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46 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
 rayhpeng
|
00e0e9a49a |
feat(persistence): add unified persistence layer with event store, token tracking, and feedback (#1930)
* feat(persistence): add SQLAlchemy 2.0 async ORM scaffold Introduce a unified database configuration (DatabaseConfig) that controls both the LangGraph checkpointer and the DeerFlow application persistence layer from a single `database:` config section. New modules: - deerflow.config.database_config — Pydantic config with memory/sqlite/postgres backends - deerflow.persistence — async engine lifecycle, DeclarativeBase with to_dict mixin, Alembic skeleton - deerflow.runtime.runs.store — RunStore ABC + MemoryRunStore implementation Gateway integration initializes/tears down the persistence engine in the existing langgraph_runtime() context manager. Legacy checkpointer config is preserved for backward compatibility. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(persistence): add RunEventStore ABC + MemoryRunEventStore Phase 2-A prerequisite for event storage: adds the unified run event stream interface (RunEventStore) with an in-memory implementation, RunEventsConfig, gateway integration, and comprehensive tests (27 cases). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(persistence): add ORM models, repositories, DB/JSONL event stores, RunJournal, and API endpoints Phase 2-B: run persistence + event storage + token tracking. - ORM models: RunRow (with token fields), ThreadMetaRow, RunEventRow - RunRepository implements RunStore ABC via SQLAlchemy ORM - ThreadMetaRepository with owner access control - DbRunEventStore with trace content truncation and cursor pagination - JsonlRunEventStore with per-run files and seq recovery from disk - RunJournal (BaseCallbackHandler) captures LLM/tool/lifecycle events, accumulates token usage by caller type, buffers and flushes to store - RunManager now accepts optional RunStore for persistent backing - Worker creates RunJournal, writes human_message, injects callbacks - Gateway deps use factory functions (RunRepository when DB available) - New endpoints: messages, run messages, run events, token-usage - ThreadCreateRequest gains assistant_id field - 92 tests pass (33 new), zero regressions Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(persistence): add user feedback + follow-up run association Phase 2-C: feedback and follow-up tracking. - FeedbackRow ORM model (rating +1/-1, optional message_id, comment) - FeedbackRepository with CRUD, list_by_run/thread, aggregate stats - Feedback API endpoints: create, list, stats, delete - follow_up_to_run_id in RunCreateRequest (explicit or auto-detected from latest successful run on the thread) - Worker writes follow_up_to_run_id into human_message event metadata - Gateway deps: feedback_repo factory + getter - 17 new tests (14 FeedbackRepository + 3 follow-up association) - 109 total tests pass, zero regressions Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * test+config: comprehensive Phase 2 test coverage + deprecate checkpointer config - config.example.yaml: deprecate standalone checkpointer section, activate unified database:sqlite as default (drives both checkpointer + app data) - New: test_thread_meta_repo.py (14 tests) — full ThreadMetaRepository coverage including check_access owner logic, list_by_owner pagination - Extended test_run_repository.py (+4 tests) — completion preserves fields, list ordering desc, limit, owner_none returns all - Extended test_run_journal.py (+8 tests) — on_chain_error, track_tokens=false, middleware no ai_message, unknown caller tokens, convenience fields, tool_error, non-summarization custom event - Extended test_run_event_store.py (+7 tests) — DB batch seq continuity, make_run_event_store factory (memory/db/jsonl/fallback/unknown) - Extended test_phase2b_integration.py (+4 tests) — create_or_reject persists, follow-up metadata, summarization in history, full DB-backed lifecycle - Fixed DB integration test to use proper fake objects (not MagicMock) for JSON-serializable metadata - 157 total Phase 2 tests pass, zero regressions Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * config: move default sqlite_dir to .deer-flow/data Keep SQLite databases alongside other DeerFlow-managed data (threads, memory) under the .deer-flow/ directory instead of a top-level ./data folder. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * refactor(persistence): remove UTFJSON, use engine-level json_serializer + datetime.now() - Replace custom UTFJSON type with standard sqlalchemy.JSON in all ORM models. Add json_serializer=json.dumps(ensure_ascii=False) to all create_async_engine calls so non-ASCII text (Chinese etc.) is stored as-is in both SQLite and Postgres. - Change ORM datetime defaults from datetime.now(UTC) to datetime.now(), remove UTC imports. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * refactor(gateway): simplify deps.py with getter factory + inline repos - Replace 6 identical getter functions with _require() factory. - Inline 3 _make_*_repo() factories into langgraph_runtime(), call get_session_factory() once instead of 3 times. - Add thread_meta upsert in start_run (services.py). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(docker): add UV_EXTRAS build arg for optional dependencies Support installing optional dependency groups (e.g. postgres) at Docker build time via UV_EXTRAS build arg: UV_EXTRAS=postgres docker compose build Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * refactor(journal): fix flush, token tracking, and consolidate tests RunJournal fixes: - _flush_sync: retain events in buffer when no event loop instead of dropping them; worker's finally block flushes via async flush(). - on_llm_end: add tool_calls filter and caller=="lead_agent" guard for ai_message events; mark message IDs for dedup with record_llm_usage. - worker.py: persist completion data (tokens, message count) to RunStore in finally block. Model factory: - Auto-inject stream_usage=True for BaseChatOpenAI subclasses with custom api_base, so usage_metadata is populated in streaming responses. Test consolidation: - Delete test_phase2b_integration.py (redundant with existing tests). - Move DB-backed lifecycle test into test_run_journal.py. - Add tests for stream_usage injection in test_model_factory.py. - Clean up executor/task_tool dead journal references. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(events): widen content type to str|dict in all store backends Allow event content to be a dict (for structured OpenAI-format messages) in addition to plain strings. Dict values are JSON-serialized for the DB backend and deserialized on read; memory and JSONL backends handle dicts natively. Trace truncation now serializes dicts to JSON before measuring. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(events): use metadata flag instead of heuristic for dict content detection Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(converters): add LangChain-to-OpenAI message format converters Pure functions langchain_to_openai_message, langchain_to_openai_completion, langchain_messages_to_openai, and _infer_finish_reason for converting LangChain BaseMessage objects to OpenAI Chat Completions format, used by RunJournal for event storage. 15 unit tests added. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(converters): handle empty list content as null, clean up test Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(events): human_message content uses OpenAI user message format Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * feat(events): ai_message uses OpenAI format, add ai_tool_call message event - ai_message content now uses {"role": "assistant", "content": "..."} format - New ai_tool_call message event emitted when lead_agent LLM responds with tool_calls - ai_tool_call uses langchain_to_openai_message converter for consistent format - Both events include finish_reason in metadata ("stop" or "tool_calls") Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(events): add tool_result message event with OpenAI tool message format Cache tool_call_id from on_tool_start keyed by run_id as fallback for on_tool_end, then emit a tool_result message event (role=tool, tool_call_id, content) after each successful tool completion. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * feat(events): summary content uses OpenAI system message format Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(events): replace llm_start/llm_end with llm_request/llm_response in OpenAI format Add on_chat_model_start to capture structured prompt messages as llm_request events. Replace llm_end trace events with llm_response using OpenAI Chat Completions format. Track llm_call_index to pair request/response events. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(events): add record_middleware method for middleware trace events Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * test(events): add full run sequence integration test for OpenAI content format Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * feat(events): align message events with checkpoint format and add middleware tag injection - Message events (ai_message, ai_tool_call, tool_result, human_message) now use BaseMessage.model_dump() format, matching LangGraph checkpoint values.messages - on_tool_end extracts tool_call_id/name/status from ToolMessage objects - on_tool_error now emits tool_result message events with error status - record_middleware uses middleware:{tag} event_type and middleware category - Summarization custom events use middleware:summarize category - TitleMiddleware injects middleware:title tag via get_config() inheritance - SummarizationMiddleware model bound with middleware:summarize tag - Worker writes human_message using HumanMessage.model_dump() Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(threads): switch search endpoint to threads_meta table and sync title - POST /api/threads/search now queries threads_meta table directly, removing the two-phase Store + Checkpointer scan approach - Add ThreadMetaRepository.search() with metadata/status filters - Add ThreadMetaRepository.update_display_name() for title sync - Worker syncs checkpoint title to threads_meta.display_name on run completion - Map display_name to values.title in search response for API compatibility Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(threads): history endpoint reads messages from event store - POST /api/threads/{thread_id}/history now combines two data sources: checkpointer for checkpoint_id, metadata, title, thread_data; event store for messages (complete history, not truncated by summarization) - Strip internal LangGraph metadata keys from response - Remove full channel_values serialization in favor of selective fields Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: remove duplicate optional-dependencies header in pyproject.toml Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(middleware): pass tagged config to TitleMiddleware ainvoke call Without the config, the middleware:title tag was not injected, causing the LLM response to be recorded as a lead_agent ai_message in run_events. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: resolve merge conflict in .env.example Keep both DATABASE_URL (from persistence-scaffold) and WECOM credentials (from main) after the merge. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(persistence): address review feedback on PR #1851 - Fix naive datetime.now() → datetime.now(UTC) in all ORM models - Fix seq race condition in DbRunEventStore.put() with FOR UPDATE and UNIQUE(thread_id, seq) constraint - Encapsulate _store access in RunManager.update_run_completion() - Deduplicate _store.put() logic in RunManager via _persist_to_store() - Add update_run_completion to RunStore ABC + MemoryRunStore - Wire follow_up_to_run_id through the full create path - Add error recovery to RunJournal._flush_sync() lost-event scenario - Add migration note for search_threads breaking change - Fix test_checkpointer_none_fix mock to set database=None Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * chore: update uv.lock Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(persistence): address 22 review comments from CodeQL, Copilot, and Code Quality Bug fixes: - Sanitize log params to prevent log injection (CodeQL) - Reset threads_meta.status to idle/error when run completes - Attach messages only to latest checkpoint in /history response - Write threads_meta on POST /threads so new threads appear in search Lint fixes: - Remove unused imports (journal.py, migrations/env.py, test_converters.py) - Convert lambda to named function (engine.py, Ruff E731) - Remove unused logger definitions in repos (Ruff F841) - Add logging to JSONL decode errors and empty except blocks - Separate assert side-effects in tests (CodeQL) - Remove unused local variables in tests (Ruff F841) - Fix max_trace_content truncation to use byte length, not char length Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * style: apply ruff format to persistence and runtime files Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * Potential fix for pull request finding 'Statement has no effect' Co-authored-by: Copilot Autofix powered by AI <223894421+github-code-quality[bot]@users.noreply.github.com> * refactor(runtime): introduce RunContext to reduce run_agent parameter bloat Extract checkpointer, store, event_store, run_events_config, thread_meta_repo, and follow_up_to_run_id into a frozen RunContext dataclass. Add get_run_context() in deps.py to build the base context from app.state singletons. start_run() uses dataclasses.replace() to enrich per-run fields before passing ctx to run_agent. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * refactor(gateway): move sanitize_log_param to app/gateway/utils.py Extract the log-injection sanitizer from routers/threads.py into a shared utils module and rename to sanitize_log_param (public API). Eliminates the reverse service → router import in services.py. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * perf: use SQL aggregation for feedback stats and thread token usage Replace Python-side counting in FeedbackRepository.aggregate_by_run with a single SELECT COUNT/SUM query. Add RunStore.aggregate_tokens_by_thread abstract method with SQL GROUP BY implementation in RunRepository and Python fallback in MemoryRunStore. Simplify the thread_token_usage endpoint to delegate to the new method, eliminating the limit=10000 truncation risk. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: annotate DbRunEventStore.put() as low-frequency path Add docstring clarifying that put() opens a per-call transaction with FOR UPDATE and should only be used for infrequent writes (currently just the initial human_message event). High-throughput callers should use put_batch() instead. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(threads): fall back to Store search when ThreadMetaRepository is unavailable When database.backend=memory (default) or no SQL session factory is configured, search_threads now queries the LangGraph Store instead of returning 503. Returns empty list if neither Store nor repo is available. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * refactor(persistence): introduce ThreadMetaStore ABC for backend-agnostic thread metadata Add ThreadMetaStore abstract base class with create/get/search/update/delete interface. ThreadMetaRepository (SQL) now inherits from it. New MemoryThreadMetaStore wraps LangGraph BaseStore for memory-mode deployments. deps.py now always provides a non-None thread_meta_repo, eliminating all `if thread_meta_repo is not None` guards in services.py, worker.py, and routers/threads.py. search_threads no longer needs a Store fallback branch. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * refactor(history): read messages from checkpointer instead of RunEventStore The /history endpoint now reads messages directly from the checkpointer's channel_values (the authoritative source) instead of querying RunEventStore.list_messages(). The RunEventStore API is preserved for other consumers. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(persistence): address new Copilot review comments - feedback.py: validate thread_id/run_id before deleting feedback - jsonl.py: add path traversal protection with ID validation - run_repo.py: parse `before` to datetime for PostgreSQL compat - thread_meta_repo.py: fix pagination when metadata filter is active - database_config.py: use resolve_path for sqlite_dir consistency Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * Implement skill self-evolution and skill_manage flow (#1874) * chore: ignore .worktrees directory * Add skill_manage self-evolution flow * Fix CI regressions for skill_manage * Address PR review feedback for skill evolution * fix(skill-evolution): preserve history on delete * fix(skill-evolution): tighten scanner fallbacks * docs: add skill_manage e2e evidence screenshot * fix(skill-manage): avoid blocking fs ops in session runtime --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> * fix(config): resolve sqlite_dir relative to CWD, not Paths.base_dir resolve_path() resolves relative to Paths.base_dir (.deer-flow), which double-nested the path to .deer-flow/.deer-flow/data/app.db. Use Path.resolve() (CWD-relative) instead. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * Feature/feishu receive file (#1608) * feat(feishu): add channel file materialization hook for inbound messages - Introduce Channel.receive_file(msg, thread_id) as a base method for file materialization; default is no-op. - Implement FeishuChannel.receive_file to download files/images from Feishu messages, save to sandbox, and inject virtual paths into msg.text. - Update ChannelManager to call receive_file for any channel if msg.files is present, enabling downstream model access to user-uploaded files. - No impact on Slack/Telegram or other channels (they inherit the default no-op). * style(backend): format code with ruff for lint compliance - Auto-formatted packages/harness/deerflow/agents/factory.py and tests/test_create_deerflow_agent.py using `ruff format` - Ensured both files conform to project linting standards - Fixes CI lint check failures caused by code style issues * fix(feishu): handle file write operation asynchronously to prevent blocking * fix(feishu): rename GetMessageResourceRequest to _GetMessageResourceRequest and remove redundant code * test(feishu): add tests for receive_file method and placeholder replacement * fix(manager): remove unnecessary type casting for channel retrieval * fix(feishu): update logging messages to reflect resource handling instead of image * fix(feishu): sanitize filename by replacing invalid characters in file uploads * fix(feishu): improve filename sanitization and reorder image key handling in message processing * fix(feishu): add thread lock to prevent filename conflicts during file downloads * fix(test): correct bad merge in test_feishu_parser.py * chore: run ruff and apply formatting cleanup fix(feishu): preserve rich-text attachment order and improve fallback filename handling * fix(docker): restore gateway env vars and fix langgraph empty arg issue (#1915) Two production docker-compose.yaml bugs prevent `make up` from working: 1. Gateway missing DEER_FLOW_CONFIG_PATH and DEER_FLOW_EXTENSIONS_CONFIG_PATH environment overrides. Added in |
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KKK
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055e4df049 |
fix(sandbox): add input sanitisation guard to SandboxAuditMiddleware (#1872)
* fix(sandbox): add L2 input sanitisation to SandboxAuditMiddleware Add _validate_input() to reject malformed bash commands before regex classification: empty commands, oversized commands (>10 000 chars), and null bytes that could cause detection/execution layer inconsistency. * fix(sandbox): address Copilot review — type guard, log truncation, reject reason - Coerce None/non-string command to str before validation - Truncate oversized commands in audit logs to prevent log amplification - Propagate reject_reason through _pre_process() to block message - Remove L2 label from comments and test class names * fix(sandbox): isinstance type guard + async input sanitisation tests Address review comments: - Replace str() coercion with isinstance(raw_command, str) guard so non-string truthy values (0, [], False) fall back to empty string instead of passing validation as "0"/"[]"/"False". - Add TestInputSanitisationBlocksInAwrapToolCall with 4 async tests covering empty, null-byte, oversized, and None command via awrap_tool_call path. |
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Zhou
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1ced6e977c |
fix(backend): preserve viewed image reducer metadata (#1900)
Fix concurrent viewed_images state updates for multi-image input by preserving the reducer metadata in the vision middleware state schema. |
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thefoolgy
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8049785de6 |
fix(memory): case-insensitive fact deduplication and positive reinforcement detection (#1804)
* fix(memory): case-insensitive fact deduplication and positive reinforcement detection Two fixes to the memory system: 1. _fact_content_key() now lowercases content before comparison, preventing semantically duplicate facts like "User prefers Python" and "user prefers python" from being stored separately. 2. Adds detect_reinforcement() to MemoryMiddleware (closes #1719), mirroring detect_correction(). When users signal approval ("yes exactly", "perfect", "完全正确", etc.), the memory updater now receives reinforcement_detected=True and injects a hint prompting the LLM to record confirmed preferences and behaviors with high confidence. Changes across the full signal path: - memory_middleware.py: _REINFORCEMENT_PATTERNS + detect_reinforcement() - queue.py: reinforcement_detected field in ConversationContext and add() - updater.py: reinforcement_detected param in update_memory() and update_memory_from_conversation(); builds reinforcement_hint alongside the existing correction_hint Tests: 11 new tests covering deduplication, hint injection, and signal detection (Chinese + English patterns, window boundary, conflict with correction). Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix(memory): address Copilot review comments on reinforcement detection - Tighten _REINFORCEMENT_PATTERNS: remove 很好, require punctuation/end-of-string boundaries on remaining patterns, split this-is-good into stricter variants - Suppress reinforcement_detected when correction_detected is true to avoid mixed-signal noise - Use casefold() instead of lower() for Unicode-aware fact deduplication - Add missing test coverage for reinforcement_detected OR merge and forwarding in queue --------- Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> |
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DanielWalnut
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2a150f5d4a |
fix: unblock concurrent threads and workspace hydration (#1839)
* fix: unblock concurrent threads and workspace hydration * fix: restore async title generation * fix: address PR review feedback * style: format lead agent prompt |
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SHIYAO ZHANG
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163121d327 |
fix(uploads): handle split-bold headings and ** ** artefacts in extract_outline (#1838)
* feat(uploads): guide agent to use grep/glob/read_file for uploaded documents Add workflow guidance to the <uploaded_files> context block so the agent knows to use grep and glob (added in #1784) alongside read_file when working with uploaded documents, rather than falling back to web search. This is the final piece of the three-PR PDF agentic search pipeline: - PR1 (#1727): pymupdf4llm converter produces structured Markdown with headings - PR2 (#1738): document outline injected into agent context with line numbers - PR3 (this): agent guided to use outline + grep + read_file workflow * feat(uploads): add file-first priority and fallback guidance to uploaded_files context * fix(uploads): handle split-bold headings and ** ** artefacts in extract_outline - Add _clean_bold_title() to merge adjacent bold spans (** **) produced by pymupdf4llm when bold text crosses span boundaries - Add _SPLIT_BOLD_HEADING_RE (Style 3) to recognise **<num>** **<title>** headings common in academic papers; excludes pure-number table headers and rows with more than 4 bold blocks - When outline is empty, read first 5 non-empty lines of the .md as a content preview and surface a grep hint in the agent context - Update _format_file_entry to render the preview + grep hint instead of silently omitting the outline section - Add 3 new extract_outline tests and 2 new middleware tests (65 total) * fix(uploads): address Copilot review comments on extract_outline regex - Replace ASCII [A-Za-z] guard with negative lookahead to support non-ASCII titles (e.g. **1** **概述**); pure-numeric/punctuation blocks still excluded - Replace .+ with [^*]+ and cap repetition at {0,2} (four blocks total) to keep _SPLIT_BOLD_HEADING_RE linear and avoid ReDoS on malformed input - Remove now-redundant len(blocks) <= 4 code-level check (enforced by regex) - Log debug message with exc_info when preview extraction fails |
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SHIYAO ZHANG
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bbd0866374 |
feat(uploads): guide agent using agentic search for uploaded documents (#1816)
* feat(uploads): guide agent to use grep/glob/read_file for uploaded documents Add workflow guidance to the <uploaded_files> context block so the agent knows to use grep and glob (added in #1784) alongside read_file when working with uploaded documents, rather than falling back to web search. This is the final piece of the three-PR PDF agentic search pipeline: - PR1 (#1727): pymupdf4llm converter produces structured Markdown with headings - PR2 (#1738): document outline injected into agent context with line numbers - PR3 (this): agent guided to use outline + grep + read_file workflow * feat(uploads): add file-first priority and fallback guidance to uploaded_files context |
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ppyt
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db82b59254 |
fix(middleware): handle list-type AIMessage.content in LoopDetectionMiddleware (#1823)
* fix: inject longTermBackground into memory prompt
The format_memory_for_injection function only processed recentMonths and
earlierContext from the history section, silently dropping longTermBackground.
The LLM writes longTermBackground correctly and it persists to memory.json,
but it was never injected into the system prompt — making the user's
long-term background invisible to the AI.
Add the missing field handling and a regression test.
* fix(middleware): handle list-type AIMessage.content in LoopDetectionMiddleware
LangChain AIMessage.content can be str | list. When using providers that
return structured content blocks (e.g. Anthropic thinking mode, certain
OpenAI-compatible gateways), content is a list of dicts like
[{"type": "text", "text": "..."}].
The hard_limit branch in _apply() concatenated content with a string via
(last_msg.content or "") + f"\n\n{_HARD_STOP_MSG}", which raises
TypeError when content is a non-empty list (list + str is invalid).
Add _append_text() static method that:
- Returns the text directly when content is None
- Appends a {"type": "text"} block when content is a list
- Falls back to string concatenation when content is a str
This is consistent with how other modules in the project already handle
list content (client.py._extract_text, memory_middleware, executor.py).
* test(middleware): add unit tests for _append_text and list content hard stop
Add regression tests to verify LoopDetectionMiddleware handles list-type
AIMessage.content correctly during hard stop:
- TestAppendText: unit tests for the new _append_text() static method
covering None, str, list (including empty list) content types
- TestHardStopWithListContent: integration tests verifying hard stop
works correctly with list content (Anthropic thinking mode), None
content, and str content
Requested by reviewer in PR #1823.
* fix(middleware): improve _append_text robustness and test isolation
- Add explicit isinstance(content, str) check with fallback for
unexpected types (coerce to str) to prevent TypeError on edge cases
- Deep-copy list content in _make_state() test helper to prevent
shared mutable references across test iterations
- Add test_unexpected_type_coerced_to_str: verify fallback for
non-str/list/None content types
- Add test_list_content_not_mutated_in_place: verify _append_text
does not modify the original list
* style: fix ruff format whitespace in test file
---------
Co-authored-by: ppyt <14163465+ppyt@users.noreply.github.com>
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SHIYAO ZHANG
|
5ff230eafd |
feat(uploads): inject document outline into agent context for converted files (#1738)
* feat(uploads): inject document outline into agent context for converted files
Extract headings from converted .md files and inject them into the
<uploaded_files> context block so the agent can navigate large documents
by line number before reading.
- Add `extract_outline()` to `file_conversion.py`: recognises standard
Markdown headings (#/##/###) and SEC-style bold structural headings
(**ITEM N. BUSINESS**, **PART II**); caps at 50 entries; excludes
cover-page boilerplate (WASHINGTON DC, CURRENT REPORT, SIGNATURES)
- Add `_extract_outline_for_file()` helper in `uploads_middleware.py`:
looks for a sibling `.md` file produced by the conversion pipeline
- Update `UploadsMiddleware._create_files_message()` to render the outline
under each file entry with `L{line}: {title}` format and a `read_file`
prompt for range-based reading
- Tests: 10 new tests for `extract_outline()`, 4 new tests for outline
injection in `UploadsMiddleware`; existing test updated for new `outline`
field in `uploaded_files` state
Partially addresses #1647 (agent ignores uploaded files).
* fix(uploads): stream outline file reads and strip inline bold from heading titles
- Switch extract_outline() from read_text().splitlines() to open()+line iteration
so large converted documents are not loaded into memory on every agent turn;
exits as soon as MAX_OUTLINE_ENTRIES is reached (Copilot suggestion)
- Strip **...** wrapper from standard Markdown heading titles before appending
to outline so agent context stays clean (e.g. "## **Overview**" → "Overview")
(Copilot suggestion)
- Remove unused pathlib.Path import and fix import sort order in test_file_conversion.py
to satisfy ruff CI lint
* fix(uploads): show truncation hint when outline exceeds MAX_OUTLINE_ENTRIES
When extract_outline() hits the cap it now appends a sentinel entry
{"truncated": True} instead of silently dropping the rest of the headings.
UploadsMiddleware reads the sentinel and renders a hint line:
... (showing first 50 headings; use `read_file` to explore further)
Without this the agent had no way to know the outline was incomplete and
would treat the first 50 headings as the full document structure.
* fix(uploads): fall back to configurable.thread_id when runtime.context lacks thread_id
runtime.context does not always carry thread_id (depends on LangGraph
invocation path). ThreadDataMiddleware already falls back to
get_config().configurable.thread_id — apply the same pattern so
UploadsMiddleware can resolve the uploads directory and attach outlines
in all invocation paths.
* style: apply ruff format
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
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||
|
SHIYAO ZHANG
|
46d0c329c1 |
fix(uploads): fall back to configurable.thread_id when runtime.context lacks thread_id (#1814)
* fix(uploads): fall back to configurable.thread_id when runtime.context lacks thread_id runtime.context does not always carry thread_id depending on the LangGraph invocation path. When absent, uploads_dir resolved to None and the entire outline/historical-files attachment was silently skipped. Apply the same fallback pattern already used by ThreadDataMiddleware: try get_config().configurable.thread_id, with a RuntimeError guard for test environments where get_config() is called outside a runnable context. Discovered via live integration testing (curl against local LangGraph). Unit tests inject uploads_dir directly and would not catch this. * style: apply ruff format to uploads_middleware.py |
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|
Rain120
|
a2aba23962 | fix: replace the offline link in the lead_agent prompt (#1800) | ||
|
ppyt
|
5664b9d413 |
fix: inject longTermBackground into memory prompt (#1734)
The format_memory_for_injection function only processed recentMonths and earlierContext from the history section, silently dropping longTermBackground. The LLM writes longTermBackground correctly and it persists to memory.json, but it was never injected into the system prompt — making the user's long-term background invisible to the AI. Add the missing field handling and a regression test. Co-authored-by: ppyt <14163465+ppyt@users.noreply.github.com> |
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|
greatmengqi
|
8128a3bc57 | fix: enable DanglingToolCallMiddleware for subagents (#1766) | ||
|
knukn
|
f8fb8d6fb1 |
feat/per agent skill filter (#1650)
* feat(agent): 为AgentConfig添加skills字段并更新lead_agent系统提示 在AgentConfig中添加skills字段以支持配置agent可用技能 更新lead_agent的系统提示模板以包含可用技能信息 * fix: resolve agent skill configuration edge cases and add tests * Update backend/packages/harness/deerflow/agents/lead_agent/prompt.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * refactor(agent): address PR review comments for skills configuration - Add detailed docstring to `skills` field in `AgentConfig` to clarify the semantics of `None` vs `[]`. - Add unit tests in `test_custom_agent.py` to verify `load_agent_config()` correctly parses omitted skills and explicit empty lists. - Fix `test_make_lead_agent_empty_skills_passed_correctly` to include `agent_name` in the runtime config, ensuring it exercises the real code path. * docs: 添加关于按代理过滤技能的配置说明 在配置示例文件和文档中添加说明，解释如何通过代理的config.yaml文件限制加载的技能 --------- Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> |
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|
肖
|
3a672b39c7 |
Fix/1681 llm call retry handling (#1683)
* fix(runtime): handle llm call errors gracefully * fix(runtime): preserve graph control flow in llm retry middleware --------- Co-authored-by: luoxiao6645 <luoxiao6645@gmail.com> |
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|
AochenShen99
|
0cdecf7b30 |
feat(memory): structured reflection + correction detection in MemoryMiddleware (#1620) (#1668)
* feat(memory): add structured reflection and correction detection * fix(memory): align sourceError schema and prompt guidance --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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|
Admire
|
aae59a8ba8 |
fix: surface configured sandbox mounts to agents (#1638)
* fix: surface configured sandbox mounts to agents * fix: address PR review feedback --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
||
|
Admire
|
9a557751d6 |
feat: support memory import and export (#1521)
* feat: support memory import and export * fix(memory): address review feedback * style: format memory settings page --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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|
rayhpeng
|
34e835bc33 |
feat(gateway): implement LangGraph Platform API in Gateway, replace langgraph-cli (#1403)
* feat(gateway): implement LangGraph Platform API in Gateway, replace langgraph-cli Implement all core LangGraph Platform API endpoints in the Gateway, allowing it to fully replace the langgraph-cli dev server for local development. This eliminates a heavyweight dependency and simplifies the development stack. Changes: - Add runs lifecycle endpoints (create, stream, wait, cancel, join) - Add threads CRUD and search endpoints - Add assistants compatibility endpoints (search, get, graph, schemas) - Add StreamBridge (in-memory pub/sub for SSE) and async provider - Add RunManager with atomic create_or_reject (eliminates TOCTOU race) - Add worker with interrupt/rollback cancel actions and runtime context injection - Route /api/langgraph/* to Gateway in nginx config - Skip langgraph-cli startup by default (SKIP_LANGGRAPH_SERVER=0 to restore) - Add unit tests for RunManager, SSE format, and StreamBridge * fix: drain bridge queue on client disconnect to prevent backpressure When on_disconnect=continue, keep consuming events from the bridge without yielding, so the worker is not blocked by a full queue. Only on_disconnect=cancel breaks out immediately. Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * fix: remove pytest import Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * fix: Fix default stream_mode to ["values", "messages-tuple"] Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * fix: Remove unused if_exists field from ThreadCreateRequest Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * fix: address review comments on gateway LangGraph API - Mount runs.py router in app.py (missing include_router) - Normalize interrupt_before/after "*" to node list before run_agent() - Use entry.id for SSE event ID instead of counter - Drain bridge queue on disconnect when on_disconnect=continue - Reuse serialization helper in wait_run() for consistent wire format - Reject unsupported multitask_strategy with 400 - Remove SKIP_LANGGRAPH_SERVER fallback, always use Gateway * feat: extract app.state access into deps.py Encapsulate read/write operations for singleton objects (RunManager, StreamBridge, checkpointer) held in app.state into a shared utility, reducing repeated access patterns across router modules. * feat: extract deerflow.runtime.serialization module with tests Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * refactor: replace duplicated serialization with deerflow.runtime.serialization Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: extract app/gateway/services.py with run lifecycle logic Create a service layer that centralizes SSE formatting, input/config normalization, and run lifecycle management. Router modules will delegate to these functions instead of using private cross-imported helpers. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * refactor: wire routers to use services layer, remove cross-module private imports Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * style: apply ruff formatting to refactored files Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(runtime): support LangGraph dev server and add compat route - Enable official LangGraph dev server for local development workflow - Decouple runtime components from agents package for better separation - Provide gateway-backed fallback route when dev server is skipped - Simplify lifecycle management using context manager in gateway * feat(runtime): add Store providers with auto-backend selection - Add async_provider.py and provider.py under deerflow/runtime/store/ - Support memory, sqlite, postgres backends matching checkpointer config - Integrate into FastAPI lifespan via AsyncExitStack in deps.py - Replace hardcoded InMemoryStore with config-driven factory * refactor(gateway): migrate thread management from checkpointer to Store and resolve multiple endpoint failures - Add Store-backed CRUD helpers (_store_get, _store_put, _store_upsert) - Replace checkpoint-scanning search with two-phase strategy: phase 1 reads Store (O(threads)), phase 2 backfills from checkpointer for legacy/LangGraph Server threads with lazy migration - Extend Store record schema with values field for title persistence - Sync thread title from checkpoint to Store after run completion - Fix /threads/{id}/runs/{run_id}/stream 405 by accepting both GET and POST methods; POST handles interrupt/rollback actions - Fix /threads/{id}/state 500 by separating read_config and write_config, adding checkpoint_ns to configurable, and shallow-copying checkpoint/metadata before mutation - Sync title to Store on state update for immediate search reflection - Move _upsert_thread_in_store into services.py, remove duplicate logic - Add _sync_thread_title_after_run: await run task, read final checkpoint title, write back to Store record - Spawn title sync as background task from start_run when Store exists * refactor(runtime): deduplicate store and checkpointer provider logic Extract _ensure_sqlite_parent_dir() helper into checkpointer/provider.py and use it in all three places that previously inlined the same mkdir logic. Consolidate duplicate error constants in store/async_provider.py by importing from store/provider.py instead of redefining them. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * refactor(runtime): move SQLite helpers to runtime/store, checkpointer imports from store _resolve_sqlite_conn_str and _ensure_sqlite_parent_dir now live in runtime/store/provider.py. agents/checkpointer/provider and agents/checkpointer/async_provider import from there, reversing the previous dependency direction (store → checkpointer becomes checkpointer → store). Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * refactor(runtime): extract SQLite helpers into runtime/store/_sqlite_utils.py Move resolve_sqlite_conn_str and ensure_sqlite_parent_dir out of checkpointer/provider.py into a dedicated _sqlite_utils module. Functions are now public (no underscore prefix), making cross-module imports semantically correct. All four provider files import from the single shared location. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix(gateway): use adelete_thread to fully remove thread checkpoints on delete AsyncSqliteSaver has no adelete method — the previous hasattr check always evaluated to False, silently leaving all checkpoint rows in the database. Switch to adelete_thread(thread_id) which deletes every checkpoint and pending-write row for the thread across all namespaces (including sub-graph checkpoints). Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix(gateway): remove dead bridge_cm/ckpt_cm code and fix StrEnum lint app.py had unreachable code after the async-with lifespan refactor: bridge_cm and ckpt_cm were referenced but never defined (F821), and the channel service startup/shutdown was outside the langgraph_runtime block so it never ran. Move channel service lifecycle inside the async-with block where it belongs. Replace str+Enum inheritance in RunStatus and DisconnectMode with StrEnum as suggested by UP042. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * style: format with ruff --------- Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> Co-authored-by: JeffJiang <for-eleven@hotmail.com> Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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|
SHIYAO ZHANG
|
9aa3ff7c48 |
feat(sandbox): add SandboxAuditMiddleware for bash command security auditing (#1532)
* feat(sandbox): add SandboxAuditMiddleware for bash command security auditing Addresses the LocalSandbox escape vector reported in #1224 where bash tool calls can execute destructive commands against the host filesystem. - Add SandboxAuditMiddleware with three-tier command classification: - High-risk (block): rm -rf /, curl|bash, dd if=, mkfs, /etc/shadow access - Medium-risk (warn): pip install, apt install, chmod 777 - Safe (pass): normal workspace operations - Register middleware after GuardrailMiddleware in _build_runtime_middlewares, applied to both lead agent and subagents - Structured audit log via standard logger (visible in langgraph.log) - Medium-risk commands execute but append a warning to the tool result, allowing the LLM to self-correct without blocking legitimate workflows - High-risk commands return an error ToolMessage without calling the handler, so the agent loop continues gracefully * fix(lint): sort imports in test_sandbox_audit_middleware * refactor(sandbox-audit): address Copilot review feedback (3/5/6) - Fix class docstring to match implementation: medium-risk commands are executed with a warning appended (not rejected), and cwd anchoring note removed (handled in a separate PR) - Remove capsys.disabled() from benchmark test to avoid CI log noise; keep assertions for recall/precision targets - Remove misleading 'cwd fix' from test module docstring * test(sandbox-audit): add async tests for awrap_tool_call * fix(sandbox-audit): address Copilot review feedback (1/2) - Narrow rm high-risk regex to only block truly destructive targets (/, /*, ~, ~/*, /home, /root); legitimate workspace paths like /mnt/user-data/ are no longer false-positived - Handle list-typed ToolMessage content in _append_warn_to_result; append a text block instead of str()-ing the list to avoid breaking structured content normalization * style: apply ruff format to sandbox_audit_middleware files * fix(sandbox-audit): update benchmark comment to match assert-based implementation --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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|
Admire
|
fc7de7fffe |
feat: support manual add and edit for memory facts (#1538)
* feat: support manual add and edit for memory facts * fix: restore memory updater save helper * fix: address memory fact review feedback * fix: remove duplicate memory fact edit action * docs: simplify memory fact review setup * docs: relax memory review startup instructions * fix: clear rebase marker in memory settings page * fix: address memory fact review and format issues * fix: address memory fact review feedback * refactor: make memory fact updates explicit patch semantics --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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|
13ernkastel
|
92c7a20cb7 |
[Security] Address critical host-shell escape in LocalSandboxProvider (#1547)
* fix(security): disable host bash by default in local sandbox * fix(security): address review feedback for local bash hardening * fix(ci): sort live test imports for lint * style: apply backend formatter --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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|
greatmengqi
|
25df82cbfd |
style: format unformatted files and add .omc/ to prettierignore (#1539)
Co-authored-by: greatmengqi <chenmengqi.0376@bytedance.com> |
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|
greatmengqi
|
084dc7e748 | ci: enforce code formatting checks for backend and frontend (#1536) | ||
|
greatmengqi
|
06a623f9c8 | feat: add create_deerflow_agent SDK entry point (Phase 1) (#1203) | ||
|
Admire
|
7eb3a150b5 |
feat: add memory management actions and local filters in memory settings (#1467)
* Add MVP memory management actions * Fix memory settings locale coverage * Polish memory management interactions * Add memory search and type filters * Refine memory settings review feedback * docs: simplify memory settings review setup * fix: restore memory updater compatibility helpers * fix: address memory settings review feedback * docs: soften memory sample review wording --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> Co-authored-by: JeffJiang <for-eleven@hotmail.com> |
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|
knukn
|
481494b9c0 |
feat(client): support custom middleware injection (#1520)
* feat(client): support custom middleware injection Add support for custom middleware, allowing custom middleware list to be passed when initializing DeerFlowClient. These middleware will be injected after the default middleware when creating the agent, extending the agent's functionality. * feat: inject custom middlewares before ClarificationMiddleware to preserve ordering - Add `custom_middlewares` param to `_build_middlewares` - Inject custom middlewares right before `ClarificationMiddleware` to keep it as the last in the chain - Remove unsafe `.extend()` in `client.py` - Update tests in `test_client.py` and `test_lead_agent_model_resolution.py` to assert correct injection ordering |
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|
Nan Gao
|
520c0352b5 |
fix(middleware): fall back to configurable thread_id in MemoryMiddleware (#1425) (#1426)
* fix(middleware): fall back to configurable thread_id in MemoryMiddleware (#1425) * Apply suggestions from code review Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> |
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|
moose-lab
|
03b144f9c9 |
fix: replace print() with logging across harness package (#1282)
Replace all bare print() calls with proper logging using Python's standard logging module across the deerflow harness package. Changes across 8 files (16 print statements replaced): - agents/middlewares/clarification_middleware.py: use logger.info/debug - agents/middlewares/memory_middleware.py: use logger.debug - agents/middlewares/thread_data_middleware.py: use logger.debug - agents/middlewares/view_image_middleware.py: use logger.debug - agents/memory/queue.py: use logger.info/debug/warning/error - agents/lead_agent/prompt.py: use logger.error - skills/loader.py: use logger.warning - skills/parser.py: use logger.error Each file follows the established codebase convention: import logging logger = logging.getLogger(__name__) Log levels chosen based on message semantics: - debug: routine operational details (directory creation, timer resets) - info: significant state changes (memory queued, updates processed) - warning: recoverable issues (config load failures, skipped updates) - error: unexpected failures (parsing errors, memory update errors) Note: client.py is intentionally excluded as it uses print() for CLI output, which is the correct behavior for a command-line client. Co-authored-by: moose-lab <moose-lab@users.noreply.github.com> |
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|
Jason
|
4708700723 |
fix(middleware): return proper content format when no images viewed (#1454)
- Fix OpenAI BadRequestError: 'No images have been viewed.' was returned as
a plain string array instead of a properly formatted content block
- The OpenAI API expects message content to be either a string or an array
of objects with 'type' field, not an array of plain strings
- Changed return from ['No images have been viewed.'] to
[{'type': 'text', 'text': 'No images have been viewed.'}]
Fixes #1441
Co-authored-by: JasonOA888 <noreply@github.com>
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|
knukn
|
1c542ab7f1 |
feat(memory): Introduce configurable memory storage abstraction (#1353)
* feat(内存存储): 添加可配置的内存存储提供者支持 实现内存存储的抽象基类 MemoryStorage 和文件存储实现 FileMemoryStorage 重构内存数据加载和保存逻辑到存储提供者中 添加 storage_class 配置项以支持自定义存储提供者 * refactor(memory): 重构内存存储模块并更新相关测试 将内存存储逻辑从updater模块移动到独立的storage模块 使用存储接口模式替代直接文件操作 更新所有相关测试以使用新的存储接口 * Update backend/packages/harness/deerflow/agents/memory/storage.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * Update backend/packages/harness/deerflow/agents/memory/storage.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * fix(内存存储): 添加线程安全锁并增加测试用例 添加线程锁确保内存存储单例初始化的线程安全 增加对无效代理名称的验证测试 补充单例线程安全性和异常处理的测试用例 * Update backend/tests/test_memory_storage.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * fix(agents): 使用统一模式验证代理名称 修改代理名称验证逻辑以使用仓库中定义的AGENT_NAME_PATTERN模式，确保代码库一致性并防止路径遍历等安全问题。同时更新测试用例以覆盖更多无效名称情况。 --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> |
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|
Admire
|
080a03f3bc |
fix(config): fix summarization model alias resolution (#1378)
Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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|
DanielWalnut
|
d119214fee |
feat(harness): integration ACP agent tool (#1344)
* refactor: extract shared utils to break harness→app cross-layer imports Move _validate_skill_frontmatter to src/skills/validation.py and CONVERTIBLE_EXTENSIONS + convert_file_to_markdown to src/utils/file_conversion.py. This eliminates the two reverse dependencies from client.py (harness layer) into gateway/routers/ (app layer), preparing for the harness/app package split. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * refactor: split backend/src into harness (deerflow.*) and app (app.*) Physically split the monolithic backend/src/ package into two layers: - **Harness** (`packages/harness/deerflow/`): publishable agent framework package with import prefix `deerflow.*`. Contains agents, sandbox, tools, models, MCP, skills, config, and all core infrastructure. - **App** (`app/`): unpublished application code with import prefix `app.*`. Contains gateway (FastAPI REST API) and channels (IM integrations). Key changes: - Move 13 harness modules to packages/harness/deerflow/ via git mv - Move gateway + channels to app/ via git mv - Rename all imports: src.* → deerflow.* (harness) / app.* (app layer) - Set up uv workspace with deerflow-harness as workspace member - Update langgraph.json, config.example.yaml, all scripts, Docker files - Add build-system (hatchling) to harness pyproject.toml - Add PYTHONPATH=. to gateway startup commands for app.* resolution - Update ruff.toml with known-first-party for import sorting - Update all documentation to reflect new directory structure Boundary rule enforced: harness code never imports from app. All 429 tests pass. Lint clean. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * chore: add harness→app boundary check test and update docs Add test_harness_boundary.py that scans all Python files in packages/harness/deerflow/ and fails if any `from app.*` or `import app.*` statement is found. This enforces the architectural rule that the harness layer never depends on the app layer. Update CLAUDE.md to document the harness/app split architecture, import conventions, and the boundary enforcement test. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat: add config versioning with auto-upgrade on startup When config.example.yaml schema changes, developers' local config.yaml files can silently become outdated. This adds a config_version field and auto-upgrade mechanism so breaking changes (like src.* → deerflow.* renames) are applied automatically before services start. - Add config_version: 1 to config.example.yaml - Add startup version check warning in AppConfig.from_file() - Add scripts/config-upgrade.sh with migration registry for value replacements - Add `make config-upgrade` target - Auto-run config-upgrade in serve.sh and start-daemon.sh before starting services - Add config error hints in service failure messages Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix comments * fix: update src.* import in test_sandbox_tools_security to deerflow.* Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix: handle empty config and search parent dirs for config.example.yaml Address Copilot review comments on PR #1131: - Guard against yaml.safe_load() returning None for empty config files - Search parent directories for config.example.yaml instead of only looking next to config.yaml, fixing detection in common setups Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix: correct skills root path depth and config_version type coercion - loader.py: fix get_skills_root_path() to use 5 parent levels (was 3) after harness split, file lives at packages/harness/deerflow/skills/ so parent×3 resolved to backend/packages/harness/ instead of backend/ - app_config.py: coerce config_version to int() before comparison in _check_config_version() to prevent TypeError when YAML stores value as string (e.g. config_version: "1") - tests: add regression tests for both fixes Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix: update test imports from src.* to deerflow.*/app.* after harness refactor Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * feat(harness): add tool-first ACP agent invocation (#37) * feat(harness): add tool-first ACP agent invocation * build(harness): make ACP dependency required * fix(harness): address ACP review feedback * feat(harness): decouple ACP agent workspace from thread data ACP agents (codex, claude-code) previously used per-thread workspace directories, causing path resolution complexity and coupling task execution to DeerFlow's internal thread data layout. This change: - Replace _resolve_cwd() with a fixed _get_work_dir() that always uses {base_dir}/acp-workspace/, eliminating virtual path translation and thread_id lookups - Introduce /mnt/acp-workspace virtual path for lead agent read-only access to ACP agent output files (same pattern as /mnt/skills) - Add security guards: read-only validation, path traversal prevention, command path allowlisting, and output masking for acp-workspace - Update system prompt and tool description to guide LLM: send self-contained tasks to ACP agents, copy results via /mnt/acp-workspace - Add 11 new security tests for ACP workspace path handling Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * refactor(prompt): inject ACP section only when ACP agents are configured The ACP agent guidance in the system prompt is now conditionally built by _build_acp_section(), which checks get_acp_agents() and returns an empty string when no ACP agents are configured. This avoids polluting the prompt with irrelevant instructions for users who don't use ACP. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix lint * fix(harness): address Copilot review comments on sandbox path handling and ACP tool - local_sandbox: fix path-segment boundary bug in _resolve_path (== or startswith +"/") and add lookahead in _resolve_paths_in_command regex to prevent /mnt/skills matching inside /mnt/skills-extra - local_sandbox_provider: replace print() with logger.warning(..., exc_info=True) - invoke_acp_agent_tool: guard getattr(option, "optionId") with None default + continue; move full prompt from INFO to DEBUG level (truncated to 200 chars) - sandbox/tools: fix _get_acp_workspace_host_path docstring to match implementation; remove misleading "read-only" language from validate_local_bash_command_paths Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix(acp): thread-isolated workspaces, permission guardrail, and ContextVar registry P1.1 – ACP workspace thread isolation - Add `Paths.acp_workspace_dir(thread_id)` for per-thread paths - `_get_work_dir(thread_id)` in invoke_acp_agent_tool now uses `{base_dir}/threads/{thread_id}/acp-workspace/`; falls back to global workspace when thread_id is absent or invalid - `_invoke` extracts thread_id from `RunnableConfig` via `Annotated[RunnableConfig, InjectedToolArg]` - `sandbox/tools.py`: `_get_acp_workspace_host_path(thread_id)`, `_resolve_acp_workspace_path(path, thread_id)`, and all callers (`replace_virtual_paths_in_command`, `mask_local_paths_in_output`, `ls_tool`, `read_file_tool`) now resolve ACP paths per-thread P1.2 – ACP permission guardrail - New `auto_approve_permissions: bool = False` field in `ACPAgentConfig` - `_build_permission_response(options, *, auto_approve: bool)` now defaults to deny; only approves when `auto_approve=True` - Document field in `config.example.yaml` P2 – Deferred tool registry race condition - Replace module-level `_registry` global with `contextvars.ContextVar` - Each asyncio request context gets its own registry; worker threads inherit the context automatically via `loop.run_in_executor` - Expose `get_deferred_registry` / `set_deferred_registry` / `reset_deferred_registry` helpers Tests: 831 pass (57 for affected modules, 3 new tests) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix(sandbox): mount /mnt/acp-workspace in docker sandbox container The AioSandboxProvider was not mounting the ACP workspace into the sandbox container, so /mnt/acp-workspace was inaccessible when the lead agent tried to read ACP results in docker mode. Changes: - `ensure_thread_dirs`: also create `acp-workspace/` (chmod 0o777) so the directory exists before the sandbox container starts — required for Docker volume mounts - `_get_thread_mounts`: add read-only `/mnt/acp-workspace` mount using the per-thread host path (`host_paths.acp_workspace_dir(thread_id)`) - Update stale CLAUDE.md description (was "fixed global workspace") Tests: `test_aio_sandbox_provider.py` (4 new tests) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix(lint): remove unused imports in test_aio_sandbox_provider Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix config --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> |
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吴旭云
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d7e510763d |
fix: add null checks for runtime.context and tighten langgraph constraint (#1326)
- Add null checks for runtime.context in uploads_middleware.py and sandbox/middleware.py to prevent NPE when langgraph runtime context is None - Tighten langgraph version constraint from >=1.0.6 to >=1.0.6,<1.0.10 to avoid context=None incompatibility with langgraph-api 0.7.x Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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Matthew
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2eca58bd86 |
fix: add null checks for runtime.context in middlewares and tools (#1269)
Add defensive null checks before accessing runtime.context.get() to prevent AttributeError when runtime.context is None. This affects: - UploadsMiddleware - MemoryMiddleware - LoopDetectionMiddleware - SandboxMiddleware - sandbox tools - setup_agent_tool - present_file_tool - task_tool Also adds .env loading in serve.sh for environment variable support. Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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greatmengqi
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16ed797e0e |
feat: add configurable log level and token usage tracking (#1301)
* feat: add configurable log level and token usage tracking - Add `log_level` config to control deerflow module log level, synced to LangGraph Server via serve.sh `--server-log-level` - Add `token_usage.enabled` config with TokenUsageMiddleware that logs input/output/total tokens per LLM call from usage_metadata - Add .omc/ to .gitignore * fix: use info level for token usage logs since feature has its own toggle * fix: sort imports to pass lint check --------- Co-authored-by: greatmengqi <chenmengqi.0376@bytedance.com> Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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d 🔹
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77b8ef79ca |
fix(middleware): use HumanMessage in LoopDetectionMiddleware for Anthropic compat (#1300)
LoopDetectionMiddleware injected SystemMessage mid-conversation to warn about repetitive tool calls. This crashes Anthropic models because langchain_anthropic's _format_messages() requires system messages to appear only at the start of the conversation — interleaved system messages raise 'Received multiple non-consecutive system messages'. Switch the warning injection from SystemMessage to HumanMessage, which works with all providers (Anthropic, OpenAI, Google, etc.). Fixes #1299 Co-authored-by: voidborne-d <voidborne-d@users.noreply.github.com> |
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Uchi Uchibeke
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a29134d7c9 |
feat(guardrails): add pre-tool-call authorization middleware with pluggable providers (#1240)
Add GuardrailMiddleware that evaluates every tool call before execution. Three provider options: built-in AllowlistProvider (zero deps), OAP passport providers (open standard), or custom providers loaded by class path. - GuardrailProvider protocol with GuardrailRequest/Decision dataclasses - GuardrailMiddleware (AgentMiddleware, position 5 in chain) - AllowlistProvider for simple deny/allow by tool name - GuardrailsConfig (Pydantic singleton, loaded from config.yaml) - 25 tests covering allow/deny, fail-closed/open, async, GraphBubbleUp - Comprehensive docs at backend/docs/GUARDRAILS.md Closes #1213 Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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haoliangxu
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e6c6770b70 |
fix(middleware): fallback to configurable thread_id in thread data middleware (#1237)
Co-authored-by: Exploreunive <Exploreunive@users.noreply.github.com> Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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haoliangxu
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3af709097e |
fix: normalize structured LLM content in serialization and memory updater (#1215)
* fix: normalize ToolMessage structured content in serialization
When models return ToolMessage content as a list of content blocks
(e.g. [{"type": "text", "text": "..."}]), the UI previously displayed
the raw Python repr string instead of the extracted text.
Replace str(msg.content) with the existing _extract_text() helper in
both _serialize_message() and stream() to properly normalize
list-of-blocks content to plain text.
Fixes #1149
Also fixes the same root cause as #1188 (characters displayed one per
line when tool response content is returned as structured blocks).
Added 11 regression tests covering string, list-of-blocks, mixed,
empty, and fallback content types.
* fix(memory): extract text from structured LLM responses in memory updater
When LLMs return response content as list of content blocks
(e.g. [{"type": "text", "text": "..."}]) instead of plain strings,
str() produces Python repr which breaks JSON parsing in the memory
updater. This caused memory updates to silently fail.
Changes:
- Add _extract_text() helper in updater.py for safe content normalization
- Use _extract_text() instead of str(response.content) in update_memory()
- Fix format_conversation_for_update() to handle plain strings in list content
- Fix subagent executor fallback path to extract text from list content
- Replace print() with structured logging (logger.info/warning/error)
- Add 13 regression tests covering _extract_text, format_conversation,
and update_memory with structured LLM responses
* fix: address Copilot review - defensive text extraction + logger.exception
- client.py _extract_text: use block.get('text') + isinstance check (prevent KeyError/TypeError)
- prompt.py format_conversation_for_update: same defensive check for dict text blocks
- executor.py: type-safe text extraction in both code paths, fallback to placeholder instead of str(raw_content)
- updater.py: use logger.exception() instead of logger.error() for traceback preservation
* Apply suggestions from code review
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* fix: preserve chunked structured content without spurious newlines
* fix: restore backend unit test compatibility
---------
Co-authored-by: Exploreunive <Exploreunive@users.noreply.github.com>
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
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greatmengqi
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accf5b5f8e | fix: add sync after_model to TitleMiddleware (#1190) | ||
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Ryanba
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f67c3d2c9e |
fix(harness): skip duplicate memory facts (#1193)
* fix(harness): skip duplicate memory facts Ultraworked with [Sisyphus](https://github.com/code-yeongyu/oh-my-opencode) Co-authored-by: Sisyphus <clio-agent@sisyphuslabs.ai> * docs: note memory fact deduplication Ultraworked with [Sisyphus](https://github.com/code-yeongyu/oh-my-opencode) Co-authored-by: Sisyphus <clio-agent@sisyphuslabs.ai> * Apply suggestions from code review Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com> --------- Co-authored-by: Sisyphus <clio-agent@sisyphuslabs.ai> Co-authored-by: Willem Jiang <willem.jiang@gmail.com> Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com> |
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lhd
|
0091d9f071 |
feat(tools): add tool_search for deferred MCP tool loading (#1176)
* feat(tools): add tool_search for deferred MCP tool loading When multiple MCP servers are enabled, total tool count can exceed 30-50, causing context bloat and degraded tool selection accuracy. This adds a deferred tool loading mechanism controlled by `tool_search.enabled` config. - Add ToolSearchConfig with single `enabled` field - Add DeferredToolRegistry with regex search (select:, +keyword, keyword) - Add tool_search tool returning OpenAI-compatible function JSON - Add DeferredToolFilterMiddleware to hide deferred schemas from bind_tools - Add <available-deferred-tools> section to system prompt - Enable MCP tool_name_prefix to prevent cross-server name collisions - Add 34 unit tests covering registry, tool, prompt, and middleware * fix: reset stale deferred registry and bump config_version - Reset deferred registry upfront in get_available_tools() to prevent stale tool entries when MCP servers are disabled between calls - Bump config_version to 2 for new tool_search config field Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix(tests): mock get_app_config in prompt section tests for CI CI has no config.yaml, causing TestDeferredToolsPromptSection to fail with FileNotFoundError. Add autouse fixture to mock get_app_config. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> |
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lailoo
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9809af1f26 |
feat: add citation/reference support to deep research reports (#1143)
* feat: add citation/reference support to deep research reports (#1141) - Enhance lead agent system prompt with mandatory citation requirements after web_search/web_fetch tool usage - Add citation examples and best practices to GitHub Deep Research skill - Add citation hints to report template (Executive Summary, Key Analysis) - Style regular markdown links in frontend for visual distinction (color, underline, hover effect) - Fix TitleMiddleware being registered when title generation is disabled * fix: address PR review comments - Revert TitleMiddleware conditional registration (agent.py) to avoid sync/async incompatibility with DeerFlowClient - Fix markdown link rendering: merge classNames instead of overwriting, only set target=_blank for external http(s) URLs - Remove unrelated package.json/pnpm-lock.yaml changes * fix: use plain markdown links in Sources section for cleaner rendering Inline citations in report body use [citation:Title](URL) for pill/badge style. Sources section uses plain [Title](URL) for simple underlined link style. * fix(frontend): render plain links as underlined text in artifact markdown Only links with citation: prefix render as Badge pills. Regular links in Sources section now render as underlined text links. --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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Ryanba
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b1913a1902 |
fix(harness): normalize structured content for titles (#1155)
* fix(harness): normalize structured content for titles Flatten structured LangChain message content before prompting the title model so list/block payloads don't leak Python reprs into generated thread titles. Ultraworked with [Sisyphus](https://github.com/code-yeongyu/oh-my-opencode) Co-authored-by: Sisyphus <clio-agent@sisyphuslabs.ai> * Apply suggestions from code review Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com> --------- Co-authored-by: Sisyphus <clio-agent@sisyphuslabs.ai> Co-authored-by: Willem Jiang <willem.jiang@gmail.com> Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com> |
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DanielWalnut
|
76803b826f |
refactor: split backend into harness (deerflow.*) and app (app.*) (#1131)
* refactor: extract shared utils to break harness→app cross-layer imports Move _validate_skill_frontmatter to src/skills/validation.py and CONVERTIBLE_EXTENSIONS + convert_file_to_markdown to src/utils/file_conversion.py. This eliminates the two reverse dependencies from client.py (harness layer) into gateway/routers/ (app layer), preparing for the harness/app package split. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * refactor: split backend/src into harness (deerflow.*) and app (app.*) Physically split the monolithic backend/src/ package into two layers: - **Harness** (`packages/harness/deerflow/`): publishable agent framework package with import prefix `deerflow.*`. Contains agents, sandbox, tools, models, MCP, skills, config, and all core infrastructure. - **App** (`app/`): unpublished application code with import prefix `app.*`. Contains gateway (FastAPI REST API) and channels (IM integrations). Key changes: - Move 13 harness modules to packages/harness/deerflow/ via git mv - Move gateway + channels to app/ via git mv - Rename all imports: src.* → deerflow.* (harness) / app.* (app layer) - Set up uv workspace with deerflow-harness as workspace member - Update langgraph.json, config.example.yaml, all scripts, Docker files - Add build-system (hatchling) to harness pyproject.toml - Add PYTHONPATH=. to gateway startup commands for app.* resolution - Update ruff.toml with known-first-party for import sorting - Update all documentation to reflect new directory structure Boundary rule enforced: harness code never imports from app. All 429 tests pass. Lint clean. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * chore: add harness→app boundary check test and update docs Add test_harness_boundary.py that scans all Python files in packages/harness/deerflow/ and fails if any `from app.*` or `import app.*` statement is found. This enforces the architectural rule that the harness layer never depends on the app layer. Update CLAUDE.md to document the harness/app split architecture, import conventions, and the boundary enforcement test. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat: add config versioning with auto-upgrade on startup When config.example.yaml schema changes, developers' local config.yaml files can silently become outdated. This adds a config_version field and auto-upgrade mechanism so breaking changes (like src.* → deerflow.* renames) are applied automatically before services start. - Add config_version: 1 to config.example.yaml - Add startup version check warning in AppConfig.from_file() - Add scripts/config-upgrade.sh with migration registry for value replacements - Add `make config-upgrade` target - Auto-run config-upgrade in serve.sh and start-daemon.sh before starting services - Add config error hints in service failure messages Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix comments * fix: update src.* import in test_sandbox_tools_security to deerflow.* Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix: handle empty config and search parent dirs for config.example.yaml Address Copilot review comments on PR #1131: - Guard against yaml.safe_load() returning None for empty config files - Search parent directories for config.example.yaml instead of only looking next to config.yaml, fixing detection in common setups Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix: correct skills root path depth and config_version type coercion - loader.py: fix get_skills_root_path() to use 5 parent levels (was 3) after harness split, file lives at packages/harness/deerflow/skills/ so parent×3 resolved to backend/packages/harness/ instead of backend/ - app_config.py: coerce config_version to int() before comparison in _check_config_version() to prevent TypeError when YAML stores value as string (e.g. config_version: "1") - tests: add regression tests for both fixes Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix: update test imports from src.* to deerflow.*/app.* after harness refactor Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> |