mirror of
https://github.com/MODSetter/SurfSense.git
synced 2026-05-13 09:42:40 +02:00
feat: improved document, folder mentions rendering
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This commit is contained in:
parent
28a02a9143
commit
c8374e6c5b
59 changed files with 1725 additions and 361 deletions
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@ -51,7 +51,9 @@ logger = logging.getLogger(__name__)
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_MEANINGFUL_PART_TYPES: frozenset[str] = frozenset({"text", "reasoning", "tool-call"})
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def _merge_tool_part_metadata(part: dict[str, Any], metadata: dict[str, Any] | None) -> None:
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def _merge_tool_part_metadata(
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part: dict[str, Any], metadata: dict[str, Any] | None
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) -> None:
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"""Shallow-merge ``metadata`` into ``part["metadata"]``; first key wins.
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Used for tool-call linkage (``spanId``, ``thinkingStepId``, …): a later
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@ -109,17 +109,18 @@ def _build_user_content(
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[{"type": "text", "text": "..."},
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{"type": "image", "image": "data:..."},
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{"type": "mentioned-documents", "documents": [{"id": int,
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"title": str, "document_type": str}, ...]}]
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"title": str, "document_type": str, "kind": "doc" | "folder"},
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...]}]
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The companion reader is
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``app.utils.user_message_multimodal.split_persisted_user_content_parts``
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which expects exactly this shape — keep them in sync.
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``mentioned_documents``: optional list of ``{id, title, document_type}``
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dicts. When non-empty (and a ``mentioned-documents`` part is not already
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in some other input shape), a single ``{"type": "mentioned-documents",
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"documents": [...]}`` part is appended. Mirrors the FE injection at
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``page.tsx:281-286`` (``persistUserTurn``).
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``mentioned_documents``: optional list of mention chip dicts. Each
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dict may include a ``kind`` discriminator (``"doc"`` or ``"folder"``)
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so the persisted ContentPart round-trips folder chips on reload.
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When ``kind`` is missing we default to ``"doc"`` so legacy clients
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that haven't migrated to the union schema still persist correctly.
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"""
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parts: list[dict[str, Any]] = [{"type": "text", "text": user_query or ""}]
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for url in user_image_data_urls or ():
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@ -135,11 +136,14 @@ def _build_user_content(
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document_type = doc.get("document_type")
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if doc_id is None or title is None or document_type is None:
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continue
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kind_raw = doc.get("kind", "doc")
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kind = kind_raw if kind_raw in ("doc", "folder") else "doc"
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normalized.append(
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{
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"id": doc_id,
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"title": str(title),
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"document_type": str(document_type),
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"kind": kind,
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}
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)
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if normalized:
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@ -43,6 +43,7 @@ from app.agents.new_chat.memory_extraction import (
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extract_and_save_memory,
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extract_and_save_team_memory,
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)
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from app.agents.new_chat.mention_resolver import resolve_mentions, substitute_in_text
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from app.agents.new_chat.middleware.busy_mutex import (
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end_turn,
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get_cancel_state,
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@ -929,6 +930,7 @@ async def stream_new_chat(
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llm_config_id: int = -1,
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mentioned_document_ids: list[int] | None = None,
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mentioned_surfsense_doc_ids: list[int] | None = None,
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mentioned_folder_ids: list[int] | None = None,
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mentioned_documents: list[dict[str, Any]] | None = None,
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checkpoint_id: str | None = None,
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needs_history_bootstrap: bool = False,
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@ -958,6 +960,7 @@ async def stream_new_chat(
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needs_history_bootstrap: If True, load message history from DB (for cloned chats)
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mentioned_document_ids: Optional list of document IDs mentioned with @ in the chat
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mentioned_surfsense_doc_ids: Optional list of SurfSense doc IDs mentioned with @ in the chat
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mentioned_folder_ids: Optional list of knowledge-base folder IDs mentioned with @ (cloud mode)
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checkpoint_id: Optional checkpoint ID to rewind/fork from (for edit/reload operations)
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Yields:
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@ -1502,6 +1505,53 @@ async def stream_new_chat(
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)
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recent_reports = list(recent_reports_result.scalars().all())
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# Resolve @-mention chips to canonical virtual paths and rewrite
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# the user-typed text so the LLM sees ``\`/documents/...\``` instead
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# of bare ``@title``. The persisted user-message text keeps
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# ``@title`` so chip rendering on reload is unchanged — see
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# ``persistence._build_user_content``.
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#
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# Cloud mode only: local-folder mode keeps the legacy
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# ``@title`` text path; mention support there is a follow-up
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# task because the path scheme (mount-rooted) and the picker
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# UI both need separate work.
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accepted_folder_ids: list[int] = []
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if fs_mode == FilesystemMode.CLOUD.value and (
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mentioned_document_ids
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or mentioned_surfsense_doc_ids
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or mentioned_folder_ids
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or mentioned_documents
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):
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from app.schemas.new_chat import (
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MentionedDocumentInfo as _MentionedDocumentInfo,
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)
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chip_objs: list[_MentionedDocumentInfo] | None = None
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if mentioned_documents:
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chip_objs = []
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for raw in mentioned_documents:
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if isinstance(raw, _MentionedDocumentInfo):
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chip_objs.append(raw)
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continue
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try:
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chip_objs.append(_MentionedDocumentInfo.model_validate(raw))
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except Exception:
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logger.debug(
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"stream_new_chat: dropping malformed mention chip %r",
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raw,
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)
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resolved = await resolve_mentions(
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session,
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search_space_id=search_space_id,
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mentioned_documents=chip_objs,
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mentioned_document_ids=mentioned_document_ids,
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mentioned_surfsense_doc_ids=mentioned_surfsense_doc_ids,
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mentioned_folder_ids=mentioned_folder_ids,
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)
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user_query = substitute_in_text(user_query, resolved.token_to_path)
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accepted_folder_ids = resolved.mentioned_folder_ids
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# Format the user query with context (SurfSense docs + reports only)
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final_query = user_query
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context_parts = []
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@ -1901,6 +1951,9 @@ async def stream_new_chat(
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runtime_context = SurfSenseContextSchema(
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search_space_id=search_space_id,
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mentioned_document_ids=list(mentioned_document_ids or []),
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mentioned_folder_ids=list(
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accepted_folder_ids or mentioned_folder_ids or []
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),
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request_id=request_id,
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turn_id=stream_result.turn_id,
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)
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@ -26,9 +26,7 @@ def handle_report_progress(
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return None, last_active_step_items
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phase = data.get("phase", "")
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topic_items = [
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item for item in last_active_step_items if item.startswith("Topic:")
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]
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topic_items = [item for item in last_active_step_items if item.startswith("Topic:")]
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if phase in ("revising_section", "adding_section"):
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plan_items = [
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@ -56,7 +54,9 @@ def handle_report_progress(
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return frame, new_items
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def handle_document_created(data: dict[str, Any], *, streaming_service: Any) -> str | None:
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def handle_document_created(
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data: dict[str, Any], *, streaming_service: Any
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) -> str | None:
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if not data.get("id"):
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return None
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return streaming_service.format_data(
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@ -13,7 +13,9 @@ from app.tasks.chat.streaming.handlers.tools import (
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)
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from app.tasks.chat.streaming.helpers.tool_output import tool_output_has_error
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from app.tasks.chat.streaming.relay.state import AgentEventRelayState
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from app.tasks.chat.streaming.relay.task_span import clear_task_span_if_delegating_task_ended
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from app.tasks.chat.streaming.relay.task_span import (
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clear_task_span_if_delegating_task_ended,
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)
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from app.tasks.chat.streaming.relay.thinking_step_sse import emit_thinking_step_frame
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@ -32,9 +34,7 @@ def iter_tool_end_frames(
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run_id = event.get("run_id", "")
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tool_name = event.get("name", "unknown_tool")
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raw_output = event.get("data", {}).get("output", "")
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staged_file_path = (
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state.file_path_by_run.pop(run_id, None) if run_id else None
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)
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staged_file_path = state.file_path_by_run.pop(run_id, None) if run_id else None
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if tool_name == "update_memory":
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state.called_update_memory = True
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@ -116,6 +116,4 @@ def iter_tool_end_frames(
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)
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yield from iter_tool_completion_emission_frames(emission_ctx)
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clear_task_span_if_delegating_task_ended(
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state, tool_name=tool_name, run_id=run_id
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)
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clear_task_span_if_delegating_task_ended(state, tool_name=tool_name, run_id=run_id)
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@ -15,7 +15,9 @@ def resolve_start_thinking(tool_name: str, tool_input: Any) -> ToolStartThinking
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def resolve_completed_thinking(
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tool_name: str, tool_output: Any, last_items: list[str],
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tool_name: str,
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tool_output: Any,
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last_items: list[str],
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) -> tuple[str, list[str]]:
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return default_thinking.resolve_completed_thinking(
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tool_name, tool_output, last_items
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@ -23,7 +23,9 @@ def resolve_start_thinking(tool_name: str, tool_input: Any) -> ToolStartThinking
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def resolve_completed_thinking(
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tool_name: str, tool_output: Any, last_items: list[str],
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tool_name: str,
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tool_output: Any,
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last_items: list[str],
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) -> tuple[str, list[str]]:
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del tool_name
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items = last_items
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@ -34,7 +34,9 @@ def resolve_start_thinking(tool_name: str, tool_input: Any) -> ToolStartThinking
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def resolve_completed_thinking(
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tool_name: str, tool_output: Any, last_items: list[str],
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tool_name: str,
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tool_output: Any,
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last_items: list[str],
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) -> tuple[str, list[str]]:
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del tool_name
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items = last_items
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@ -29,7 +29,9 @@ def resolve_start_thinking(tool_name: str, tool_input: Any) -> ToolStartThinking
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def resolve_completed_thinking(
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tool_name: str, tool_output: Any, last_items: list[str],
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tool_name: str,
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tool_output: Any,
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last_items: list[str],
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) -> tuple[str, list[str]]:
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del tool_name
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items = last_items
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@ -44,9 +46,7 @@ def resolve_completed_thinking(
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else "Report"
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)
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word_count = (
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tool_output.get("word_count", 0)
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if isinstance(tool_output, dict)
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else 0
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tool_output.get("word_count", 0) if isinstance(tool_output, dict) else 0
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)
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is_revision = (
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tool_output.get("is_revision", False)
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@ -17,7 +17,9 @@ def resolve_start_thinking(tool_name: str, tool_input: Any) -> ToolStartThinking
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def resolve_completed_thinking(
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tool_name: str, tool_output: Any, last_items: list[str],
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tool_name: str,
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tool_output: Any,
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last_items: list[str],
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) -> tuple[str, list[str]]:
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return default_thinking.resolve_completed_thinking(
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tool_name, tool_output, last_items
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@ -17,7 +17,9 @@ def resolve_start_thinking(tool_name: str, tool_input: Any) -> ToolStartThinking
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def resolve_completed_thinking(
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tool_name: str, tool_output: Any, last_items: list[str],
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tool_name: str,
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tool_output: Any,
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last_items: list[str],
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) -> tuple[str, list[str]]:
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del tool_name
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items = last_items
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@ -21,7 +21,9 @@ def resolve_start_thinking(tool_name: str, tool_input: Any) -> ToolStartThinking
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def resolve_completed_thinking(
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tool_name: str, tool_output: Any, last_items: list[str],
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tool_name: str,
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tool_output: Any,
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last_items: list[str],
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) -> tuple[str, list[str]]:
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del tool_name
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items = last_items
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@ -21,7 +21,9 @@ def resolve_start_thinking(tool_name: str, tool_input: Any) -> ToolStartThinking
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def resolve_completed_thinking(
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tool_name: str, tool_output: Any, last_items: list[str],
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tool_name: str,
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tool_output: Any,
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last_items: list[str],
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) -> tuple[str, list[str]]:
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del tool_output, tool_name
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return ("Editing file", last_items)
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@ -24,9 +24,7 @@ def iter_completion_emission_frames(
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output_text = om.group(1) if om else ""
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thread_id_str = ctx.langgraph_config.get("configurable", {}).get("thread_id", "")
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for sf_match in re.finditer(
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r"^SANDBOX_FILE:\s*(.+)$", output_text, re.MULTILINE
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):
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for sf_match in re.finditer(r"^SANDBOX_FILE:\s*(.+)$", output_text, re.MULTILINE):
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fpath = sf_match.group(1).strip()
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if fpath and fpath not in ctx.stream_result.sandbox_files:
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ctx.stream_result.sandbox_files.append(fpath)
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|
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@ -22,7 +22,9 @@ def resolve_start_thinking(tool_name: str, tool_input: Any) -> ToolStartThinking
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def resolve_completed_thinking(
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tool_name: str, tool_output: Any, last_items: list[str],
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tool_name: str,
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tool_output: Any,
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last_items: list[str],
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) -> tuple[str, list[str]]:
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del tool_name
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items = last_items
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|
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@ -21,7 +21,9 @@ def resolve_start_thinking(tool_name: str, tool_input: Any) -> ToolStartThinking
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def resolve_completed_thinking(
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tool_name: str, tool_output: Any, last_items: list[str],
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tool_name: str,
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tool_output: Any,
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last_items: list[str],
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) -> tuple[str, list[str]]:
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del tool_output, tool_name
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return ("Searching files", last_items)
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|
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@ -25,7 +25,9 @@ def resolve_start_thinking(tool_name: str, tool_input: Any) -> ToolStartThinking
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def resolve_completed_thinking(
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tool_name: str, tool_output: Any, last_items: list[str],
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tool_name: str,
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tool_output: Any,
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last_items: list[str],
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) -> tuple[str, list[str]]:
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del tool_output, tool_name
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return ("Searching content", last_items)
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|
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@ -20,7 +20,9 @@ def resolve_start_thinking(tool_name: str, tool_input: Any) -> ToolStartThinking
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def resolve_completed_thinking(
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tool_name: str, tool_output: Any, last_items: list[str],
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tool_name: str,
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tool_output: Any,
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last_items: list[str],
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) -> tuple[str, list[str]]:
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del tool_name
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if isinstance(tool_output, dict):
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@ -38,9 +40,7 @@ def resolve_completed_thinking(
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paths = [str(p) for p in parsed]
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except (ValueError, SyntaxError):
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paths = [
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line.strip()
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for line in ls_output.strip().split("\n")
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if line.strip()
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line.strip() for line in ls_output.strip().split("\n") if line.strip()
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]
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for p in paths:
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name = p.rstrip("/").split("/")[-1]
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|
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@ -17,11 +17,15 @@ def resolve_start_thinking(tool_name: str, tool_input: Any) -> ToolStartThinking
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d = as_tool_input_dict(tool_input)
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p = d.get("path", "") if isinstance(tool_input, dict) else str(tool_input)
|
||||
display = p if len(p) <= 80 else "…" + p[-77:]
|
||||
return ToolStartThinking(title="Creating folder", items=[display] if display else [])
|
||||
return ToolStartThinking(
|
||||
title="Creating folder", items=[display] if display else []
|
||||
)
|
||||
|
||||
|
||||
def resolve_completed_thinking(
|
||||
tool_name: str, tool_output: Any, last_items: list[str],
|
||||
tool_name: str,
|
||||
tool_output: Any,
|
||||
last_items: list[str],
|
||||
) -> tuple[str, list[str]]:
|
||||
del tool_output, tool_name
|
||||
return ("Creating folder", last_items)
|
||||
|
|
|
|||
|
|
@ -27,7 +27,9 @@ def resolve_start_thinking(tool_name: str, tool_input: Any) -> ToolStartThinking
|
|||
|
||||
|
||||
def resolve_completed_thinking(
|
||||
tool_name: str, tool_output: Any, last_items: list[str],
|
||||
tool_name: str,
|
||||
tool_output: Any,
|
||||
last_items: list[str],
|
||||
) -> tuple[str, list[str]]:
|
||||
del tool_output, tool_name
|
||||
return ("Moving file", last_items)
|
||||
|
|
|
|||
|
|
@ -21,7 +21,9 @@ def resolve_start_thinking(tool_name: str, tool_input: Any) -> ToolStartThinking
|
|||
|
||||
|
||||
def resolve_completed_thinking(
|
||||
tool_name: str, tool_output: Any, last_items: list[str],
|
||||
tool_name: str,
|
||||
tool_output: Any,
|
||||
last_items: list[str],
|
||||
) -> tuple[str, list[str]]:
|
||||
del tool_output, tool_name
|
||||
return ("Reading file", last_items)
|
||||
|
|
|
|||
|
|
@ -22,7 +22,9 @@ def resolve_start_thinking(tool_name: str, tool_input: Any) -> ToolStartThinking
|
|||
|
||||
|
||||
def resolve_completed_thinking(
|
||||
tool_name: str, tool_output: Any, last_items: list[str],
|
||||
tool_name: str,
|
||||
tool_output: Any,
|
||||
last_items: list[str],
|
||||
) -> tuple[str, list[str]]:
|
||||
del tool_output, tool_name
|
||||
return ("Deleting file", last_items)
|
||||
|
|
|
|||
|
|
@ -17,11 +17,15 @@ def resolve_start_thinking(tool_name: str, tool_input: Any) -> ToolStartThinking
|
|||
d = as_tool_input_dict(tool_input)
|
||||
p = d.get("path", "") if isinstance(tool_input, dict) else str(tool_input)
|
||||
display = p if len(p) <= 80 else "…" + p[-77:]
|
||||
return ToolStartThinking(title="Deleting folder", items=[display] if display else [])
|
||||
return ToolStartThinking(
|
||||
title="Deleting folder", items=[display] if display else []
|
||||
)
|
||||
|
||||
|
||||
def resolve_completed_thinking(
|
||||
tool_name: str, tool_output: Any, last_items: list[str],
|
||||
tool_name: str,
|
||||
tool_output: Any,
|
||||
last_items: list[str],
|
||||
) -> tuple[str, list[str]]:
|
||||
del tool_output, tool_name
|
||||
return ("Deleting folder", last_items)
|
||||
|
|
|
|||
|
|
@ -21,7 +21,9 @@ def resolve_start_thinking(tool_name: str, tool_input: Any) -> ToolStartThinking
|
|||
|
||||
|
||||
def resolve_completed_thinking(
|
||||
tool_name: str, tool_output: Any, last_items: list[str],
|
||||
tool_name: str,
|
||||
tool_output: Any,
|
||||
last_items: list[str],
|
||||
) -> tuple[str, list[str]]:
|
||||
del tool_output, tool_name
|
||||
return ("Writing file", last_items)
|
||||
|
|
|
|||
|
|
@ -20,15 +20,15 @@ def resolve_start_thinking(tool_name: str, tool_input: Any) -> ToolStartThinking
|
|||
return ToolStartThinking(
|
||||
title="Planning tasks",
|
||||
items=(
|
||||
[f"{todo_count} task{'s' if todo_count != 1 else ''}"]
|
||||
if todo_count
|
||||
else []
|
||||
[f"{todo_count} task{'s' if todo_count != 1 else ''}"] if todo_count else []
|
||||
),
|
||||
)
|
||||
|
||||
|
||||
def resolve_completed_thinking(
|
||||
tool_name: str, tool_output: Any, last_items: list[str],
|
||||
tool_name: str,
|
||||
tool_output: Any,
|
||||
last_items: list[str],
|
||||
) -> tuple[str, list[str]]:
|
||||
del tool_output, tool_name
|
||||
return ("Planning tasks", last_items)
|
||||
|
|
|
|||
|
|
@ -58,14 +58,18 @@ def _emission_module(tool_name: str) -> str:
|
|||
|
||||
def _import_thinking(tool_name: str):
|
||||
try:
|
||||
return importlib.import_module(f"{_BASE}.{_thinking_module(tool_name)}.thinking")
|
||||
return importlib.import_module(
|
||||
f"{_BASE}.{_thinking_module(tool_name)}.thinking"
|
||||
)
|
||||
except ModuleNotFoundError:
|
||||
return importlib.import_module(f"{_BASE}.default.thinking")
|
||||
|
||||
|
||||
def _import_emission(tool_name: str):
|
||||
try:
|
||||
return importlib.import_module(f"{_BASE}.{_emission_module(tool_name)}.emission")
|
||||
return importlib.import_module(
|
||||
f"{_BASE}.{_emission_module(tool_name)}.emission"
|
||||
)
|
||||
except ModuleNotFoundError:
|
||||
return importlib.import_module(f"{_BASE}.default.emission")
|
||||
|
||||
|
|
|
|||
|
|
@ -23,7 +23,9 @@ def resolve_start_thinking(tool_name: str, tool_input: Any) -> ToolStartThinking
|
|||
|
||||
|
||||
def resolve_completed_thinking(
|
||||
tool_name: str, tool_output: Any, last_items: list[str],
|
||||
tool_name: str,
|
||||
tool_output: Any,
|
||||
last_items: list[str],
|
||||
) -> tuple[str, list[str]]:
|
||||
del tool_name
|
||||
items = last_items
|
||||
|
|
|
|||
|
|
@ -28,11 +28,7 @@ def iter_completion_emission_frames(
|
|||
xml,
|
||||
):
|
||||
chunk_url, content = m.group(1).strip(), m.group(2).strip()
|
||||
if (
|
||||
chunk_url.startswith("http")
|
||||
and chunk_url in citations
|
||||
and content
|
||||
):
|
||||
if chunk_url.startswith("http") and chunk_url in citations and content:
|
||||
citations[chunk_url]["snippet"] = (
|
||||
content[:200] + "…" if len(content) > 200 else content
|
||||
)
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue