ci: automated safe autofixes

scripts/dashboard.py

@@ -164,7 +164,8 @@ def print_architecture():
     """Display system architecture."""
     print("🏗️  Aria Platform Architecture")
     print()
-    print("""
+    print(
+        """
    Frontend Layer:
    ├─ Aria Web UI (http://localhost:8080)
    │  └─ Interactive 3D character with voice/text I/O
@@ -203,7 +204,8 @@ def print_architecture():
    ├─ Logs: data_out/*/
    ├─ Config: config/
    └─ Monitoring: status.json files
-    """)
+    """
+    )
 
 
 def main():
@@ -225,7 +227,8 @@ def main():
     print_architecture()
 
     print_header("Next Steps")
-    print("""
+    print(
+        """
 1️⃣  START BACKEND SERVICES
    $ func host start                    # Start Azure Functions on port 7071
    $ cd apps/aria && python server.py   # Start Aria server on port 8080
@@ -249,7 +252,8 @@ def main():
    • AUTONOMOUS_TRAINING_REPORT.md — Detailed training analysis
    • ARIA_QUICKREF.txt — Quick reference guide
    • .github/copilot-instructions.md — Complete architecture docs
-   """)
+   """
+    )
 
     print("=" * 70 + "\n")
 

scripts/demo_quantum_llm.py

@@ -95,7 +95,8 @@ def demonstrate_quantum_llm_integration():
     # 4. Show workflow
     print("\n\n🔄 Training Workflow:")
     print("-" * 80)
-    print("""
+    print(
+        """
     Autonomous Training Cycle (every 30 minutes):
     ├── 1. Discover datasets (quantum, chat, vision)
     ├── 2. Download new datasets if needed
@@ -121,12 +122,14 @@ def demonstrate_quantum_llm_integration():
     - Quantum feature encoding for richer representations
     - Hybrid quantum-classical architecture
     - Cost-aware execution (local simulator vs Azure Quantum)
-    """)
+    """
+    )
 
     # 5. Show command examples
     print("\n📝 Usage Examples:")
     print("-" * 80)
-    print("""
+    print(
+        """
     # Active Training (single run)
     python scripts/quantum_llm_trainer.py \\
       --dataset datasets/chat/aria_chat \\
@@ -147,12 +150,14 @@ def demonstrate_quantum_llm_integration():
     # Full Repository Automation
     python scripts/repo_automation.py --start
     # (Includes quantum LLM training in the full automation suite)
-    """)
+    """
+    )
 
     # 6. Show benefits
     print("\n\n✨ Key Benefits:")
     print("-" * 80)
-    print("""
+    print(
+        """
     1. Quantum Advantage:
        - Exponential feature space (2^n for n qubits)
        - Novel attention optimization patterns
@@ -177,7 +182,8 @@ def demonstrate_quantum_llm_integration():
        - Track quantum circuit executions
        - Monitor quantum advantage ratio
        - Detailed metrics and logging
-    """)
+    """
+    )
 
     # 7. Show status
     print("\n\n📊 Current Status:")

scripts/gradio_hello.py

@@ -1043,7 +1043,8 @@ def run_llm_smoke_test(
 
 with gr.Blocks() as demo:
     with gr.Column(elem_id="appCard"):
-        gr.HTML("""
+        gr.HTML(
+            """
             <div class="hero-banner">
                 <div style="display:flex;align-items:center;gap:14px;">
                     <span style="font-size:2.4rem;line-height:1;filter:drop-shadow(0 2px 6px rgba(20,83,45,0.16));">🌿</span>
@@ -1059,7 +1060,8 @@ def run_llm_smoke_test(
                     <span class="pill">🎙️&nbsp;TTS support</span>
                 </div>
             </div>
-            """)
+            """
+        )
 
         with gr.Row(equal_height=False):
             with gr.Column(scale=7, elem_id="surfaceBlock", elem_classes=["surface-card"]):

scripts/setup_env_check.py

@@ -352,7 +352,8 @@ def print_next_steps() -> None:
     """Print recommended next steps."""
     print_section("Next Steps")
 
-    print(f"""
+    print(
+        f"""
 {BOLD}1. Start Services:{RESET}
    • Ollama:    ollama serve
    • LM Studio: lm-studio (GUI application)
@@ -376,7 +377,8 @@ def print_next_steps() -> None:
     • Quick start:     cat QUICK_START_AUTOMATION.md
     • Automation:      cat AUTOMATION_RUNNER.md
     • Watch status:    python3 scripts/watch_continuous_automation.py
-""")
+"""
+    )
 
 
 def main() -> int:

shared/agi_persistence_sqlite.py

@@ -34,15 +34,17 @@ def __init__(self, path: str) -> None:
             self._conn.execute("PRAGMA synchronous=NORMAL;")
         except Exception:
             pass
-        self._conn.execute("""
+        self._conn.execute(
+            """
             CREATE TABLE IF NOT EXISTS agi_events (
                 id TEXT PRIMARY KEY,
                 ts REAL,
                 type TEXT,
                 meta TEXT,
                 payload TEXT
             )
-            """)
+            """
+        )
         self._conn.commit()
 
     def write_reasoning_chain(self, chain: list[dict[str, Any]], meta: dict[str, Any] | None = None) -> str:

shared/chat_memory.py

@@ -377,7 +377,8 @@ def fetch_similar_messages(
                     (scoped_session_id,),
                 )
             else:
-                cur.execute("""
+                cur.execute(
+                    """
                     SELECT
                         e.message_id,
                         e.embedding_vector,
@@ -387,7 +388,8 @@ def fetch_similar_messages(
                     FROM embeddings e
                     LEFT JOIN chat_messages cm ON cm.message_id = e.message_id
                     LEFT JOIN messages m ON m.message_id = e.message_id
-                    """)
+                    """
+                )
             rows = cur.fetchall()
             has_joined_metadata = True
         except Exception:

shared/db_logging.py

@@ -132,7 +132,9 @@ def _parse_quantum_summary() -> dict[str, Any]:
         return {}
 
 
-def log_quantum_run_safe(job, result: dict[str, Any], dataset_name: str, log_path: str) -> dict[str, Any]:  # noqa: ANN001
+def log_quantum_run_safe(
+    job, result: dict[str, Any], dataset_name: str, log_path: str
+) -> dict[str, Any]:  # noqa: ANN001
     """Best-effort quantum run logging; returns a skip/error dict on failure."""
     conn = _get_conn()
     if not conn:

shared/runtime_env.py

@@ -71,7 +71,8 @@ def probe_python_packages(
             "error": f"Python executable not found: {python}",
         }
 
-    code = dedent(f"""
+    code = dedent(
+        f"""
         import importlib.metadata as md
         import importlib.util
         import json
@@ -86,7 +87,8 @@ def probe_python_packages(
                 vers[m] = None
 
         print(json.dumps({{'available': avail, 'versions': vers}}))
-        """).strip()
+        """
+    ).strip()
 
     try:
         proc = subprocess.run(