* test: stabilize reporter evidence and guard missing chat nodes
* feat(models): scope Web model choices to tasks, turns and conversations
* test(e2e): mock model-control preview for ordinary chat submissions
* fix(models): harden scoped choices and stale Agent submissions
---------
Co-authored-by: Totoro-qaq <279883115+Totoro-qaq@users.noreply.github.com>
* feat(models): add declarative reasoning capability contract (#5073)
Introduce an optional per-model `reasoning:` block beside the legacy
`supports_thinking` / `supports_reasoning_effort` booleans. It declares
thinking availability (unsupported | optional | required), the accepted
effort values with aliases, default, and serialization path, the payload
dialect, and the reasoning-history requirement. When present the booleans
are derived from it and contradictory profiles fail at config load.
`deerflow.models.reasoning` normalizes legacy and declared profiles into
one immutable contract and resolves every caller's generic request against
it. `create_chat_model` is the single enforcement point: required-thinking
models never receive a synthesized disable payload, unsupported effort
values never reach the provider, and the dialect synthesizes the on/off
payload when no template exists. Legacy profiles keep the historical path
byte-for-byte. The lead agent and subagent descriptor resolve the same
policy first so run metadata reports effective values.
`/api/models` and `DeerFlowClient` project the contract as `reasoning`;
the frontend derives mode clamping and effort choices from it through
`core/models/reasoning.ts`, and user preferences accept provider-specific
effort tokens. The setup wizard's Z.AI GLM-5.3-Flash profile migrates to
the contract, restoring its low/high/max effort control.
* docs(models): move the reasoning contract guidance into models/AGENTS.md
backend/AGENTS.md sits within 46 bytes of the 96 KiB effective-chain hard
limit for the middlewares, runtime, sandbox, and subagents guides, so the
new section pushed scripts/check_agent_guidance.py over it. The models
guide is the nearest file for the factory and the contract module, and
its chain has ample room.
* fix(models): address review on the reasoning contract
- vLLM dialect: the enable path now mirrors whichever chat_template_kwargs
switch the template declares, like the disable path already did, so a
template using the older `thinking` key no longer also grows
`enable_thinking`.
- Validate operator-supplied effort values at `effort.path` inside
`when_thinking_enabled`, `when_thinking_disabled`, and the `thinking`
shortcut against the contract, not only the profile-level value; they are
forwarded when the caller chooses nothing, so the "unknown values never
reach the provider" guarantee now holds for them too.
- Constrain `effort.path` to dotted identifiers and reject single-segment
paths that would replace a whole mapping (`extra_body`, `thinking`,
`model_kwargs`, `default_headers`, `default_query`).
- Z.AI GLM-5.3-Flash profile: `default: high` instead of `max`, because the
default also governs summarization, title generation, and subagent calls
that never choose an effort; `max` stays selectable. Documented in the
config example, the configuration manual, and the design note.
* fix(models): close reasoning contract review gaps
* fix(models): preserve native Ollama reasoning config
* fix(models): keep native reasoning strings and project reasoning into the descriptor
- `ModelConfig.reasoning` also accepts the level string ChatOllama takes
for gpt-oss style models (`low` / `medium` / `high`); the factory forwards
both the boolean and the string on the legacy path, so profiles that
passed `reasoning: high` through before the contract field existed keep
loading and keep sending it.
- The assembly descriptor no longer excludes `reasoning` from
`model_parameters`: the native ChatOllama value and a declared contract's
dialect/history/effort change the request payload, so they now move the
assembly fingerprint.
- e2e: the sidecar spec pinned the pre-contract body where a model without
effort control still received `reasoning_effort: minimal`; the preset is
now dropped for such models (the Gateway discarded it anyway), so the
assertion expects the key to be absent.
* feat(subagents): show runtime metadata on task cards
* fix(subagents): stop task-card render loop and dedupe model fetches
Address code review on the runtime-metadata cards:
- P1 render loop: the terminal ToolMessage is re-parsed on every
MessageList render and always carries modelName/usage, so the
presence-based setTasks condition fired a fresh state object each
render -> "Maximum update depth exceeded". computeNextSubtask now
returns a value-compared `changed` flag and a pure subtaskNotification()
routes terminal transitions through the deferred after-render path
while skipping no-op re-parses.
- Per-card useModels refetch: add staleTime: Infinity to the ["models"]
query so every subtask card shares one /api/models fetch instead of
refetching on each mount.
* make format
* refactor(subagents): dedupe token-usage validators + tidy event narrowing
Address PR review follow-ups:
- DRY: extract one shared token-usage validator per side. Backend
status_contract.normalize_token_usage() now backs both the terminal
ToolMessage metadata and the subagent.step/.end run events
(step_events.py), and frontend messages/usage.normalizeTokenUsage()
backs both the live task_running event (lifecycle.ts) and the terminal
ToolMessage metadata (subtask-result.ts). Prevents the input/output/
total_tokens validation from drifting across the four former copies.
- Nit: onCustomEvent narrows event.type once instead of re-checking the
object shape per branch; the redundant task_started early-return
(already validated by taskEventToSubtaskUpdate) is dropped.
This PR improves MiniMax Code Plan integration in DeerFlow by fixing three issues in the current flow: stream errors were not clearly surfaced in the UI, the frontend could not display the actual provider model ID, and MiniMax reasoning output could leak into final assistant content as inline <think>...</think>. The change adds a MiniMax-specific adapter, exposes real model IDs end-to-end, and adds a frontend fallback for historical messages.
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* feat: Add reasoning effort configuration support
* Add `reasoning_effort` parameter to model config and agent initialization
* Support reasoning effort levels (minimal/low/medium/high) for Doubao/GPT-5 models
* Add UI controls in input box for reasoning effort selection
* Update doubao-seed-1.8 example config with reasoning effort support
Fixes & Cleanup:
* Ensure UTF-8 encoding for file operations
* Remove unused imports
* fix: set reasoning_effort to None for unsupported models
* fix: unit test error
* Update frontend/src/components/workspace/input-box.tsx
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
