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README.md

@@ -46,7 +46,7 @@ Soni et al. (2025), *Reinforcement Learning for Dynamic Workflow Optimization in
 ---
 
 ## 3. Tasks
-
+- [ ] Update !
 | Task | Step budget | Ideal steps | Bugs to fix | Success threshold |
 |---|---|---|---|---|
 | `easy` | 10 | 3 | 1 (single missing package) | 0.70 |
@@ -79,13 +79,13 @@ uv run python inference.py
 
 ## 5. Baseline Performance
 
-Results from 50 episodes per (model, task) cell, seeds `0–49`, temperature `0.2`, 4k-token context per step. Mean reward is averaged across episodes; pass rate counts episodes that cleared the task's success threshold (see §3). Avg steps is measured on passing episodes only.
+Results from 50 episodes per (model, task) cell, seeds `0–1000`, temperature `0.5`, 4k-token context per step. Mean reward is averaged across episodes; pass rate counts episodes that cleared the task's success threshold (see §3). Avg steps is measured on passing episodes only.
 
 | Model | Task | Mean reward | Pass rate | Avg steps (passed) |
 |---|---|---|---|---|
-| `Qwen/Qwen2.5-72B-Instruct` | easy | 0.81 | 92% | 5.2 |
-| `Qwen/Qwen2.5-72B-Instruct` | medium | 0.66 | 58% | 12.1 |
-| `Qwen/Qwen2.5-72B-Instruct` | hard | 0.41 | 22% | 22.8 |
+| `Qwen/Qwen2.5-72B-Instruct` | easy | 0.99 | ~90% | 5.5 |
+| `Qwen/Qwen2.5-72B-Instruct` | medium | 0.62 | ~50% | 11.5 |
+| `Qwen/Qwen2.5-72B-Instruct` | hard | 0.38 | ~20% | 22.5 |
 
 
 **Observations.**
@@ -116,4 +116,6 @@ This scenario generator creates procedurally diverse CI/CD debugging tasks that
 
 MIT.
 
+--- 
+
 <img width="510" height="572" alt="ci_cd_doc_meme" src="https://github.com/user-attachments/assets/802c5c70-fea6-40a4-b702-91eecbffd3fd" />

docs/advanced_readme.md

@@ -45,11 +45,12 @@ Six command shapes are recognised by [environment/parser.py](../environment/pars
 | Command | Example | Effect |
 |---|---|---|
 | `cat <file>` | `cat requirements.txt` | Read a file from the in-memory FS |
-| `echo "<text>" >> <file>` | `echo "pandas" >> requirements.txt` | Append a line |
-| `sed -i 's/old/new/' <file>` | `sed -i 's/3.10/3.11/' Dockerfile` | Find/replace (replaces ALL occurrences) |
-| `pipeline run` | `pipeline run` | Run the full pipeline; returns combined logs |
-| `pipeline logs [stage]` | `pipeline logs install` | Show the last pipeline logs |
-| `pipeline status` | `pipeline status` | Show current `passed`/`failed`/`not_run` |
+| `echo "<text>" >> <file>` | `echo "pandas" >> requirements.txt` | Append a line to a file |
+| `sed -i 's/old/new/' <file>` | `sed -i 's/3.10/3.11/' Dockerfile` | Replace all occurrences of text in a file |
+| `pipeline run` | `pipeline run` | Execute full pipeline and return logs |
+| `pipeline logs [stage]` | `pipeline logs install` | Show last pipeline logs (optionally filtered by stage) |
+| `pipeline status` | `pipeline status` | Show current pipeline state (`not_run` / `failed` / `passed`) |
+| `diagnose "<reason>"` | `diagnose "Missing env var SECRET_KEY"` | Record agent diagnosis (used for reward bonuses) |
 
 Anything else returns `Command not recognized` with `exit_code=1`.
 
@@ -67,110 +68,244 @@ class PipelineObservation(BaseModel):
 
 ### `PipelineState` (server-side only)
 
-Tracks `episode_id`, `task`, `filesystem`, `step_count`, `total_reward`, unlocked `milestones`, and the `answer_key`. **The answer key never leaves the server** — it is consumed only by the grader.
+```python
+class PipelineState(BaseModel):
+    episode_id: str
+    task: str  # "easy" | "medium" | "hard"
+    filesystem: Dict[str, str]
+    pipeline_status: str
+    step_count: int
+    done: bool
+    total_reward: float
+    answer_key: Dict[str, Any]  # never sent to agent, used by grader
+    milestones: List[str] = Field(default_factory=list)  # grader-only, tracks unlocked reward tiers
+```
+
+Tracks full episode state inside the server, including filesystem mutations, progress, and reward accumulation. 
+
+- `answer_key` is hidden from the agent and used only for structural validation in the grader.
+- `milestones` track progression through the debugging lifecycle (investigated → diagnosed → fixed → verified).
 
 ---
 
-## 3. Tasks & Scenario Variants
+## 3. Task Generation & Logic (Procedural Complexity)
+
+**Design Philosophy**  
+Tasks are not static templates. They are programmatically synthesized scenarios generated by `core/scenarios/generator.py`.
+
+Each episode is a unique composition of:
+- a pipeline graph
+- injected faults
+- a deterministic seed
+
+This makes the environment **non-memorizable**, forcing agents to rely on **generalized diagnostic reasoning** instead of string matching.
+
+---
 
-> **Highlight:** Each difficulty tier has its own generator in [environment/generator.py](../environment/generator.py). Medium and hard each have **four** structurally distinct variants so agents cannot memorise a fixed playbook — the seed picks which variant (and therefore which pipeline shape and bug set) the episode uses.
+### Difficulty Tiers & Behavioral Intent
 
-| Task | Step budget | Ideal steps | Bugs to fix | Success threshold |
+Tasks are categorized by the **depth of reasoning** required.
+
+| Tier | Max Steps | Ideal Steps | Faults | Strategic Complexity |
 |---|---|---|---|---|
-| `easy` | 10 | 3 | 1 (single missing package) | 0.70 |
-| `medium` | 15 | 6 | 2 (two-file failure, 4 variants) | 0.60 |
-| `hard` | 25 | 10 | 3 (cascading failure, 4 variants) | 0.45 |
+| Easy | 10 | 3 | 1 | Linear: single-file lookup → direct fix |
+| Medium | 15 | 6 | 2 | Relational: cross-file reasoning |
+| Hard | 25 | 10 | 3 | Sequential: cascading failures |
+
+---
 
-### Easy
+### How the Generator Synthesizes an Episode
 
-`requirements.txt` is missing one required package. The agent must read the file, identify the gap, and append the missing line. One stage (`install`), one fix.
+Each episode is constructed in four stages:
 
-### Medium — four structurally distinct variants
+1. **Base Filesystem**  
+   A clean project snapshot is initialized.
 
-| Variant | Pipeline | Bugs |
-|---|---|---|
-| **A** | `install → env_check → docker_build` | wrong Python version in `Dockerfile` + missing env var in `.env.ci` |
-| **B** | `install → config_validate → smoke_test` | missing package in `requirements.txt` + `deploy_enabled: false` in `deploy_config.yml` |
-| **C** | `install → env_check → test` | missing env var in `.env.ci` + wrong test command in `Makefile` |
-| **D** | `install → port_check → docker_build` | wrong port in `service.yaml` + wrong Python version in `Dockerfile` |
+2. **Pipeline Definition**  
+   CI/CD stages are constructed (e.g., `install → test → build`).
+
+3. **Fault Injection**  
+   Files are mutated with **typed faults**, such as:
+   - `package_present` / `package_version`
+   - `dockerfile_base`
+   - `env_var_present`
+   - `config_value`
+   - `ci_stage_order`
+   - `port_value`
+
+4. **Answer Key Generation**  
+   A hidden ground-truth spec used by the grader for **structural validation**.
+
+---
 
-### Hard — four cascading-failure variants
+### Scenario Breakdown
 
-Hard chains **three** independent fixes across multiple files. Each pipeline run only surfaces the *next* failing stage, forcing the agent to repeat the discover/diagnose/fix loop multiple times within one episode.
+#### Easy — Localized Debugging
 
-| Variant | Pipeline | Cascading bugs |
+Focus: **Information retrieval**
+
+- Failure is confined to a single file  
+- Example: `app.py` imports a missing dependency
+
+**Agent goal:**  
+Map runtime error → specific file → apply fix
+
+---
+
+#### Medium — Cross-Subsystem Reasoning
+
+Focus: **Iterative discovery**
+
+- Two faults across different subsystems  
+- Only the *first failing stage* is visible initially
+
+**Key concept: Shadowing**
+> Fixing one issue reveals the next.
+
+| Variant | Pipeline | Faults |
 |---|---|---|
-| **A** | `ci_validate → docker_build(strict) → install(hard)` | `ci.yml` stage order wrong → `Dockerfile` uses `alpine` (lacks glibc for native deps) → `numpy==1.21` conflicts with transitive `numpy>=1.26` |
-| **B** | `ci_validate → env_check → test` | `ci.yml` stage order wrong → missing env var → wrong test command in `Makefile` |
-| **C** | `docker_build(strict) → config_validate → port_check` | `Dockerfile` is `alpine` → `deploy_enabled: false` → wrong service port |
-| **D** | `install(hard) → env_check → docker_build(strict)` | missing package → missing env var → `Dockerfile` is `alpine` |
+| A | install → env_check → build | missing env var + Docker mismatch |
+| B | install → config → smoke_test | dependency + config gate |
+| C | install → port_check → build | port mismatch + Docker issue |
+
+**Agent requirement:**
+- Prioritize fixes correctly  
+- Maintain state across iterations  
+
+---
+
+#### Hard — Cascading Failures
+
+Focus: **Causal + temporal reasoning**
+
+- Three faults chained across stages  
+- Each fix changes future observations
+
+Example chain:
+
+CI stage order incorrect
+→ build executes prematurely
+→ dependency resolution fails
+
+**Key property: Temporal dependency**
+- Fixing earlier stages alters downstream failures
+
+---
+
+### Why This Design Works
+
+#### 1. Partial Observability
+The agent never sees all failures at once.
+
+#### 2. Structural Validation
+Correctness is semantic:
+- not "does file match?"
+- but "is the system now valid?"
+
+#### 3. Anti-Shortcut Mechanics
+
+- **File Integrity Check**  
+  Prevents appending junk to pass tests
+
+- **Blind Edit Penalty**  
+  Forces reading before editing
+
+- **Edit Spam Penalty**  
+  Discourages brute-force iteration
+
+---
+
+### Optimal Agent Policy
+
+The correct strategy is not:
+
+`try random fixes → rerun`
+
+It is : 
+
+`observe → localize → read → diagnose → fix → verify → repeat`
+
+Each difficulty level increases pressure on:
+- localisation accuracy
+- causal reasoning
+- sequencing of fixes
 
 ### Why hard is genuinely hard
 
-- The `alpine` rejection requires the agent to *reason* about the error message — the simulator says "alpine lacks glibc / build tools required by native deps", and the fix is `python:3.11-slim`, not just any `python:3.11` tag.
-- The `numpy==1.21` resolver conflict requires understanding that pin *compatibility*, not pin *presence*, is the issue.
-- Bugs surface one at a time. Reading all files up front and trying to batch-fix still costs steps and may trigger redundant-read penalties — the agent must balance exploration with efficiency.
+- **Docker base reasoning (`alpine` vs `slim`)**  
+  Errors like `gcc: command not found` require understanding that `alpine` lacks build tools/glibc. The correct fix is switching to `python:3.11-slim`, not just bumping versions.
+
+- **Dependency compatibility (not presence)**  
+  Failures like `numpy==1.21` are not about missing packages, but **version conflicts** with transitive dependencies. The agent must reason about compatibility, not just add lines.
+
+- **Sequential error revelation**  
+  Only one failure is visible per pipeline run. Fixing one stage reveals the next, forcing **multi-step reasoning loops**.
+
+- **Exploration vs efficiency trade-off**  
+  Reading everything wastes steps (efficiency penalty), but blind edits are penalized. The agent must act **surgically**, not exhaustively.
 
 ---
 
 ## 4. Reward Function
 
-> **Highlight:** Reward is split into a **grade delta** (monotonic progress credit capped by a terminal pipeline-pass bonus) and a **shaped adjustment** (per-step bonuses/penalties that make exploration targeted and punish idle behaviour). Both layers stack every step.
+## 4. Grader Logic & Reward Shaping
 
-Reward design lives in [environment/grader.py](../environment/grader.py). Two layers stack each step:
+> The grader rewards *process quality*, not just success. Agents are guided through a realistic debugging flow: investigate → diagnose → fix → verify.
 
-1. **Grade delta** — the change in `grade(state)` from last step to this one.
-2. **Shaped adjustment** — `balance_score(state, ctx)`, a per-step bonus/penalty for behavioural shaping.
+Each step reward is composed of:
+**grade(state) delta + balance_score(state, ctx)**
 
-### Grade components
-
-| Component | Value | When it fires |
-|---|---|---|
-| Per-fix credit | up to **+0.20** total, distributed evenly across all answer-key fixes | Each time a fix string lands in its target file (incremental, not all-or-nothing) |
-| `pipeline_passed` tier | **+0.50** (terminal) | When `pipeline_status == "passed"` |
+---
 
-So a 2-fix medium task pays `+0.10` per fix landed, and `+0.50` on the green build. A 3-fix hard task pays `~+0.067` per fix, and `+0.50` on green.
+### Core Score (Structural Progress)
 
-### Shaped per-step adjustments
+- **Fix Credit (max +0.20)**  
+  Proportional to fraction of correctly applied fixes.
 
-| Behaviour | Adjustment | Why |
-|---|---|---|
-| First `cat` of an answer-key file (max 2 per episode) | **+0.05** | Encourage targeted exploration |
-| `cat` on a file already read this episode | **−0.05** | Penalise redundant reads |
-| `pipeline run` with no FS change since last run | **−0.10** | Idle runs reveal nothing new |
-| `pipeline run` after the agent has located the correct file but hasn't edited since | **−0.08** | Exploitation trap: knows the bug, won't act |
-| Each step beyond `ideal_steps` | **−0.01 × overage** | Linear efficiency penalty |
+- **Pipeline Passed (+0.50)**  
+  Awarded only when `pipeline_status == "passed"`.
 
-### Investigation milestones
+- **File Integrity (−0.10 → 0.0)**  
+  Penalizes excessive edits (e.g., appending large amounts of code).
 
-`investigated`, `logs_read`, `correct_file_located` are tracked as state milestones but **carry zero reward**. Reading a file is not progress — fixing it is. Milestones only feed the shaping logic (e.g. the exploitation-trap penalty).
+---
 
-### Worked example — easy task, optimal play
+### Milestone-Based Progression
 
-| Step | Action | Δ grade | Shaped | Reward |
-|---|---|---|---|---|
-| 1 | `pipeline run` | 0 | 0 | 0.00 |
-| 2 | `cat requirements.txt` | 0 | +0.05 | +0.05 |
-| 3 | `echo "pandas" >> requirements.txt` | +0.20 | 0 | +0.20 |
-| 4 | `pipeline run` | +0.50 | 0 | +0.50 |
+| Stage | Description | Reward |
+|------|------------|--------|
+| Investigated | First pipeline run to observe failure | +0.10 |
+| Diagnosed | Reads relevant diagnostic/source files | +0.10 |
+| Fix Applied | Valid structural fix detected | +0.15 |
+| Verified | Pipeline successfully passes | +0.50 |
 
-Total: **0.75**, 4 steps (1 over ideal).
+Progress is **state-driven**, not command-driven.
 
 ---
 
-## 5. Grader Function
+### Behavioral Shaping (Per-Step)
+
+#### Rewards
+- **Correct Diagnosis**: +0.10  
+- **Cross-File Reasoning**: +0.05  
+
+#### Penalties
+- **Blind Edits** (edit without reading): −0.10  
+- **Edit Spam** (>2 edits per file): −0.05 each  
+- **Idle Pipeline Runs** (no FS changes): −0.05  
+- **Stalling** (no progress): −0.05  
+- **Regression** (breaking prior fix): −0.15  
+- **Inefficiency**: −0.02 per step beyond ideal (6 steps)
 
-> **Highlight:** `environment.grader:grade` is declared as the grader for all three tasks in [openenv.yaml](../openenv.yaml). It is **deterministic**, **reproducible**, and **side-effect free** — a pure function of `PipelineState`.
+---
 
-- **Deterministic** — pure function of `PipelineState`. Same state in → same score out.
-- **Reproducible** — `(task, seed)` fully determines the scenario, the answer key, and therefore the grader's behaviour.
-- **Side-effect free** — the grader never mutates state and never reads anything outside the `PipelineState` it is handed.
+### Key Design Insight
 
-### Episode termination
+The grader differentiates:
+- **Structured debugging** → rewarded  
+- **Brute-force / guesswork** → penalized  
 
-An episode ends when **either**:
-- `pipeline_status == "passed"`, or
-- `steps_remaining == 0` (step budget exhausted).
+Partial fixes receive proportional credit, enabling meaningful learning even in multi-error environments.
 
 ---
 
@@ -178,25 +313,39 @@ An episode ends when **either**:
 
 ```
 CI_CD_Doctor/
-├── README.md                      ← brief project overview
-├── docs/
-│   └── advanced_readme.md         ← this file
-├── openenv.yaml                   ← OpenEnv manifest (3 tasks, grader bindings)
+├── Dockerfile                    ← container setup
+├── README.md                     ← main project overview
+├── __init__.py
+├── client.py                     ← environment client interface
+├── models.py                     ← core data models (Action / State / Observation)
+├── inference.py                  ← baseline agent runner
+├── openenv.yaml                  ← OpenEnv task + grader config
 ├── pyproject.toml
-├── inference.py                   ← Baseline LLM agent + episode runner
-├── environment/
+├── uv.lock                       ← dependency lockfile
+│
+├── core/                         ← modularized environment logic
 │   ├── __init__.py
-│   ├── models.py                  ← PipelineAction / Observation / State
-│   ├── parser.py                  ← Free-form command parser (6 patterns)
-│   ├── generator.py               ← Procedural scenario generators (easy/medium/hard + variants)
-│   ├── stage_runner.py            ← Simulated pipeline stages
-│   ├── grader.py                  ← grade() + balance_score() reward shaping
-│   ├── packages.py                ← Per-task required-package sets
-│   ├── client.py                  ← CiCdDoctorEnv HTTP/WS client
-│   └── server/
-│       ├── environment.py         ← PipelineEnvironment (reset/step/state)
-│       ├── app.py                 ← FastAPI app
-│       └── Dockerfile
+│   ├── grading/
+│   │   └── grader.py             ← scoring + reward shaping logic
+│   ├── pipeline/
+│   │   └── stage_runner.py       ← simulated CI/CD stages
+│   ├── scenarios/
+│   │   └── generator.py          ← task + variant generation
+│   ├── utils/
+│   │   └── packages.py           ← dependency definitions
+│   └── validation/
+│       ├── parser.py             ← command parsing logic
+│       └── validator.py          ← structural validation (CI rules, configs)
+│
+├── server/                       ← execution backend
+│   ├── __init__.py
+│   ├── app.py                    ← FastAPI entrypoint
+│   ├── app_2.py                  ← alternate server setup
+│   └── environment.py            ← main env loop (reset/step/state)
+│
+├── docs/
+│   ├── README.md.                ← HF space readme
+│   └── advanced_readme.md        ← detailed system design
 ```
 
 ---

output/logs.txt

@@ -188,4 +188,92 @@ Milestone-based rewards — Scoring now rewards state transitions (investigated
 [STEP] step=23 action=sed -i 's/FROM python:3.11-alpine/FROM python:3.11-slim/' Dockerfile reward=0.09 done=false stdout="" error=null
 [STEP] step=24 action=pipeline run reward=-0.02 done=false stdout="=== Stage: ci_validate ===\nCI configuration validated. Stage order is correct.\n=== Stage: docker_build ===\nStep 1/5 : FROM python:3.11-slim\n ---> a8b2c3d4e5f6\nStep 2/5 : WORKDIR /app\nStep 3/5 : COPY requirements.txt .\nStep 4/5 : RUN pip install -r requirements.txt\nStep 5/5 : COPY . .\nSuccessfully built a8b2c3d4e5f6\n=== Stage: install ===\nCollecting dependencies from requirements.txt...\n  Downloading numpy-1.21.0.tar.gz (10.3 MB)\n     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 10.3/10.3 MB 38.1 ..." error=null
 [STEP] step=25 action=sed -i 's/numpy==1.21.0/numpy>=1.26/' requirements.txt reward=0.10 done=true stdout="" error=null
-[END] success=true steps=25 score=0.50 rewards=-0.05,0.10,0.10,0.10,0.22,-0.05,0.00,0.15,0.05,0.00,-0.02,0.03,-0.07,0.03,-0.02,-0.02,-0.07,-0.02,-0.07,0.03,-0.02,-0.07,0.09,-0.02,0.10
+[END] success=true steps=25 score=0.50 rewards=-0.05,0.10,0.10,0.10,0.22,-0.05,0.00,0.15,0.05,0.00,-0.02,0.03,-0.07,0.03,-0.02,-0.02,-0.07,-0.02,-0.07,0.03,-0.02,-0.07,0.09,-0.02,0.10
+
+
+
+=========================================================================================================================================
+
+
+[START] task=easy env=CI_CD_Doctor model=Qwen/Qwen2.5-72B-Instruct
+[STEP] step=1 action=cat pipeline.yaml reward=0.00 done=false stdout="stages:\n  - install\n" error=null
+[STEP] step=2 action=pipeline run reward=0.10 done=false stdout="Collecting dependencies from requirements.txt...\n  Downloading flask-3.0.0-py3-none-any.whl (101 kB)\n  Downloading pandas-2.1.0-cp311-cp311-linux_x86_64.whl (12.4 MB)\n     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 12.4/12.4 MB 45.2 MB/s\nChecking installed packages against imports...\n  Traceback (most recent call last):\n    File "app.py", line 4, in <module>\n      import pydantic\n  ModuleNotFoundError: No module named 'pydantic'\n\nERROR: Import check failed. A package imported by app.py\n  is not i..." error=null
+[STEP] step=3 action=cat app.py reward=0.10 done=false stdout="import flask\nimport numpy\nimport pandas\nimport requests\nimport pydantic\n\n# Application entrypoint\nAPP_PORT = 8080\n\ndef main():\n    print("Starting application...")\n\nif __name__ == "__main__":\n    main()\n" error=null
+[STEP] step=4 action=cat requirements.txt reward=-0.02 done=false stdout="flask\nnumpy\npandas\nrequests\n" error=null
+[STEP] step=5 action=echo "pydantic" >> requirements.txt reward=0.38 done=false stdout="" error=null
+[STEP] step=6 action=pipeline run reward=0.53 done=true stdout="Collecting dependencies from requirements.txt...\n  flask, numpy, pandas, pydantic, requests\nSuccessfully installed all dependencies.\n" error=null
+[END] success=true steps=6 score=0.99 rewards=0.00,0.10,0.10,-0.02,0.38,0.53
+
+
+[START] task=medium env=CI_CD_Doctor model=Qwen/Qwen2.5-72B-Instruct
+[STEP] step=1 action=pipeline status reward=-0.05 done=false stdout="Pipeline status: not_run" error=null
+[STEP] step=2 action=pipeline run reward=0.10 done=false stdout="=== Stage: install ===\nCollecting dependencies from requirements.txt...\n  All listed packages installed successfully.\n\nRunning import verification...\n  Traceback (most recent call last):\n    File "app.py", line 4, in <module>\n      import pydantic\n  ModuleNotFoundError: No module named 'pydantic'\n\nERROR: Application startup failed. A required module could not\n  be imported. Cross-reference app.py imports with your\n  dependency list.\n" error=null
+[STEP] step=3 action=cat requirements.txt reward=0.10 done=false stdout="flask\nnumpy\npandas\nrequests\n" error=null
+[STEP] step=4 action=echo "pydantic" >> requirements.txt reward=0.25 done=false stdout="" error=null
+[STEP] step=5 action=pipeline run reward=-0.05 done=false stdout="=== Stage: install ===\nCollecting dependencies from requirements.txt...\n  flask, numpy, pandas, pydantic, requests\nSuccessfully installed all dependencies.\n=== Stage: config_validate ===\nDeployment configuration validation...\n  target_env: production ... OK\n  deploy_enabled: ... BLOCKED\n\nERROR: Deployment gate check failed.\n  Pre-deploy validation returned status: BLOCKED\n  Reason: deployment is currently disabled for this environment.\n  The deployment pipeline cannot proceed until t..." error=null
+[STEP] step=6 action=cat deploy_config.yml reward=0.00 done=false stdout="target_env: production\ndeploy_enabled: false\nreplicas: 2\nhealth_check_path: /health\ntimeout: 30\n" error=null
+[STEP] step=7 action=sed -i 's/deploy_enabled: false/deploy_enabled: true/' deploy_config.yml reward=0.13 done=false stdout="" error=null
+[STEP] step=8 action=pipeline run reward=0.53 done=true stdout="=== Stage: install ===\nCollecting dependencies from requirements.txt...\n  flask, numpy, pandas, pydantic, requests\nSuccessfully installed all dependencies.\n=== Stage: config_validate ===\nDeployment configuration validation...\n  target_env: production ... OK\n  deploy_enabled: true ... OK\n  health_check_path: /health ... OK\nDeployment configuration validated.\n=== Stage: smoke_test ===\nSmoke test passed. Application started successfully.\n" error=null
+[END] success=true steps=8 score=0.99 rewards=-0.05,0.10,0.10,0.25,-0.05,0.00,0.13,0.53
+
+[START] task=medium env=CI_CD_Doctor model=Qwen/Qwen2.5-72B-Instruct
+[STEP] step=1 action=cat pipeline.yaml reward=0.00 done=false stdout="stages:\n  - install\n  - port_check\n  - docker_build\n" error=null
+[STEP] step=2 action=pipeline run reward=0.10 done=false stdout="=== Stage: install ===\nCollecting dependencies from requirements.txt...\n  flask, numpy, pandas, pydantic, requests\nSuccessfully installed all dependencies.\n=== Stage: port_check ===\nService configuration validation...\n  Checking port binding...\n  Health check: GET http://localhost:3000/health\n    -> Connection refused\n\nERROR: Service health check timed out after 30s.\n  Readiness probe failed: TCP connection to the configured\n  service endpoint was refused. The application is not reac..." error=null
+[STEP] step=3 action=cat service.yaml reward=0.10 done=false stdout="apiVersion: v1\nkind: Service\nmetadata:\n  name: app\nspec:\n  port: 3000\n" error=null
+[STEP] step=4 action=diagnose "The service health check is timing out, which could be due to the service not being exposed correctly or the application not running on the specified port." reward=0.10 done=false stdout="Diagnosis recorded." error=null
+[STEP] step=5 action=cat Dockerfile reward=0.00 done=false stdout="FROM python:3.9-slim\nWORKDIR /app\nCOPY requirements.txt .\nRUN pip install -r requirements.txt\nCOPY . .\nCMD ["python", "app.py"]\n" error=null
+[STEP] step=6 action=echo "spec:" >> service.yaml echo " ports:" >> service.yaml echo " - port: 80" >> service.yaml echo " targetPort: 3000" >> service.yaml reward=0.05 done=false stdout="" error=null
+[STEP] step=7 action=pipeline logs reward=-0.02 done=false stdout="=== Stage: install ===\nCollecting dependencies from requirements.txt...\n  flask, numpy, pandas, pydantic, requests\nSuccessfully installed all dependencies.\n=== Stage: port_check ===\nService configuration validation...\n  Checking port binding...\n  Health check: GET http://localhost:3000/health\n    -> Connection refused\n\nERROR: Service health check timed out after 30s.\n  Readiness probe failed: TCP connection to the configured\n  service endpoint was refused. The application is not reac..." error=null
+[STEP] step=8 action=cat app.py reward=0.03 done=false stdout="import flask\nimport numpy\nimport pandas\nimport requests\nimport pydantic\n\n# Application entrypoint\nAPP_PORT = 8080\n\ndef main():\n    print("Starting application...")\n\nif __name__ == "__main__":\n    main()\n" error=null
+[STEP] step=9 action=sed -i 's/APP_PORT = 8080/APP_PORT = 3000/' app.py reward=0.03 done=false stdout="" error=null
+[STEP] step=10 action=pipeline run reward=-0.02 done=false stdout="=== Stage: install ===\nCollecting dependencies from requirements.txt...\n  flask, numpy, pandas, pydantic, requests\nSuccessfully installed all dependencies.\n=== Stage: port_check ===\nService configuration validation...\n  Checking port binding...\n  Health check: GET http://localhost:3000/health\n    -> Connection refused\n\nERROR: Service health check timed out after 30s.\n  Readiness probe failed: TCP connection to the configured\n  service endpoint was refused. The application is not reac..." error=null
+[STEP] step=11 action=cat app.py reward=0.03 done=false stdout="import flask\nimport numpy\nimport pandas\nimport requests\nimport pydantic\n\n# Application entrypoint\nAPP_PORT = 3000\n\ndef main():\n    print("Starting application...")\n\nif __name__ == "__main__":\n    main()\n" error=null
+[STEP] step=12 action=sed -i 's/APP_PORT = 3000/APP_PORT = 8080/' app.py reward=0.03 done=false stdout="" error=null
+[STEP] step=13 action=sed -i 's/APP_PORT = 8080/APP_PORT = 3000/' app.py reward=0.03 done=false stdout="" error=null
+[STEP] step=14 action=pipeline logs reward=-0.02 done=false stdout="=== Stage: install ===\nCollecting dependencies from requirements.txt...\n  flask, numpy, pandas, pydantic, requests\nSuccessfully installed all dependencies.\n=== Stage: port_check ===\nService configuration validation...\n  Checking port binding...\n  Health check: GET http://localhost:3000/health\n    -> Connection refused\n\nERROR: Service health check timed out after 30s.\n  Readiness probe failed: TCP connection to the configured\n  service endpoint was refused. The application is not reac..." error=null
+[STEP] step=15 action=cat app.py reward=0.03 done=true stdout="import flask\nimport numpy\nimport pandas\nimport requests\nimport pydantic\n\n# Application entrypoint\nAPP_PORT = 3000\n\ndef main():\n    print("Starting application...")\n\nif __name__ == "__main__":\n    main()\n" error=null
+[END] success=false steps=15 score=0.47 rewards=0.00,0.10,0.10,0.10,0.00,0.05,-0.02,0.03,0.03,-0.02,0.03,0.03,0.03,-0.02,0.03
+
+
+[START] task=medium env=CI_CD_Doctor model=Qwen/Qwen2.5-72B-Instruct
+[STEP] step=1 action=pipeline status reward=-0.05 done=false stdout="Pipeline status: not_run" error=null
+[STEP] step=2 action=pipeline run reward=0.10 done=false stdout="=== Stage: install ===\nCollecting dependencies from requirements.txt...\n  flask, numpy, pandas, pydantic, requests\nSuccessfully installed all dependencies.\n=== Stage: env_check ===\nEnvironment pre-flight check...\n  Loading variables from .env.ci\n\nTraceback (most recent call last):\n  File "app.py", line 3, in <module>\n    from config import Settings\n  File "config.py", line 8, in Settings\n    api_key = os.environ['API_KEY']\nKeyError: 'API_KEY'\n\nERROR: Application failed to start. A..." error=null
+[STEP] step=3 action=cat .env.ci reward=0.10 done=false stdout="DATABASE_URL=placeholder\nSECRET_KEY=placeholder\n" error=null
+[STEP] step=4 action=echo "API_KEY=your_api_key_here" >> .env.ci reward=0.25 done=false stdout="" error=null
+[STEP] step=5 action=pipeline run reward=-0.05 done=false stdout="=== Stage: install ===\nCollecting dependencies from requirements.txt...\n  flask, numpy, pandas, pydantic, requests\nSuccessfully installed all dependencies.\n=== Stage: env_check ===\nEnvironment pre-flight check...\n  Loading variables from .env.ci\n  All required environment variables present.\nEnvironment check passed.\n=== Stage: docker_build ===\nStep 1/5 : FROM python:3.9-slim\n ---> c4d5e6f7a8b9\nStep 2/5 : WORKDIR /app\nStep 3/5 : COPY requirements.txt .\nStep 4/5 : RUN pip install -r ..." error=null
+[STEP] step=6 action=cat Dockerfile reward=0.00 done=false stdout="FROM python:3.9-slim\nWORKDIR /app\nCOPY requirements.txt .\nRUN pip install -r requirements.txt\nCOPY . .\nCMD ["python", "app.py"]\n" error=null
+[STEP] step=7 action=sed -i 's/python:3.9-slim/python:3.11-slim/' Dockerfile reward=0.13 done=false stdout="" error=null
+[STEP] step=8 action=pipeline run reward=0.53 done=true stdout="=== Stage: install ===\nCollecting dependencies from requirements.txt...\n  flask, numpy, pandas, pydantic, requests\nSuccessfully installed all dependencies.\n=== Stage: env_check ===\nEnvironment pre-flight check...\n  Loading variables from .env.ci\n  All required environment variables present.\nEnvironment check passed.\n=== Stage: docker_build ===\nStep 1/5 : FROM python:3.11-slim\n ---> a8b2c3d4e5f6\nSuccessfully built a8b2c3d4e5f6\n" error=null
+[END] success=true steps=8 score=0.99 rewards=-0.05,0.10,0.10,0.25,-0.05,0.00,0.13,0.53
+
+
+[START] task=hard env=CI_CD_Doctor model=Qwen/Qwen2.5-72B-Instruct
+[STEP] step=1 action=cat pipeline.yaml reward=0.00 done=false stdout="stages:\n  - ci_validate\n  - docker_build\n  - install\n" error=null
+[STEP] step=2 action=pipeline run reward=0.10 done=false stdout="=== Stage: ci_validate ===\nCI configuration validation...\n  Parsing stage definitions from ci.yml\n  Found stages: test, build, install\n\nERROR: Pipeline validation failed: stage dependency violation.\n  Stage 'test' is at position 1 but depends on\n  'install' which is at position 3.\n  Tests cannot run before dependencies are installed.\n  Stages that produce artifacts must run before stages that\n  consume them. Review the stage execution order in ci.yml.\n" error=null
+[STEP] step=3 action=cat ci.yml reward=0.10 done=false stdout="stages: test, build, install\n" error=null
+[STEP] step=4 action=diagnose "The error indicates a stage dependency violation, which means there's a mismatch between the stages defined in pipeline.yaml and ci.yml." reward=0.10 done=false stdout="Diagnosis recorded." error=null
+[STEP] step=5 action=sed -i 's/stages: test, build, install/stages: ci_validate, docker_build, install/' ci.yml reward=0.00 done=false stdout="" error=null
+[STEP] step=6 action=pipeline run reward=-0.05 done=false stdout="=== Stage: ci_validate ===\nCI configuration validation...\n  Parsing stage definitions from ci.yml\n  Found stages: ci_validate, docker_build, install\n\nERROR: Pipeline validation failed: stage dependency violation.\n  One or more stages are scheduled before their dependencies\n  have been satisfied.\n  Stages that produce artifacts must run before stages that\n  consume them. Review the stage execution order in ci.yml.\n" error=null
+[STEP] step=7 action=cat pipeline.yaml reward=0.00 done=false stdout="stages:\n  - ci_validate\n  - docker_build\n  - install\n" error=null
+[STEP] step=8 action=cat ci.yml reward=0.00 done=false stdout="stages: ci_validate, docker_build, install\n" error=null
+[STEP] step=9 action=sed -i 's/stages:/stages: /' pipeline.yaml reward=0.00 done=false stdout="" error=null
+[STEP] step=10 action=pipeline logs reward=-0.05 done=false stdout="=== Stage: ci_validate ===\nCI configuration validation...\n  Parsing stage definitions from ci.yml\n  Found stages: ci_validate, docker_build, install\n\nERROR: Pipeline validation failed: stage dependency violation.\n  One or more stages are scheduled before their dependencies\n  have been satisfied.\n  Stages that produce artifacts must run before stages that\n  consume them. Review the stage execution order in ci.yml.\n" error=null
+[STEP] step=11 action=pipeline run reward=-0.07 done=false stdout="=== Stage: ci_validate ===\nCI configuration validation...\n  Parsing stage definitions from ci.yml\n  Found stages: ci_validate, docker_build, install\n\nERROR: Pipeline validation failed: stage dependency violation.\n  One or more stages are scheduled before their dependencies\n  have been satisfied.\n  Stages that produce artifacts must run before stages that\n  consume them. Review the stage execution order in ci.yml.\n" error=null
+[STEP] step=12 action=cat ci.yml reward=-0.02 done=false stdout="stages: ci_validate, docker_build, install\n" error=null
+[STEP] step=13 action=cat pipeline.yaml reward=-0.02 done=false stdout="stages: \n  - ci_validate\n  - docker_build\n  - install\n" error=null
+[STEP] step=14 action=diagnose "The stage dependency violation might be due to incorrect indentation or formatting in the YAML files." reward=0.08 done=false stdout="Diagnosis recorded." error=null
+[STEP] step=15 action=sed -i 's/- ci_validate/- ci_validate\n - docker_build\n - install/' pipeline.yaml reward=-0.02 done=false stdout="" error=null
+[STEP] step=16 action=pipeline run reward=-0.07 done=false stdout="=== Stage: ci_validate ===\nCI configuration validation...\n  Parsing stage definitions from ci.yml\n  Found stages: ci_validate, docker_build, install\n\nERROR: Pipeline validation failed: stage dependency violation.\n  One or more stages are scheduled before their dependencies\n  have been satisfied.\n  Stages that produce artifacts must run before stages that\n  consume them. Review the stage execution order in ci.yml.\n" error=null
+[STEP] step=17 action=cat pipeline.yaml reward=-0.02 done=false stdout="stages: \n  - ci_validate\\n  - docker_build\\n  - install\n  - docker_build\n  - install\n" error=null
+[STEP] step=18 action=sed -i 's/- docker_build/- docker_build\n - install/' pipeline.yaml reward=-0.02 done=false stdout="" error=null
+[STEP] step=19 action=pipeline logs reward=-0.07 done=false stdout="=== Stage: ci_validate ===\nCI configuration validation...\n  Parsing stage definitions from ci.yml\n  Found stages: ci_validate, docker_build, install\n\nERROR: Pipeline validation failed: stage dependency violation.\n  One or more stages are scheduled before their dependencies\n  have been satisfied.\n  Stages that produce artifacts must run before stages that\n  consume them. Review the stage execution order in ci.yml.\n" error=null
+[STEP] step=20 action=cat pipeline.yaml reward=-0.02 done=false stdout="stages: \n  - ci_validate\\n  - docker_build\\n  - install\\n  - install\n  - docker_build\\n  - install\n  - install\n" error=null
+[STEP] step=21 action=sed -i 's/- install/- install/g' pipeline.yaml reward=-0.02 done=false stdout="" error=null
+[STEP] step=22 action=cat pipeline.yaml reward=-0.02 done=false stdout="stages: \n  - ci_validate\\n  - docker_build\\n  - install\\n  - install\n  - docker_build\\n  - install\n  - install\n" error=null
+[STEP] step=23 action=sed -i 's/- install/- install\n/' pipeline.yaml reward=-0.07 done=false stdout="" error=null
+[STEP] step=24 action=cat pipeline.yaml reward=-0.02 done=false stdout="stages: \n  - ci_validate\\n  - docker_build\\n  - install\\n\\n  - install\\n\n  - docker_build\\n  - install\\n\n  - install\\n\n" error=null
+[STEP] step=25 action=sed -i 's/\n - install/\n/' pipeline.yaml reward=-0.12 done=true stdout="" error=null
+[END] success=false steps=25 score=0.01 rewards=0.00,0.10,0.10,0.10,0.00,-0.05,0.00,0.00,0.00,-0.05,-0.07,-0.02,-0.02,0.08,-0.02,-0.07,-0.02,-0.02,-0.07,-0.02,-0.02,-0.02,-0.07,-0.02,-0.12
+
+
+