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server/app.py โ FastAPI + Gradio server for Cloud Incident Response OpenEnv.
Endpoints (OpenEnv spec):
GET /health โ {"status": "ok"}
POST /reset โ Observation (accepts JSON body or query params)
POST /step โ {"observation": ..., "reward": ..., "done": ..., "info": ...}
GET /state โ EpisodeState
GET /tasks โ task list with action schemas
GET /grader โ grading result for current episode
POST /baseline โ run inference.py
"""
from __future__ import annotations
import json
import os
import subprocess
import sys
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from contextlib import asynccontextmanager
from fastapi import FastAPI, HTTPException, Request
from fastapi.middleware.cors import CORSMiddleware
from server.environment import IncidentEnvironment
from server.models import Action, ActionParameters
from tasks import ALL_TASKS, list_tasks
_ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
_env: IncidentEnvironment | None = None
@asynccontextmanager
async def lifespan(app: FastAPI):
global _env
_env = IncidentEnvironment()
yield
def _get_env() -> IncidentEnvironment:
if _env is None:
raise HTTPException(503, "Environment initialising โ retry in a moment")
return _env
def _get_env_direct() -> IncidentEnvironment:
if _env is None:
raise RuntimeError("Environment not initialised yet")
return _env
app = FastAPI(
title="Cloud Incident Response โ OpenEnv",
version="0.1.0",
description=(
"OpenEnv environment for training AI agents on cloud SRE incident response. "
"Implements step()/reset()/state() API with typed Observation, Action, and Reward models."
),
lifespan=lifespan,
)
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_methods=["*"],
allow_headers=["*"],
)
# โโ OpenEnv API Endpoints โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
@app.get("/health")
def health():
"""Health check endpoint."""
return {"status": "ok", "version": "0.1.0"}
@app.get("/api/info")
def api_info():
"""Environment metadata."""
return {
"status": "running",
"name": "cloud-incident-response",
"version": "0.1.0",
"description": "OpenEnv environment for cloud SRE incident response",
"tasks": list(ALL_TASKS.keys()),
"docs": "/docs",
}
@app.post("/reset")
async def reset(request: Request):
"""Reset the environment and start a new episode.
Accepts task_id and scenario_index via:
- Query parameters: /reset?task_id=...&scenario_index=...
- JSON body: {"task_id": "...", "scenario_index": 0}
- Empty body: uses defaults (alert_classification, scenario 0)
Returns: Observation dict
"""
task_id = "alert_classification"
scenario_index = 0
# Parse query params
qp = request.query_params
if qp.get("task_id"):
task_id = qp["task_id"]
if qp.get("scenario_index"):
try:
scenario_index = int(qp["scenario_index"])
except ValueError:
pass
# Parse JSON body (may be empty {} or have fields)
try:
body = await request.json()
if isinstance(body, dict):
task_id = body.get("task_id", task_id)
si = body.get("scenario_index")
if si is not None:
scenario_index = int(si)
except Exception:
pass # Empty body or non-JSON is fine โ use defaults
env = _get_env()
try:
obs = env.reset(task_id=task_id, scenario_index=scenario_index)
return obs.model_dump()
except ValueError as e:
raise HTTPException(400, str(e))
except Exception as e:
raise HTTPException(500, str(e))
@app.post("/step")
def step(action: Action):
"""Take one step in the environment.
Accepts: Action JSON body with action_type and parameters
Returns: {"observation": {...}, "reward": {...}, "done": bool, "info": {...}}
"""
env = _get_env()
try:
obs, reward, done, info = env.step(action)
return {
"observation": obs.model_dump(),
"reward": reward.model_dump(),
"done": done,
"info": info,
}
except RuntimeError as e:
raise HTTPException(400, str(e))
except Exception as e:
raise HTTPException(500, str(e))
@app.get("/state")
def state():
"""Get the current episode state.
Returns: EpisodeState dict with full action history and internal state
"""
env = _get_env()
try:
return env.state().model_dump()
except RuntimeError as e:
raise HTTPException(400, str(e))
except Exception as e:
raise HTTPException(500, str(e))
@app.get("/tasks")
def tasks():
"""List all available tasks with action schemas."""
return {
"tasks": list_tasks(),
"total": len(ALL_TASKS),
"action_schema": {
"diagnostic": [
{"action_type": "query_logs", "parameters": {"service": "string"}},
{"action_type": "check_metrics", "parameters": {"service": "string"}},
{"action_type": "check_dependencies", "parameters": {"service": "string"}},
{"action_type": "check_recent_deploys", "parameters": {"service": "string"}},
{"action_type": "check_service_status", "parameters": {"service": "string"}},
],
"remediation": [
{"action_type": "restart_service", "parameters": {"service": "string"}},
{"action_type": "rollback_deploy", "parameters": {"service": "string", "target_version": "string"}},
{"action_type": "scale_service", "parameters": {"service": "string", "replicas": "int"}},
{"action_type": "disable_feature_flag", "parameters": {"flag": "string"}},
{"action_type": "clear_cache", "parameters": {"service": "string"}},
{"action_type": "execute_runbook_step", "parameters": {"runbook_action": "string"}},
],
"submission": [
{"action_type": "submit_severity", "parameters": {"severity": "P1|P2|P3|P4", "service": "string"}},
{"action_type": "submit_root_cause", "parameters": {"service": "string", "failure_mode": "string"}},
{"action_type": "submit_resolution", "parameters": {"summary": "string"}},
],
},
}
@app.get("/grader")
def grader():
"""Grade the current episode. Returns score 0.0-1.0 with breakdown."""
env = _get_env()
try:
s = env.state()
from graders import grade
result = grade(s.task_id, s.model_dump(), env._scenario)
return {
"total": result["total"],
"breakdown": result["breakdown"],
"feedback": result["feedback"],
"task_id": s.task_id,
"scenario_id": s.scenario_id,
"steps_used": s.step_count,
"done": s.done,
}
except RuntimeError as e:
raise HTTPException(400, str(e))
except Exception as e:
raise HTTPException(500, str(e))
@app.post("/baseline")
def baseline():
"""Run the baseline inference script and return results."""
script = os.path.join(_ROOT, "inference.py")
if not os.path.exists(script):
raise HTTPException(500, "inference.py not found")
try:
result = subprocess.run(
[sys.executable, script],
capture_output=True, text=True, timeout=1200, cwd=_ROOT,
env={**os.environ, "ENV_BASE_URL": "http://localhost:7860"},
)
except subprocess.TimeoutExpired:
raise HTTPException(500, "inference.py timed out (>20 min)")
if result.returncode != 0:
raise HTTPException(500, result.stderr[-2000:])
lines = result.stdout.strip().splitlines()
last = lines[-1] if lines else ""
try:
return json.loads(last)
except Exception:
return {"raw_output": result.stdout[-3000:]}
@app.get("/status")
def root_status():
"""Root health check โ returns JSON."""
return {
"status": "running",
"name": "cloud-incident-response",
"version": "0.1.0",
"tasks": list(ALL_TASKS.keys()),
}
# โโ Gradio UI โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
import gradio as gr
DIFFICULTY_BADGE = {
"alert_classification": "๐ข Easy",
"root_cause_analysis": "๐ก Medium",
"remediation_planning": "๐ด Hard",
}
DIFFICULTY_INFO = {
"alert_classification": "3 steps ยท Classify severity P1โP4",
"root_cause_analysis": "10 steps ยท Find root cause service + failure mode",
"remediation_planning": "15 steps ยท Diagnose, fix, and document",
}
SUBMIT_ACTION = {
"alert_classification": "submit_severity",
"root_cause_analysis": "submit_root_cause",
"remediation_planning": "submit_resolution",
}
_DIAG_ACTIONS = [
"query_logs", "check_metrics", "check_dependencies",
"check_recent_deploys", "check_service_status",
]
_REM_ACTIONS = [
"restart_service", "rollback_deploy", "scale_service",
"disable_feature_flag", "clear_cache", "execute_runbook_step",
]
def _fmt_obs(obs: dict) -> str:
lines = []
lines.append(f"### ๐ Scenario `{obs.get('scenario_id', 'โ')}`\n")
summary = obs.get("incident_summary", "")
if summary:
lines.append(f"> {summary[:600]}\n")
alert = obs.get("alert", {})
if alert:
lines.append("#### ๐ Alert Details\n")
if alert.get("title"):
lines.append(f"**Title:** {alert['title']}\n")
symptoms = alert.get("symptoms", [])
if symptoms:
lines.append("**Symptoms:**")
for s in symptoms:
lines.append(f"- {s}")
lines.append("")
info_items = []
if alert.get("error_rate") is not None:
info_items.append(f"Error Rate: **{alert['error_rate']:.0%}**")
if alert.get("duration_minutes") is not None:
info_items.append(f"Duration: **{alert['duration_minutes']} min**")
if alert.get("revenue_impact_per_min") is not None:
info_items.append(f"Revenue: **${alert['revenue_impact_per_min']:,.0f}/min**")
if info_items:
lines.append(" ยท ".join(info_items) + "\n")
known = obs.get("known_services", [])
if known:
lines.append(f"#### ๐ฅ๏ธ Known Services\n`{'` ยท `'.join(known)}`\n")
task_id = obs.get("task_id", "")
submit = SUBMIT_ACTION.get(task_id, "")
if submit:
diff = DIFFICULTY_INFO.get(task_id, "")
lines.append(f"#### ๐ Submit: `{submit}`")
if diff:
lines.append(f"*{diff}*\n")
err = obs.get("last_action_error")
if err:
lines.append(f"#### โ ๏ธ Last Action Error\n`{err}`\n")
qd = obs.get("queried_data", {})
if qd:
lines.append("---\n#### ๐ Evidence Collected\n")
for action_type, services in qd.items():
if isinstance(services, dict):
for svc, data in services.items():
d = str(data)
if len(d) > 400:
d = d[:400] + " โฆ"
lines.append(f"**`[{action_type}]` โ `{svc}`**")
lines.append(f"```\n{d}\n```\n")
return "\n".join(lines)
def _fmt_state(s: dict) -> str:
task_id = s.get("task_id", "โ")
diff = DIFFICULTY_BADGE.get(task_id, "")
done = s.get("done", False)
status = "๐ Complete" if done else "โก Active"
step_count = s.get("step_count", 0)
max_steps = s.get("max_steps", 0)
cum_reward = s.get("cumulative_reward", 0.0)
pct = (step_count / max_steps * 100) if max_steps > 0 else 0
bar_filled = int(pct / 5)
bar = "โ" * bar_filled + "โ" * (20 - bar_filled)
return (
f"### {status}\n\n"
f"| Field | Value |\n|---|---|\n"
f"| **Task** | `{task_id}` {diff} |\n"
f"| **Episode** | `{s.get('episode_id', 'โ')[:12]}โฆ` |\n"
f"| **Progress** | {step_count}/{max_steps} `{bar}` {pct:.0f}% |\n"
f"| **Reward** | `{cum_reward:+.4f}` |\n"
f"| **Submitted** | {'โ
' if s.get('submitted') else 'โ'} |\n"
)
def _fmt_history(action_history: list[dict]) -> str:
if not action_history:
return "*No actions yet.*"
lines = ["| Step | Action | Parameters |", "|:---:|---|---|"]
for a in action_history:
step = a.get("step", "?")
at = a.get("action_type", "?")
p = a.get("parameters", {})
p_str = ", ".join(f"`{k}={v}`" for k, v in p.items() if v) or "โ"
icon = "๐" if at in _DIAG_ACTIONS else ("๐ง" if at in _REM_ACTIONS else "๐")
lines.append(f"| {step} | {icon} `{at}` | {p_str} |")
return "\n".join(lines)
def _fmt_reward(reward_text: str, grader_result: dict | None = None) -> str:
lines = [reward_text]
if grader_result:
total = grader_result.get("total", 0.0)
emoji = "๐ข" if total >= 0.8 else ("๐ก" if total >= 0.5 else "๐ด")
lines.append(f"\n### {emoji} Grader Score: **{total:.4f}** / 1.0\n")
bd = grader_result.get("breakdown", {})
if bd:
lines.append("| Component | Value |\n|---|---|")
for k, v in bd.items():
lines.append(f"| {k} | `{v}` |")
lines.append("")
fb = grader_result.get("feedback", "")
if fb:
lines.append(f"> {fb}")
return "\n".join(lines)
def _gr_reset(task_id: str, scenario_index: str):
try:
env = _get_env_direct()
obs = env.reset(task_id=task_id, scenario_index=int(scenario_index))
st = env.state()
services = obs.known_services
return (
_fmt_obs(obs.model_dump()),
_fmt_state(st.model_dump()),
_fmt_history([]),
"โ
Episode started.",
gr.Dropdown(choices=services, value=services[0] if services else None),
)
except Exception as e:
err = f"โ **Error:** {e}"
return (err, err, "", err, gr.Dropdown(choices=[]))
def _gr_step(action_type, service, severity, failure_mode, summary, flag, runbook_action, target_version):
try:
env = _get_env_direct()
params = ActionParameters(
service=service or None, severity=severity if severity else None,
failure_mode=failure_mode or None, summary=summary or None,
flag=flag or None, runbook_action=runbook_action or None,
target_version=target_version or None,
)
action = Action(action_type=action_type, parameters=params)
obs, reward, done, info = env.step(action)
st = env.state()
reward_text = (
f"### Step Reward: `{reward.score:+.4f}`\n\n"
f"**Cumulative:** `{reward.cumulative:+.4f}`\n\n"
f"**Feedback:** {reward.reason}"
)
if done:
reward_text += "\n\n---\n๐ **EPISODE COMPLETE** โ Click **Grade Episode**"
return (
_fmt_obs(obs.model_dump()),
_fmt_state(st.model_dump()),
_fmt_history(st.action_history),
reward_text,
)
except Exception as e:
err = f"โ **Error:** {e}"
return (err, "", "", err)
def _gr_grade():
try:
env = _get_env_direct()
s = env.state()
from graders import grade
result = grade(s.task_id, s.model_dump(), env._scenario)
return _fmt_reward("### Final Grading", result)
except Exception as e:
return f"โ {e}"
def _gr_state():
try:
env = _get_env_direct()
return _fmt_state(env.state().model_dump())
except Exception as e:
return f"โ {e}"
CUSTOM_CSS = """
:root, html, body, .gradio-container { color-scheme: light !important; }
body.dark, html.dark, .dark {
color-scheme: light !important;
--body-background-fill: #ffffff !important;
--background-fill-primary: #ffffff !important;
--background-fill-secondary: #f8fafc !important;
}
.gradio-container {
background: #ffffff !important;
max-width: 1500px !important;
margin: 0 auto !important;
}
.env-header {
display: flex; justify-content: space-between; align-items: center;
padding: 20px 16px; border-bottom: 2px solid #e2e8f0;
margin-bottom: 20px; background: linear-gradient(135deg, #f8fafc, #ffffff);
border-radius: 12px 12px 0 0;
}
.env-header-left {
display: flex; align-items: center; gap: 14px;
font-size: 1.5rem; font-weight: 800; color: #0f172a;
}
.env-header-dot {
width: 14px; height: 14px; border-radius: 50%;
background: #22c55e; box-shadow: 0 0 8px rgba(34,197,94,0.4);
}
.env-header-right { font-size: 0.9rem; font-weight: 600; color: #94a3b8; text-transform: uppercase; }
.section-title {
font-weight: 700; font-size: 0.95rem; color: #1e293b;
margin: 16px 0 8px; padding: 8px 12px; background: #f1f5f9;
border-radius: 8px; border-left: 3px solid #3b82f6;
}
"""
FORCE_LIGHT_JS = """
function() {
document.body.classList.remove('dark');
document.documentElement.classList.remove('dark');
document.documentElement.style.setProperty('color-scheme', 'light');
}
"""
with gr.Blocks(
title="Cloud Incident Response โ OpenEnv",
css=CUSTOM_CSS, js=FORCE_LIGHT_JS,
theme=gr.themes.Soft(primary_hue="blue", neutral_hue="slate",
font=gr.themes.GoogleFont("Inter")),
) as demo:
gr.HTML("""
<div class="env-header">
<div class="env-header-left">
<span class="env-header-dot"></span> โ๏ธ Cloud Incident Response
</div>
<span class="env-header-right">OpenEnv ยท v0.1.0</span>
</div>
""")
with gr.Accordion("๐ How to Use", open=False):
gr.Markdown("""
### Quick Start
1. Select **Task** + **Scenario** โ Click **๐ Reset**
2. Choose **Action Type** + **Service** โ Click **โถ๏ธ Execute**
3. Repeat: investigate โ remediate โ submit
4. Click **๐ Grade** for final score (0.0โ1.0)
### Tasks
| Task | Difficulty | Steps | Submission |
|---|---|---|---|
| `alert_classification` | ๐ข Easy | 3 | `submit_severity` |
| `root_cause_analysis` | ๐ก Medium | 10 | `submit_root_cause` |
| `remediation_planning` | ๐ด Hard | 15 | `submit_resolution` |
### Important
- **Medium/Hard**: `check_recent_deploys` requires prior `query_logs` or `check_metrics` on that service
- Each action gives immediate reward feedback
- Wrong remediation actions are penalized
""")
with gr.Row(equal_height=False):
with gr.Column(scale=2, min_width=380):
gr.HTML('<div class="section-title">๐ฏ Episode Setup</div>')
with gr.Row():
task_dd = gr.Dropdown(
choices=[("๐ข Easy โ Alert Classification", "alert_classification"),
("๐ก Medium โ Root Cause Analysis", "root_cause_analysis"),
("๐ด Hard โ Remediation Planning", "remediation_planning")],
value="alert_classification", label="Task", scale=2)
scenario_dd = gr.Dropdown(
choices=[("Scenario 0", "0"), ("Scenario 1", "1"), ("Scenario 2", "2")],
value="0", label="Scenario", scale=1)
reset_btn = gr.Button("๐ Reset Environment", variant="secondary", size="lg")
gr.HTML('<div class="section-title">๐ฎ Action Controls</div>')
action_type_dd = gr.Dropdown(
choices=[("๐ query_logs", "query_logs"), ("๐ check_metrics", "check_metrics"),
("๐ check_dependencies", "check_dependencies"),
("๐ check_recent_deploys", "check_recent_deploys"),
("๐ check_service_status", "check_service_status"),
("๐ง restart_service", "restart_service"),
("๐ง rollback_deploy", "rollback_deploy"),
("๐ง scale_service", "scale_service"),
("๐ง disable_feature_flag", "disable_feature_flag"),
("๐ง clear_cache", "clear_cache"),
("๐ง execute_runbook_step", "execute_runbook_step"),
("๐ submit_severity", "submit_severity"),
("๐ submit_root_cause", "submit_root_cause"),
("๐ submit_resolution", "submit_resolution")],
value="query_logs", label="Action Type")
service_dd = gr.Dropdown(choices=[], label="Target Service",
allow_custom_value=True, info="Populated after Reset")
with gr.Accordion("๐ Parameters", open=False):
severity_dd = gr.Dropdown(
choices=[("โ", ""), ("P1 Critical", "P1"), ("P2 High", "P2"),
("P3 Medium", "P3"), ("P4 Low", "P4")],
value="", label="Severity")
failure_mode_input = gr.Textbox(label="Failure Mode", lines=1,
placeholder="e.g. unbounded query OOM killing postgres-db")
summary_input = gr.Textbox(label="Resolution Summary", lines=4,
placeholder="3+ sentences: what failed, what you did, status")
flag_input = gr.Textbox(label="Feature Flag", lines=1, placeholder="e.g. full_history_export")
runbook_input = gr.Textbox(label="Runbook Action", lines=1, placeholder="e.g. restore_bgp_routes")
target_version_input = gr.Textbox(label="Target Version", lines=1, placeholder="e.g. previous")
step_btn = gr.Button("โถ๏ธ Execute Action", variant="primary", size="lg")
gr.HTML('<div class="section-title">๐ Controls</div>')
with gr.Row():
grade_btn = gr.Button("๐ Grade", variant="secondary", size="sm")
state_btn = gr.Button("๐ State", variant="secondary", size="sm")
gr.HTML('<div class="section-title">๐ State</div>')
state_display = gr.Markdown("### โณ Ready\n\nSelect task โ Reset โ Begin")
with gr.Column(scale=3, min_width=480):
gr.HTML('<div class="section-title">๐๏ธ Observation</div>')
obs_display = gr.Markdown("### ๐ Welcome\n\nSelect a task and click **Reset** to begin.")
gr.HTML('<div class="section-title">๐ History</div>')
history_display = gr.Markdown("*No actions yet.*")
gr.HTML('<div class="section-title">๐ฐ Reward</div>')
reward_display = gr.Markdown("*Start an episode first.*")
reset_btn.click(fn=_gr_reset, inputs=[task_dd, scenario_dd],
outputs=[obs_display, state_display, history_display, reward_display, service_dd])
step_btn.click(fn=_gr_step,
inputs=[action_type_dd, service_dd, severity_dd, failure_mode_input,
summary_input, flag_input, runbook_input, target_version_input],
outputs=[obs_display, state_display, history_display, reward_display])
grade_btn.click(fn=_gr_grade, outputs=[reward_display])
state_btn.click(fn=_gr_state, outputs=[state_display])
app = gr.mount_gradio_app(app, demo, path="/")
def main():
"""Start the OpenEnv server."""
import uvicorn
uvicorn.run("server.app:app", host="0.0.0.0", port=7860, reload=False)
if __name__ == "__main__":
main() |