* refactor(agent): ground runtime decisions in structured evidence
Use producer status and structured errors for tool recovery, preserve memory context without lexical confirmation, and remove predetermined receipt and skill conclusions.
Require explicit MCP discovery and authenticated schedule trial actions. Preserve authorization, ownership, isolation, and bounded execution; update documentation and regression coverage.
* test(sandbox): expect read_file initialization error callback
* fix(agent): address evidence review follow-ups
* fix(agent): preserve retry budgets for OpenAI transport errors
* fix(agent): expose tool execution status in model requests
Project validated execution metadata and exact tool text into request-only JSON so status survives provider serialization. Preserve stored results and receipt hashes, cover SDK and graph boundaries, and migrate replay input hashes without changing recorded responses.
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* fix(mindie): degrade unserializable tool args to str() in XML replay
The XML parser's literal_eval fallback puts values json.dumps rejects
(e.g. Python sets from set-literal arguments) into AIMessage tool_calls
args. Replaying that message from history hit the unguarded json.dumps
in _fix_messages' args join, raising TypeError and failing the whole
request — and every later turn, since the poisoned message rides the
history. Mirror the tool-result json block handling already in the same
function: degrade the value to str() so one unserializable argument
cannot fail the request.
* fix(mindie): reject non-finite floats in literal sets and tuples
* fix(mindie): validate literal dictionary keys recursively
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
The no-tool native stream applied _decode_escaped_newlines_outside_fences
to each streamed chunk independently, but a fenced code block almost never
opens and closes within one token-sized chunk, so the per-chunk fence regex
never saw a complete ``` pair and decoded every literal \n inside the fence.
Code like print("a\nb") reached the streamed answer and the persisted
message content with a real newline, while the non-streaming path and the
tool-mode simulated stream preserved it.
Decode the native stream with a fence-stateful decoder instead: it carries
whether the stream is inside a fence across chunks and holds back a
trailing partial ```/`\n` sequence, so the joined stream equals the one-shot
decode of the same reply. A fence left unclosed by a truncated reply keeps
its escapes, matching how an unterminated fence still renders as code.
Document native no-tool streaming in the MindIE decode contract.
* fix(models): preserve structured MindIE tool results
Signed-off-by: lovett55 <xbzz101800@163.com>
* fix(models): redact and bound structured MindIE tool results
* fix(models): keep structured MindIE ToolMessage content visible
_fix_messages flattened list content keeping only string and type=text
blocks, so a JSON tool result became an empty <tool_response> and the
model could not see the tool output on the next turn. Serialize type=json
blocks onto the same text channel; the existing XML escaping applies to
the serialized text unchanged.
Fixes#6010
Signed-off-by: Yufeng He <40085740+he-yufeng@users.noreply.github.com>
* fix(models): harden the MindIE json channel from review
Review follow-ups on the structured-content fix:
- json.dumps can also raise ValueError (circular reference); catch it
alongside TypeError so the payload degrades to str() instead of
failing the whole request normalization.
- A {"type": "json"} block with no json key keeps the old drop
behavior instead of emitting a literal "null" into the frame.
- PiiRedactionMiddleware now redacts json block payloads leaf-wise
(nested dict/list strings scanned, keys and non-string leaves kept),
so the newly serialized channel participates in the configured
redaction policy for user messages and remote tool results alike.
Without it, redaction-enabled deployments would ship structured PII
raw once the provider serializes the block.
Tests: fallback degrade for both exception paths, missing-key drop,
leaf-wise redaction on the model-call and tool boundaries, and a
middleware-to-MindIE regression pinning redaction through provider
serialization. Red/green verified: the 6 new redaction/json tests
fail without the source changes, 155 pass with them.
Signed-off-by: Yufeng He <40085740+he-yufeng@users.noreply.github.com>
* fix(models): close MindIE structured tool redaction gaps
* fix(agents): budget structured json tool output before provider normalization
Willem's P2 on #6208: _message_text() returned None for {"type": "json"}
blocks, so a large structured ToolMessage slipped past both the tool-call
and history budget gates and reached MindIE's serializer at full size,
ignoring the externalize threshold and the fallback cap.
Render those blocks with the same json.dumps(..., ensure_ascii=False)
serialization the MindIE adapter applies (str() fallback included), so
they count toward the budget everywhere _message_text is consulted.
Images and other non-textual blocks still skip enforcement.
Signed-off-by: Yufeng He <40085740+he-yufeng@users.noreply.github.com>
* fix(mindie): render json blocks for tool messages only
InputSanitizationMiddleware neutralizes strings and text blocks, so a
{"type": "json"} block smuggled into a genuine user message reaches
_fix_messages with its payload untouched. Rendering it into the text
channel handed the model an unescaped, unframed injection (e.g. a
literal <system-reminder>), bypassing the guardrail entirely.
Gate the json-block serialization on ToolMessage: structured tool
results keep riding the text channel (and still get html.escape plus
the <tool_response> framing), while user/assistant json blocks go back
to the old drop behavior. Adds unit coverage for the drop paths plus a
chain regression that runs a genuine user message through the
sanitization middleware and then _fix_messages, asserting the smuggled
payload never reaches the model-bound text.
Signed-off-by: Yufeng He <40085740+he-yufeng@users.noreply.github.com>
* fix(models): preserve configured budgets in combined MindIE fix
---------
Signed-off-by: lovett55 <xbzz101800@163.com>
Signed-off-by: Yufeng He <40085740+he-yufeng@users.noreply.github.com>
Co-authored-by: lovett55 <xbzz101800@163.com>
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
In tool-enabled requests MindIEChatModel._astream falls back to awaiting the full _agenerate response and re-emitting it as simulated AIMessageChunks. The full response carries usage_metadata, but none of the simulated chunks copied it, so chunk aggregation (add_ai_message_chunks) produced a final message with usage_metadata=None. Token usage therefore vanished from token accounting, run stats, persistence and the UI for every tool-enabled streamed turn.
Mirror OpenAI's terminal-usage-frame convention: attach msg.usage_metadata to exactly the last simulated chunk (the trailing tool-call chunk when present, else the last text chunk / the single tool-only chunk) so the aggregated message carries it exactly once. add_usage() is per-chunk additive, so attaching usage to every chunk would multiply the totals.
Scope: MindIEChatModel only; other providers keep native streaming and ainvoke/non-tool astream were already correct.
Tests: regression guard asserting exactly one carrier chunk equals the last one and that merged usage equals the original across all three simulated-stream branches, plus chain-level tests driving the public astream() wrapper and asserting the persisted model_dump() shape.
Closes#5192
* feat(channels): enhance Discord with mention-only mode, thread routing, and typing indicators
Add mention_only config to only respond when bot is mentioned, with
allowed_channels override. Add thread_mode for Hermes-style auto-thread
creation. Add periodic typing indicators while bot is processing.
* fix(discord): include allowed_channels in mention_only skip condition (line 274)
* docs: fix Discord config example to match boolean thread_mode implementation
* style: format with ruff
* fix(discord): apply Copilot review fixes and resolve lint errors
- Remove unused Optional import
- Fix thread_ts type hints to str | None
- Fix has_mention logic for None values
- Implement thread_mode fallback to channel replies on thread creation failure
- Fix thread_mode docstring alignment
- Fix allowed_channels comment formatting in config.example.yaml
* fix(discord): reset context for orphaned threads in mention_only mode
When a message arrives in a thread not tracked by _active_threads,
clear thread_id and typing_target so the message falls through to
the standard channel handling pipeline, which creates a fresh thread
instead of incorrectly routing to the stale thread.
* fix(discord): create new thread on @ when channel has existing tracked thread
When mention_only is enabled and a user @-s the bot in a channel
that already has a tracked thread, create a new thread instead of
incorrectly routing to the old one.
* fix(discord): allow no-@ thread replies while skipping no-@ channel messages
The skip block for no-@ messages was too aggressive — it blocked
continuation replies within tracked threads AND incorrectly routed
no-@ channel messages to the existing thread.
Now:
- Thread message, no @ → routed to existing tracked thread
- Channel message, no @ → skipped
- Channel message, with @ → creates new thread
* feat(discord): add checkmark reaction to acknowledge received messages
* Move discord.py to optional dependency and auto-detect from config.yaml
- Add discord extra to [project.optional-dependencies] in pyproject.toml
- Update detect_uv_extras.py to map channels.discord.enabled: true -> --extra discord
- Set UV_EXTRAS=discord in docker-compose-dev.yaml gateway env
* fix(discord): persist thread-channel mappings to store for recovery after restart
Discord's _active_threads dict was purely in-memory, so all channel-to-thread
mappings were lost on server restart. This fix bridges ChannelStore into
DiscordChannel:
- Save thread mappings to store.json after every thread creation
- Restore active threads from store on DiscordChannel startup
- Pass channel_store to all channels via service.py config injection
Store keys follow the pattern: discord:<channel_id>:<thread_id>
* fix(discord): address Copilot review — fix types, typing targets, cross-thread safety, and config comments
* fix(tests): add multitask_strategy param to mock for clarification follow-up test
* fix(tests): explicitly set model_name=None for title middleware test isolation
* fix(discord): use trigger_typing() instead of typing() for typing indicators
discord.py 2.x TextChannel.typing() and Thread.typing() are async context
managers, not one-shot coroutines. Use trigger_typing() for periodic
typing indicator pings.
* fix(discord): cancel typing tasks on channel shutdown
Prevents 'Task was destroyed but it is pending' warnings when the
Discord client stops while typing indicator loops are still running.
* fix(scripts): detect nested YAML config for discord extra
section_value() only matched top-level YAML sections. Added
nested_section_value() that handles two-level nesting (e.g.,
channels.discord.enabled), so auto-detection of the discord
extra works when config uses the standard nested format.
* fix(docker): remove hard-coded UV_EXTRAS=discord from dev compose
Relies on auto-detection via detect_uv_extras.py instead of forcing
discord.py install even when channels.discord.enabled is false.
Matches production docker-compose.yaml behavior (UV_EXTRAS:-).
* refactor(nginx): move proxy_buffering/proxy_cache to server level
DRY cleanup — these directives were repeated in 14 location blocks.
Set at server level once, reducing duplication and risk of drift.
* fix(discord): use dedicated JSON file for thread persistence
Replace ChannelStore usage for Discord thread-ID persistence with a
dedicated discord_threads.json file. ChannelStore is designed to map
IM conversations to DeerFlow thread IDs — using it to persist Discord
thread IDs was semantically wrong and confusing.
Changes:
- _save_thread() now reads/writes a simple {channel_id: thread_id} JSON dict
- _load_active_threads() reads directly from the JSON file
- File path derived from ChannelStore directory (when available) or
defaults to ~/.deer-flow/channels/discord_threads.json
- Removed unused ChannelStore import
* fix(discord): address WillemJiang's code review comments on PR #2842
1. Remove semantically incorrect message_in_thread variable. At this code
point (after the Thread case is handled above), we're guaranteed to be in
a channel, not a thread. Always apply mention_only check here.
2. Add _active_thread_ids reverse-lookup set for O(1) thread ID membership
checks instead of O(n) scan of _active_threads.values(). Keep the set
in sync with _active_threads in _load_active_threads() and _save_thread().
3. Add _thread_store_lock (threading.Lock) to protect _active_threads and
the JSON file from concurrent access between the Discord loop thread
(_run_client) and the main thread (_load_active_threads, _save_thread).
* feat(models): 适配 MindIE引擎的模型
* test: add unit tests for MindIEChatModel adapter and fix PR review comments
* chore: update uv.lock with pytest-asyncio
* build: add pytest-asyncio to test dependencies
* fix: address PR review comments (lazy import, cache clients, safe newline escape, strict xml regex)
* fix(mindie): preserve string args without JSON quotes in XML tool call serialization
* fix(mindie): preserve string args without JSON quotes in XML tool call serialization
* test_mindie_provider:format
* Potential fix for pull request finding
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
* fix(mindie): prevent nested tool_call params from leaking into outer args
* fixed by escaping XML entities in _fix_messages and unescaping during parse, with regression tests added.
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
