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* 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 infb2d99f(#1836) but accidentally reverted byca2fb95(#1847). Without them, gateway reads host paths from .env via env_file, causing FileNotFoundError inside the container. 2. Langgraph command fails when LANGGRAPH_ALLOW_BLOCKING is unset (default). Empty $${allow_blocking} inserts a bare space between flags, causing ' --no-reload' to be parsed as unexpected extra argument. Fix by building args string first and conditionally appending --allow-blocking. Co-authored-by: cooper <cooperfu@tencent.com> * fix(frontend): resolve invalid HTML nesting and tabnabbing vulnerabilities (#1904) * fix(frontend): resolve invalid HTML nesting and tabnabbing vulnerabilities Fix `<button>` inside `<a>` invalid HTML in artifact components and add missing `noopener,noreferrer` to `window.open` calls to prevent reverse tabnabbing. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix(frontend): address Copilot review on tabnabbing and double-tab-open Remove redundant parent onClick on web_fetch ChainOfThoughtStep to prevent opening two tabs on link click, and explicitly null out window.opener after window.open() for defensive tabnabbing hardening. --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> * refactor(persistence): organize entities into per-entity directories Restructure the persistence layer from horizontal "models/ + repositories/" split into vertical entity-aligned directories. Each entity (thread_meta, run, feedback) now owns its ORM model, abstract interface (where applicable), and concrete implementations under a single directory with an aggregating __init__.py for one-line imports. Layout: persistence/thread_meta/{base,model,sql,memory}.py persistence/run/{model,sql}.py persistence/feedback/{model,sql}.py models/__init__.py is kept as a facade so Alembic autogenerate continues to discover all ORM tables via Base.metadata. RunEventRow remains under models/run_event.py because its storage implementation lives in runtime/events/store/db.py and has no matching repository directory. The repositories/ directory is removed entirely. All call sites in gateway/deps.py and tests are updated to import from the new entity packages, e.g.: from deerflow.persistence.thread_meta import ThreadMetaRepository from deerflow.persistence.run import RunRepository from deerflow.persistence.feedback import FeedbackRepository Full test suite passes (1690 passed, 14 skipped). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(gateway): sync thread rename and delete through ThreadMetaStore The POST /threads/{id}/state endpoint previously synced title changes only to the LangGraph Store via _store_upsert. In sqlite mode the search endpoint reads from the ThreadMetaRepository SQL table, so renames never appeared in /threads/search until the next agent run completed (worker.py syncs title from checkpoint to thread_meta in its finally block). Likewise the DELETE /threads/{id} endpoint cleaned up the filesystem, Store, and checkpointer but left the threads_meta row orphaned in sqlite, so deleted threads kept appearing in /threads/search. Fix both endpoints by routing through the ThreadMetaStore abstraction which already has the correct sqlite/memory implementations wired up by deps.py. The rename path now calls update_display_name() and the delete path calls delete() — both work uniformly across backends. Verified end-to-end with curl in gateway mode against sqlite backend. Existing test suite (1690 passed) and focused router/repo tests pass. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * refactor(gateway): route all thread metadata access through ThreadMetaStore Following the rename/delete bug fix in PR1, migrate the remaining direct LangGraph Store reads/writes in the threads router and services to the ThreadMetaStore abstraction so that the sqlite and memory backends behave identically and the legacy dual-write paths can be removed. Migrated endpoints (threads.py): - create_thread: idempotency check + write now use thread_meta_repo.get/create instead of dual-writing the LangGraph Store and the SQL row. - get_thread: reads from thread_meta_repo.get; the checkpoint-only fallback for legacy threads is preserved. - patch_thread: replaced _store_get/_store_put with thread_meta_repo.update_metadata. - delete_thread_data: dropped the legacy store.adelete; thread_meta_repo.delete already covers it. Removed dead code (services.py): - _upsert_thread_in_store — redundant with the immediately following thread_meta_repo.create() call. - _sync_thread_title_after_run — worker.py's finally block already syncs the title via thread_meta_repo.update_display_name() after each run. Removed dead code (threads.py): - _store_get / _store_put / _store_upsert helpers (no remaining callers). - THREADS_NS constant. - get_store import (router no longer touches the LangGraph Store directly). New abstract method: - ThreadMetaStore.update_metadata(thread_id, metadata) merges metadata into the thread's metadata field. Implemented in both ThreadMetaRepository (SQL, read-modify-write inside one session) and MemoryThreadMetaStore. Three new unit tests cover merge / empty / nonexistent behaviour. Net change: -134 lines. Full test suite: 1693 passed, 14 skipped. Verified end-to-end with curl in gateway mode against sqlite backend (create / patch / get / rename / search / delete). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> Co-authored-by: Copilot Autofix powered by AI <223894421+github-code-quality[bot]@users.noreply.github.com> Co-authored-by: DanielWalnut <45447813+hetaoBackend@users.noreply.github.com> Co-authored-by: Willem Jiang <willem.jiang@gmail.com> Co-authored-by: JilongSun <965640067@qq.com> Co-authored-by: jie <49781832+stan-fu@users.noreply.github.com> Co-authored-by: cooper <cooperfu@tencent.com> Co-authored-by: yangzheli <43645580+yangzheli@users.noreply.github.com>
248 lines
11 KiB
Python
248 lines
11 KiB
Python
"""Tool for creating and evolving custom skills."""
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from __future__ import annotations
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import asyncio
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import logging
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import shutil
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from typing import Any
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from weakref import WeakValueDictionary
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from langchain.tools import ToolRuntime, tool
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from langgraph.typing import ContextT
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from deerflow.agents.lead_agent.prompt import clear_skills_system_prompt_cache
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from deerflow.agents.thread_state import ThreadState
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from deerflow.mcp.tools import _make_sync_tool_wrapper
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from deerflow.skills.manager import (
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append_history,
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atomic_write,
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custom_skill_exists,
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ensure_custom_skill_is_editable,
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ensure_safe_support_path,
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get_custom_skill_dir,
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get_custom_skill_file,
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public_skill_exists,
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read_custom_skill_content,
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validate_skill_markdown_content,
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validate_skill_name,
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)
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from deerflow.skills.security_scanner import scan_skill_content
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logger = logging.getLogger(__name__)
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_skill_locks: WeakValueDictionary[str, asyncio.Lock] = WeakValueDictionary()
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def _get_lock(name: str) -> asyncio.Lock:
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lock = _skill_locks.get(name)
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if lock is None:
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lock = asyncio.Lock()
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_skill_locks[name] = lock
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return lock
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def _get_thread_id(runtime: ToolRuntime[ContextT, ThreadState] | None) -> str | None:
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if runtime is None:
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return None
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if runtime.context and runtime.context.get("thread_id"):
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return runtime.context.get("thread_id")
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return runtime.config.get("configurable", {}).get("thread_id")
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def _history_record(*, action: str, file_path: str, prev_content: str | None, new_content: str | None, thread_id: str | None, scanner: dict[str, Any]) -> dict[str, Any]:
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return {
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"action": action,
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"author": "agent",
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"thread_id": thread_id,
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"file_path": file_path,
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"prev_content": prev_content,
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"new_content": new_content,
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"scanner": scanner,
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}
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async def _scan_or_raise(content: str, *, executable: bool, location: str) -> dict[str, str]:
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result = await scan_skill_content(content, executable=executable, location=location)
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if result.decision == "block":
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raise ValueError(f"Security scan blocked the write: {result.reason}")
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if executable and result.decision != "allow":
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raise ValueError(f"Security scan rejected executable content: {result.reason}")
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return {"decision": result.decision, "reason": result.reason}
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async def _to_thread(func, /, *args, **kwargs):
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return await asyncio.to_thread(func, *args, **kwargs)
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async def _skill_manage_impl(
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runtime: ToolRuntime[ContextT, ThreadState],
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action: str,
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name: str,
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content: str | None = None,
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path: str | None = None,
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find: str | None = None,
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replace: str | None = None,
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expected_count: int | None = None,
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) -> str:
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"""Manage custom skills under skills/custom/.
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Args:
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action: One of create, patch, edit, delete, write_file, remove_file.
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name: Skill name in hyphen-case.
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content: New file content for create, edit, or write_file.
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path: Supporting file path for write_file or remove_file.
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find: Existing text to replace for patch.
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replace: Replacement text for patch.
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expected_count: Optional expected number of replacements for patch.
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"""
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name = validate_skill_name(name)
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lock = _get_lock(name)
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thread_id = _get_thread_id(runtime)
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async with lock:
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if action == "create":
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if await _to_thread(custom_skill_exists, name):
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raise ValueError(f"Custom skill '{name}' already exists.")
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if content is None:
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raise ValueError("content is required for create.")
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await _to_thread(validate_skill_markdown_content, name, content)
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scan = await _scan_or_raise(content, executable=False, location=f"{name}/SKILL.md")
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skill_file = await _to_thread(get_custom_skill_file, name)
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await _to_thread(atomic_write, skill_file, content)
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await _to_thread(
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append_history,
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name,
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_history_record(action="create", file_path="SKILL.md", prev_content=None, new_content=content, thread_id=thread_id, scanner=scan),
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)
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clear_skills_system_prompt_cache()
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return f"Created custom skill '{name}'."
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if action == "edit":
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await _to_thread(ensure_custom_skill_is_editable, name)
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if content is None:
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raise ValueError("content is required for edit.")
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await _to_thread(validate_skill_markdown_content, name, content)
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scan = await _scan_or_raise(content, executable=False, location=f"{name}/SKILL.md")
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skill_file = await _to_thread(get_custom_skill_file, name)
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prev_content = await _to_thread(skill_file.read_text, encoding="utf-8")
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await _to_thread(atomic_write, skill_file, content)
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await _to_thread(
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append_history,
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name,
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_history_record(action="edit", file_path="SKILL.md", prev_content=prev_content, new_content=content, thread_id=thread_id, scanner=scan),
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)
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clear_skills_system_prompt_cache()
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return f"Updated custom skill '{name}'."
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if action == "patch":
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await _to_thread(ensure_custom_skill_is_editable, name)
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if find is None or replace is None:
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raise ValueError("find and replace are required for patch.")
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skill_file = await _to_thread(get_custom_skill_file, name)
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prev_content = await _to_thread(skill_file.read_text, encoding="utf-8")
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occurrences = prev_content.count(find)
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if occurrences == 0:
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raise ValueError("Patch target not found in SKILL.md.")
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if expected_count is not None and occurrences != expected_count:
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raise ValueError(f"Expected {expected_count} replacements but found {occurrences}.")
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replacement_count = expected_count if expected_count is not None else 1
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new_content = prev_content.replace(find, replace, replacement_count)
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await _to_thread(validate_skill_markdown_content, name, new_content)
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scan = await _scan_or_raise(new_content, executable=False, location=f"{name}/SKILL.md")
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await _to_thread(atomic_write, skill_file, new_content)
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await _to_thread(
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append_history,
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name,
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_history_record(action="patch", file_path="SKILL.md", prev_content=prev_content, new_content=new_content, thread_id=thread_id, scanner=scan),
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)
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clear_skills_system_prompt_cache()
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return f"Patched custom skill '{name}' ({replacement_count} replacement(s) applied, {occurrences} match(es) found)."
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if action == "delete":
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await _to_thread(ensure_custom_skill_is_editable, name)
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skill_dir = await _to_thread(get_custom_skill_dir, name)
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prev_content = await _to_thread(read_custom_skill_content, name)
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await _to_thread(
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append_history,
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name,
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_history_record(action="delete", file_path="SKILL.md", prev_content=prev_content, new_content=None, thread_id=thread_id, scanner={"decision": "allow", "reason": "Deletion requested."}),
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)
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await _to_thread(shutil.rmtree, skill_dir)
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clear_skills_system_prompt_cache()
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return f"Deleted custom skill '{name}'."
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if action == "write_file":
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await _to_thread(ensure_custom_skill_is_editable, name)
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if path is None or content is None:
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raise ValueError("path and content are required for write_file.")
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target = await _to_thread(ensure_safe_support_path, name, path)
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exists = await _to_thread(target.exists)
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prev_content = await _to_thread(target.read_text, encoding="utf-8") if exists else None
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executable = "scripts/" in path or path.startswith("scripts/")
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scan = await _scan_or_raise(content, executable=executable, location=f"{name}/{path}")
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await _to_thread(atomic_write, target, content)
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await _to_thread(
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append_history,
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name,
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_history_record(action="write_file", file_path=path, prev_content=prev_content, new_content=content, thread_id=thread_id, scanner=scan),
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)
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return f"Wrote '{path}' for custom skill '{name}'."
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if action == "remove_file":
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await _to_thread(ensure_custom_skill_is_editable, name)
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if path is None:
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raise ValueError("path is required for remove_file.")
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target = await _to_thread(ensure_safe_support_path, name, path)
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if not await _to_thread(target.exists):
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raise FileNotFoundError(f"Supporting file '{path}' not found for skill '{name}'.")
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prev_content = await _to_thread(target.read_text, encoding="utf-8")
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await _to_thread(target.unlink)
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await _to_thread(
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append_history,
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name,
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_history_record(action="remove_file", file_path=path, prev_content=prev_content, new_content=None, thread_id=thread_id, scanner={"decision": "allow", "reason": "Deletion requested."}),
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)
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return f"Removed '{path}' from custom skill '{name}'."
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if await _to_thread(public_skill_exists, name):
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raise ValueError(f"'{name}' is a built-in skill. To customise it, create a new skill with the same name under skills/custom/.")
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raise ValueError(f"Unsupported action '{action}'.")
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@tool("skill_manage", parse_docstring=True)
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async def skill_manage_tool(
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runtime: ToolRuntime[ContextT, ThreadState],
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action: str,
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name: str,
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content: str | None = None,
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path: str | None = None,
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find: str | None = None,
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replace: str | None = None,
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expected_count: int | None = None,
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) -> str:
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"""Manage custom skills under skills/custom/.
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Args:
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action: One of create, patch, edit, delete, write_file, remove_file.
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name: Skill name in hyphen-case.
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content: New file content for create, edit, or write_file.
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path: Supporting file path for write_file or remove_file.
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find: Existing text to replace for patch.
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replace: Replacement text for patch.
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expected_count: Optional expected number of replacements for patch.
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"""
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return await _skill_manage_impl(
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runtime=runtime,
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action=action,
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name=name,
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content=content,
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path=path,
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find=find,
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replace=replace,
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expected_count=expected_count,
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)
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skill_manage_tool.func = _make_sync_tool_wrapper(_skill_manage_impl, "skill_manage")
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