Add LLM request/response logging to database

Log every LLM call (analysis, chat, image, raw_analyze) to a new
LlmLog table with request type, model, token counts, duration,
success/failure, and truncated request/response payloads. Enables
debugging prompt issues and tracking usage.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

utils/database.py

@@ -126,6 +126,23 @@ class Database:
                 ALTER TABLE UserState ADD UserNotes NVARCHAR(MAX) NULL
         """)
 
+        cursor.execute("""
+            IF NOT EXISTS (SELECT * FROM sys.tables WHERE name = 'LlmLog')
+            CREATE TABLE LlmLog (
+                Id            BIGINT IDENTITY(1,1) PRIMARY KEY,
+                RequestType   NVARCHAR(50) NOT NULL,
+                Model         NVARCHAR(100) NOT NULL,
+                InputTokens   INT NULL,
+                OutputTokens  INT NULL,
+                DurationMs    INT NOT NULL,
+                Success       BIT NOT NULL,
+                Request       NVARCHAR(MAX) NOT NULL,
+                Response      NVARCHAR(MAX) NULL,
+                Error         NVARCHAR(MAX) NULL,
+                CreatedAt     DATETIME2 NOT NULL DEFAULT SYSUTCDATETIME()
+            )
+        """)
+
         cursor.close()
 
     def _parse_database_name(self) -> str:
@@ -348,6 +365,55 @@ class Database:
         finally:
             conn.close()
 
+    # ------------------------------------------------------------------
+    # LLM Log (fire-and-forget via asyncio.create_task)
+    # ------------------------------------------------------------------
+    async def save_llm_log(
+        self,
+        request_type: str,
+        model: str,
+        duration_ms: int,
+        success: bool,
+        request: str,
+        response: str | None = None,
+        error: str | None = None,
+        input_tokens: int | None = None,
+        output_tokens: int | None = None,
+    ) -> None:
+        """Save an LLM request/response log entry."""
+        if not self._available:
+            return
+        try:
+            await asyncio.to_thread(
+                self._save_llm_log_sync,
+                request_type, model, duration_ms, success, request,
+                response, error, input_tokens, output_tokens,
+            )
+        except Exception:
+            logger.exception("Failed to save LLM log")
+
+    def _save_llm_log_sync(
+        self, request_type, model, duration_ms, success, request,
+        response, error, input_tokens, output_tokens,
+    ):
+        conn = self._connect()
+        try:
+            cursor = conn.cursor()
+            cursor.execute(
+                """INSERT INTO LlmLog
+                   (RequestType, Model, InputTokens, OutputTokens, DurationMs,
+                    Success, Request, Response, Error)
+                   VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)""",
+                request_type, model, input_tokens, output_tokens, duration_ms,
+                1 if success else 0,
+                request[:4000] if request else "",
+                response[:4000] if response else None,
+                error[:4000] if error else None,
+            )
+            cursor.close()
+        finally:
+            conn.close()
+
     async def close(self):
         """No persistent connection to close (connections are per-operation)."""
         pass