greatmengqi b1aabe88b8
fix(backend): stream DeerFlowClient AI text as token deltas (#1969) (#1974)
* fix(backend): stream DeerFlowClient AI text as token deltas (#1969)

DeerFlowClient.stream() subscribed to LangGraph stream_mode=["values",
"custom"] which only delivers full-state snapshots at graph-node
boundaries, so AI replies were dumped as a single messages-tuple event
per node instead of streaming token-by-token. `client.stream("hello")`
looked identical to `client.chat("hello")` — the bug reported in #1969.

Subscribe to "messages" mode as well, forward AIMessageChunk deltas as
messages-tuple events with delta semantics (consumers accumulate by id),
and dedup the values-snapshot path so it does not re-synthesize AI
text that was already streamed. Introduce a per-id usage_metadata
counter so the final AIMessage in the values snapshot and the final
"messages" chunk — which carry the same cumulative usage — are not
double-counted.

chat() now accumulates per-id deltas and returns the last message's
full accumulated text. Non-streaming mock sources (single event per id)
are a degenerate case of the same logic, keeping existing callers and
tests backward compatible.

Verified end-to-end against a real LLM: a 15-number count emits 35
messages-tuple events with BPE subword boundaries clearly visible
("eleven" -> "ele" / "ven", "twelve" -> "tw" / "elve"), 476ms across
the window, end-event usage matches the values-snapshot usage exactly
(not doubled). tests/test_client_live.py::TestLiveStreaming passes.

New unit tests:
- test_messages_mode_emits_token_deltas: 3 AIMessageChunks produce 3
  delta events with correct content/id/usage, values-snapshot does not
  duplicate, usage counted once.
- test_chat_accumulates_streamed_deltas: chat() rebuilds full text
  from deltas.
- test_messages_mode_tool_message: ToolMessage delivered via messages
  mode is not duplicated by the values-snapshot synthesis path.

The stream() docstring now documents why this client does not reuse
Gateway's run_agent() / StreamBridge pipeline (sync vs async, raw
LangChain objects vs serialized dicts, single caller vs HTTP fan-out).

Fixes #1969

* refactor(backend): simplify DeerFlowClient streaming helpers (#1969)

Post-review cleanup for the token-level streaming fix. No behavior
change for correct inputs; one efficiency regression fixed.

Fix: chat() O(n²) accumulator
-----------------------------
`chat()` accumulated per-id text via `buffers[id] = buffers.get(id,"") + delta`,
which is O(n) per concat → O(n²) total over a streamed response. At
~2 KB cumulative text this becomes user-visible; at 50 KB / 5000 chunks
it costs roughly 100-300 ms of pure copying. Switched to
`dict[str, list[str]]` + `"".join()` once at return.

Cleanup
-------
- Extract `_serialize_tool_calls`, `_ai_text_event`, `_ai_tool_calls_event`,
  and `_tool_message_event` static helpers. The messages-mode and
  values-mode branches previously repeated four inline dict literals each;
  they now call the same builders.
- `StreamEvent.type` is now typed as `Literal["values", "messages-tuple",
  "custom", "end"]` via a `StreamEventType` alias. Makes the closed set
  explicit and catches typos at type-check time.
- Direct attribute access on `AIMessage`/`AIMessageChunk`: `.usage_metadata`,
  `.tool_calls`, `.id` all have default values on the base class, so the
  `getattr(..., None)` fallbacks were dead code. Removed from the hot
  path.
- `_account_usage` parameter type loosened to `Any` so that LangChain's
  `UsageMetadata` TypedDict is accepted under strict type checking.
- Trimmed narrating comments on `seen_ids` / `streamed_ids` / the
  values-synthesis skip block; kept the non-obvious ones that document
  the cross-mode dedup invariant.

Net diff: -15 lines. All 132 unit tests + harness boundary test still
pass; ruff check and ruff format pass.

* docs(backend): add STREAMING.md design note (#1969)

Dedicated design document for the token-level streaming architecture,
prompted by the bug investigation in #1969.

Contents:
- Why two parallel streaming paths exist (Gateway HTTP/async vs
  DeerFlowClient sync/in-process) and why they cannot be merged.
- LangGraph's three-layer mode naming (Graph "messages" vs Platform
  SDK "messages-tuple" vs HTTP SSE) and why a shared string constant
  would be harmful.
- Gateway path: run_agent + StreamBridge + sse_consumer with a
  sequence diagram.
- DeerFlowClient path: sync generator + direct yield, delta semantics,
  chat() accumulator.
- Why the three id sets (seen_ids / streamed_ids / counted_usage_ids)
  each carry an independent invariant and cannot be collapsed.
- End-to-end sequence for a real conversation turn.
- Lessons from #1969: why mock-based tests missed the bug, why
  BPE subword boundaries in live output are the strongest
  correctness signal, and the regression test that locks it in.
- Source code location index.

Also:
- Link from backend/CLAUDE.md Embedded Client section.
- Link from backend/docs/README.md under Feature Documentation.

* test(backend): add refactor regression guards for stream() (#1969)

Three new tests in TestStream that lock the contract introduced by
PR #1974 so any future refactor (sync->async migration, sharing a
core with Gateway's run_agent, dedup strategy change) cannot
silently change behavior.

- test_dedup_requires_messages_before_values_invariant: canary that
  documents the order-dependence of cross-mode dedup. streamed_ids
  is populated only by the messages branch, so values-before-messages
  for the same id produces duplicate AI text events. Real LangGraph
  never inverts this order, but a refactor that does (or that makes
  dedup idempotent) must update this test deliberately.

- test_messages_mode_golden_event_sequence: locks the *exact* event
  sequence (4 events: 2 messages-tuple deltas, 1 values snapshot, 1
  end) for a canonical streaming turn. List equality gives a clear
  diff on any drift in order, type, or payload shape.

- test_chat_accumulates_in_linear_time: perf canary for the O(n^2)
  fix in commit 1f11ba10. 10,000 single-char chunks must accumulate
  in under 1s; the threshold is wide enough to pass on slow CI but
  tight enough to fail if buffer = buffer + delta is restored.

All three tests pass alongside the existing 12 TestStream tests
(15/15). ruff check + ruff format clean.

* docs(backend): clarify stream() docstring on JSON serialization (#1969)

Replace the misleading "raw LangChain objects (AIMessage,
usage_metadata as dataclasses), not dicts" claim in the
"Why not reuse Gateway's run_agent?" section. The implementation
already yields plain Python dicts (StreamEvent.data is dict, and
usage_metadata is a TypedDict), so the original wording suggested
a richer return type than the API actually delivers.

The corrected wording focuses on what is actually true and
relevant: this client skips the JSON/SSE serialization layer that
Gateway adds for HTTP wire transmission, and yields stream event
payloads directly as Python data structures.

Addresses Copilot review feedback on PR #1974.

* test(backend): document none-id messages dedup limitation (#1969)

Add test_none_id_chunks_produce_duplicates_known_limitation to
TestStream that explicitly documents and asserts the current
behavior when an LLM provider emits AIMessageChunk with id=None
(vLLM, certain custom backends).

The cross-mode dedup machinery cannot record a None id in
streamed_ids (guarded by ``if msg_id:``), so the values snapshot's
reassembled AIMessage with a real id falls through and synthesizes
a duplicate AI text event. The test asserts len == 2 and locks
this as a known limitation rather than silently letting future
contributors hit it without context.

Why this is documented rather than fixed:
* Falling back to ``metadata.get("id")`` does not help — LangGraph's
  messages-mode metadata never carries the message id.
* Synthesizing ``f"_synth_{id(msg_chunk)}"`` only helps if the
  values snapshot uses the same fallback, which it does not.
* A real fix requires provider cooperation (always emit chunk ids)
  or content-based dedup (false-positive risk), neither of which
  belongs in this PR.

If a real fix lands, replace this test with a positive assertion
that dedup works for None-id chunks.

Addresses Copilot review feedback on PR #1974 (client.py:515).

* fix(frontend): UI polish - fix CSS typo, dark mode border, and hardcoded colors (#1942)

- Fix `font-norma` typo to `font-normal` in message-list subtask count
- Fix dark mode `--border` using reddish hue (22.216) instead of neutral
- Replace hardcoded `rgb(184,184,192)` in hero with `text-muted-foreground`
- Replace hardcoded `bg-[#a3a1a1]` in streaming indicator with `bg-muted-foreground`
- Add missing `font-sans` to welcome description `<pre>` for consistency
- Make case-study-section padding responsive (`px-4 md:px-20`)

Closes #1940

* docs: clarify deployment sizing guidance (#1963)

* fix(frontend): prevent stale 'new' thread ID from triggering 422 history requests (#1960)

After history.replaceState updates the URL from /chats/new to
/chats/{UUID}, Next.js useParams does not update because replaceState
bypasses the router. The useEffect in useThreadChat would then set
threadIdFromPath ('new') as the threadId, causing the LangGraph SDK
to call POST /threads/new/history which returns HTTP 422 (Invalid
thread ID: must be a UUID).

This fix adds a guard to skip the threadId update when
threadIdFromPath is the literal string 'new', preserving the
already-correct UUID that was set when the thread was created.

* fix(frontend): avoid using route new as thread id (#1967)

Co-authored-by: luoxiao6645 <luoxiao6645@gmail.com>

* Fix(subagent): Event loop conflict in SubagentExecutor.execute() (#1965)

* Fix event loop conflict in SubagentExecutor.execute()

When SubagentExecutor.execute() is called from within an already-running
event loop (e.g., when the parent agent uses async/await), calling
asyncio.run() creates a new event loop that conflicts with asyncio
primitives (like httpx.AsyncClient) that were created in and bound to
the parent loop.

This fix detects if we're already in a running event loop, and if so,
runs the subagent in a separate thread with its own isolated event loop
to avoid conflicts.

Fixes: sub-task cards not appearing in Ultra mode when using async parent agents

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

* fix(subagent): harden isolated event loop execution

---------

Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>

* refactor(backend): remove dead getattr in _tool_message_event

---------

Co-authored-by: greatmengqi <chenmengqi.0376@bytedance.com>
Co-authored-by: Xinmin Zeng <135568692+fancyboi999@users.noreply.github.com>
Co-authored-by: 13ernkastel <LennonCMJ@live.com>
Co-authored-by: siwuai <458372151@qq.com>
Co-authored-by: 肖 <168966994+luoxiao6645@users.noreply.github.com>
Co-authored-by: luoxiao6645 <luoxiao6645@gmail.com>
Co-authored-by: Saber <11769524+hawkli-1994@users.noreply.github.com>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
2026-04-10 18:16:38 +08:00
..