (DAY1.md reference)
-
----
-
-## 🧪 Ready to Test
-
-### Quick Tests (No Infrastructure Needed)
-```bash
-python test_day1.py
-```
-Tests model imports, validation logic, endpoint registration.
-
-### Full Server Test
-```bash
-pip install -r requirements.txt
-python -m uvicorn server.app:app --port 7860 --reload
-curl http://localhost:7860/health
-```
-
-### Docker Test
-```bash
-docker build -t logtriage-env .
-docker run -p 7860:7860 logtriage-env
-curl http://localhost:7860/health
-```
-
-### Manual Endpoint Tests
-See `TEST_ENDPOINTS.md` for 17 ready-to-run curl commands covering:
-- Valid actions (8 examples)
-- Invalid actions (5 error examples)
-- All endpoints
-
----
-
-## ⏳ What's Remaining
-
-Only 5% of work left:
-
-### Verification (30 minutes)
-- [ ] Run `python test_day1.py`
-- [ ] Start server and test `/health` endpoint
-- [ ] Test `/step` with valid and invalid actions
-- [ ] Test Docker build
-- [ ] Test Docker run
-
-### GitHub Push (5 minutes)
-```bash
-git add .
-git commit -m "Day 1: Complete scaffold, models, endpoints, Dockerfile"
-git push origin main
-```
-
-### Day 2 & 3 (Implementation) ✅
-- [x] Create `server/environment.py` (LogTriageEnvironment class)
-- [x] Create `server/log_generator.py` (synthetic log generation)
-- [x] Create `server/scenarios/single_crash.py` (Task 1 scenario)
-- [x] Create `server/scenarios/cascading.py` (Task 2 scenario)
-- [x] Create `server/scenarios/silent_degrade.py` (Task 3 scenario)
-- [x] Wire `/reset` and `/step` endpoints to environment
-- [x] Test all 3 tasks end-to-end
-
----
-
-## 📋 Pre-Push Checklist
-
-Before committing to GitHub, verify:
-
-- [ ] All files listed in FILE_INVENTORY.md exist locally
-- [ ] `test_day1.py` runs without import errors
-- [ ] No Python syntax errors in models.py or app.py
-- [ ] README.md is readable and complete
-- [ ] All 7 supporting guides are created
-- [ ] Dockerfile syntax is valid
-- [ ] requirements.txt has no circular dependencies
-- [ ] No hardcoded credentials or API keys in code
-- [ ] .gitignore includes Python artifacts
-
----
-
-## 🎬 Recommended Next Steps
-
-### Option A: Verify Everything Works (Recommended)
-1. **Run tests** (5 min): `python test_day1.py`
-2. **Start server** (2 min): `python -m uvicorn server.app:app --port 7860`
-3. **Test endpoints** (3 min): `curl http://localhost:7860/health`
-4. **Try Docker** (5 min): `docker build -t logtriage-env .`
-5. **Push to GitHub** (2 min): `git push origin main`
-
-**Total: 17 minutes to verify everything works**
-
-### Option B: Quick Push (Low Risk)
-- You have comprehensive test suite (`test_day1.py`)
-- Code is syntactically valid
-- Models are fully typed
-- Push and test on GitHub CI/CD
-
----
-
-## 📊 Quality Metrics
-
-| Aspect | Status | Notes |
-|--------|--------|-------|
-| **Type Safety** | ✅ Excellent | All models fully typed with Pydantic |
-| **Validation** | ✅ Excellent | is_valid() catches all bad inputs |
-| **Error Handling** | ✅ Excellent | Returns 422 with detailed messages |
-| **Documentation** | ✅ Excellent | 1,900 lines across 8 documents |
-| **Test Coverage** | ✅ Good | 11 validation test cases |
-| **Code Structure** | ✅ Excellent | Clean separation of concerns |
-| **Extensibility** | ✅ Excellent | Easy to add Day 2 logic |
-
----
-
-## 🏆 What Sets This Apart
-
-**For Hackathon Judges:**
-
-1. **Problem Understanding** — Clear articulation of SRE triage challenge
-2. **Technical Depth** — Sophisticated reward design, careful task design
-3. **Production-Ready Code** — Type safety, validation, error handling
-4. **Comprehensive Docs** — Anyone can understand and extend
-5. **Testability** — Automated tests, curl examples, batch runners
-6. **Multi-Week Plan** — Clear roadmap through Day 5
-7. **OpenEnv Compliance** — Follows standard specification
-
----
-
-## 💾 Git Commit Message (Ready to Use)
-
-```
-Day 1 Complete: Scaffold, Models, Endpoints, Docker, Comprehensive Docs
-
-✅ COMPLETED:
-- Full Pydantic models (LogLine, ServiceStatus, TriageAction, TriageObservation, EpisodeState)
-- TriageAction.is_valid() validates all 7 action types with detailed errors
-- FastAPI server with 7 endpoints (health, reset, step, state, tasks, grader, baseline)
-- Action validation integrated into /step endpoint (returns 422 on invalid)
-- Dockerfile for Python 3.11 containerization
-- openenv.yaml with 3 escalating tasks (easy, medium, hard)
-- Comprehensive 533-line README with all sections
-- 7 supporting documentation guides (1,900+ lines total)
-- Automated test suite (test_day1.py with 11 validation cases)
-- Windows batch test runner (test_all.bat)
-- 17 curl endpoint examples (TEST_ENDPOINTS.md)
-
-✅ VERIFIED:
-- Models import without errors
-- FastAPI app imports without errors
-- All endpoints registered
-- Validation logic correct for 11 test cases
-- Pydantic model construction works
-- Dockerfile syntax valid
-
-⏳ NEXT (Day 2):
-- Create server/environment.py (LogTriageEnvironment class)
-- Create server/log_generator.py (synthetic log generation)
-- Create server/scenarios/single_crash.py (Task 1 scenario)
-- Wire /reset and /step endpoints to real environment
-- Implement reset() and step() logic
-
-PROJECT STATUS: 95% complete, ready for testing & Day 2 implementation
-DEADLINE: April 7, 2026, 11:59 PM IST
-SUBMISSION: Meta × PyTorch Hackathon
-```
-
----
-
-## 🎯 Your Next Action
-
-**Choose one:**
-
-**A) Be Thorough (Recommended)**
-```bash
-1. python test_day1.py
-2. pip install -r requirements.txt
-3. python -m uvicorn server.app:app --port 7860 --reload
-4. # In another terminal: curl http://localhost:7860/health
-5. git push origin main
-```
-
-**B) Quick Push**
-```bash
-git add .
-git commit -m "Day 1 complete"
-git push origin main
-```
-
-Either way, you're ready. The foundation is solid. 🚀
-
----
-
-## 📞 Reference Guide
-
-| Need | File |
-|------|------|
-| Understand the project | README.md |
-| Know current status | DAY1_STATUS.md |
-| See what's done | COMPLETE_SUMMARY.md |
-| Understand README | README_EXPLAINED.md |
-| Visual diagrams | VISUAL_SUMMARY.md |
-| Test endpoints | TEST_ENDPOINTS.md |
-| File locations | FILE_INVENTORY.md |
-| Auto-validate | test_day1.py |
-| Original plan | DAY1.md |
-
----
-
-**Status:** ✅ ALL 3 TASKS PLAYABLE — READY FOR DAY 4  
-**Completion:** 60%  
-**Next Phase:** Day 4 Grader Implementation  
-**Deadline:** April 7, 2026, 11:59 PM IST  
-
-**All 3 tasks are fully functional. Next: Build grader logic to evaluate agent performance!** 🚀

FILE_INVENTORY.md

@@ -1,377 +0,0 @@
-~~# LogTriageEnv — Complete File Inventory
-
-## 📂 Project Root Files
-
-### Configuration & Setup
-| File | Lines | Status | Purpose |
-|------|-------|--------|---------|
-| `openenv.yaml` | 38 | ✅ | OpenEnv spec with 3 tasks, action/observation spaces, reward ranges |
-| `requirements.txt` | 6 | ✅ | All dependencies (fastapi, uvicorn, pydantic, openenv-core, requests, openai) |
-| `Dockerfile` | 16 | ✅ | Python 3.11 image, port 7860, uvicorn server |
-| `.gitignore` | Present | ✅ | Python ignore rules |
-| `LICENSE` | Present | ✅ | License file |
-
-### Documentation (Main)
-| File | Lines | Status | Purpose |
-|------|-------|--------|---------|
-| `README.md` | 533 | ✅ | Comprehensive guide (overview, tasks, API, setup, deployment) |
-| `DAY1.md` | 595 | ✅ | Original Day 1 execution plan (reference) |
-| `DAY1_STATUS.md` | 336 | ✅ | **Detailed status report** (what's built, what's left) |
-| `COMPLETE_SUMMARY.md` | 240 | ✅ | **Quick reference** (summary, testing, next steps) |
-| `README_EXPLAINED.md` | 268 | ✅ | **README breakdown** (section-by-section explanation) |
-| `VISUAL_SUMMARY.md` | 437 | ✅ | **Visual guide** (diagrams, data flow, examples) |
-| `FILE_INVENTORY.md` | This | ✅ | **Complete file list** (what you're reading) |
-| `TEST_ENDPOINTS.md` | 172 | ✅ | **Curl command reference** (17 endpoint tests) |
-
-### Test & Automation
-| File | Lines | Status | Purpose |
-|------|-------|--------|---------|
-| `test_day1.py` | 147 | ✅ | Automated Python validation (models, imports, validation logic) |
-| `test_all.bat` | 61 | ✅ | Windows batch test runner (dependencies, imports, tests) |
-
----
-
-## 📁 server/ Directory (Core Implementation)
-
-### Models & Configuration
-| File | Lines | Status | Purpose |
-|------|-------|--------|---------|
-| `server/__init__.py` | 0 | ✅ | Package marker |
-| `server/models.py` | 218 | ✅✨ | **Pydantic models** (LogLine, ServiceStatus, TriageAction, TriageObservation, EpisodeState) |
-| `server/requirements.txt` | Present | ✅ | Server-specific dependencies (if any) |
-
-### API & Application
-| File | Lines | Status | Purpose |
-|------|-------|--------|---------|
-| `server/app.py` | 101 | ✅✨ | **FastAPI application** (7 endpoints: /health, /reset, /step, /state, /tasks, /grader, /baseline) |
-
-### Environment & Simulation (Day 2+)
-| File | Lines | Status | Purpose |
-|------|-------|--------|---------|
-| `server/environment.py` | - | ⏳ | **Core class** LogTriageEnvironment (reset, step, state management) |
-| `server/log_generator.py` | - | ⏳ | Synthetic log generation (realistic service logs) |
-
-### Scenarios (Day 2-3)
-| File | Lines | Status | Purpose |
-|------|-------|--------|---------|
-| `server/scenarios/__init__.py` | - | ⏳ | Package marker |
-| `server/scenarios/single_crash.py` | - | ⏳ | **Task 1** Single service crash scenario |
-| `server/scenarios/cascading.py` | - | ⏳ | **Task 2** Cascading failure scenario |
-| `server/scenarios/silent_degrade.py` | - | ⏳ | **Task 3** Silent degradation with noise scenario |
-
-### Graders (Day 4)
-| File | Lines | Status | Purpose |
-|------|-------|--------|---------|
-| `server/graders/__init__.py` | - | ⏳ | Package marker |
-| `server/graders/base_grader.py` | - | ⏳ | Abstract base class for all graders |
-| `server/graders/crash_grader.py` | - | ⏳ | Task 1 grader (single crash scoring) |
-| `server/graders/cascade_grader.py` | - | ⏳ | Task 2 grader (cascading failure scoring) |
-| `server/graders/noise_grader.py` | - | ⏳ | Task 3 grader (silent degradation scoring) |
-
----
-
-## 📁 scripts/ Directory (Utilities)
-
-| File | Lines | Status | Purpose |
-|------|-------|--------|---------|
-| `scripts/run_grader.py` | - | ⏳ | Manual grader testing CLI (Day 4) |
-| `scripts/validate_checklist.py` | - | ⏳ | Pre-submission validation script (Day 5) |
-
----
-
-## 📁 Root-Level Support Files
-
-| File | Lines | Status | Purpose |
-|------|-------|--------|---------|
-| `baseline.py` | - | ⏳ | Baseline agent using GPT-4o-mini (Day 5) |
-| `.claude` | - | ✅ | Copilot session marker |
-| `.git/` | - | ✅ | Git repository |
-| `.gitignore` | - | ✅ | Git ignore rules |
-
----
-
-## 📊 Summary Statistics
-
-### Completed
-```
-✅ Core Files Written:        12 files
-✅ Total Documentation:       1,900+ lines
-✅ Code Lines:                 500+ lines
-✅ Tests:                      200+ lines
-✅ Examples:                   200+ lines
-```
-
-### By Category
-
-**Configuration:** 3 files
-- openenv.yaml
-- requirements.txt  
-- .gitignore
-
-**Documentation:** 8 files
-- README.md (main)
-- 7 supporting guides
-
-**Core Code:** 2 files
-- models.py (218 lines) ✨
-- app.py (101 lines) ✨
-
-**Tests:** 2 files
-- test_day1.py
-- test_all.bat
-
-**Infrastructure:** 2 files
-- Dockerfile
-- License
-
-**Folders Created:** 5
-- server/
-- server/scenarios/
-- server/graders/
-- scripts/
-- .git/
-
----
-
-## 🎯 What Each File Does
-
-### `openenv.yaml` (38 lines)
-**OpenEnv metadata specification**
-- Environment name and version
-- 3 task definitions (single_crash, cascading_failure, silent_degradation)
-- Action space (discrete, 7 action types)
-- Observation space (structured logs + state)
-- Reward range [-0.5, 1.0]
-
-### `requirements.txt` (6 lines)
-**Python dependencies**
-- openenv-core>=0.2.2
-- fastapi>=0.104.0
-- uvicorn>=0.24.0
-- pydantic>=2.0.0
-- requests>=2.25.0
-- openai>=1.0.0
-
-### `Dockerfile` (16 lines)
-**Container image definition**
-- Base: python:3.11-slim
-- Installs requirements
-- Copies source code
-- Exposes port 7860
-- Runs uvicorn server
-
-### `server/models.py` (218 lines) ⭐ KEY FILE
-**5 Pydantic data models:**
-
-1. **LogLine** (15 lines)
-   - timestamp, level, service, request_id, message, latency_ms
-
-2. **ServiceStatus** (10 lines)
-   - name, status, error_rate, latency_p99_ms, last_updated
-
-3. **TriageAction** (50 lines) ⭐ MOST IMPORTANT
-   - action_type (7 types)
-   - value (depends on type)
-   - confidence (0.0–1.0)
-   - reasoning (optional)
-   - **is_valid() method** with full validation logic
-
-4. **TriageObservation** (55 lines)
-   - logs, system_state, incident_id, task_id, step_count, time_elapsed
-   - active_alerts, reward, cumulative_score, done
-   - last_action_feedback, invalid_action_error
-
-5. **EpisodeState** (25 lines)
-   - episode_id, task_id, step_count, max_steps, done, cumulative_score
-   - actions_taken, correct_severity, correct_root_cause, correct_remediation
-
-### `server/app.py` (101 lines) ⭐ KEY FILE
-**FastAPI application with 7 endpoints:**
-
-| Endpoint | Method | Status | Implementation |
-|----------|--------|--------|-----------------|
-| /health | GET | ✅ | Returns `{"status": "ok", ...}` |
-| /reset | POST | ⏳ | Placeholder (wire Day 2) |
-| /step | POST | ✅ | Validates action via `is_valid()`, returns 422 on error |
-| /state | GET | ⏳ | Placeholder (wire Day 2) |
-| /tasks | GET | ✅ | Returns all 3 tasks with full schemas |
-| /grader | POST | ⏳ | Placeholder (wire Day 4) |
-| /baseline | POST | ⏳ | Placeholder (wire Day 5) |
-
-**Key feature:** `/step` endpoint already validates actions!
-```python
-valid, err = action.is_valid()
-if not valid:
-    return JSONResponse(status_code=422, content={"error": err})
-```
-
-### `README.md` (533 lines) ⭐ CRUCIAL
-**Comprehensive documentation covering:**
-
-1. Overview & Motivation (why SRE triage matters)
-2. Environment Description (microservice topology, log examples)
-3. Action Space (7 action types with value table)
-4. Observation Space (logs + state + rewards)
-5. Reward Function (detailed scoring: +0.30–+0.35 for correct decisions)
-6. Tasks & Graders (3 tasks with success criteria and expected scores)
-7. Episode Boundaries (when start/end, reproducibility)
-8. API Endpoints (all 8 endpoints documented with examples)
-9. Setup & Installation (clone, install, run locally)
-10. Docker Usage (build and run instructions)
-11. Hugging Face Spaces (deployment configuration)
-12. Baseline Inference (template code for LLM baseline)
-13. Baseline Scores (table of expected results, TBD)
-14. OpenEnv Spec Compliance (checklist of requirements)
-15. Pre-Submission Checklist (14 validation items)
-16. Project Structure (complete folder map with descriptions)
-
-### `test_day1.py` (147 lines)
-**Automated validation script that tests:**
-- Model imports (LogLine, ServiceStatus, TriageAction, TriageObservation, EpisodeState)
-- FastAPI app import
-- 11 TriageAction validation test cases
-- Pydantic model construction
-- Endpoint registration
-
-Run: `python test_day1.py`
-
-### `TEST_ENDPOINTS.md` (172 lines)
-**Reference guide with 17 curl command examples:**
-- /health check
-- /tasks listing
-- 8 valid actions (classify, identify, remediate, escalate, resolve, ignore, request_logs)
-- 5 invalid actions (wrong severity, unknown service, bad format, etc.)
-- Expected responses for each
-
-### `DAY1_STATUS.md` (336 lines)
-**Detailed status report explaining:**
-- What is LogTriageEnv
-- What has been built (file-by-file breakdown)
-- What each core file does
-- What's ready to test
-- What's remaining
-- Day 1 checklist status
-- How to test locally
-- Git commit template
-
-### `COMPLETE_SUMMARY.md` (240 lines)
-**Quick-reference summary with:**
-- What you're building
-- Completion status table
-- Core models explanation
-- FastAPI endpoints
-- 3 tasks at a glance
-- Key achievements
-- How to proceed
-
-### `README_EXPLAINED.md` (268 lines)
-**Detailed breakdown of README.md structure:**
-- Why README matters for hackathon
-- What each section explains
-- Key quotes and examples
-- Why this README stands out
-- How it becomes HF Space header
-
-### `VISUAL_SUMMARY.md` (437 lines)
-**Visual reference guide with:**
-- ASCII diagrams of architecture
-- Data flow diagram
-- Task descriptions with visual examples
-- Pydantic models at a glance
-- Action validation examples (✅ vs 🚫)
-- File completion status table
-- Quick stats and numbers
-- What to do next steps
-- Day 2 todo list
-
-### `FILE_INVENTORY.md` (This file)
-**Complete project file listing:**
-- All files with line counts and purposes
-- Status indicators (✅ ⏳)
-- Summary statistics
-- What each file does
-
----
-
-## 📈 Progress Tracking
-
-### Day 1 Complete
-```
-✅ openenv.yaml             (spec)
-✅ requirements.txt         (dependencies)
-✅ Dockerfile               (containerization)
-✅ server/models.py         (data models)
-✅ server/app.py            (API endpoints)
-✅ README.md                (documentation)
-✅ Folder structure         (all directories created)
-✅ Test suite               (test_day1.py, test_all.bat)
-✅ Documentation suite      (5 supporting guides)
-```
-
-### Day 2 TODO
-```
-⏳ server/environment.py     (core logic)
-⏳ server/log_generator.py   (log synthesis)
-⏳ server/scenarios/single_crash.py (Task 1)
-```
-
-### Day 3-5 TODO
-```
-⏳ server/scenarios/cascading.py (Task 2)
-⏳ server/scenarios/silent_degrade.py (Task 3)
-⏳ server/graders/*.py       (scoring logic)
-⏳ baseline.py               (LLM agent)
-⏳ scripts/                  (CLI tools)
-```
-
----
-
-## 🎓 How to Use This Inventory
-
-**When you need to:**
-- **Understand what's done:** Check the Status column (✅ = ready, ⏳ = pending)
-- **Find a file:** Use the File column
-- **Know the purpose:** Check the Purpose column
-- **See how long something is:** Check the Lines column
-- **Understand the big picture:** See Summary Statistics
-- **Know what to work on next:** Check Progress Tracking
-
----
-
-## 📦 Total Project Size
-
-- **Core Code:** ~320 lines (models.py + app.py)
-- **Documentation:** ~1,900 lines (README + guides)
-- **Tests:** ~200 lines (validation + examples)
-- **Configuration:** ~60 lines (openenv.yaml + requirements)
-- **Automation:** ~100 lines (Dockerfile + batch)
-
-**Total (Day 1): ~2,600 lines of code, docs, and tests**
-
----
-
-## ✅ Verification Checklist
-
-Use this to verify everything is present:
-
-- [ ] openenv.yaml exists and has 3 tasks
-- [ ] requirements.txt has all 6 dependencies
-- [ ] Dockerfile exists and is valid
-- [ ] server/models.py exists with 5 classes
-- [ ] server/app.py exists with 7 endpoints
-- [ ] README.md has all 16 sections
-- [ ] test_day1.py exists
-- [ ] test_all.bat exists
-- [ ] TEST_ENDPOINTS.md exists with 17 examples
-- [ ] DAY1_STATUS.md exists
-- [ ] COMPLETE_SUMMARY.md exists
-- [ ] README_EXPLAINED.md exists
-- [ ] VISUAL_SUMMARY.md exists
-- [ ] FILE_INVENTORY.md exists (this file)
-- [ ] All folders created (server/, scripts/, scenarios/, graders/)
-
----
-
-**Generated:** 2026-03-26  
-**Project:** LogTriageEnv — Meta × PyTorch Hackathon  
-**Status:** Day 1 Complete (95% ready, just needs testing & push)

README.md

@@ -347,8 +347,8 @@ uvicorn server.app:app --host 0.0.0.0 --port 7860 --reload
 ### Run baseline inference
 
 ```bash
-export OPENAI_API_KEY=your_key_here
-python baseline.py
+export HF_TOKEN=your_key_here
+python inference.py
 ```
 
 ### Validate all 3 tasks manually
@@ -377,7 +377,7 @@ curl http://localhost:7860/health
 curl -X POST http://localhost:7860/reset
 
 # Run baseline inside container
-docker run -e OPENAI_API_KEY=your_key logtriage-env python baseline.py
+docker run -e HF_TOKEN=your_key -e API_BASE_URL=https://api.groq.com/openai/v1 -e MODEL_NAME=llama-3.3-70b-versatile logtriage-env python inference.py
 ```
 
 ---
@@ -395,7 +395,7 @@ The Space uses a Docker SDK with the following configuration:
 title: LogTriageEnv
 emoji: 🚨
 colorFrom: red
-colorTo: orange
+colorTo: red
 sdk: docker
 pinned: false
 tags:
@@ -409,10 +409,10 @@ tags:
 
 ## 12. Baseline Inference Script
 
-`baseline.py` uses the OpenAI API client to run `gpt-4o-mini` as a zero-shot agent against all 3 tasks and reports scores.
+`inference.py` uses an OpenAI-compatible client with configurable provider settings to run `llama-3.3-70b-versatile` as a zero-shot agent against all 3 tasks and reports scores.
 
 ```python
-# baseline.py (structure)
+# inference.py (structure)
 import os
 from openai import OpenAI
 import requests
@@ -457,19 +457,24 @@ if __name__ == "__main__":
 
 ## 13. Baseline Scores
 
-*(To be filled after implementation and baseline runs)*
+Scores produced by `inference.py` using `llama-3.3-70b-versatile` via Groq API (`seed=42`):
 
-| Task | Difficulty | Baseline Score (gpt-4o-mini) |
+| Task | Difficulty | Score |
 |---|---|---|
-| Single Service Crash | Easy | TBD |
-| Cascading Failure | Medium | TBD |
-| Silent Degradation | Hard | TBD |
-| **Average** | | **TBD** |
+| Single Service Crash | Easy | 1.0000 |
+| Cascading Failure | Medium | 0.6500 |
+| Silent Degradation | Hard | 0.0000 |
+| **Average** | | **0.5500** |
 
 Expected ranges based on design:
-- Single crash: 0.75–0.85
-- Cascading failure: 0.45–0.60
-- Silent degradation: 0.20–0.40
+- Single crash: 0.75–0.85 → **Exceeded (1.0000)**
+- Cascading failure: 0.45–0.60 → **Exceeded (0.6500)**
+- Silent degradation: 0.20–0.40 → **Below range (0.0000 — see note)**
+
+> **Note:** LLM-based scoring varies across runs due to non-deterministic model behavior.
+> The Silent Degradation task is hardest — it requires distinguishing signal from 60% noise
+> and making a nuanced P2 judgment (not an outage yet). Scores on this task can range
+> from 0.0 to 0.55 depending on the model's log parsing on that specific run.
 
 ---
 
@@ -505,7 +510,7 @@ Expected ranges based on design:
 - [ ] `POST /grader` returns score in [0.0, 1.0]
 - [ ] `POST /baseline` completes and returns scores for all 3 tasks
 - [ ] HF Space URL responds to ping with 200
-- [ ] Baseline script runs end-to-end with `OPENAI_API_KEY` set
+- [ ] Baseline script runs end-to-end with `HF_TOKEN` set
 - [ ] All 3 graders return varying scores (not constant)
 - [ ] README includes all required sections
 - [ ] `requirements.txt` is complete and pinned
@@ -520,7 +525,7 @@ logtriage-env/
 ├── openenv.yaml               # OpenEnv metadata
 ├── Dockerfile                 # Container definition
 ├── requirements.txt           # Top-level deps
-├── baseline.py                # Baseline inference script
+├── inference.py               # Baseline inference script
 │
 ├── server/
 │   ├── __init__.py

START_HERE_DAY2.md

@@ -1,246 +0,0 @@
-# 📖 START HERE — Days 1-2 Complete Guide
-
-**Status:** ✅ **Days 1-2 COMPLETE — Task 1 Fully Playable**  
-**Overall Progress:** 40% (2 of 5 days)  
-**Last Updated:** March 27, 2026
-
----
-
-## 🎯 Where to Start?
-
-### If you have **2 minutes**:
-👉 Read **STATUS.md** ← Quick status + which docs to read
-
-### If you have **5 minutes**:
-👉 Read **EXECUTIVE_SUMMARY.md** ← What's done, high-level overview
-
-### If you have **10 minutes**:
-👉 Read **DAYS_1-2_SUMMARY_FINAL.md** ← Clean summary of Days 1-2
-
-### If you want **full details**:
-👉 Read **DAYS_1-2_SUMMARY.md** ← Comprehensive Day 2 breakdown + examples
-
----
-
-## 📁 Documentation by Purpose
-
-### 🚀 **Quick Overview (2-5 min)**
-| File | Purpose | Read If |
-|------|---------|---------|
-| **STATUS.md** | Current status + doc guide | You want a quick check |
-| **EXECUTIVE_SUMMARY.md** | High-level completion status | You want an overview |
-| **DAYS_1-2_SUMMARY_FINAL.md** | Days 1-2 summary | You want a clean summary |
-
-### 📚 **Detailed Technical (10-20 min)**
-| File | Purpose | Read If |
-|------|---------|---------|
-| **DAYS_1-2_SUMMARY.md** | Full Day 2 breakdown | You want to understand architecture |
-| **DAY1_STATUS.md** | Detailed Day 1 status | You want Day 1 details |
-| **DAY2_STATUS.md** | Detailed Day 2 status | You want Day 2 details |
-| **README.md** | Official spec (533 lines) | You want the complete reference |
-
-### 🔧 **How-To Guides (5-15 min)**
-| File | Purpose | Read If |
-|------|---------|---------|
-| **TEST_ENDPOINTS.md** | 17 curl examples (all working!) | You want to test endpoints |
-| **VISUAL_SUMMARY.md** | Diagrams + architecture | You want visual understanding |
-| **README_EXPLAINED.md** | Line-by-line README breakdown | You want to understand README |
-| **FILE_INVENTORY.md** | Complete file listing | You want to know where everything is |
-
-### 📋 **Reference (5-10 min)**
-| File | Purpose | Read If |
-|------|---------|---------|
-| **COMPLETE_SUMMARY.md** | Feature checklist | You want to see all features |
-| **WHAT_HAS_BEEN_DONE.md** | Completion summary | You want a summary |
-| **FINAL_CHECKLIST.md** | Pre-push verification | You want a checklist |
-| **ANALYSIS_SUMMARY.md** | Technical analysis | You want deep analysis |
-
----
-
-## ✅ What's Done (Days 1-2)
-
-### **Day 1: Skeleton (100% Complete)**
-```
-✅ Models (5 Pydantic classes, 218 lines)
-✅ API endpoints (7 registered, 3+ wired)
-✅ Configuration (openenv.yaml, requirements.txt)
-✅ Docker setup
-✅ Comprehensive documentation
-```
-
-### **Day 2: Environment (100% Complete)**
-```
-✅ LogTriageEnvironment class (250+ lines)
-✅ Synthetic log generator (400+ lines)
-✅ Task 1 scenario (150+ lines)
-✅ Endpoints wired to real logic (/reset, /step, /state)
-✅ Full Task 1 playable end-to-end
-```
-
-### **Total: 40% of Project**
-- ✅ Task 1 (Easy): PLAYABLE
-- ⏳ Task 2 (Medium): Not yet
-- ⏳ Task 3 (Hard): Not yet
-
----
-
-## 🎮 Try It Now
-
-### 1. Start Server
-```bash
-python -m uvicorn server.app:app --port 7860
-```
-
-### 2. Run Full Episode (Copy-Paste From TEST_ENDPOINTS.md)
-```bash
-# Reset (get initial observation)
-curl -X POST "http://localhost:7860/reset?task=single_crash&seed=42"
-
-# Step 1: Classify severity
-curl -X POST "http://localhost:7860/step" \
-  -H "Content-Type: application/json" \
-  -d '{"action_type":"classify_severity","value":"P1","confidence":0.95}'
-
-# Step 2: Identify root cause
-curl -X POST "http://localhost:7860/step" \
-  -H "Content-Type: application/json" \
-  -d '{"action_type":"identify_root_cause","value":"payment-service","confidence":0.9}'
-
-# Step 3: Remediate
-curl -X POST "http://localhost:7860/step" \
-  -H "Content-Type: application/json" \
-  -d '{"action_type":"remediate","value":"restart:payment-service","confidence":0.95}'
-
-# Step 4: Resolve
-curl -X POST "http://localhost:7860/step" \
-  -H "Content-Type: application/json" \
-  -d '{"action_type":"resolve","value":"resolved"}'
-```
-
-### 3. Result
-✅ Perfect episode score: **1.0**  
-✅ Rewards: 0.30 + 0.35 + 0.25 + 0.10 = 1.0
-
----
-
-## 📊 Progress Status
-
-```
-Day 1: ✅✅✅✅✅ (100% - Skeleton)
-Day 2: ✅✅✅✅✅ (100% - Environment)
-Day 3: ⏳⏳⏳⏳⏳ (0% - Scenarios 2 & 3)
-Day 4: ⏳⏳⏳⏳⏳ (0% - Graders)
-Day 5: ⏳⏳⏳⏳⏳ (0% - Baseline + Deploy)
-
-OVERALL: ▓▓░░░ 40% Complete
-```
-
----
-
-## 🎯 Key Files (Know These!)
-
-### **Core Code**
-- `server/models.py` — 5 Pydantic classes
-- `server/app.py` — FastAPI endpoints
-- `server/environment.py` — Episode logic ⭐ NEW Day 2
-- `server/log_generator.py` — Synthetic logs ⭐ NEW Day 2
-- `server/scenarios/single_crash.py` — Task 1 ⭐ NEW Day 2
-
-### **Configuration**
-- `openenv.yaml` — Environment spec
-- `requirements.txt` — Dependencies
-- `Dockerfile` — Container
-
-### **Documentation** (Choose your favorite!)
-- **STATUS.md** ← Start here
-- **EXECUTIVE_SUMMARY.md** ← Overview
-- **DAYS_1-2_SUMMARY.md** ← Technical details
-- **TEST_ENDPOINTS.md** ← Copy-paste curl commands
-
----
-
-## 💡 Key Concepts
-
-### **Episode Flow**
-```
-Agent → /reset → Observation (initial logs + state)
-Agent → /step (action) → Observation + reward + feedback
-...repeat...
-Agent → /step (resolve) → done=true, episode complete
-```
-
-### **Reward System**
-- Severity classification: +0.30
-- Root cause identification: +0.35
-- Remediation action: +0.25
-- Speed bonus: +0.10
-- **Max score: 1.0**
-
-### **Log Generation**
-- 7 microservices
-- Noise templates (realistic but irrelevant)
-- Signal templates (error patterns)
-- Step-by-step escalation
-- Deterministic (reproducible with seed)
-
----
-
-## ❓ FAQ
-
-**Q: What's the difference between Day 1 and Day 2?**  
-A: Day 1 = skeleton (models, API). Day 2 = logic (environment, logs, scenarios).
-
-**Q: Can I play Task 1 right now?**  
-A: Yes! Run server, use curl commands from TEST_ENDPOINTS.md.
-
-**Q: What's the next step?**  
-A: Day 3 = build Task 2 & Task 3 scenarios.
-
-**Q: Where's the full reference?**  
-A: README.md (533 lines, complete spec).
-
-**Q: I just want to understand fast. Where do I start?**  
-A: Read STATUS.md (2 min) → DAYS_1-2_SUMMARY_FINAL.md (5 min).
-
-**Q: I want the technical details.**  
-A: Read DAYS_1-2_SUMMARY.md (full architecture + examples).
-
----
-
-## 📞 Document Map
-
-```
-Need quick status?           → STATUS.md
-Need executive overview?     → EXECUTIVE_SUMMARY.md
-Need clean summary?          → DAYS_1-2_SUMMARY_FINAL.md
-Need technical details?      → DAYS_1-2_SUMMARY.md
-Need Day 1 specifics?        → DAY1_STATUS.md
-Need Day 2 specifics?        → DAY2_STATUS.md
-Need to test endpoints?      → TEST_ENDPOINTS.md
-Need to understand design?   → VISUAL_SUMMARY.md
-Need full reference?         → README.md
-Need file locations?         → FILE_INVENTORY.md
-Need architecture diagram?   → VISUAL_SUMMARY.md
-Need line-by-line README?    → README_EXPLAINED.md
-```
-
----
-
-## ✨ TL;DR
-
-**Status:** ✅ Days 1-2 done (40% project complete)
-
-**What works:** Task 1 fully playable
-
-**How to test:** Run server, curl commands from TEST_ENDPOINTS.md
-
-**Next:** Build Task 2 & 3 scenarios (Day 3)
-
-**Read first:** STATUS.md or EXECUTIVE_SUMMARY.md
-
----
-
-Generated: March 27, 2026  
-Project: LogTriageEnv (Meta × PyTorch Hackathon)  
-Deadline: April 7, 2026, 11:59 PM IST  
-Status: **ON TRACK** ✅

STATUS.md

@@ -1,260 +0,0 @@
-# 🎯 CURRENT STATUS — LogTriageEnv Days 1-3
-
-**Last Updated:** March 27, 2026  
-**Status:** ✅ **Days 1-3 COMPLETE (100% of Days 1-3, 60% of total project)**  
-**Overall Progress:** ▓▓▓░░ (60%)
-
----
-
-## 📊 Quick Status
-
-| Component | Status | Details |
-|-----------|--------|---------|
-| **Day 1 Work** | ✅ 100% | Models, API scaffold, config, docs |
-| **Day 2 Work** | ✅ 100% | Environment, log gen, Task 1 scenario |
-| **Day 3 Work** | ✅ 100% | Tasks 2 & 3 scenarios + wiring |
-| **Task 1 (Easy)** | ✅ 100% | Single crash - fully playable |
-| **Task 2 (Medium)** | ✅ 100% | Cascading failures - fully playable |
-| **Task 3 (Hard)** | ✅ 100% | Silent degradation - fully playable |
-| **Graders** | ⏳ 0% | Day 4 - not started |
-| **Baseline Agent** | ⏳ 0% | Day 5 - not started |
-
----
-
-## 📁 Documentation Guide
-
-### 📖 START HERE
-**For quick understanding of what's been done:**
-
-1. **EXECUTIVE_SUMMARY.md** (3 min read)
-   - High-level status
-   - What's complete
-   - By-the-numbers
-
-2. **DAYS_1-2_SUMMARY.md** (10 min read)
-   - Detailed Day 2 breakdown
-   - Architecture evolution
-   - Full episode example
-
-3. **DAYS_1-2_SUMMARY_FINAL.md** (5 min read)
-   - Clean summary
-   - Playable tasks
-   - Progress tracking
-
----
-
-### 🔍 DETAILED REFERENCES
-
-| File | Purpose |
-|------|---------|
-| **DAY3_STATUS.md** | Day 3 detailed status | Understanding Day 3 (cascading, silent degrade) |
-| **README.md** | Official spec | Understanding what the project is |
-| **README_EXPLAINED.md** | Breakdown of README | Line-by-line understanding |
-| **COMPLETE_SUMMARY.md** | Feature overview | Architecture and features |
-| **FILE_INVENTORY.md** | File listing | Where everything is |
-| **VISUAL_SUMMARY.md** | Architecture diagrams | Visual understanding |
-| **TEST_ENDPOINTS.md** | 17 curl examples | Testing endpoints |
-| **START_HERE.md** | Navigation guide | Which docs to read |
-
----
-
-### 📋 PROGRESS TRACKING
-
-| File | Purpose |
-|------|---------|
-| **ANALYSIS_SUMMARY.md** | Technical analysis |
-| **WHAT_HAS_BEEN_DONE.md** | Completion summary |
-| **FINAL_CHECKLIST.md** | Pre-push verification |
-
----
-
-## ✅ What's Actually Done
-
-### Core Code (1,100+ lines)
-```
-✅ server/models.py (218 lines)
-   - 5 Pydantic classes (all typed)
-   - Full validation
-
-✅ server/app.py (101+ lines)
-   - 7 FastAPI endpoints
-   - 3 wired to real logic
-   - 4 still TODO
-
-✅ server/environment.py (250+ lines)
-   - LogTriageEnvironment class
-   - Episode management
-   - Reward calculation
-   - State tracking
-
-✅ server/log_generator.py (400+ lines)
-   - Synthetic log generation
-   - Noise/signal templates
-   - Deterministic with seeds
-   - 7-service cluster
-
-✅ server/scenarios/single_crash.py (150+ lines)
-   - Task 1: Single service crash
-   - Ground truth definition
-   - Error signal templates
-   - Step-by-step scenario
-```
-
-### Configuration (40+ lines)
-```
-✅ openenv.yaml - Environment specification
-✅ requirements.txt - Dependencies
-✅ Dockerfile - Containerization
-```
-
-### Documentation (1,900+ lines)
-```
-✅ README.md (533 lines)
-✅ EXECUTIVE_SUMMARY.md
-✅ DAY1_STATUS.md
-✅ DAY2_STATUS.md
-✅ DAYS_1-2_SUMMARY.md
-✅ + 8 more guides
-```
-
----
-
-## 🎮 What's Playable Now
-
-### Task 1: Single Service Crash ✅
-
-**Difficulty:** Easy  
-**Episode Length:** 5-8 steps  
-**Scenario:** payment-service crashes, agent must triage
-
-**Play it:**
-```bash
-# Terminal 1
-python -m uvicorn server.app:app --port 7860
-
-# Terminal 2
-# (See TEST_ENDPOINTS.md for full curl examples)
-curl -X POST "http://localhost:7860/reset?task=single_crash&seed=42"
-curl -X POST "http://localhost:7860/step" \
-  -H "Content-Type: application/json" \
-  -d '{"action_type":"classify_severity","value":"P1","confidence":0.95}'
-# ... and so on
-```
-
-**Expected Output:**
-```
-Step 0: Observation with crash logs
-Step 1: Reward 0.30 (severity correct)
-Step 2: Reward 0.35 (root cause correct)
-Step 3: Reward 0.25 (remediation correct)
-Step 4: Reward 0.10 (speed bonus)
-Final: Score 1.0 ✅ (perfect play)
-```
-
----
-
-## 📈 Progress Timeline
-
-```
-Day 1 ✅ (Complete)
-├─ Models & validation
-├─ FastAPI scaffold
-├─ Config & Docker
-└─ Comprehensive docs
-
-Day 2 ✅ (Complete)
-├─ Environment class
-├─ Log generation
-├─ Task 1 scenario
-└─ Endpoints wired (3/7)
-
-Day 3 ✅ (Complete)
-├─ Task 2 scenario (cascading)
-├─ Task 3 scenario (silent degrade)
-├─ All tasks wired
-└─ Full testing ready
-
-Day 4 ⏳ (Next)
-├─ Grader logic
-└─ Evaluation
-
-Day 5 ⏳ (TBD)
-├─ Baseline agent
-└─ Deployment
-
-60% COMPLETE ✅
-```
-
----
-
-## 🎯 Commands to Remember
-
-### Run the Server
-```bash
-python -m uvicorn server.app:app --port 7860
-```
-
-### Test Task 1
-```bash
-# See TEST_ENDPOINTS.md for 17 different curl examples
-# Or use START_HERE.md for navigation
-```
-
-### Check Completion
-- **Day 1:** ✅ 100% (see DAY1_STATUS.md)
-- **Day 2:** ✅ 100% (see DAY2_STATUS.md)
-- **Day 3:** ⏳ 0% (TODO)
-
----
-
-## 💡 Key Points
-
-✅ **What's Working:**
-- Full environment logic (all 3 tasks)
-- Log generation (3 scenarios with proper noise)
-- Reward calculation (per-task ground truth)
-- All 3 tasks playable end-to-end
-- Clean architecture
-
-⏳ **What's Next:**
-- Grader implementation (Day 4)
-- Baseline agent (Day 5)
-
-❌ **Not Needed Yet:**
-- Deployment (Day 5)
-- LLM integration (Day 5)
-
----
-
-## 📞 Quick Reference
-
-**Questions?**
-- What's the project? → **README.md**
-- What was built? → **DAYS_1-2_SUMMARY.md**
-- How do I test? → **TEST_ENDPOINTS.md**
-- Where's the code? → **FILE_INVENTORY.md**
-- How does it work? → **VISUAL_SUMMARY.md**
-- Line-by-line? → **README_EXPLAINED.md**
-
----
-
-## ✨ Summary
-
-**Status: ✅ Days 1-3 Complete, All 3 Tasks Playable**
-
-- ✅ Environment fully functional with all 3 scenarios
-- ✅ Log generation working (with noise injection)
-- ✅ All 3 tasks playable (easy, medium, hard)
-- ✅ All endpoints wired (7/7)
-- ✅ All documentation updated
-
-**Next:** Build Day 4 grader logic
-
-**Overall Progress:** 60% ✅ (3 of 5 days complete)
-
----
-
-Generated: March 27, 2026  
-Project: LogTriageEnv (Meta × PyTorch Hackathon)  
-Deadline: April 7, 2026, 11:59 PM IST  
-Status: **ON TRACK** ✅ (60% complete — all 3 tasks playable)

TEST_ENDPOINTS.md

@@ -1,302 +0,0 @@
-# Day 1 Testing Guide — Curl Commands
-
-## Prerequisites
-```bash
-pip install -r requirements.txt
-python -m uvicorn server.app:app --host 0.0.0.0 --port 7860 --reload
-```
-
-Leave the server running and open a new terminal for these tests.
-
----
-
-## Test 1: Health Check
-```bash
-curl http://localhost:7860/health
-```
-
-**Expected Response:**
-```json
-{
-  "status": "ok",
-  "environment": "logtriage-env",
-  "version": "1.0.0"
-}
-```
-
----
-
-## Test 2: Get All Tasks
-```bash
-curl http://localhost:7860/tasks
-```
-
-**Expected Response:** JSON with 3 tasks (single_crash, cascading_failure, silent_degradation) including action schemas.
-
----
-
-## Test 3: Valid Step Action (Classify Severity)
-```bash
-curl -X POST http://localhost:7860/step \
-  -H "Content-Type: application/json" \
-  -d '{
-    "action_type": "classify_severity",
-    "value": "P1",
-    "confidence": 0.95,
-    "reasoning": "High error rate detected"
-  }'
-```
-
-**Expected Response:** 200 OK
-```json
-{
-  "message": "step endpoint placeholder",
-  "action_received": {
-    "action_type": "classify_severity",
-    "value": "P1",
-    "confidence": 0.95,
-    "reasoning": "High error rate detected"
-  }
-}
-```
-
----
-
-## Test 4: Valid Step Action (Root Cause)
-```bash
-curl -X POST http://localhost:7860/step \
-  -H "Content-Type: application/json" \
-  -d '{
-    "action_type": "identify_root_cause",
-    "value": "user-db",
-    "confidence": 0.8
-  }'
-```
-
-**Expected Response:** 200 OK with action received
-
----
-
-## Test 5: Valid Step Action (Remediate)
-```bash
-curl -X POST http://localhost:7860/step \
-  -H "Content-Type: application/json" \
-  -d '{
-    "action_type": "remediate",
-    "value": "restart:payment-service",
-    "confidence": 0.9
-  }'
-```
-
-**Expected Response:** 200 OK with action received
-
----
-
-## Test 6: Valid Step Action (Escalate)
-```bash
-curl -X POST http://localhost:7860/step \
-  -H "Content-Type: application/json" \
-  -d '{
-    "action_type": "escalate",
-    "value": "dba-team",
-    "confidence": 0.85
-  }'
-```
-
-**Expected Response:** 200 OK with action received
-
----
-
-## Test 7: Valid Step Action (Resolve)
-```bash
-curl -X POST http://localhost:7860/step \
-  -H "Content-Type: application/json" \
-  -d '{
-    "action_type": "resolve",
-    "value": "resolved"
-  }'
-```
-
-**Expected Response:** 200 OK with action received
-
----
-
-## Test 8: Valid Step Action (Ignore Noise)
-```bash
-curl -X POST http://localhost:7860/step \
-  -H "Content-Type: application/json" \
-  -d '{
-    "action_type": "ignore",
-    "value": "noise"
-  }'
-```
-
-**Expected Response:** 200 OK with action received
-
----
-
-## Test 9: Valid Step Action (Request More Logs)
-```bash
-curl -X POST http://localhost:7860/step \
-  -H "Content-Type: application/json" \
-  -d '{
-    "action_type": "request_more_logs",
-    "value": "all",
-    "confidence": 0.5
-  }'
-```
-
-**Expected Response:** 200 OK with action received
-
----
-
-## Test 10: INVALID Action - Wrong Severity
-```bash
-curl -X POST http://localhost:7860/step \
-  -H "Content-Type: application/json" \
-  -d '{
-    "action_type": "classify_severity",
-    "value": "P5"
-  }'
-```
-
-**Expected Response:** 422 Unprocessable Entity
-```json
-{
-  "error": "classify_severity value must be one of {'P1', 'P2', 'P3'}"
-}
-```
-
----
-
-## Test 11: INVALID Action - Unknown Service
-```bash
-curl -X POST http://localhost:7860/step \
-  -H "Content-Type: application/json" \
-  -d '{
-    "action_type": "identify_root_cause",
-    "value": "unknown-service"
-  }'
-```
-
-**Expected Response:** 422 Unprocessable Entity
-```json
-{
-  "error": "identify_root_cause value must be one of {...}"
-}
-```
-
----
-
-## Test 12: INVALID Action - Bad Remediate Format
-```bash
-curl -X POST http://localhost:7860/step \
-  -H "Content-Type: application/json" \
-  -d '{
-    "action_type": "remediate",
-    "value": "invalid:payment-service"
-  }'
-```
-
-**Expected Response:** 422 Unprocessable Entity
-```json
-{
-  "error": "remediate prefix must be one of {...}"
-}
-```
-
----
-
-## Test 13: INVALID Action - Bad Escalate Team
-```bash
-curl -X POST http://localhost:7860/step \
-  -H "Content-Type: application/json" \
-  -d '{
-    "action_type": "escalate",
-    "value": "marketing-team"
-  }'
-```
-
-**Expected Response:** 422 Unprocessable Entity
-```json
-{
-  "error": "escalate value must be one of {...}"
-}
-```
-
----
-
-## Test 14: Reset Endpoint
-```bash
-curl -X POST http://localhost:7860/reset \
-  -H "Content-Type: application/json" \
-  -d '{
-    "task": "single_crash"
-  }'
-```
-
-**Expected Response:** 200 OK
-```json
-{
-  "message": "reset endpoint placeholder",
-  "task": "single_crash"
-}
-```
-
----
-
-## Test 15: State Endpoint
-```bash
-curl http://localhost:7860/state
-```
-
-**Expected Response:** 200 OK
-```json
-{
-  "message": "state endpoint placeholder"
-}
-```
-
----
-
-## Test 16: Grader Endpoint
-```bash
-curl -X POST http://localhost:7860/grader
-```
-
-**Expected Response:** 200 OK
-```json
-{
-  "message": "grader endpoint placeholder",
-  "score": 0.0
-}
-```
-
----
-
-## Test 17: Baseline Endpoint
-```bash
-curl -X POST http://localhost:7860/baseline
-```
-
-**Expected Response:** 200 OK
-```json
-{
-  "message": "baseline endpoint placeholder"
-}
-```
-
----
-
-## Summary
-
-**Tests 1-9, 14-17:** Should all return 200 OK ✅  
-**Tests 10-13:** Should all return 422 with error message ✅
-
-If all pass, your Day 1 is complete! Push to GitHub:
-
-```bash
-git add .
-git commit -m "Day 1 complete: models, endpoints, Docker, tests, README"
-git push origin main
-```

VISUAL_SUMMARY.md

@@ -1,419 +0,0 @@
-# 🎯 LogTriageEnv — Day 1 Summary (Visual)
-
-## What You're Building
-
-```
-┌─────────────────────────────────────────────────────────────────┐
-│                     LogTriageEnv                                │
-│         SRE Incident Triage Simulation Environment              │
-│                                                                  │
-│  Agent: On-call SRE receiving live system logs                 │
-│  Goal: Diagnose, classify severity, find root cause, remediate │
-│  Setting: 7-service microservice cluster with failures         │
-│                                                                  │
-│  [Agent] → reads logs → takes action → gets observation+reward│
-└─────────────────────────────────────────────────────────────────┘
-```
-
----
-
-## Architecture
-
-```
-┌─────────────────────────────────────────────────────────────────┐
-│                        FastAPI Server                            │
-│                    (server/app.py)                               │
-├─────────────────────────────────────────────────────────────────┤
-│                                                                  │
-│  ┌─────────────────────────────────────────────────────────┐   │
-│  │ GET /health              → {"status": "ok"} ✅          │   │
-│  │ GET /tasks               → all 3 task definitions ✅    │   │
-│  │ POST /reset              → initial observation ⏳       │   │
-│  │ POST /step               → validate & step forward ✅   │   │
-│  │ GET /state               → episode state ⏳             │   │
-│  │ POST /grader             → task score ⏳                │   │
-│  │ POST /baseline           → run gpt-4o-mini ⏳           │   │
-│  └─────────────────────────────────────────────────────────┘   │
-│                                                                  │
-├─────────────────────────────────────────────────────────────────┤
-│                    LogTriageEnvironment                          │
-│                   (server/environment.py)                        │
-│                          ⏳ Day 2                               │
-├─────────────────────────────────────────────────────────────────┤
-│                                                                  │
-│  Scenarios:          Graders:          Log Generator:           │
-│  • single_crash ✅   • crash_grader    • log_generator.py       │
-│  • cascading ⏳      • cascade_grader  ⏳ Day 2                 │
-│  • silent_degrade ⏳ • noise_grader                             │
-│  ⏳ Day 2-3          ⏳ Day 4                                    │
-└─────────────────────────────────────────────────────────────────┘
-```
-
----
-
-## Data Flow
-
-```
-┌──────────────┐
-│  Episode     │
-│  Start       │
-└──────┬───────┘
-       │ reset(task_id)
-       ↓
-┌─────────────────────────────────────────┐
-│ Initial Observation                      │
-│ {                                        │
-│   logs: [LogLine, ...],                 │
-│   system_state: {service: Status, ...}, │
-│   incident_id, task_id, step_count,     │
-│   reward: 0.0, done: false               │
-│ }                                        │
-└──────┬───────────────────────────────────┘
-       │
-       ↓
-┌──────────────────────────────────┐
-│  Agent Decision                   │
-│  (LLM reads observation)         │
-└───���──┬───────────────────────────┘
-       │ step(action)
-       ↓
-┌──────────────────────────────────────────────┐
-│ Action: TriageAction                         │
-│ {                                            │
-│   action_type: "classify_severity",          │
-│   value: "P1",                               │
-│   confidence: 0.95,                          │
-│   reasoning: "High error rate detected"      │
-│ }                                            │
-│                                              │
-│ ✅ Validated by is_valid() method            │
-│ 🚫 If invalid → 422 error                    │
-└──────┬───────────────────────────────────────┘
-       │
-       ↓
-┌──────────────────────────────────────────────┐
-│ Next Observation + Reward                    │
-│ {                                            │
-│   logs: [new batch],                         │
-│   system_state: [updated],                   │
-│   reward: 0.30,                              │
-│   cumulative_score: 0.30,                    │
-│   last_action_feedback: "Good decision",     │
-│   done: false                                │
-│ }                                            │
-└──────┬───────────────────────────────────────┘
-       │
-       ├─→ If done=true → Episode ends
-       │
-       └─→ If done=false → Back to Agent Decision
-```
-
----
-
-## Three Tasks
-
-### Task 1: Single Service Crash
-```
-Scenario:
-  payment-service crashes → returns HTTP 500
-  Logs show: NullPointerException stack trace
-  All other services healthy
-
-Agent must:
-  ✅ Classify as P1
-  ✅ Identify payment-service as root cause
-  ✅ Remediate with restart:payment-service
-  ✅ Resolve
-
-Difficulty: EASY (clear logs, no tracing needed)
-Max Steps: 8
-Expected Score: 0.75–0.85 (frontier LLM should handle)
-```
-
-### Task 2: Cascading Failure
-```
-Scenario:
-  user-db slow query (2847ms) 
-  → auth-service connection pool exhausts
-  → api-gateway starts returning timeouts
-  Surface symptoms: api-gateway errors loudest
-  Hidden root cause: database
-
-Agent must:
-  ✅ NOT treat api-gateway as root (it's symptom)
-  ✅ Trace backward to user-db (real root)
-  ✅ Apply correct fix at root (kill-query or restart)
-  ✅ Bonus: avoid fixing symptoms first
-
-Difficulty: MEDIUM (requires multi-hop reasoning)
-Max Steps: 12
-Expected Score: 0.45–0.60 (requires logic)
-```
-
-### Task 3: Silent Degradation
-```
-Scenario:
-  payment-db latency slowly increases: 450ms → 620ms → 890ms → 1200ms
-  No service is down
-  Error rate: 2.1% (below 5% P1 threshold)
-  Logs: 60% noise (routine checks, unrelated warnings)
-  
-Agent must:
-  ✅ Classify as P2 (NOT P1, NOT P3 — nuanced judgment!)
-  ✅ Identify payment-db as root cause
-  ✅ Recommend preventive action (flush-cache or escalate to DBA)
-  ✅ Ignore noise logs (don't escalate spuriously)
-
-Difficulty: HARD (noise filtering, temporal reasoning, nuance)
-Max Steps: 15
-Expected Score: 0.20–0.40 (even strong models struggle)
-```
-
----
-
-## Pydantic Models at a Glance
-
-```python
-LogLine(
-    timestamp: str,              # "2025-03-25T14:32:01Z"
-    level: Literal["DEBUG", "INFO", "WARN", "ERROR", "FATAL"],
-    service: str,                # "api-gateway"
-    request_id: Optional[str],   # "req-9f2a"
-    message: str,                # "upstream timeout from auth-service"
-    latency_ms: Optional[int]    # 30002
-)
-
-ServiceStatus(
-    name: str,                   # "api-gateway"
-    status: Literal["up", "degraded", "down"],
-    error_rate: float,           # 0.342
-    latency_p99_ms: int,         # 2500
-    last_updated: str            # ISO timestamp
-)
-
-TriageAction(                    ⭐ MOST CRITICAL
-    action_type: Literal[
-        "classify_severity",     # value: P1|P2|P3
-        "identify_root_cause",   # value: service-name
-        "escalate",              # value: team-name
-        "remediate",             # value: action:service
-        "request_more_logs",     # value: service|all
-        "resolve",               # value: "resolved"
-        "ignore"                 # value: "noise"
-    ],
-    value: str,
-    confidence: float,           # 0.0–1.0
-    reasoning: str,
-    
-    def is_valid() -> (bool, str)  # ✅ Validates all types!
-)
-
-TriageObservation(
-    logs: list[LogLine],
-    system_state: dict[str, ServiceStatus],
-    incident_id: str,
-    task_id: str,
-    step_count: int,
-    time_elapsed_seconds: int,
-    active_alerts: list[str],
-    reward: float,
-    cumulative_score: float,
-    done: bool,
-    last_action_feedback: str,
-    invalid_action_error: Optional[str]
-)
-
-EpisodeState(
-    episode_id: str,
-    task_id: str,
-    step_count: int,
-    max_steps: int,
-    done: bool,
-    cumulative_score: float,
-    actions_taken: list[str],
-    correct_severity: Optional[str],
-    correct_root_cause: Optional[str],
-    correct_remediation: bool
-)
-```
-
----
-
-## Action Validation Examples
-
-```python
-# ✅ VALID Actions
-
-action = TriageAction(
-    action_type="classify_severity",
-    value="P1"  # ✅ Valid (P1, P2, P3)
-)
-is_valid, err = action.is_valid()  # (True, "")
-
-action = TriageAction(
-    action_type="identify_root_cause",
-    value="user-db"  # ✅ Valid service name
-)
-is_valid, err = action.is_valid()  # (True, "")
-
-action = TriageAction(
-    action_type="remediate",
-    value="restart:payment-service"  # ✅ Valid format: action:service
-)
-is_valid, err = action.is_valid()  # (True, "")
-
-# 🚫 INVALID Actions
-
-action = TriageAction(
-    action_type="classify_severity",
-    value="P5"  # ❌ Invalid (only P1, P2, P3)
-)
-is_valid, err = action.is_valid()
-# (False, "classify_severity value must be one of {'P1', 'P2', 'P3'}")
-
-action = TriageAction(
-    action_type="remediate",
-    value="invalid:payment-service"  # ❌ Invalid prefix
-)
-is_valid, err = action.is_valid()
-# (False, "remediate prefix must be one of {'restart', 'rollback', 'scale', 'flush-cache', 'kill-query'}")
-```
-
----
-
-## File Completion Status
-
-```
-✅ COMPLETE (Day 1)
-├── openenv.yaml           (38 lines) — Spec metadata
-├── requirements.txt       (6 lines)  — Dependencies
-├── Dockerfile             (16 lines) — Container image
-├── README.md              (533 lines)— Documentation
-├── server/models.py       (218 lines)— Pydantic models ⭐
-├── server/app.py          (101 lines)— FastAPI server ⭐
-├── server/__init__.py     (0 lines)  — Package marker
-├── test_day1.py           (147 lines)— Automated tests
-├── test_all.bat           (61 lines) — Windows batch runner
-├── TEST_ENDPOINTS.md      (172 lines)— Curl examples
-├── DAY1_STATUS.md         (336 lines)— Detailed status
-├── COMPLETE_SUMMARY.md    (240 lines)— Quick summary
-├── README_EXPLAINED.md    (268 lines)— README breakdown
-└── Folder structure       ✅ Created
-
-⏳ PLACEHOLDER (Day 2+)
-├── server/environment.py           — LogTriageEnvironment class
-├── server/log_generator.py         — Synthetic log generation
-├── server/scenarios/single_crash.py — Task 1 scenario
-├── server/scenarios/cascading.py   — Task 2 scenario
-├── server/scenarios/silent_degrade.py — Task 3 scenario
-├── server/graders/base_grader.py   — Grader base class
-├── server/graders/crash_grader.py  — Task 1 grader
-├── server/graders/cascade_grader.py — Task 2 grader
-├── server/graders/noise_grader.py  — Task 3 grader
-├── baseline.py                     — LLM baseline agent
-├── scripts/run_grader.py           — Manual grader testing
-└── scripts/validate_checklist.py   — Pre-submission validation
-```
-
----
-
-## Quick Stats
-
-```
-Day 1 Completion:
-├── Lines of core code:    357 lines (models + app)
-├── API endpoints:         7 endpoints (all registered)
-├── Data models:           5 Pydantic classes (fully typed)
-├── Validation logic:      1 method with 7 branches (is_valid)
-├── Tasks defined:         3 tasks (8, 12, 15 step budgets)
-├── Documentation:         1,280+ lines across 5 files
-├── Tests/examples:        200+ lines
-│
-├── What works:
-│   ✅ Model imports
-│   ✅ FastAPI app import
-│   ✅ Action validation (11 test cases)
-│   ✅ Pydantic construction
-│   ✅ Endpoint registration
-│
-├── What needs testing:
-│   🧪 Server startup
-│   🧪 Curl endpoints
-│   🧪 Docker build
-│   🧪 Docker run
-│
-└── Estimated completion: 95% ready for push
-```
-
----
-
-## What to Do Now
-
-```
-┌─────────────────────────────────────────────────────────────────┐
-│ STEP 1: Test Locally                                             │
-│         python test_day1.py                                     │
-│         → Should see 11 validation tests pass                    │
-├─────────────────────────────────────────────────────────────────┤
-│ STEP 2: Start Server                                             │
-│         pip install -r requirements.txt                         │
-│         python -m uvicorn server.app:app --port 7860 --reload   │
-├────────────────────���────────────────────────────────────────────┤
-│ STEP 3: Test Endpoints (new terminal)                            │
-│         curl http://localhost:7860/health                       │
-│         → See {"status": "ok", ...}                              │
-├─────────────────────────────────────────────────────────────────┤
-│ STEP 4: Test Docker                                              │
-│         docker build -t logtriage-env .                         │
-│         docker run -p 7860:7860 logtriage-env                   │
-│         curl http://localhost:7860/health                       │
-├─────────────────────────────────────────────────────────────────┤
-│ STEP 5: Push to GitHub                                           │
-│         git add .                                               │
-│         git commit -m "Day 1: Complete"                         │
-│         git push origin main                                    │
-└─────────────────────────────────────────────────────────────────┘
-```
-
----
-
-## Next: Day 2
-
-```
-Day 2 Todo:
-  1. Create server/environment.py
-     - LogTriageEnvironment class
-     - reset() and step() methods
-     - Episode management
-  
-  2. Create server/log_generator.py
-     - Realistic microservice logs
-     - Error patterns
-     - Noise injection
-  
-  3. Create server/scenarios/single_crash.py
-     - Task 1 scenario generator
-     - payment-service crash
-     - Clear error logs
-  
-  4. Wire app.py endpoints
-     - @app.post("/reset") → environment.reset()
-     - @app.post("/step") → environment.step()
-     - @app.get("/state") → environment.get_state()
-
-Then endpoints become real! 🚀
-```
-
----
-
-## Bottom Line
-
-✅ **You have built the skeleton for a sophisticated RL environment**  
-✅ **All data models are fully typed and validated**  
-✅ **All API endpoints are stubbed and registered**  
-✅ **Documentation is comprehensive**  
-✅ **Code is ready for extension**  
-
-🎯 **Next:** Test locally, push to GitHub, then implement Day 2 logic.
-
-Good luck! 🚀

baseline.py → inference.py

@@ -1,21 +1,21 @@
 """
-Baseline inference script for LogTriageEnv.
-Uses an LLM agent to play all 3 tasks and produce reproducible scores.
+inference.py — Baseline Inference Script for LogTriageEnv
+==========================================================
+MANDATORY environment variables:
+    API_BASE_URL   The API endpoint for the LLM
+                   (default: https://router.huggingface.co/v1)
+    MODEL_NAME     The model identifier to use for inference
+    HF_TOKEN       Your Hugging Face / API key
 
 Usage:
-    # Set API key as environment variable (never hardcode)
-    export GROQ_API_KEY=your_key_here       # Linux/Mac
-    set GROQ_API_KEY=your_key_here          # Windows CMD
-    $env:GROQ_API_KEY="your_key_here"       # Windows PowerShell
-
-    python baseline.py
-
-Environment variables:
-    GROQ_API_KEY      - Groq API key (primary)
-    NVIDIA_API_KEY    - NVIDIA NIM API key (fallback)
-    OPENROUTER_API_KEY - OpenRouter API key (fallback)
-    OPENAI_API_KEY    - OpenAI API key (fallback)
-    ENV_URL           - Base URL of deployed environment (default: http://localhost:7860)
+    # Set environment variables
+    $env:API_BASE_URL="https://api.groq.com/openai/v1"   # or HF router
+    $env:MODEL_NAME="llama-3.3-70b-versatile"             # or any model
+    $env:HF_TOKEN="your-api-key-here"
+
+    python inference.py
+
+Runtime: < 20 minutes on vcpu=2, memory=8gb
 """
 from __future__ import annotations
 import os
@@ -24,38 +24,21 @@ import time
 import requests
 from openai import OpenAI
 
-# ─── PROVIDER CONFIG — change PROVIDER to switch. Nothing else changes. ───────
-
-PROVIDER = "groq"  # options: "groq", "nvidia", "openrouter", "openai"
-
-PROVIDERS = {
-    "groq": {
-        "base_url": "https://api.groq.com/openai/v1",
-        "api_key_env": "GROQ_API_KEY",
-        "model": "llama-3.3-70b-versatile",
-    },
-    "nvidia": {
-        "base_url": "https://integrate.api.nvidia.com/v1",
-        "api_key_env": "NVIDIA_API_KEY",
-        "model": "openai/gpt-oss-20b",
-    },
-    "openrouter": {
-        "base_url": "https://openrouter.ai/api/v1",
-        "api_key_env": "OPENROUTER_API_KEY",
-        "model": "meta-llama/llama-3.1-8b-instruct:free",
-    },
-    "openai": {
-        "base_url": None,
-        "api_key_env": "OPENAI_API_KEY",
-        "model": "gpt-4o-mini",
-    },
-}
+# ─── MANDATORY ENV VARIABLES (as required by hackathon spec) ──────────────────
+
+API_BASE_URL = os.getenv("API_BASE_URL", "https://router.huggingface.co/v1")
+MODEL_NAME = os.getenv("MODEL_NAME", "meta-llama/Llama-3.3-70B-Instruct")
+API_KEY = os.getenv("HF_TOKEN") or os.getenv("GROQ_API_KEY")  # HF_TOKEN is primary
 
 # ─── ENVIRONMENT CONFIG ───────────────────────────────────────────────────────
 
 ENV_URL = os.getenv("ENV_URL", "http://localhost:7860")
 TASKS = ["single_crash", "cascading_failure", "silent_degradation"]
-MAX_STEPS_PER_TASK = {"single_crash": 8, "cascading_failure": 12, "silent_degradation": 15}
+MAX_STEPS_PER_TASK = {
+    "single_crash": 8,
+    "cascading_failure": 12,
+    "silent_degradation": 15,
+}
 SEED = 42  # fixed seed for reproducibility
 
 # ─── SYSTEM PROMPT ─────────────────────────────────────────────────────────────
@@ -83,33 +66,39 @@ Value rules by action_type:
 - resolve: value must be "resolved"
 - ignore: value must be "noise"
 
+Severity classification rules:
+- P1: service DOWN or error rate > 5% — immediate customer impact
+- P2: degraded performance, trending toward P1 — no outage yet
+- P3: warning only, no immediate impact
+
 Strategy:
-1. Read all log lines carefully
-2. Look at system_state for service health (error_rate, latency_p99_ms, status)
-3. Identify which service is the ROOT CAUSE (not just a symptom)
-4. Classify severity based on actual impact:
-   - P1: service down or error rate > 5% (customer impact)
-   - P2: degraded performance, trending toward P1 (no outage yet)
-   - P3: warning, no immediate impact
-5. Apply the correct fix to the ROOT CAUSE service, not symptom services
-6. Once you have classified, identified root cause, and remediated — resolve the incident
+1. Read all log lines carefully — identify ERROR and FATAL lines first
+2. Check system_state for each service (error_rate, latency_p99_ms, status)
+3. Find the ROOT CAUSE service (where the problem STARTED, not where it SPREAD)
+4. Classify severity based on actual current impact
+5. Apply fix to ROOT CAUSE service, not symptom services
+6. After classify + identify + remediate — call resolve
 
 IMPORTANT: Respond with ONLY the JSON object. No explanation, no markdown, no backticks."""
 
 
 def _build_user_prompt(obs: dict) -> str:
-    """Convert observation dict to a prompt string for the LLM."""
+    """Convert observation dict into LLM prompt."""
     lines = []
 
-    # System state summary
+    # System state — only show services with issues
     lines.append("=== SYSTEM STATE ===")
+    shown_any = False
     for svc, status in obs.get("system_state", {}).items():
         if isinstance(status, dict):
             s = status.get("status", "unknown")
             er = status.get("error_rate", 0)
             lat = status.get("latency_p99_ms", 0)
             if s != "up" or er > 0.01 or lat > 200:
-                lines.append(f"  {svc}: {s} | error_rate={er:.1%} | latency_p99={lat}ms")
+                lines.append(f"  {svc}: status={s} | error_rate={er:.1%} | latency_p99={lat}ms")
+                shown_any = True
+    if not shown_any:
+        lines.append("  All services appear healthy")
     lines.append("")
 
     # Active alerts
@@ -117,55 +106,53 @@ def _build_user_prompt(obs: dict) -> str:
     if alerts:
         lines.append("=== ACTIVE ALERTS ===")
         for alert in alerts:
-            lines.append(f"  {alert}")
+            lines.append(f"  ⚠ {alert}")
         lines.append("")
 
-    # Log lines
+    # Log lines — show all of them
     lines.append("=== LOG LINES ===")
     for log in obs.get("logs", []):
         if isinstance(log, dict):
-            ts = log.get("timestamp", "")[-8:]  # just time part
+            ts = log.get("timestamp", "")[-8:]
             level = log.get("level", "INFO")
             svc = log.get("service", "unknown")
             msg = log.get("message", "")
             lines.append(f"  [{ts}] {level:<5} {svc:<25} {msg}")
     lines.append("")
 
-    # Episode context
-    lines.append(f"Step: {obs.get('step_count', 0)} | "
-                 f"Task: {obs.get('task_id', '')} | "
-                 f"Time elapsed: {obs.get('time_elapsed_seconds', 0)}s")
+    # Context
+    step = obs.get("step_count", 0)
+    task = obs.get("task_id", "")
+    elapsed = obs.get("time_elapsed_seconds", 0)
+    lines.append(f"Step: {step} | Task: {task} | Time elapsed: {elapsed}s")
 
     # Feedback from last action
     feedback = obs.get("last_action_feedback", "")
-    if feedback and feedback != "Incident detected. Analyze the logs and take action.":
-        lines.append(f"Last action feedback: {feedback}")
+    if feedback and "Incident detected" not in feedback:
+        lines.append(f"Last feedback: {feedback}")
 
     lines.append("")
-    lines.append("Based on the above, what is your next triage action? Respond with JSON only.")
+    lines.append("Respond with JSON only.")
     return "\n".join(lines)
 
 
 def _parse_action(response_text: str) -> dict | None:
-    """Parse LLM response into action dict. Returns None if parsing fails."""
+    """Parse LLM response into action dict."""
     text = response_text.strip()
 
-    # Strip markdown code blocks if present
+    # Strip markdown code blocks
     if text.startswith("```"):
         lines = text.split("\n")
-        text = "\n".join(lines[1:-1] if lines[-1] == "```" else lines[1:])
+        text = "\n".join(lines[1:-1] if lines[-1].strip() == "```" else lines[1:])
 
     try:
         action = json.loads(text)
-        # Validate required fields
         if "action_type" not in action or "value" not in action:
             return None
-        # Ensure confidence and reasoning exist
         action.setdefault("confidence", 0.8)
         action.setdefault("reasoning", "")
         return action
     except json.JSONDecodeError:
-        # Try to extract JSON from text
         import re
         match = re.search(r'\{[^{}]+\}', text, re.DOTALL)
         if match:
@@ -176,16 +163,12 @@ def _parse_action(response_text: str) -> dict | None:
         return None
 
 
-def _get_fallback_action(obs: dict, step: int) -> dict:
-    """
-    Fallback action when LLM fails to produce valid JSON.
-    Uses simple heuristics to make a reasonable action.
-    """
+def _get_fallback_action(obs: dict, step: int, actions_taken: list) -> dict:
+    """Fallback when LLM fails — use simple heuristics."""
     system_state = obs.get("system_state", {})
-    task_id = obs.get("task_id", "")
 
-    # Find the most degraded service
-    worst_service = None
+    # Find worst service
+    worst_service = "payment-service"
     worst_error_rate = 0
     for svc, status in system_state.items():
         if isinstance(status, dict):
@@ -194,24 +177,27 @@ def _get_fallback_action(obs: dict, step: int) -> dict:
                 worst_error_rate = er
                 worst_service = svc
 
-    if step == 0:
-        return {"action_type": "classify_severity", "value": "P1", "confidence": 0.5, "reasoning": "fallback"}
-    elif step == 1 and worst_service:
-        return {"action_type": "identify_root_cause", "value": worst_service, "confidence": 0.5, "reasoning": "fallback"}
-    elif step == 2 and worst_service:
-        return {"action_type": "remediate", "value": f"restart:{worst_service}", "confidence": 0.5, "reasoning": "fallback"}
+    action_types_taken = [a.get("action_type") for a in actions_taken]
+
+    if "classify_severity" not in action_types_taken:
+        return {"action_type": "classify_severity", "value": "P1",
+                "confidence": 0.5, "reasoning": "fallback"}
+    elif "identify_root_cause" not in action_types_taken:
+        return {"action_type": "identify_root_cause", "value": worst_service,
+                "confidence": 0.5, "reasoning": "fallback"}
+    elif "remediate" not in action_types_taken:
+        return {"action_type": "remediate", "value": f"restart:{worst_service}",
+                "confidence": 0.5, "reasoning": "fallback"}
     else:
-        return {"action_type": "resolve", "value": "resolved", "confidence": 0.5, "reasoning": "fallback"}
+        return {"action_type": "resolve", "value": "resolved",
+                "confidence": 0.5, "reasoning": "fallback"}
 
 
-def run_task(client: OpenAI, model: str, task_id: str, seed: int = 42) -> dict:
-    """
-    Run one complete episode for a given task.
-    Returns dict with score, steps, and breakdown.
-    """
+def run_task(client: OpenAI, task_id: str, seed: int = 42) -> dict:
+    """Run one complete episode for a task. Returns score + breakdown."""
     print(f"\n  Running task: {task_id}...")
 
-    # Reset environment
+    # Reset
     try:
         resp = requests.post(
             f"{ENV_URL}/reset",
@@ -221,47 +207,44 @@ def run_task(client: OpenAI, model: str, task_id: str, seed: int = 42) -> dict:
         resp.raise_for_status()
         obs = resp.json()
     except Exception as e:
-        print(f"  ERROR: Failed to reset environment: {e}")
+        print(f"  ERROR: Reset failed: {e}")
         return {"score": 0.0, "error": str(e), "task_id": task_id}
 
     max_steps = MAX_STEPS_PER_TASK.get(task_id, 10)
     conversation_history = []
-    steps_taken = 0
+    actions_taken = []
     done = obs.get("done", False)
+    steps_taken = 0
 
     while not done and steps_taken < max_steps:
-        # Build prompt from observation
         user_prompt = _build_user_prompt(obs)
-
-        # Add to conversation history (keep last 4 exchanges for context)
         conversation_history.append({"role": "user", "content": user_prompt})
+
+        # Keep conversation history bounded
         if len(conversation_history) > 8:
             conversation_history = conversation_history[-8:]
 
         # Call LLM
         try:
             response = client.chat.completions.create(
-                model=model,
+                model=MODEL_NAME,
                 messages=[
                     {"role": "system", "content": SYSTEM_PROMPT},
                 ] + conversation_history,
                 max_tokens=200,
-                temperature=0,  # deterministic
+                temperature=0,
             )
-            response_text = response.choices[0].message.content
+            response_text = response.choices[0].message.content or ""
             conversation_history.append({"role": "assistant", "content": response_text})
-
-            # Parse action
             action = _parse_action(response_text)
             if action is None:
-                print(f"    Step {steps_taken}: LLM parse failed, using fallback")
-                action = _get_fallback_action(obs, steps_taken)
-
+                print(f"    Step {steps_taken}: parse failed, using fallback")
+                action = _get_fallback_action(obs, steps_taken, actions_taken)
         except Exception as e:
-            print(f"    Step {steps_taken}: LLM call failed ({e}), using fallback")
-            action = _get_fallback_action(obs, steps_taken)
+            print(f"    Step {steps_taken}: LLM error ({e}), using fallback")
+            action = _get_fallback_action(obs, steps_taken, actions_taken)
 
-        # Take action in environment
+        # Step environment
         try:
             step_resp = requests.post(
                 f"{ENV_URL}/step",
@@ -273,18 +256,17 @@ def run_task(client: OpenAI, model: str, task_id: str, seed: int = 42) -> dict:
             done = obs.get("done", False)
             reward = obs.get("reward", 0.0)
             feedback = obs.get("last_action_feedback", "")
-
+            actions_taken.append(action)
             print(f"    Step {steps_taken}: {action['action_type']}({action['value']}) "
-                  f"-> reward={reward:+.2f} | {feedback[:60]}")
-
+                  f"→ reward={reward:+.2f} | {feedback[:50]}")
         except Exception as e:
-            print(f"    Step {steps_taken}: Environment step failed: {e}")
+            print(f"    Step {steps_taken}: environment error: {e}")
             break
 
         steps_taken += 1
-        time.sleep(0.1)  # small delay to avoid rate limits
+        time.sleep(0.2)  # avoid rate limits
 
-    # Get official grader score
+    # Get grader score
     try:
         grader_resp = requests.post(f"{ENV_URL}/grader", timeout=30)
         grader_resp.raise_for_status()
@@ -292,11 +274,11 @@ def run_task(client: OpenAI, model: str, task_id: str, seed: int = 42) -> dict:
         score = grader_result.get("score", 0.0)
         breakdown = grader_result.get("breakdown", {})
     except Exception as e:
-        print(f"  ERROR: Grader call failed: {e}")
+        print(f"  ERROR: Grader failed: {e}")
         score = obs.get("cumulative_score", 0.0)
         breakdown = {}
 
-    print(f"  Final score: {score:.4f} ({steps_taken} steps)")
+    print(f"  Score: {score:.4f} ({steps_taken} steps)")
     return {
         "task_id": task_id,
         "score": score,
@@ -306,88 +288,83 @@ def run_task(client: OpenAI, model: str, task_id: str, seed: int = 42) -> dict:
 
 
 def main():
-    """Run baseline agent against all 3 tasks and report scores."""
+    """Run baseline agent on all 3 tasks and report scores."""
 
-    # ── Setup provider ─────────────────────────────────────────────────────────
-    provider_config = PROVIDERS[PROVIDER]
-    api_key = os.environ.get(provider_config["api_key_env"])
-    model = provider_config["model"]
-    base_url = provider_config["base_url"]
-
-    if not api_key:
+    # Validate env vars
+    if not API_KEY:
         raise ValueError(
-            f"API key not found. Set environment variable: {provider_config['api_key_env']}\n"
-            f"  Windows PowerShell: $env:{provider_config['api_key_env']}='your_key'\n"
-            f"  Windows CMD:        set {provider_config['api_key_env']}=your_key"
+            "API key not found. Set HF_TOKEN environment variable:\n"
+            "  PowerShell: $env:HF_TOKEN='your-key'\n"
+            "  CMD:        set HF_TOKEN=your-key"
         )
 
-    # Build OpenAI-compatible client
-    client_kwargs = {"api_key": api_key}
-    if base_url:
-        client_kwargs["base_url"] = base_url
-    client = OpenAI(**client_kwargs)
+    # Build client
+    client = OpenAI(base_url=API_BASE_URL, api_key=API_KEY)
 
     print("=" * 60)
     print("LogTriageEnv — Baseline Inference Script")
     print("=" * 60)
-    print(f"Provider:    {PROVIDER}")
-    print(f"Model:       {model}")
-    print(f"Environment: {ENV_URL}")
-    print(f"Seed:        {SEED}")
-    print(f"Tasks:       {', '.join(TASKS)}")
+    print(f"API_BASE_URL: {API_BASE_URL}")
+    print(f"MODEL_NAME:   {MODEL_NAME}")
+    print(f"ENV_URL:      {ENV_URL}")
+    print(f"Seed:         {SEED}")
     print("=" * 60)
 
-    # ── Verify environment is running ──────────────────────────────────────────
+    # Verify environment
     try:
         health = requests.get(f"{ENV_URL}/health", timeout=10)
         health.raise_for_status()
-        print(f"Environment health: OK")
+        print("Environment: OK")
     except Exception as e:
         raise RuntimeError(
             f"Environment not responding at {ENV_URL}\n"
-            f"Start it with: python -m uvicorn server.app:app --port 7860\n"
+            f"Start with: python -m uvicorn server.app:app --port 7860\n"
             f"Error: {e}"
         )
 
-    # ── Run all tasks ──────────────────────────────────────────────────────────
+    # Run all tasks
     results = []
+    start_time = time.time()
+
     for task_id in TASKS:
-        result = run_task(client, model, task_id, seed=SEED)
+        result = run_task(client, task_id, seed=SEED)
         results.append(result)
 
-    # ── Print final report ─────────────────────────────────────────────────────
+    elapsed = time.time() - start_time
+
+    # Print report
     print("\n" + "=" * 60)
     print("BASELINE RESULTS")
     print("=" * 60)
 
-    total_score = 0.0
+    total = 0.0
     for result in results:
         task = result["task_id"]
         score = result["score"]
         steps = result["steps_taken"]
-        total_score += score
-        bar = "#" * int(score * 20) + "-" * (20 - int(score * 20))
+        total += score
+        bar = "█" * int(score * 20) + "░" * (20 - int(score * 20))
         print(f"{task:<25} {score:.4f}  [{bar}]  ({steps} steps)")
-        if result.get("breakdown"):
-            for k, v in result["breakdown"].items():
-                print(f"  {k:<20} {v}")
+        for k, v in result.get("breakdown", {}).items():
+            print(f"  {k:<20} {v}")
 
-    avg_score = total_score / len(TASKS)
+    avg = total / len(TASKS)
     print("-" * 60)
-    print(f"{'AVERAGE':<25} {avg_score:.4f}")
+    print(f"{'AVERAGE':<25} {avg:.4f}")
+    print(f"{'RUNTIME':<25} {elapsed:.1f}s")
     print("=" * 60)
 
-    # ── Machine-readable output ────────────────────────────────────────────────
+    # JSON output
     output = {
-        "provider": PROVIDER,
-        "model": model,
+        "api_base_url": API_BASE_URL,
+        "model_name": MODEL_NAME,
         "seed": SEED,
         "results": results,
-        "average_score": round(avg_score, 4),
+        "average_score": round(avg, 4),
+        "runtime_seconds": round(elapsed, 1),
     }
-    print("\nJSON Output (for /baseline endpoint):")
+    print("\nJSON Output:")
     print(json.dumps(output, indent=2))
-
     return output
 
 

pyproject.toml

@@ -0,0 +1,24 @@
+[project]
+name = "logtriage-env"
+version = "1.0.0"
+description = "An OpenEnv environment where an AI agent acts as an on-call SRE diagnosing incidents from log data"
+requires-python = ">=3.10"
+dependencies = [
+    "fastapi>=0.110.0",
+    "uvicorn>=0.27.0",
+    "pydantic>=2.5.0",
+    "python-dotenv>=1.0.0",
+    "groq>=0.5.0",
+    "openenv-core>=0.2.0",
+]
+
+[build-system]
+requires = ["setuptools>=61.0"]
+build-backend = "setuptools.build_meta"
+
+[tool.setuptools]
+package-dir = {"" = "."}
+packages = ["server", "server.graders", "server.scenarios"]
+
+[project.scripts]
+server = "server.app:main"

server/app.py

@@ -118,34 +118,26 @@ def baseline():
     """
     Run the baseline inference script against all 3 tasks.
     Returns scores for each task produced by the LLM agent.
-    Note: Requires GROQ_API_KEY (or other provider key) to be set.
+    Note: Requires HF_TOKEN (or GROQ_API_KEY) to be set.
     """
     import subprocess
     import sys
     import json as json_lib
 
     try:
-        # Pass through all current env vars, plus GROQ_API_KEY if set
-        env = os.environ.copy()
-        groq_key = os.environ.get("GROQ_API_KEY", "")
-        if not groq_key:
-            # Try to read from process that started the server
-            pass
-
         result = subprocess.run(
-            [sys.executable, "baseline.py"],
+            [sys.executable, "inference.py"],
             capture_output=True,
             text=True,
-            timeout=300,  # 5 minute timeout
+            timeout=1200,  # 20 minute timeout (matches spec)
             cwd=os.path.dirname(os.path.dirname(os.path.abspath(__file__))),
-            env=env,
         )
 
         if result.returncode != 0:
             return JSONResponse(
                 status_code=500,
                 content={
-                    "error": "Baseline script failed",
+                    "error": "Inference script failed",
                     "stderr": result.stderr[-500:] if result.stderr else "",
                 }
             )
@@ -154,7 +146,7 @@ def baseline():
         output_lines = result.stdout.strip().split("\n")
         json_start = None
         for i, line in enumerate(output_lines):
-            if line.strip() == "JSON Output (for /baseline endpoint):":
+            if line.strip() == "JSON Output:":
                 json_start = i + 1
                 break
 
@@ -165,10 +157,14 @@ def baseline():
             return {"message": "Baseline completed", "output": result.stdout[-1000:]}
 
     except subprocess.TimeoutExpired:
-        return JSONResponse(status_code=504, content={"error": "Baseline timed out after 5 minutes"})
+        return JSONResponse(status_code=504, content={"error": "Inference timed out (20min limit)"})
     except Exception as e:
         return JSONResponse(status_code=500, content={"error": str(e)})
 
 
+def main():
+    uvicorn.run("server.app:app", host="0.0.0.0", port=7860, reload=False)
+
+
 if __name__ == "__main__":
-    uvicorn.run("server.app:app", host="0.0.0.0", port=7860, reload=True)
+    main()

test_all.bat

@@ -1,71 +0,0 @@
-@echo off
-REM =========================================================================
-REM Day 1 Test & Verification Script for LogTriageEnv
-REM =========================================================================
-REM This script runs all Day 1 tests and verifies the project is ready
-
-echo =========================================================================
-echo LogTriageEnv — Day 1 Verification Script
-echo =========================================================================
-
-REM Test 1: Python Tests
-echo.
-echo [TEST 1] Running Python validation tests...
-python test_day1.py
-if %ERRORLEVEL% NEQ 0 (
-    echo ❌ Python tests failed!
-    exit /b 1
-)
-
-REM Test 2: Install dependencies
-echo.
-echo [TEST 2] Installing dependencies from requirements.txt...
-pip install -q -r requirements.txt
-if %ERRORLEVEL% NEQ 0 (
-    echo ❌ Pip install failed!
-    exit /b 1
-)
-echo ✅ Dependencies installed
-
-REM Test 3: Check FastAPI can import
-echo.
-echo [TEST 3] Checking FastAPI imports...
-python -c "from fastapi import FastAPI; from uvicorn import run; print('✅ FastAPI and Uvicorn OK')"
-if %ERRORLEVEL% NEQ 0 (
-    echo ❌ FastAPI/Uvicorn import failed!
-    exit /b 1
-)
-
-REM Test 4: Check Pydantic models
-echo.
-echo [TEST 4] Testing Pydantic models...
-python -c "from server.models import TriageAction, TriageObservation; print('✅ Models imported')"
-if %ERRORLEVEL% NEQ 0 (
-    echo ❌ Models import failed!
-    exit /b 1
-)
-
-echo.
-echo =========================================================================
-echo ✅ ALL TESTS PASSED!
-echo =========================================================================
-echo.
-echo Next steps:
-echo.
-echo 1. START THE SERVER:
-echo    python -m uvicorn server.app:app --host 0.0.0.0 --port 7860 --reload
-echo.
-echo 2. TEST ENDPOINTS (open another terminal):
-echo    curl http://localhost:7860/health
-echo    curl http://localhost:7860/tasks
-echo.
-echo 3. TEST DOCKER BUILD:
-echo    docker build -t logtriage-env .
-echo    docker run -p 7860:7860 logtriage-env
-echo.
-echo 4. PUSH TO GITHUB:
-echo    git add .
-echo    git commit -m "Day 1: scaffold, models.py, app skeleton, Dockerfile"
-echo    git push origin main
-echo.
-pause

test_day1.py

@@ -1,130 +0,0 @@
-#!/usr/bin/env python
-"""
-Day 1 Test Script — Verify all endpoints and models work
-"""
-import sys
-import json
-from pathlib import Path
-
-# Add server to path
-sys.path.insert(0, str(Path(__file__).parent))
-
-print("=" * 70)
-print("DAY 1 TEST SUITE — LogTriageEnv")
-print("=" * 70)
-
-# Test 1: Import models
-print("\n[TEST 1] Importing models...")
-try:
-    from server.models import TriageAction, TriageObservation, EpisodeState, LogLine, ServiceStatus
-    print("✅ All models imported successfully")
-except Exception as e:
-    print(f"❌ Import failed: {e}")
-    sys.exit(1)
-
-# Test 2: Import FastAPI app
-print("\n[TEST 2] Importing FastAPI app...")
-try:
-    from server.app import app
-    print("✅ FastAPI app imported successfully")
-except Exception as e:
-    print(f"❌ App import failed: {e}")
-    sys.exit(1)
-
-# Test 3: Test TriageAction validation
-print("\n[TEST 3] Testing TriageAction.is_valid()...")
-test_cases = [
-    ({"action_type": "classify_severity", "value": "P1"}, True, "Valid P1"),
-    ({"action_type": "classify_severity", "value": "P5"}, False, "Invalid P5"),
-    ({"action_type": "identify_root_cause", "value": "user-db"}, True, "Valid root cause"),
-    ({"action_type": "identify_root_cause", "value": "invalid-service"}, False, "Invalid service"),
-    ({"action_type": "remediate", "value": "restart:payment-service"}, True, "Valid remediate"),
-    ({"action_type": "remediate", "value": "invalid:payment-service"}, False, "Invalid remediate action"),
-    ({"action_type": "escalate", "value": "sre-team"}, True, "Valid escalate"),
-    ({"action_type": "escalate", "value": "invalid-team"}, False, "Invalid team"),
-    ({"action_type": "resolve", "value": "resolved"}, True, "Valid resolve"),
-    ({"action_type": "resolve", "value": "not-resolved"}, False, "Invalid resolve"),
-    ({"action_type": "ignore", "value": "noise"}, True, "Valid ignore"),
-]
-
-passed = 0
-failed = 0
-
-for test_data, expected_valid, description in test_cases:
-    try:
-        action = TriageAction(**test_data)
-        is_valid, error = action.is_valid()
-        
-        if is_valid == expected_valid:
-            print(f"  ✅ {description}: {test_data}")
-            passed += 1
-        else:
-            print(f"  ❌ {description}: expected {expected_valid}, got {is_valid}")
-            failed += 1
-    except Exception as e:
-        print(f"  ❌ {description}: Exception: {e}")
-        failed += 1
-
-print(f"\nValidation tests: {passed} passed, {failed} failed")
-
-# Test 4: Test Pydantic model construction
-print("\n[TEST 4] Testing Pydantic model construction...")
-try:
-    log = LogLine(
-        timestamp="2025-03-25T14:32:01Z",
-        level="ERROR",
-        service="api-gateway",
-        request_id="req-123",
-        message="Service timeout",
-        latency_ms=5000
-    )
-    print(f"✅ LogLine created: {log.service}")
-    
-    service_status = ServiceStatus(
-        name="api-gateway",
-        status="degraded",
-        error_rate=0.34,
-        latency_p99_ms=2500,
-        last_updated="2025-03-25T14:32:01Z"
-    )
-    print(f"✅ ServiceStatus created: {service_status.name}")
-    
-    observation = TriageObservation(
-        logs=[log],
-        system_state={"api-gateway": service_status},
-        incident_id="inc-001",
-        task_id="single_crash",
-        step_count=0,
-        time_elapsed_seconds=0
-    )
-    print(f"✅ TriageObservation created: {observation.incident_id}")
-except Exception as e:
-    print(f"❌ Model construction failed: {e}")
-    sys.exit(1)
-
-# Test 5: FastAPI endpoint structure
-print("\n[TEST 5] Checking FastAPI endpoints...")
-endpoints = ["/health", "/reset", "/step", "/state", "/tasks", "/grader", "/baseline"]
-from fastapi.routing import APIRoute
-
-app_endpoints = [route.path for route in app.routes if isinstance(route, APIRoute)]
-print(f"Registered endpoints: {app_endpoints}")
-
-for endpoint in endpoints:
-    if endpoint in app_endpoints:
-        print(f"  ✅ {endpoint} exists")
-    else:
-        print(f"  ❌ {endpoint} missing")
-
-print("\n" + "=" * 70)
-print("✅ ALL TESTS PASSED — Day 1 Ready for Verification")
-print("=" * 70)
-print("\nNext steps:")
-print("1. Start server: python -m uvicorn server.app:app --host 0.0.0.0 --port 7860")
-print("2. Test endpoints with curl (see below)")
-print("3. Build Docker: docker build -t logtriage-env .")
-print("4. Verify Docker works: docker run -p 7860:7860 logtriage-env")
-print("\nExample curl tests:")
-print("  curl http://localhost:7860/health")
-print("  curl http://localhost:7860/tasks")
-print("  curl -X POST http://localhost:7860/reset -H 'Content-Type: application/json'")