chore: import upstream snapshot with attribution

application/logging.py

@@ -0,0 +1,268 @@
+import datetime
+import functools
+import inspect
+import time
+
+import logging
+import uuid
+from typing import Any, Callable, Dict, Generator, List
+
+from application.core import log_context
+from application.storage.db.repositories.stack_logs import StackLogsRepository
+from application.storage.db.session import db_session
+
+logging.basicConfig(
+    level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s"
+)
+
+
+class LogContext:
+    def __init__(self, endpoint, activity_id, user, api_key, query):
+        self.endpoint = endpoint
+        self.activity_id = activity_id
+        self.user = user
+        self.api_key = api_key
+        self.query = query
+        self.stacks = []
+        # Per-activity response aggregates populated by ``_consume_and_log``
+        # while it forwards stream items, then flushed onto the
+        # ``activity_finished`` event so every Flask request gets the
+        # same summary that ``run_agent_logic`` used to log only for the
+        # Celery webhook path.
+        self.answer_length = 0
+        self.thought_length = 0
+        self.source_count = 0
+        self.tool_call_count = 0
+
+
+def build_stack_data(
+    obj: Any,
+    include_attributes: List[str] = None,
+    exclude_attributes: List[str] = None,
+    custom_data: Dict = None,
+) -> Dict:
+    if obj is None:
+        raise ValueError("The 'obj' parameter cannot be None")
+    data = {}
+    if include_attributes is None:
+        include_attributes = []
+        for name, value in inspect.getmembers(obj):
+            if (
+                not name.startswith("_")
+                and not inspect.ismethod(value)
+                and not inspect.isfunction(value)
+            ):
+                include_attributes.append(name)
+    for attr_name in include_attributes:
+        if exclude_attributes and attr_name in exclude_attributes:
+            continue
+        try:
+            attr_value = getattr(obj, attr_name)
+            if attr_value is not None:
+                if isinstance(attr_value, (int, float, str, bool)):
+                    data[attr_name] = attr_value
+                elif isinstance(attr_value, list):
+                    if all(isinstance(item, dict) for item in attr_value):
+                        data[attr_name] = attr_value
+                    elif all(hasattr(item, "__dict__") for item in attr_value):
+                        data[attr_name] = [item.__dict__ for item in attr_value]
+                    else:
+                        data[attr_name] = [str(item) for item in attr_value]
+                elif isinstance(attr_value, dict):
+                    data[attr_name] = {k: str(v) for k, v in attr_value.items()}
+        except AttributeError as e:
+            logging.warning(f"AttributeError while accessing {attr_name}: {e}")
+        except AttributeError:
+            pass
+    if custom_data:
+        data.update(custom_data)
+    return data
+
+
+def log_activity() -> Callable:
+    def decorator(func: Callable) -> Callable:
+        @functools.wraps(func)
+        def wrapper(*args: Any, **kwargs: Any) -> Any:
+            activity_id = str(uuid.uuid4())
+            data = build_stack_data(args[0])
+            endpoint = data.get("endpoint", "")
+            user = data.get("user", "local")
+            api_key = data.get("user_api_key", "")
+            query = kwargs.get("query", getattr(args[0], "query", ""))
+            agent_id = getattr(args[0], "agent_id", None) or kwargs.get("agent_id")
+            conversation_id = (
+                kwargs.get("conversation_id")
+                or getattr(args[0], "conversation_id", None)
+            )
+            model = getattr(args[0], "gpt_model", None) or getattr(args[0], "model", None)
+
+            # Capture the surrounding activity_id before overlaying ours,
+            # so nested activities record the parent → child link.
+            parent_activity_id = log_context.snapshot().get("activity_id")
+
+            context = LogContext(endpoint, activity_id, user, api_key, query)
+            kwargs["log_context"] = context
+
+            ctx_token = log_context.bind(
+                activity_id=activity_id,
+                parent_activity_id=parent_activity_id,
+                user_id=user,
+                agent_id=agent_id,
+                conversation_id=conversation_id,
+                endpoint=endpoint,
+                model=model,
+            )
+
+            started_at = time.monotonic()
+            logging.info(
+                "activity_started",
+                extra={
+                    "activity_id": activity_id,
+                    "parent_activity_id": parent_activity_id,
+                    "user_id": user,
+                    "agent_id": agent_id,
+                    "conversation_id": conversation_id,
+                    "endpoint": endpoint,
+                    "model": model,
+                },
+            )
+
+            error: BaseException | None = None
+            try:
+                generator = func(*args, **kwargs)
+                yield from _consume_and_log(generator, context)
+            except Exception as exc:
+                # Only ``Exception`` counts as an activity error; ``GeneratorExit``
+                # (consumer disconnected mid-stream) and ``KeyboardInterrupt``
+                # flow through the finally as ``status="ok"``, matching
+                # ``_consume_and_log``.
+                error = exc
+                raise
+            finally:
+                _emit_activity_finished(
+                    context=context,
+                    parent_activity_id=parent_activity_id,
+                    started_at=started_at,
+                    error=error,
+                )
+                log_context.reset(ctx_token)
+
+        return wrapper
+
+    return decorator
+
+
+def _emit_activity_finished(
+    *,
+    context: "LogContext",
+    parent_activity_id: str | None,
+    started_at: float,
+    error: BaseException | None,
+) -> None:
+    """Emit the paired ``activity_finished`` event with duration, outcome,
+    and per-activity response aggregates accumulated in ``_consume_and_log``.
+    """
+    duration_ms = int((time.monotonic() - started_at) * 1000)
+    logging.info(
+        "activity_finished",
+        extra={
+            "activity_id": context.activity_id,
+            "parent_activity_id": parent_activity_id,
+            "user_id": context.user,
+            "endpoint": context.endpoint,
+            "duration_ms": duration_ms,
+            "status": "error" if error is not None else "ok",
+            "error_class": type(error).__name__ if error is not None else None,
+            "answer_length": context.answer_length,
+            "thought_length": context.thought_length,
+            "source_count": context.source_count,
+            "tool_call_count": context.tool_call_count,
+        },
+    )
+
+
+def _accumulate_response_summary(item: Any, context: "LogContext") -> None:
+    """Mirror the per-line aggregation that ``run_agent_logic`` did for the
+    Celery webhook path, but at the generator-consumption layer so every
+    ``Agent.gen`` activity (Flask streaming, sub-agents, workflow agents)
+    gets the same summary.
+    """
+    if not isinstance(item, dict):
+        return
+    if "answer" in item:
+        context.answer_length += len(str(item["answer"]))
+        return
+    if "thought" in item:
+        context.thought_length += len(str(item["thought"]))
+        return
+    sources = item.get("sources") if "sources" in item else None
+    if isinstance(sources, list):
+        context.source_count += len(sources)
+        return
+    tool_calls = item.get("tool_calls") if "tool_calls" in item else None
+    if isinstance(tool_calls, list):
+        context.tool_call_count += len(tool_calls)
+
+
+def _consume_and_log(generator: Generator, context: "LogContext"):
+    try:
+        for item in generator:
+            _accumulate_response_summary(item, context)
+            yield item
+    except Exception as e:
+        logging.exception(f"Error in {context.endpoint} - {context.activity_id}: {e}")
+        context.stacks.append({"component": "error", "data": {"message": str(e)}})
+        _log_activity_to_db(
+            endpoint=context.endpoint,
+            activity_id=context.activity_id,
+            user=context.user,
+            api_key=context.api_key,
+            query=context.query,
+            stacks=context.stacks,
+            level="error",
+        )
+        raise
+    finally:
+        _log_activity_to_db(
+            endpoint=context.endpoint,
+            activity_id=context.activity_id,
+            user=context.user,
+            api_key=context.api_key,
+            query=context.query,
+            stacks=context.stacks,
+            level="info",
+        )
+
+
+def _log_activity_to_db(
+    endpoint: str,
+    activity_id: str,
+    user: str,
+    api_key: str,
+    query: str,
+    stacks: List[Dict],
+    level: str,
+) -> None:
+    """Append a per-request activity log row to Postgres (``stack_logs``)."""
+    try:
+        # Clean up text fields to be no longer than 10000 characters so a
+        # runaway payload can't blow up the insert.
+        def _truncate(val):
+            if isinstance(val, str) and len(val) > 10000:
+                return val[:10000]
+            return val
+
+        with db_session() as conn:
+            StackLogsRepository(conn).insert(
+                activity_id=activity_id,
+                endpoint=_truncate(endpoint),
+                level=_truncate(level),
+                user_id=_truncate(user),
+                api_key=_truncate(api_key),
+                query=_truncate(query),
+                stacks=stacks,
+                timestamp=datetime.datetime.now(datetime.timezone.utc),
+            )
+        logging.debug(f"Logged activity to Postgres: {activity_id}")
+    except Exception as e:
+        logging.error(f"Failed to log activity to Postgres: {e}", exc_info=True)