fix(ci): resolve ruff linter and format errors

openadapt_ml/benchmarks/azure_ops_tracker.py

@@ -160,7 +160,9 @@ def start_operation(
             log_tail=[],  # Clear stale logs
             started_at=self._start_time.isoformat(),
             elapsed_seconds=0.0,
-            eta_seconds=TYPICAL_DURATIONS.get(operation),  # Use typical duration as initial ETA
+            eta_seconds=TYPICAL_DURATIONS.get(
+                operation
+            ),  # Use typical duration as initial ETA
             cost_usd=0.0,
             hourly_rate_usd=self.hourly_rate,
             vm_ip=vm_ip,
@@ -284,7 +286,9 @@ def parse_docker_build_line(self, line: str) -> dict[str, Any]:
             downloaded_unit = download_match.group(2)
             total = float(download_match.group(3))
             total_unit = download_match.group(4)
-            result["download_bytes"] = int(downloaded * size_multipliers[downloaded_unit])
+            result["download_bytes"] = int(
+                downloaded * size_multipliers[downloaded_unit]
+            )
             result["download_total_bytes"] = int(total * size_multipliers[total_unit])
 
         # Extract phase from buildx output
@@ -384,7 +388,9 @@ def _update_progress(self) -> None:
 
             # ETA from download speed
             if self._status.download_bytes > 0 and self._status.elapsed_seconds > 1:
-                bytes_per_sec = self._status.download_bytes / self._status.elapsed_seconds
+                bytes_per_sec = (
+                    self._status.download_bytes / self._status.elapsed_seconds
+                )
                 remaining_bytes = (
                     self._status.download_total_bytes - self._status.download_bytes
                 )
@@ -402,9 +408,15 @@ def _update_progress(self) -> None:
                 remaining_steps = self._status.total_steps - self._status.step
                 step_eta = time_per_step * remaining_steps
                 # Use step ETA if we don't have download ETA or if step progress > download
-                if eta_seconds is None or step_pct > (
-                    self._status.download_bytes / max(self._status.download_total_bytes, 1)
-                ) * 100:
+                if (
+                    eta_seconds is None
+                    or step_pct
+                    > (
+                        self._status.download_bytes
+                        / max(self._status.download_total_bytes, 1)
+                    )
+                    * 100
+                ):
                     eta_seconds = step_eta
 
         # 3. Fallback: Use typical duration if no progress info

openadapt_ml/benchmarks/viewer.py

@@ -38,18 +38,10 @@
 
 from __future__ import annotations
 
-import warnings
-
-warnings.warn(
-    "openadapt_ml.benchmarks.viewer is deprecated. "
-    "Use openadapt_viewer instead: from openadapt_viewer import generate_benchmark_viewer",
-    DeprecationWarning,
-    stacklevel=2,
-)
-
 import base64
 import json
 import logging
+import warnings
 from pathlib import Path
 from typing import Any
 
@@ -58,6 +50,13 @@
     generate_shared_header_html as _generate_shared_header_html,
 )
 
+warnings.warn(
+    "openadapt_ml.benchmarks.viewer is deprecated. "
+    "Use openadapt_viewer instead: from openadapt_viewer import generate_benchmark_viewer",
+    DeprecationWarning,
+    stacklevel=2,
+)
+
 logger = logging.getLogger(__name__)
 
 

openadapt_ml/benchmarks/vm_monitor.py

@@ -1014,7 +1014,9 @@ def detect_vm_activity(
                 return VMActivity(
                     is_active=is_running,
                     activity_type="benchmark_running" if is_running else "idle",
-                    description="WAA benchmark running" if is_running else "WAA ready - idle",
+                    description="WAA benchmark running"
+                    if is_running
+                    else "WAA ready - idle",
                     benchmark_progress=probe_data,
                 )
             except json.JSONDecodeError:

openadapt_ml/benchmarks/waa_deploy/api_agent.py

@@ -43,7 +43,7 @@
 import os
 import re
 from io import BytesIO
-from typing import Any, Dict, List
+from typing import Dict, List
 
 from PIL import Image
 
@@ -210,6 +210,7 @@ def __init__(
                 )
             try:
                 from anthropic import Anthropic
+
                 self._client = Anthropic(api_key=self.api_key)
             except ImportError:
                 raise RuntimeError(
@@ -225,6 +226,7 @@ def __init__(
                 )
             try:
                 from openai import OpenAI
+
                 self._client = OpenAI(api_key=self.api_key)
             except ImportError:
                 raise RuntimeError(
@@ -240,9 +242,13 @@ def __init__(
         self.memory_block_text = "# empty memory block"
         self.step_counter = 0
 
-        logger.info(f"ApiAgent initialized with provider={provider}, model={self.model}")
+        logger.info(
+            f"ApiAgent initialized with provider={provider}, model={self.model}"
+        )
         if self.demo:
-            logger.info(f"Demo trajectory provided ({len(self.demo)} chars) - will persist across all steps")
+            logger.info(
+                f"Demo trajectory provided ({len(self.demo)} chars) - will persist across all steps"
+            )
 
     def predict(self, instruction: str, obs: Dict) -> tuple:
         """Predict the next action based on observation.
@@ -325,10 +331,9 @@ def predict(self, instruction: str, obs: Dict) -> tuple:
         # Add action history if enabled (enhanced: includes reasoning, not just raw actions)
         if self.use_history and self.history:
             # Use rich history with reasoning (like PC Agent-E)
-            history_entries = self.history[-self.history_cutoff:]
+            history_entries = self.history[-self.history_cutoff :]
             history_str = "\n\n".join(
-                f"[Step {i+1}] {entry}"
-                for i, entry in enumerate(history_entries)
+                f"[Step {i + 1}] {entry}" for i, entry in enumerate(history_entries)
             )
             content_parts.append(f"History of previous steps:\n{history_str}")
             logs["history_entries"] = len(history_entries)
@@ -381,14 +386,18 @@ def predict(self, instruction: str, obs: Dict) -> tuple:
             actions = [code_text]
             self.prev_actions.append(code_text)
             # Store rich history with reasoning (memory + action)
-            self._add_to_history(f"Thought: {self.memory_block_text}\nAction: {code_text}")
+            self._add_to_history(
+                f"Thought: {self.memory_block_text}\nAction: {code_text}"
+            )
         else:
             # Try to extract action from response text
             action = self._parse_action_from_text(response_text, w, h)
             if action:
                 actions = [action]
                 self.prev_actions.append(action)
-                self._add_to_history(f"Thought: {self.memory_block_text}\nAction: {action}")
+                self._add_to_history(
+                    f"Thought: {self.memory_block_text}\nAction: {action}"
+                )
             else:
                 logger.warning("Could not extract action from response")
                 actions = ["# Could not parse action"]
@@ -483,33 +492,25 @@ def _parse_action_from_text(self, text: str, width: int, height: int) -> str | N
             Python code string or None if parsing failed.
         """
         # Try to find click coordinates
-        click_match = re.search(
-            r"click.*?(\d+)\s*,\s*(\d+)", text, re.IGNORECASE
-        )
+        click_match = re.search(r"click.*?(\d+)\s*,\s*(\d+)", text, re.IGNORECASE)
         if click_match:
             x, y = int(click_match.group(1)), int(click_match.group(2))
             return f"computer.click({x}, {y})"
 
         # Try to find type text
-        type_match = re.search(
-            r'type[:\s]+["\'](.+?)["\']', text, re.IGNORECASE
-        )
+        type_match = re.search(r'type[:\s]+["\'](.+?)["\']', text, re.IGNORECASE)
         if type_match:
             text_to_type = type_match.group(1)
             return f'computer.type("{text_to_type}")'
 
         # Try to find key press
-        key_match = re.search(
-            r"press[:\s]+(\w+)", text, re.IGNORECASE
-        )
+        key_match = re.search(r"press[:\s]+(\w+)", text, re.IGNORECASE)
         if key_match:
             key = key_match.group(1).lower()
             return f'computer.press("{key}")'
 
         # Try to find hotkey
-        hotkey_match = re.search(
-            r"hotkey[:\s]+(\w+)\s*\+\s*(\w+)", text, re.IGNORECASE
-        )
+        hotkey_match = re.search(r"hotkey[:\s]+(\w+)\s*\+\s*(\w+)", text, re.IGNORECASE)
         if hotkey_match:
             key1, key2 = hotkey_match.group(1).lower(), hotkey_match.group(2).lower()
             return f'computer.hotkey("{key1}", "{key2}")'

openadapt_ml/cloud/local.py

@@ -1078,11 +1078,17 @@ def do_GET(self):
                         status["session_id"] = session.get("session_id")
                         status["session_is_active"] = session.get("is_active", False)
                         # Include accumulated time from previous sessions for hybrid display
-                        status["accumulated_seconds"] = session.get("accumulated_seconds", 0.0)
+                        status["accumulated_seconds"] = session.get(
+                            "accumulated_seconds", 0.0
+                        )
                         # Calculate current session time (total - accumulated)
-                        current_session_seconds = max(0, status["elapsed_seconds"] - status["accumulated_seconds"])
+                        current_session_seconds = max(
+                            0, status["elapsed_seconds"] - status["accumulated_seconds"]
+                        )
                         status["current_session_seconds"] = current_session_seconds
-                        status["current_session_cost_usd"] = (current_session_seconds / 3600) * session.get("hourly_rate_usd", 0.422)
+                        status["current_session_cost_usd"] = (
+                            current_session_seconds / 3600
+                        ) * session.get("hourly_rate_usd", 0.422)
 
                     try:
                         tunnel_mgr = get_tunnel_manager()
@@ -3212,12 +3218,18 @@ def compute_server_side_values(status: dict) -> dict:
                     status["session_id"] = session.get("session_id")
                     status["session_is_active"] = session.get("is_active", False)
                     # Include accumulated time from previous sessions for hybrid display
-                    status["accumulated_seconds"] = session.get("accumulated_seconds", 0.0)
+                    status["accumulated_seconds"] = session.get(
+                        "accumulated_seconds", 0.0
+                    )
                     # Calculate current session time (total - accumulated)
-                    current_session_seconds = max(0, status["elapsed_seconds"] - status["accumulated_seconds"])
+                    current_session_seconds = max(
+                        0, status["elapsed_seconds"] - status["accumulated_seconds"]
+                    )
                     status["current_session_seconds"] = current_session_seconds
                     hourly_rate = session.get("hourly_rate_usd", 0.422)
-                    status["current_session_cost_usd"] = (current_session_seconds / 3600) * hourly_rate
+                    status["current_session_cost_usd"] = (
+                        current_session_seconds / 3600
+                    ) * hourly_rate
 
                 try:
                     tunnel_mgr = get_tunnel_manager()

openadapt_ml/scripts/capture_screenshots.py

@@ -35,9 +35,7 @@
 from __future__ import annotations
 
 import argparse
-import base64
 import datetime
-import os
 import re
 import subprocess
 import sys
@@ -108,7 +106,6 @@ def capture_web_page_selenium(url: str, output_path: Path) -> bool:
     try:
         from selenium import webdriver
         from selenium.webdriver.chrome.options import Options
-        from selenium.webdriver.chrome.service import Service
 
         options = Options()
         options.add_argument("--headless")
@@ -358,7 +355,9 @@ def capture_vm_screenshot_from_vm(output_path: Path) -> bool:
     )
 
     if result.returncode != 0:
-        print(f"  VM screenshot failed: {result.stderr[:200] if result.stderr else 'Unknown error'}")
+        print(
+            f"  VM screenshot failed: {result.stderr[:200] if result.stderr else 'Unknown error'}"
+        )
         return False
 
     # The CLI saves to training_output/current/vm_screenshot.png
@@ -499,7 +498,7 @@ def main():
                 print(f"  OK: {output_path.name} ({size_kb:.1f} KB)")
                 results[target] = str(output_path)
             else:
-                print(f"  SKIP: Not available or capture failed")
+                print("  SKIP: Not available or capture failed")
                 results[target] = None
         except Exception as e:
             print(f"  ERROR: {e}")

openadapt_ml/training/viewer.py

@@ -13,7 +13,14 @@
 
 from __future__ import annotations
 
+import json
 import warnings
+from pathlib import Path
+
+from openadapt_ml.training.shared_ui import (
+    get_shared_header_css as _get_shared_header_css,
+    generate_shared_header_html as _generate_shared_header_html,
+)
 
 warnings.warn(
     "openadapt_ml.training.viewer is deprecated. "
@@ -22,14 +29,6 @@
     stacklevel=2,
 )
 
-import json
-from pathlib import Path
-
-from openadapt_ml.training.shared_ui import (
-    get_shared_header_css as _get_shared_header_css,
-    generate_shared_header_html as _generate_shared_header_html,
-)
-
 
 def _copy_transcript_and_audio(capture_path: Path | None, output_dir: Path) -> None:
     """Copy transcript.json and convert audio to mp3 for viewer playback.