feat: add Agents chat UI for cloud threads (#1323)
* feat(ui): add Agents chat UI ported from open-swe-app
Introduce a Cursor-style Agents surface separate from the dashboard, with ported chat/diff components and mock thread data until LangGraph APIs land.
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(dashboard): wire Agents UI to LangGraph thread APIs
Add dashboard thread list/detail/run/message/stream endpoints with a LangGraph message adapter, dashboard OAuth auth for runs, and TanStack Query hooks replacing mock data.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(dashboard): single agent reply per turn in Agents UI
Use UUID thread IDs LangGraph accepts, skip confirming_completion for
dashboard threads, and merge adapter agent messages so duplicate bubbles
do not render.
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(ui): polish Agents UI with floating prompt and layout cleanup
Remove no-op chrome (git panel, headers, sidebar search), port CloudPromptBar
from open-swe-app, and refine chat layout so messages scroll behind the input.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(agent): patch deepagents reducer for None messages on checkpoint replay
LangGraph thread state could 500 when cancelled runs left messages as None.
Apply the reducer guard before graph import, fall back to metadata in the
dashboard API, and adjust Agents prompt bar layout.
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(ui): unify sidebar user menu and clean up Agents UI navigation
Extract SidebarUserMenu so the dashboard and Agents sidebars render the
same profile button, drop the redundant Agents nav row in favor of the
existing Back to Agents link, add the open-swe logo header to the Agents
sidebar, flatten the New Agent button, and cap the home screen run list
to keep the prompt input in view.
* feat(ui): resizable/collapsible sidebar shared across dashboard and Agents
Add a useSidebarLayout hook + SidebarFrame wrapper so both sidebars
share a persisted width (default 260px, drag to resize, 200-420 range)
and a collapse toggle that hides the panel and surfaces a floating
reopen button. Also adds a DELETE /threads/{id} endpoint and an X-on-
hover thread delete control in the Agents sidebar.
* feat(ui): instant user message and busy indicator on Agents transition
Stash submitted prompts in sessionStorage, pre-populate the new thread
detail cache, and merge pending prompts into the rendered message list
so the Agents page renders the user bubble plus the existing thinking
spinner immediately instead of flashing a skeleton and "Agent is
starting" while the run boots.
* feat(ui): token-stream agent replies in the Agents thread view
Opt the LangGraph runs into messages-tuple streaming and forward those
events through the existing SSE channel. The frontend now applies
AIMessageChunk deltas directly to the cached thread (cancelling any
in-flight refetch first so optimistic tokens are not clobbered) and
keeps positional pending prompts so the user bubble stays in the right
place while the agent streams its reply.
* fix(dashboard): await threads.join_stream before iterating
threads.join_stream is async def returning an AsyncIterator, so it must
be awaited before async for. The SSE endpoint was raising
TypeError: 'async for' requires an object with __aiter__ method, got
coroutine on every connection.
* fix(dashboard): drop messages-tuple stream_mode that broke thinking-mode tool turns
Setting stream_mode=["values","messages-tuple","updates"] on
runs.create forces langchain_anthropic into streaming, and on the
second model call (after tool execution) its serialized thinking
blocks come back malformed, so Anthropic rejects the request with
'messages.1.content.0.thinking.thinking: Field required'. Revert to
the default stream_mode so claude-opus thinking + tool use runs to
completion. The frontend keeps the messages-event handler in place
as a no-op fallback for when streaming is re-enabled.
* feat(agents): per-thread model picker wired through to the run
Add optional model_id/effort to the create-thread and send-message
request bodies, forward them as agent_model_id/agent_effort in the
LangGraph run configurable, and record the resolved choice in thread
metadata so the UI can show the model the run is actually using.
get_agent now picks the per-thread override last (highest priority over
team default + profile override) and falls back gracefully when it is
absent or unsupported.
The frontend prompt bar becomes a controlled component fed by a
shared useModelOptions hook (options + profile -> defaultSelection).
AgentsHome seeds the picker from the user's profile default; the
thread view seeds from the thread's recorded model/effort and lets
each follow-up retarget the run.
* refactor(ui): align Agents prompt bar layout with open-swe-app PromptBar
Drop the absolute-positioned send button, restore the original
px-4 py-3.5 min-h-[106px] flex-col container, and move the model
picker into a mt-auto pt-2 footer row so the placeholder text and
the model selector share the same horizontal padding.
* chore: fix lint/format CI failures
Remove unused imports and reformat two files flagged by ruff.
* fix(tests): stop messages-reducer patch tests from polluting the suite
Restore agent modules after reducer patch tests and import LangSmithSandbox
from agent.server in proxy refresh tests so isinstance checks stay valid.
---------
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
Co-authored-by: Cursor <cursoragent@cursor.com>
2026-05-22 11:15:59 -07:00
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"""Dashboard thread list/detail/run/stream endpoints backed by LangGraph."""
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from __future__ import annotations
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import json
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import logging
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import os
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import uuid
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from collections.abc import AsyncIterator
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from datetime import UTC, datetime
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from typing import Any
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from fastapi import HTTPException
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from langgraph_sdk.errors import InternalServerError
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from pydantic import BaseModel, Field
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from ..utils.auth import persist_encrypted_github_token
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from ..utils.thread_ops import is_thread_active, langgraph_client, queue_message_for_thread
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from .agent_overrides import get_profile_default_repo
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from .message_adapter import state_messages_to_ui
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from .options import SUPPORTED_MODEL_IDS, model_supports_effort
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from .profiles import OAUTH_TOKENS_NAMESPACE, get_profile, get_valid_access_token
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from .profiles import _get_value as get_oauth_record
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logger = logging.getLogger(__name__)
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_ASSISTANT_ID = "agent"
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_DASHBOARD_SOURCE = "dashboard"
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2026-05-22 16:02:43 -07:00
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_DASHBOARD_STREAM_MODES: tuple[str, ...] = ("values", "updates", "messages-tuple")
|
feat: add Agents chat UI for cloud threads (#1323)
* feat(ui): add Agents chat UI ported from open-swe-app
Introduce a Cursor-style Agents surface separate from the dashboard, with ported chat/diff components and mock thread data until LangGraph APIs land.
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(dashboard): wire Agents UI to LangGraph thread APIs
Add dashboard thread list/detail/run/message/stream endpoints with a LangGraph message adapter, dashboard OAuth auth for runs, and TanStack Query hooks replacing mock data.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(dashboard): single agent reply per turn in Agents UI
Use UUID thread IDs LangGraph accepts, skip confirming_completion for
dashboard threads, and merge adapter agent messages so duplicate bubbles
do not render.
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(ui): polish Agents UI with floating prompt and layout cleanup
Remove no-op chrome (git panel, headers, sidebar search), port CloudPromptBar
from open-swe-app, and refine chat layout so messages scroll behind the input.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(agent): patch deepagents reducer for None messages on checkpoint replay
LangGraph thread state could 500 when cancelled runs left messages as None.
Apply the reducer guard before graph import, fall back to metadata in the
dashboard API, and adjust Agents prompt bar layout.
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(ui): unify sidebar user menu and clean up Agents UI navigation
Extract SidebarUserMenu so the dashboard and Agents sidebars render the
same profile button, drop the redundant Agents nav row in favor of the
existing Back to Agents link, add the open-swe logo header to the Agents
sidebar, flatten the New Agent button, and cap the home screen run list
to keep the prompt input in view.
* feat(ui): resizable/collapsible sidebar shared across dashboard and Agents
Add a useSidebarLayout hook + SidebarFrame wrapper so both sidebars
share a persisted width (default 260px, drag to resize, 200-420 range)
and a collapse toggle that hides the panel and surfaces a floating
reopen button. Also adds a DELETE /threads/{id} endpoint and an X-on-
hover thread delete control in the Agents sidebar.
* feat(ui): instant user message and busy indicator on Agents transition
Stash submitted prompts in sessionStorage, pre-populate the new thread
detail cache, and merge pending prompts into the rendered message list
so the Agents page renders the user bubble plus the existing thinking
spinner immediately instead of flashing a skeleton and "Agent is
starting" while the run boots.
* feat(ui): token-stream agent replies in the Agents thread view
Opt the LangGraph runs into messages-tuple streaming and forward those
events through the existing SSE channel. The frontend now applies
AIMessageChunk deltas directly to the cached thread (cancelling any
in-flight refetch first so optimistic tokens are not clobbered) and
keeps positional pending prompts so the user bubble stays in the right
place while the agent streams its reply.
* fix(dashboard): await threads.join_stream before iterating
threads.join_stream is async def returning an AsyncIterator, so it must
be awaited before async for. The SSE endpoint was raising
TypeError: 'async for' requires an object with __aiter__ method, got
coroutine on every connection.
* fix(dashboard): drop messages-tuple stream_mode that broke thinking-mode tool turns
Setting stream_mode=["values","messages-tuple","updates"] on
runs.create forces langchain_anthropic into streaming, and on the
second model call (after tool execution) its serialized thinking
blocks come back malformed, so Anthropic rejects the request with
'messages.1.content.0.thinking.thinking: Field required'. Revert to
the default stream_mode so claude-opus thinking + tool use runs to
completion. The frontend keeps the messages-event handler in place
as a no-op fallback for when streaming is re-enabled.
* feat(agents): per-thread model picker wired through to the run
Add optional model_id/effort to the create-thread and send-message
request bodies, forward them as agent_model_id/agent_effort in the
LangGraph run configurable, and record the resolved choice in thread
metadata so the UI can show the model the run is actually using.
get_agent now picks the per-thread override last (highest priority over
team default + profile override) and falls back gracefully when it is
absent or unsupported.
The frontend prompt bar becomes a controlled component fed by a
shared useModelOptions hook (options + profile -> defaultSelection).
AgentsHome seeds the picker from the user's profile default; the
thread view seeds from the thread's recorded model/effort and lets
each follow-up retarget the run.
* refactor(ui): align Agents prompt bar layout with open-swe-app PromptBar
Drop the absolute-positioned send button, restore the original
px-4 py-3.5 min-h-[106px] flex-col container, and move the model
picker into a mt-auto pt-2 footer row so the placeholder text and
the model selector share the same horizontal padding.
* chore: fix lint/format CI failures
Remove unused imports and reformat two files flagged by ruff.
* fix(tests): stop messages-reducer patch tests from polluting the suite
Restore agent modules after reducer patch tests and import LangSmithSandbox
from agent.server in proxy refresh tests so isinstance checks stay valid.
---------
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
Co-authored-by: Cursor <cursoragent@cursor.com>
2026-05-22 11:15:59 -07:00
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def _agent_version_metadata() -> dict[str, str]:
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revision = os.environ.get("LANGCHAIN_REVISION_ID")
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return {"LANGSMITH_AGENT_VERSION": revision} if revision else {}
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class ThreadCreateBody(BaseModel):
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prompt: str = Field(min_length=1, max_length=20_000)
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repo: str | None = None
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model_id: str | None = None
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effort: str | None = None
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class ThreadMessageBody(BaseModel):
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content: str = Field(min_length=1, max_length=20_000)
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model_id: str | None = None
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effort: str | None = None
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def _normalize_model_choice(
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model_id: str | None, effort: str | None
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) -> tuple[str | None, str | None]:
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if not isinstance(model_id, str) or model_id not in SUPPORTED_MODEL_IDS:
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return None, None
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if not isinstance(effort, str) or not model_supports_effort(model_id, effort):
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return None, None
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return model_id, effort
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def _now_ms() -> int:
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return int(datetime.now(UTC).timestamp() * 1000)
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def _parse_repo(full_name: str | None) -> dict[str, str] | None:
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if not isinstance(full_name, str):
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return None
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parts = full_name.strip().split("/", 1)
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if len(parts) != 2:
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return None
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owner, name = parts[0].strip(), parts[1].strip()
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if not owner or not name:
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return None
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return {"owner": owner, "name": name}
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async def _persist_dashboard_github_token(thread_id: str, login: str) -> None:
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token = await get_valid_access_token(login)
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if not token:
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raise HTTPException(401, "github token unavailable, re-login required")
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record = await get_oauth_record(OAUTH_TOKENS_NAMESPACE, login)
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expires_at = record.get("token_expires_at") if isinstance(record, dict) else None
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await persist_encrypted_github_token(
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thread_id,
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token,
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expires_at=expires_at if isinstance(expires_at, str) else None,
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)
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def _thread_owner_login(metadata: dict[str, Any]) -> str | None:
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login = metadata.get("github_login")
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return login.strip() if isinstance(login, str) and login.strip() else None
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def _assert_thread_owner(metadata: dict[str, Any], login: str) -> None:
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owner = _thread_owner_login(metadata)
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if owner != login:
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raise HTTPException(404, "thread not found")
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if metadata.get("source") != _DASHBOARD_SOURCE:
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raise HTTPException(404, "thread not found")
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def _metadata_repo(metadata: dict[str, Any]) -> tuple[str, str, str]:
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owner = metadata.get("repo_owner")
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name = metadata.get("repo_name")
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if isinstance(owner, str) and isinstance(name, str) and owner and name:
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return owner, name, f"{owner}/{name}"
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repo = metadata.get("repo")
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if isinstance(repo, dict):
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o = repo.get("owner")
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n = repo.get("name")
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if isinstance(o, str) and isinstance(n, str) and o and n:
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return o, n, f"{o}/{n}"
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return "", "", ""
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def _run_status_to_agent_status(thread_status: str | None, run_status: str | None) -> str:
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if thread_status == "busy" or run_status in {"pending", "running"}:
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return "running"
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if run_status in {"error", "failed", "timeout", "interrupted"}:
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return "error"
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if run_status == "success":
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return "finished"
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return "idle"
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def _thread_summary(
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thread: dict[str, Any], *, messages: list[dict[str, Any]] | None = None
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) -> dict[str, Any]:
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metadata = thread.get("metadata") if isinstance(thread.get("metadata"), dict) else {}
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owner, name, full_name = _metadata_repo(metadata)
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created_at = metadata.get("created_at_ms")
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updated_at = metadata.get("updated_at_ms")
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title = metadata.get("title") if isinstance(metadata.get("title"), str) else "Untitled agent"
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model = metadata.get("model") if isinstance(metadata.get("model"), str) else "Default"
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effort = metadata.get("effort") if isinstance(metadata.get("effort"), str) else None
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thread_status = thread.get("status") if isinstance(thread.get("status"), str) else "idle"
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latest_run_status = metadata.get("latest_run_status")
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status = _run_status_to_agent_status(
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thread_status,
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latest_run_status if isinstance(latest_run_status, str) else None,
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)
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pr_number = metadata.get("pr_number")
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pr_url = metadata.get("pr_url")
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pr_title = metadata.get("pr_title")
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pr_state = metadata.get("pr_state")
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summary: dict[str, Any] = {
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"id": thread.get("thread_id") or thread.get("id"),
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"title": title,
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"repo": name or "unknown",
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"repoFullName": full_name or "unknown/unknown",
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"branch": metadata.get("branch_name") or metadata.get("base_branch") or "main",
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"model": model,
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"effort": effort,
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"status": status,
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"createdAt": int(created_at) if isinstance(created_at, (int, float)) else _now_ms(),
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"updatedAt": int(updated_at) if isinstance(updated_at, (int, float)) else _now_ms(),
|
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}
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|
|
if isinstance(pr_number, int) and isinstance(pr_url, str):
|
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summary["pr"] = {
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|
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"number": pr_number,
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"title": pr_title if isinstance(pr_title, str) else title,
|
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|
|
"state": pr_state if isinstance(pr_state, str) else "open",
|
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"headRef": metadata.get("branch_name") or "",
|
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|
|
"baseRef": metadata.get("base_branch") or "main",
|
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|
|
"url": pr_url,
|
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|
|
}
|
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|
if messages is not None:
|
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|
|
summary["messages"] = messages
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|
else:
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|
|
summary["messages"] = []
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|
return summary
|
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|
|
async def _latest_run_status(thread_id: str) -> str | None:
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|
runs = await langgraph_client().runs.list(thread_id, limit=1)
|
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|
if not runs:
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|
|
return None
|
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|
|
run = runs[0]
|
|
|
|
|
raw = run.get("status") if isinstance(run, dict) else getattr(run, "status", None)
|
|
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|
|
return raw.lower() if isinstance(raw, str) else None
|
|
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|
|
async def list_dashboard_threads(login: str, *, limit: int = 50) -> list[dict[str, Any]]:
|
|
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|
|
threads = await langgraph_client().threads.search(
|
|
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|
|
metadata={"source": _DASHBOARD_SOURCE, "github_login": login},
|
|
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|
|
limit=limit,
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|
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|
|
sort_by="updated_at",
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|
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|
|
sort_order="desc",
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)
|
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|
|
out: list[dict[str, Any]] = []
|
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|
|
|
for thread in threads or []:
|
|
|
|
|
if isinstance(thread, dict):
|
|
|
|
|
out.append(_thread_summary(thread))
|
|
|
|
|
return out
|
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|
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|
|
async def get_dashboard_thread(thread_id: str, login: str) -> dict[str, Any]:
|
|
|
|
|
client = langgraph_client()
|
|
|
|
|
try:
|
|
|
|
|
thread = await client.threads.get(thread_id)
|
|
|
|
|
except Exception as exc: # noqa: BLE001
|
|
|
|
|
logger.debug("Thread lookup failed for %s", thread_id, exc_info=True)
|
|
|
|
|
raise HTTPException(404, "thread not found") from exc
|
|
|
|
|
|
|
|
|
|
metadata = thread.get("metadata") if isinstance(thread.get("metadata"), dict) else {}
|
|
|
|
|
_assert_thread_owner(metadata, login)
|
|
|
|
|
|
|
|
|
|
messages: list[dict[str, Any]] = []
|
|
|
|
|
try:
|
|
|
|
|
state = await client.threads.get_state(thread_id)
|
|
|
|
|
except InternalServerError:
|
|
|
|
|
logger.warning(
|
|
|
|
|
"Thread state unavailable for %s (checkpoint replay failed); returning metadata only",
|
|
|
|
|
thread_id,
|
|
|
|
|
)
|
|
|
|
|
else:
|
|
|
|
|
values = state.get("values") if isinstance(state, dict) else {}
|
|
|
|
|
raw_messages = values.get("messages") if isinstance(values, dict) else []
|
|
|
|
|
messages = state_messages_to_ui(raw_messages if isinstance(raw_messages, list) else [])
|
|
|
|
|
|
|
|
|
|
latest_run_status = await _latest_run_status(thread_id)
|
|
|
|
|
if latest_run_status and latest_run_status != metadata.get("latest_run_status"):
|
|
|
|
|
metadata = {**metadata, "latest_run_status": latest_run_status}
|
|
|
|
|
thread = {**thread, "metadata": metadata}
|
|
|
|
|
|
|
|
|
|
return _thread_summary(thread, messages=messages)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
async def _resolve_repo_config(login: str, repo: str | None) -> dict[str, str]:
|
|
|
|
|
parsed = _parse_repo(repo)
|
|
|
|
|
if parsed:
|
|
|
|
|
return parsed
|
|
|
|
|
profile_repo = await get_profile_default_repo(login)
|
|
|
|
|
if profile_repo:
|
|
|
|
|
return profile_repo
|
|
|
|
|
profile = await get_profile(login)
|
|
|
|
|
parsed = _parse_repo(profile.get("default_repo") if isinstance(profile, dict) else None)
|
|
|
|
|
if parsed:
|
|
|
|
|
return parsed
|
|
|
|
|
raise HTTPException(400, "no default repository configured — set one in Cloud Agents settings")
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
async def _start_agent_run(
|
|
|
|
|
thread_id: str,
|
|
|
|
|
*,
|
|
|
|
|
login: str,
|
|
|
|
|
repo_config: dict[str, str],
|
|
|
|
|
prompt: str,
|
|
|
|
|
title: str | None = None,
|
|
|
|
|
model_id: str | None = None,
|
|
|
|
|
effort: str | None = None,
|
|
|
|
|
) -> dict[str, Any]:
|
|
|
|
|
profile = await get_profile(login) or {}
|
|
|
|
|
now_ms = _now_ms()
|
|
|
|
|
chosen_model, chosen_effort = _normalize_model_choice(model_id, effort)
|
|
|
|
|
metadata_model = chosen_model or profile.get("default_model") or "Default"
|
|
|
|
|
metadata_effort = chosen_effort or profile.get("reasoning_effort")
|
|
|
|
|
metadata = {
|
|
|
|
|
"source": _DASHBOARD_SOURCE,
|
|
|
|
|
"github_login": login,
|
|
|
|
|
"title": title or prompt[:80] or "New agent",
|
|
|
|
|
"repo_owner": repo_config["owner"],
|
|
|
|
|
"repo_name": repo_config["name"],
|
|
|
|
|
"base_branch": profile.get("base_branch") or "main",
|
|
|
|
|
"branch_prefix": profile.get("branch_prefix"),
|
|
|
|
|
"model": metadata_model,
|
|
|
|
|
"effort": metadata_effort,
|
|
|
|
|
"created_at_ms": now_ms,
|
|
|
|
|
"updated_at_ms": now_ms,
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
client = langgraph_client()
|
|
|
|
|
await client.threads.create(thread_id=thread_id, metadata=metadata, if_exists="do_nothing")
|
|
|
|
|
await client.threads.update(thread_id=thread_id, metadata=metadata)
|
|
|
|
|
await _persist_dashboard_github_token(thread_id, login)
|
|
|
|
|
|
|
|
|
|
configurable: dict[str, Any] = {
|
|
|
|
|
"thread_id": thread_id,
|
|
|
|
|
"source": _DASHBOARD_SOURCE,
|
|
|
|
|
"github_login": login,
|
|
|
|
|
"repo": repo_config,
|
|
|
|
|
"user_email": profile.get("email"),
|
|
|
|
|
}
|
|
|
|
|
if chosen_model and chosen_effort:
|
|
|
|
|
configurable["agent_model_id"] = chosen_model
|
|
|
|
|
configurable["agent_effort"] = chosen_effort
|
|
|
|
|
|
|
|
|
|
run = await client.runs.create(
|
|
|
|
|
thread_id,
|
|
|
|
|
_ASSISTANT_ID,
|
|
|
|
|
input={"messages": [{"role": "user", "content": prompt}]},
|
|
|
|
|
config={"configurable": configurable, "metadata": _agent_version_metadata()},
|
|
|
|
|
if_not_exists="create",
|
2026-05-22 16:02:43 -07:00
|
|
|
stream_mode=list(_DASHBOARD_STREAM_MODES),
|
|
|
|
|
stream_resumable=True,
|
feat: add Agents chat UI for cloud threads (#1323)
* feat(ui): add Agents chat UI ported from open-swe-app
Introduce a Cursor-style Agents surface separate from the dashboard, with ported chat/diff components and mock thread data until LangGraph APIs land.
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(dashboard): wire Agents UI to LangGraph thread APIs
Add dashboard thread list/detail/run/message/stream endpoints with a LangGraph message adapter, dashboard OAuth auth for runs, and TanStack Query hooks replacing mock data.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(dashboard): single agent reply per turn in Agents UI
Use UUID thread IDs LangGraph accepts, skip confirming_completion for
dashboard threads, and merge adapter agent messages so duplicate bubbles
do not render.
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(ui): polish Agents UI with floating prompt and layout cleanup
Remove no-op chrome (git panel, headers, sidebar search), port CloudPromptBar
from open-swe-app, and refine chat layout so messages scroll behind the input.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(agent): patch deepagents reducer for None messages on checkpoint replay
LangGraph thread state could 500 when cancelled runs left messages as None.
Apply the reducer guard before graph import, fall back to metadata in the
dashboard API, and adjust Agents prompt bar layout.
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(ui): unify sidebar user menu and clean up Agents UI navigation
Extract SidebarUserMenu so the dashboard and Agents sidebars render the
same profile button, drop the redundant Agents nav row in favor of the
existing Back to Agents link, add the open-swe logo header to the Agents
sidebar, flatten the New Agent button, and cap the home screen run list
to keep the prompt input in view.
* feat(ui): resizable/collapsible sidebar shared across dashboard and Agents
Add a useSidebarLayout hook + SidebarFrame wrapper so both sidebars
share a persisted width (default 260px, drag to resize, 200-420 range)
and a collapse toggle that hides the panel and surfaces a floating
reopen button. Also adds a DELETE /threads/{id} endpoint and an X-on-
hover thread delete control in the Agents sidebar.
* feat(ui): instant user message and busy indicator on Agents transition
Stash submitted prompts in sessionStorage, pre-populate the new thread
detail cache, and merge pending prompts into the rendered message list
so the Agents page renders the user bubble plus the existing thinking
spinner immediately instead of flashing a skeleton and "Agent is
starting" while the run boots.
* feat(ui): token-stream agent replies in the Agents thread view
Opt the LangGraph runs into messages-tuple streaming and forward those
events through the existing SSE channel. The frontend now applies
AIMessageChunk deltas directly to the cached thread (cancelling any
in-flight refetch first so optimistic tokens are not clobbered) and
keeps positional pending prompts so the user bubble stays in the right
place while the agent streams its reply.
* fix(dashboard): await threads.join_stream before iterating
threads.join_stream is async def returning an AsyncIterator, so it must
be awaited before async for. The SSE endpoint was raising
TypeError: 'async for' requires an object with __aiter__ method, got
coroutine on every connection.
* fix(dashboard): drop messages-tuple stream_mode that broke thinking-mode tool turns
Setting stream_mode=["values","messages-tuple","updates"] on
runs.create forces langchain_anthropic into streaming, and on the
second model call (after tool execution) its serialized thinking
blocks come back malformed, so Anthropic rejects the request with
'messages.1.content.0.thinking.thinking: Field required'. Revert to
the default stream_mode so claude-opus thinking + tool use runs to
completion. The frontend keeps the messages-event handler in place
as a no-op fallback for when streaming is re-enabled.
* feat(agents): per-thread model picker wired through to the run
Add optional model_id/effort to the create-thread and send-message
request bodies, forward them as agent_model_id/agent_effort in the
LangGraph run configurable, and record the resolved choice in thread
metadata so the UI can show the model the run is actually using.
get_agent now picks the per-thread override last (highest priority over
team default + profile override) and falls back gracefully when it is
absent or unsupported.
The frontend prompt bar becomes a controlled component fed by a
shared useModelOptions hook (options + profile -> defaultSelection).
AgentsHome seeds the picker from the user's profile default; the
thread view seeds from the thread's recorded model/effort and lets
each follow-up retarget the run.
* refactor(ui): align Agents prompt bar layout with open-swe-app PromptBar
Drop the absolute-positioned send button, restore the original
px-4 py-3.5 min-h-[106px] flex-col container, and move the model
picker into a mt-auto pt-2 footer row so the placeholder text and
the model selector share the same horizontal padding.
* chore: fix lint/format CI failures
Remove unused imports and reformat two files flagged by ruff.
* fix(tests): stop messages-reducer patch tests from polluting the suite
Restore agent modules after reducer patch tests and import LangSmithSandbox
from agent.server in proxy refresh tests so isinstance checks stay valid.
---------
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
Co-authored-by: Cursor <cursoragent@cursor.com>
2026-05-22 11:15:59 -07:00
|
|
|
)
|
|
|
|
|
run_id = run.get("run_id") if isinstance(run, dict) else getattr(run, "run_id", None)
|
|
|
|
|
await client.threads.update(
|
|
|
|
|
thread_id=thread_id,
|
|
|
|
|
metadata={"latest_run_id": run_id, "latest_run_status": "pending", "updated_at_ms": now_ms},
|
|
|
|
|
)
|
|
|
|
|
thread = await client.threads.get(thread_id)
|
|
|
|
|
return _thread_summary(
|
|
|
|
|
thread if isinstance(thread, dict) else {"thread_id": thread_id, "metadata": metadata}
|
|
|
|
|
)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
async def create_dashboard_thread(login: str, body: ThreadCreateBody) -> dict[str, Any]:
|
|
|
|
|
repo_config = await _resolve_repo_config(login, body.repo)
|
|
|
|
|
thread_id = str(uuid.uuid4())
|
|
|
|
|
return await _start_agent_run(
|
|
|
|
|
thread_id,
|
|
|
|
|
login=login,
|
|
|
|
|
repo_config=repo_config,
|
|
|
|
|
prompt=body.prompt.strip(),
|
|
|
|
|
model_id=body.model_id,
|
|
|
|
|
effort=body.effort,
|
|
|
|
|
)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
async def send_dashboard_message(
|
|
|
|
|
thread_id: str, login: str, body: ThreadMessageBody
|
|
|
|
|
) -> dict[str, Any]:
|
|
|
|
|
client = langgraph_client()
|
|
|
|
|
try:
|
|
|
|
|
thread = await client.threads.get(thread_id)
|
|
|
|
|
except Exception as exc: # noqa: BLE001
|
|
|
|
|
raise HTTPException(404, "thread not found") from exc
|
|
|
|
|
|
|
|
|
|
metadata = thread.get("metadata") if isinstance(thread.get("metadata"), dict) else {}
|
|
|
|
|
_assert_thread_owner(metadata, login)
|
|
|
|
|
owner, name, _ = _metadata_repo(metadata)
|
|
|
|
|
if not owner or not name:
|
|
|
|
|
raise HTTPException(400, "thread is missing repository metadata")
|
|
|
|
|
|
|
|
|
|
prompt = body.content.strip()
|
|
|
|
|
now_ms = _now_ms()
|
|
|
|
|
chosen_model, chosen_effort = _normalize_model_choice(body.model_id, body.effort)
|
|
|
|
|
metadata_update: dict[str, Any] = {"updated_at_ms": now_ms}
|
|
|
|
|
if chosen_model and chosen_effort:
|
|
|
|
|
metadata_update["model"] = chosen_model
|
|
|
|
|
metadata_update["effort"] = chosen_effort
|
|
|
|
|
await client.threads.update(thread_id=thread_id, metadata=metadata_update)
|
|
|
|
|
|
|
|
|
|
if await is_thread_active(thread_id):
|
|
|
|
|
queued = await queue_message_for_thread(thread_id, prompt)
|
|
|
|
|
if not queued:
|
|
|
|
|
raise HTTPException(502, "failed to queue follow-up message")
|
|
|
|
|
thread = await client.threads.get(thread_id)
|
|
|
|
|
return _thread_summary(
|
|
|
|
|
thread if isinstance(thread, dict) else {"thread_id": thread_id, "metadata": metadata}
|
|
|
|
|
)
|
|
|
|
|
|
|
|
|
|
await _persist_dashboard_github_token(thread_id, login)
|
|
|
|
|
profile = await get_profile(login) or {}
|
|
|
|
|
configurable: dict[str, Any] = {
|
|
|
|
|
"thread_id": thread_id,
|
|
|
|
|
"source": _DASHBOARD_SOURCE,
|
|
|
|
|
"github_login": login,
|
|
|
|
|
"repo": {"owner": owner, "name": name},
|
|
|
|
|
"user_email": profile.get("email"),
|
|
|
|
|
}
|
|
|
|
|
if chosen_model and chosen_effort:
|
|
|
|
|
configurable["agent_model_id"] = chosen_model
|
|
|
|
|
configurable["agent_effort"] = chosen_effort
|
|
|
|
|
run = await client.runs.create(
|
|
|
|
|
thread_id,
|
|
|
|
|
_ASSISTANT_ID,
|
|
|
|
|
input={"messages": [{"role": "user", "content": prompt}]},
|
|
|
|
|
config={"configurable": configurable, "metadata": _agent_version_metadata()},
|
2026-05-22 16:02:43 -07:00
|
|
|
stream_mode=list(_DASHBOARD_STREAM_MODES),
|
|
|
|
|
stream_resumable=True,
|
feat: add Agents chat UI for cloud threads (#1323)
* feat(ui): add Agents chat UI ported from open-swe-app
Introduce a Cursor-style Agents surface separate from the dashboard, with ported chat/diff components and mock thread data until LangGraph APIs land.
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(dashboard): wire Agents UI to LangGraph thread APIs
Add dashboard thread list/detail/run/message/stream endpoints with a LangGraph message adapter, dashboard OAuth auth for runs, and TanStack Query hooks replacing mock data.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(dashboard): single agent reply per turn in Agents UI
Use UUID thread IDs LangGraph accepts, skip confirming_completion for
dashboard threads, and merge adapter agent messages so duplicate bubbles
do not render.
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(ui): polish Agents UI with floating prompt and layout cleanup
Remove no-op chrome (git panel, headers, sidebar search), port CloudPromptBar
from open-swe-app, and refine chat layout so messages scroll behind the input.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(agent): patch deepagents reducer for None messages on checkpoint replay
LangGraph thread state could 500 when cancelled runs left messages as None.
Apply the reducer guard before graph import, fall back to metadata in the
dashboard API, and adjust Agents prompt bar layout.
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(ui): unify sidebar user menu and clean up Agents UI navigation
Extract SidebarUserMenu so the dashboard and Agents sidebars render the
same profile button, drop the redundant Agents nav row in favor of the
existing Back to Agents link, add the open-swe logo header to the Agents
sidebar, flatten the New Agent button, and cap the home screen run list
to keep the prompt input in view.
* feat(ui): resizable/collapsible sidebar shared across dashboard and Agents
Add a useSidebarLayout hook + SidebarFrame wrapper so both sidebars
share a persisted width (default 260px, drag to resize, 200-420 range)
and a collapse toggle that hides the panel and surfaces a floating
reopen button. Also adds a DELETE /threads/{id} endpoint and an X-on-
hover thread delete control in the Agents sidebar.
* feat(ui): instant user message and busy indicator on Agents transition
Stash submitted prompts in sessionStorage, pre-populate the new thread
detail cache, and merge pending prompts into the rendered message list
so the Agents page renders the user bubble plus the existing thinking
spinner immediately instead of flashing a skeleton and "Agent is
starting" while the run boots.
* feat(ui): token-stream agent replies in the Agents thread view
Opt the LangGraph runs into messages-tuple streaming and forward those
events through the existing SSE channel. The frontend now applies
AIMessageChunk deltas directly to the cached thread (cancelling any
in-flight refetch first so optimistic tokens are not clobbered) and
keeps positional pending prompts so the user bubble stays in the right
place while the agent streams its reply.
* fix(dashboard): await threads.join_stream before iterating
threads.join_stream is async def returning an AsyncIterator, so it must
be awaited before async for. The SSE endpoint was raising
TypeError: 'async for' requires an object with __aiter__ method, got
coroutine on every connection.
* fix(dashboard): drop messages-tuple stream_mode that broke thinking-mode tool turns
Setting stream_mode=["values","messages-tuple","updates"] on
runs.create forces langchain_anthropic into streaming, and on the
second model call (after tool execution) its serialized thinking
blocks come back malformed, so Anthropic rejects the request with
'messages.1.content.0.thinking.thinking: Field required'. Revert to
the default stream_mode so claude-opus thinking + tool use runs to
completion. The frontend keeps the messages-event handler in place
as a no-op fallback for when streaming is re-enabled.
* feat(agents): per-thread model picker wired through to the run
Add optional model_id/effort to the create-thread and send-message
request bodies, forward them as agent_model_id/agent_effort in the
LangGraph run configurable, and record the resolved choice in thread
metadata so the UI can show the model the run is actually using.
get_agent now picks the per-thread override last (highest priority over
team default + profile override) and falls back gracefully when it is
absent or unsupported.
The frontend prompt bar becomes a controlled component fed by a
shared useModelOptions hook (options + profile -> defaultSelection).
AgentsHome seeds the picker from the user's profile default; the
thread view seeds from the thread's recorded model/effort and lets
each follow-up retarget the run.
* refactor(ui): align Agents prompt bar layout with open-swe-app PromptBar
Drop the absolute-positioned send button, restore the original
px-4 py-3.5 min-h-[106px] flex-col container, and move the model
picker into a mt-auto pt-2 footer row so the placeholder text and
the model selector share the same horizontal padding.
* chore: fix lint/format CI failures
Remove unused imports and reformat two files flagged by ruff.
* fix(tests): stop messages-reducer patch tests from polluting the suite
Restore agent modules after reducer patch tests and import LangSmithSandbox
from agent.server in proxy refresh tests so isinstance checks stay valid.
---------
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
Co-authored-by: Cursor <cursoragent@cursor.com>
2026-05-22 11:15:59 -07:00
|
|
|
)
|
|
|
|
|
run_id = run.get("run_id") if isinstance(run, dict) else getattr(run, "run_id", None)
|
|
|
|
|
await client.threads.update(
|
|
|
|
|
thread_id=thread_id,
|
|
|
|
|
metadata={"latest_run_id": run_id, "latest_run_status": "pending", "updated_at_ms": now_ms},
|
|
|
|
|
)
|
|
|
|
|
thread = await client.threads.get(thread_id)
|
|
|
|
|
return _thread_summary(
|
|
|
|
|
thread if isinstance(thread, dict) else {"thread_id": thread_id, "metadata": metadata}
|
|
|
|
|
)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
async def cancel_dashboard_thread(thread_id: str, login: str) -> dict[str, Any]:
|
|
|
|
|
client = langgraph_client()
|
|
|
|
|
try:
|
|
|
|
|
thread = await client.threads.get(thread_id)
|
|
|
|
|
except Exception as exc: # noqa: BLE001
|
|
|
|
|
raise HTTPException(404, "thread not found") from exc
|
|
|
|
|
|
|
|
|
|
metadata = thread.get("metadata") if isinstance(thread.get("metadata"), dict) else {}
|
|
|
|
|
_assert_thread_owner(metadata, login)
|
|
|
|
|
|
|
|
|
|
run_id = metadata.get("latest_run_id")
|
|
|
|
|
if isinstance(run_id, str) and run_id:
|
|
|
|
|
try:
|
|
|
|
|
await client.runs.cancel(thread_id, run_id, wait=False)
|
|
|
|
|
except Exception:
|
|
|
|
|
logger.debug("Could not cancel run %s for thread %s", run_id, thread_id, exc_info=True)
|
|
|
|
|
|
|
|
|
|
await client.threads.update(
|
|
|
|
|
thread_id=thread_id,
|
|
|
|
|
metadata={"latest_run_status": "interrupted", "updated_at_ms": _now_ms()},
|
|
|
|
|
)
|
|
|
|
|
thread = await client.threads.get(thread_id)
|
|
|
|
|
return _thread_summary(
|
|
|
|
|
thread if isinstance(thread, dict) else {"thread_id": thread_id, "metadata": metadata}
|
|
|
|
|
)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
async def delete_dashboard_thread(thread_id: str, login: str) -> None:
|
|
|
|
|
client = langgraph_client()
|
|
|
|
|
try:
|
|
|
|
|
thread = await client.threads.get(thread_id)
|
|
|
|
|
except Exception as exc: # noqa: BLE001
|
|
|
|
|
raise HTTPException(404, "thread not found") from exc
|
|
|
|
|
|
|
|
|
|
metadata = thread.get("metadata") if isinstance(thread.get("metadata"), dict) else {}
|
|
|
|
|
_assert_thread_owner(metadata, login)
|
|
|
|
|
|
|
|
|
|
run_id = metadata.get("latest_run_id")
|
|
|
|
|
if isinstance(run_id, str) and run_id:
|
|
|
|
|
try:
|
|
|
|
|
await client.runs.cancel(thread_id, run_id, wait=False)
|
|
|
|
|
except Exception:
|
|
|
|
|
logger.debug("Could not cancel run %s for thread %s", run_id, thread_id, exc_info=True)
|
|
|
|
|
|
|
|
|
|
await client.threads.delete(thread_id)
|
|
|
|
|
|
|
|
|
|
|
2026-05-22 16:02:43 -07:00
|
|
|
async def stream_dashboard_thread(
|
|
|
|
|
thread_id: str, login: str, *, last_event_id: str | None = None
|
|
|
|
|
) -> AsyncIterator[str]:
|
feat: add Agents chat UI for cloud threads (#1323)
* feat(ui): add Agents chat UI ported from open-swe-app
Introduce a Cursor-style Agents surface separate from the dashboard, with ported chat/diff components and mock thread data until LangGraph APIs land.
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(dashboard): wire Agents UI to LangGraph thread APIs
Add dashboard thread list/detail/run/message/stream endpoints with a LangGraph message adapter, dashboard OAuth auth for runs, and TanStack Query hooks replacing mock data.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(dashboard): single agent reply per turn in Agents UI
Use UUID thread IDs LangGraph accepts, skip confirming_completion for
dashboard threads, and merge adapter agent messages so duplicate bubbles
do not render.
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(ui): polish Agents UI with floating prompt and layout cleanup
Remove no-op chrome (git panel, headers, sidebar search), port CloudPromptBar
from open-swe-app, and refine chat layout so messages scroll behind the input.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(agent): patch deepagents reducer for None messages on checkpoint replay
LangGraph thread state could 500 when cancelled runs left messages as None.
Apply the reducer guard before graph import, fall back to metadata in the
dashboard API, and adjust Agents prompt bar layout.
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(ui): unify sidebar user menu and clean up Agents UI navigation
Extract SidebarUserMenu so the dashboard and Agents sidebars render the
same profile button, drop the redundant Agents nav row in favor of the
existing Back to Agents link, add the open-swe logo header to the Agents
sidebar, flatten the New Agent button, and cap the home screen run list
to keep the prompt input in view.
* feat(ui): resizable/collapsible sidebar shared across dashboard and Agents
Add a useSidebarLayout hook + SidebarFrame wrapper so both sidebars
share a persisted width (default 260px, drag to resize, 200-420 range)
and a collapse toggle that hides the panel and surfaces a floating
reopen button. Also adds a DELETE /threads/{id} endpoint and an X-on-
hover thread delete control in the Agents sidebar.
* feat(ui): instant user message and busy indicator on Agents transition
Stash submitted prompts in sessionStorage, pre-populate the new thread
detail cache, and merge pending prompts into the rendered message list
so the Agents page renders the user bubble plus the existing thinking
spinner immediately instead of flashing a skeleton and "Agent is
starting" while the run boots.
* feat(ui): token-stream agent replies in the Agents thread view
Opt the LangGraph runs into messages-tuple streaming and forward those
events through the existing SSE channel. The frontend now applies
AIMessageChunk deltas directly to the cached thread (cancelling any
in-flight refetch first so optimistic tokens are not clobbered) and
keeps positional pending prompts so the user bubble stays in the right
place while the agent streams its reply.
* fix(dashboard): await threads.join_stream before iterating
threads.join_stream is async def returning an AsyncIterator, so it must
be awaited before async for. The SSE endpoint was raising
TypeError: 'async for' requires an object with __aiter__ method, got
coroutine on every connection.
* fix(dashboard): drop messages-tuple stream_mode that broke thinking-mode tool turns
Setting stream_mode=["values","messages-tuple","updates"] on
runs.create forces langchain_anthropic into streaming, and on the
second model call (after tool execution) its serialized thinking
blocks come back malformed, so Anthropic rejects the request with
'messages.1.content.0.thinking.thinking: Field required'. Revert to
the default stream_mode so claude-opus thinking + tool use runs to
completion. The frontend keeps the messages-event handler in place
as a no-op fallback for when streaming is re-enabled.
* feat(agents): per-thread model picker wired through to the run
Add optional model_id/effort to the create-thread and send-message
request bodies, forward them as agent_model_id/agent_effort in the
LangGraph run configurable, and record the resolved choice in thread
metadata so the UI can show the model the run is actually using.
get_agent now picks the per-thread override last (highest priority over
team default + profile override) and falls back gracefully when it is
absent or unsupported.
The frontend prompt bar becomes a controlled component fed by a
shared useModelOptions hook (options + profile -> defaultSelection).
AgentsHome seeds the picker from the user's profile default; the
thread view seeds from the thread's recorded model/effort and lets
each follow-up retarget the run.
* refactor(ui): align Agents prompt bar layout with open-swe-app PromptBar
Drop the absolute-positioned send button, restore the original
px-4 py-3.5 min-h-[106px] flex-col container, and move the model
picker into a mt-auto pt-2 footer row so the placeholder text and
the model selector share the same horizontal padding.
* chore: fix lint/format CI failures
Remove unused imports and reformat two files flagged by ruff.
* fix(tests): stop messages-reducer patch tests from polluting the suite
Restore agent modules after reducer patch tests and import LangSmithSandbox
from agent.server in proxy refresh tests so isinstance checks stay valid.
---------
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
Co-authored-by: Cursor <cursoragent@cursor.com>
2026-05-22 11:15:59 -07:00
|
|
|
try:
|
|
|
|
|
thread = await langgraph_client().threads.get(thread_id)
|
|
|
|
|
except Exception as exc: # noqa: BLE001
|
|
|
|
|
raise HTTPException(404, "thread not found") from exc
|
|
|
|
|
|
|
|
|
|
metadata = thread.get("metadata") if isinstance(thread.get("metadata"), dict) else {}
|
|
|
|
|
_assert_thread_owner(metadata, login)
|
|
|
|
|
|
2026-05-22 16:02:43 -07:00
|
|
|
stream = await langgraph_client().threads.join_stream(
|
|
|
|
|
thread_id,
|
|
|
|
|
last_event_id=last_event_id,
|
|
|
|
|
)
|
feat: add Agents chat UI for cloud threads (#1323)
* feat(ui): add Agents chat UI ported from open-swe-app
Introduce a Cursor-style Agents surface separate from the dashboard, with ported chat/diff components and mock thread data until LangGraph APIs land.
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(dashboard): wire Agents UI to LangGraph thread APIs
Add dashboard thread list/detail/run/message/stream endpoints with a LangGraph message adapter, dashboard OAuth auth for runs, and TanStack Query hooks replacing mock data.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(dashboard): single agent reply per turn in Agents UI
Use UUID thread IDs LangGraph accepts, skip confirming_completion for
dashboard threads, and merge adapter agent messages so duplicate bubbles
do not render.
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(ui): polish Agents UI with floating prompt and layout cleanup
Remove no-op chrome (git panel, headers, sidebar search), port CloudPromptBar
from open-swe-app, and refine chat layout so messages scroll behind the input.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(agent): patch deepagents reducer for None messages on checkpoint replay
LangGraph thread state could 500 when cancelled runs left messages as None.
Apply the reducer guard before graph import, fall back to metadata in the
dashboard API, and adjust Agents prompt bar layout.
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(ui): unify sidebar user menu and clean up Agents UI navigation
Extract SidebarUserMenu so the dashboard and Agents sidebars render the
same profile button, drop the redundant Agents nav row in favor of the
existing Back to Agents link, add the open-swe logo header to the Agents
sidebar, flatten the New Agent button, and cap the home screen run list
to keep the prompt input in view.
* feat(ui): resizable/collapsible sidebar shared across dashboard and Agents
Add a useSidebarLayout hook + SidebarFrame wrapper so both sidebars
share a persisted width (default 260px, drag to resize, 200-420 range)
and a collapse toggle that hides the panel and surfaces a floating
reopen button. Also adds a DELETE /threads/{id} endpoint and an X-on-
hover thread delete control in the Agents sidebar.
* feat(ui): instant user message and busy indicator on Agents transition
Stash submitted prompts in sessionStorage, pre-populate the new thread
detail cache, and merge pending prompts into the rendered message list
so the Agents page renders the user bubble plus the existing thinking
spinner immediately instead of flashing a skeleton and "Agent is
starting" while the run boots.
* feat(ui): token-stream agent replies in the Agents thread view
Opt the LangGraph runs into messages-tuple streaming and forward those
events through the existing SSE channel. The frontend now applies
AIMessageChunk deltas directly to the cached thread (cancelling any
in-flight refetch first so optimistic tokens are not clobbered) and
keeps positional pending prompts so the user bubble stays in the right
place while the agent streams its reply.
* fix(dashboard): await threads.join_stream before iterating
threads.join_stream is async def returning an AsyncIterator, so it must
be awaited before async for. The SSE endpoint was raising
TypeError: 'async for' requires an object with __aiter__ method, got
coroutine on every connection.
* fix(dashboard): drop messages-tuple stream_mode that broke thinking-mode tool turns
Setting stream_mode=["values","messages-tuple","updates"] on
runs.create forces langchain_anthropic into streaming, and on the
second model call (after tool execution) its serialized thinking
blocks come back malformed, so Anthropic rejects the request with
'messages.1.content.0.thinking.thinking: Field required'. Revert to
the default stream_mode so claude-opus thinking + tool use runs to
completion. The frontend keeps the messages-event handler in place
as a no-op fallback for when streaming is re-enabled.
* feat(agents): per-thread model picker wired through to the run
Add optional model_id/effort to the create-thread and send-message
request bodies, forward them as agent_model_id/agent_effort in the
LangGraph run configurable, and record the resolved choice in thread
metadata so the UI can show the model the run is actually using.
get_agent now picks the per-thread override last (highest priority over
team default + profile override) and falls back gracefully when it is
absent or unsupported.
The frontend prompt bar becomes a controlled component fed by a
shared useModelOptions hook (options + profile -> defaultSelection).
AgentsHome seeds the picker from the user's profile default; the
thread view seeds from the thread's recorded model/effort and lets
each follow-up retarget the run.
* refactor(ui): align Agents prompt bar layout with open-swe-app PromptBar
Drop the absolute-positioned send button, restore the original
px-4 py-3.5 min-h-[106px] flex-col container, and move the model
picker into a mt-auto pt-2 footer row so the placeholder text and
the model selector share the same horizontal padding.
* chore: fix lint/format CI failures
Remove unused imports and reformat two files flagged by ruff.
* fix(tests): stop messages-reducer patch tests from polluting the suite
Restore agent modules after reducer patch tests and import LangSmithSandbox
from agent.server in proxy refresh tests so isinstance checks stay valid.
---------
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
Co-authored-by: Cursor <cursoragent@cursor.com>
2026-05-22 11:15:59 -07:00
|
|
|
async for part in stream:
|
2026-05-22 16:02:43 -07:00
|
|
|
event = getattr(part, "event", None) or (
|
|
|
|
|
part.get("event") if isinstance(part, dict) else None
|
|
|
|
|
)
|
|
|
|
|
data = getattr(part, "data", None) if not isinstance(part, dict) else part.get("data")
|
|
|
|
|
event_id = getattr(part, "id", None) if not isinstance(part, dict) else part.get("id")
|
|
|
|
|
payload: dict[str, Any] = {"event": event, "data": data}
|
|
|
|
|
if event_id is not None:
|
|
|
|
|
payload["id"] = event_id
|
|
|
|
|
chunk = f"data: {json.dumps(payload, default=str)}\n\n"
|
|
|
|
|
if event_id is not None:
|
|
|
|
|
chunk = f"id: {event_id}\n{chunk}"
|
|
|
|
|
yield chunk
|