refactor(chat): add streaming/shared/ package for StreamResult and utils

Foundation layer for the parallel refactor of stream_new_chat.py.
Extracts the StreamResult dataclass (tracks per-turn streaming state)
and a small set of shared utilities (resume_step_prefix, safe_float).

Add-only; no existing code imports from this package yet. Existing
stream_new_chat.py keeps its inline equivalents until cutover.

surfsense_backend/app/tasks/chat/streaming/shared/__init__.py

@@ -0,0 +1,15 @@
+"""Shared building blocks used across every streaming flow."""
+
+from __future__ import annotations
+
+from app.tasks.chat.streaming.shared.stream_result import StreamResult
+from app.tasks.chat.streaming.shared.utils import (
+    resume_step_prefix,
+    safe_float,
+)
+
+__all__ = [
+    "StreamResult",
+    "resume_step_prefix",
+    "safe_float",
+]

surfsense_backend/app/tasks/chat/streaming/shared/stream_result.py

@@ -0,0 +1,37 @@
+"""Per-turn streaming state shared between the orchestrator and event loop."""
+
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import Any
+
+
+@dataclass
+class StreamResult:
+    accumulated_text: str = ""
+    is_interrupted: bool = False
+    sandbox_files: list[str] = field(default_factory=list)
+    request_id: str | None = None
+    turn_id: str = ""
+    filesystem_mode: str = "cloud"
+    client_platform: str = "web"
+    intent_detected: str = "chat_only"
+    intent_confidence: float = 0.0
+    write_attempted: bool = False
+    write_succeeded: bool = False
+    verification_succeeded: bool = False
+    commit_gate_passed: bool = True
+    commit_gate_reason: str = ""
+    # Pre-allocated assistant ``new_chat_messages.id`` for this turn, captured by
+    # ``persist_assistant_shell`` right after the user row is persisted. ``None``
+    # for the legacy/anonymous code paths that don't opt in to server-side
+    # ``ContentPart[]`` projection.
+    assistant_message_id: int | None = None
+    # In-memory mirror of the FE's assistant-ui ``ContentPartsState``, populated
+    # by the lifecycle methods called from the streaming event loop at each
+    # ``streaming_service.format_*`` yield site. Snapshot in the streaming
+    # ``finally`` to produce the rich JSONB persisted by
+    # ``finalize_assistant_turn``. ``repr=False`` keeps the log-on-error path
+    # (``StreamResult`` is logged in some error branches) from dumping a
+    # potentially-large parts list.
+    content_builder: Any | None = field(default=None, repr=False)

surfsense_backend/app/tasks/chat/streaming/shared/utils.py

@@ -0,0 +1,27 @@
+"""Small utilities used by streaming orchestrators and phases."""
+
+from __future__ import annotations
+
+from typing import Any
+
+
+def resume_step_prefix(turn_id: str) -> str:
+    """Per-turn ``step_prefix`` for resume invocations.
+
+    Each ``stream_agent_events`` call constructs a fresh
+    ``AgentEventRelayState`` with ``thinking_step_counter=0``, so two consecutive
+    resume turns would otherwise both emit ``thinking-resume-1``, ``-2`` etc.
+    The frontend rehydrates ``currentThinkingSteps`` from the immediate prior
+    assistant message at the start of every resume — if the new stream's IDs
+    collide with the seeded ones, React renders sibling Timeline rows with the
+    same key. Salting with ``turn_id`` guarantees disjoint IDs across resumes
+    within one thread.
+    """
+    return f"thinking-resume-{turn_id}"
+
+
+def safe_float(value: Any, default: float = 0.0) -> float:
+    try:
+        return float(value)
+    except (TypeError, ValueError):
+        return default