* Refactor sandbox state management and improve Docker integration
- Removed FileSandboxStateStore and SandboxStateStore classes for a cleaner architecture.
- Enhanced LocalContainerBackend to handle port allocation retries and introduced environment variable support for sandbox host configuration.
- Updated Paths class to include host_base_dir for Docker volume mounts and ensured proper permissions for sandbox directories.
- Modified ExtensionsConfig to improve error handling when loading configuration files and adjusted environment variable resolution.
- Updated sandbox configuration to include a replicas option for managing concurrent sandbox containers.
- Improved logging and context management in SandboxMiddleware for better sandbox lifecycle handling.
- Enhanced network port allocation logic to bind to 0.0.0.0 for compatibility with Docker.
- Updated Docker Compose files to ensure proper volume management and environment variable configuration.
- Created scripts to ensure necessary configuration files are present before starting services.
- Cleaned up unused MCP server configurations in extensions_config.example.json.
* Address Copilot review suggestions from PR #1068 (#9)
---------
Co-authored-by: Copilot <198982749+Copilot@users.noreply.github.com>
* fix(subagents): cleanup background tasks after completion to prevent memory leak
Added cleanup_background_task() function to remove completed subagent results
from the global _background_tasks dict. Found a small issue: completed tasks
were never removed, causing memory to grow indefinitely with each subagent
execution.
Alternative approaches considered:
- Future + SubagentHandle pattern: Not chosen due to requiring refactoring
Chose the simple cleanup approach for minimal code changes while effectively
resolving the memory leak.
Changes:
- Add cleanup_background_task() in executor.py
- Call cleanup in all task_tool return paths (completed, failed, timed out)
* fix(subagents): prevent race condition in background task cleanup
Address Copilot review feedback on memory leak fix:
- Add terminal state check in cleanup_background_task() to only remove
tasks that are COMPLETED/FAILED/TIMED_OUT or have completed_at set
- Remove cleanup call from polling safety-timeout branch in task_tool
since the task may still be running
- Add comprehensive tests for cleanup behavior including:
- Verification that cleanup is called on terminal states
- Verification that cleanup is NOT called on polling timeout
- Tests for terminal state check logic in executor
This prevents KeyError when the background executor tries to update
a task that was prematurely removed from _background_tasks.
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* fix(checkpointer): return InMemorySaver instead of None when not configured (#1016)
* fix(checkpointer): also fix get_checkpointer() to return InMemorySaver
Make all three checkpointer functions consistent:
- make_checkpointer() (async) → InMemorySaver
- checkpointer_context() (sync) → InMemorySaver
- get_checkpointer() (sync singleton) → InMemorySaver
This ensures DeerFlowClient always has a valid checkpointer.
* fix: address CI failure and Copilot review feedback
- Fix import order in test_checkpointer_none_fix.py (I001 ruff error)
- Fix type annotation: _checkpointer should be Checkpointer | None
- Update docstring: change "None if not configured" to "InMemorySaver if not configured"
- Ensure app config is loaded before checking checkpointer config to prevent incorrect InMemorySaver fallback
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* feat: add claude-to-deerflow skill for DeerFlow API integration
Add a new skill that enables Claude Code to interact with the DeerFlow
AI agent platform via its HTTP API, including chat streaming and status
checking capabilities.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: fix telegram channel
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* feat: add IM channels system for Feishu, Slack, and Telegram integration
Bridge external messaging platforms to DeerFlow via LangGraph Server with
async message bus, thread management, and per-channel configuration.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: address review comments on IM channels system
Fix topic_id handling in store remove/list_entries and manager commands,
correct Telegram reply threading, remove unused imports/variables, update
docstrings and docs to match implementation, and prevent config mutation.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* update skill creator
* fix im reply text
* fix comments
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* Add checkpointer configuration to config.example.yaml
- Introduced a new section for checkpointer configuration to enable state persistence for the embedded DeerFlowClient.
- Documented supported types: memory, sqlite, and postgres, along with examples for each.
- Clarified that the LangGraph Server manages its own state persistence separately.
* refactor(checkpointer): streamline checkpointer initialization and logging
* fix(uv.lock): update revision and add new wheel URLs for brotlicffi package
* feat: add langchain-anthropic dependency and update related configurations
* Fix checkpointer lifecycle, docstring, and path resolution bugs from PR #1005 review (#4)
* Initial plan
* Address all review suggestions from PR #1005
Co-authored-by: foreleven <4785594+foreleven@users.noreply.github.com>
* Fix resolve_path to always return real Path; move SQLite special-string handling to callers
Co-authored-by: foreleven <4785594+foreleven@users.noreply.github.com>
---------
Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: foreleven <4785594+foreleven@users.noreply.github.com>
---------
Co-authored-by: Copilot <198982749+Copilot@users.noreply.github.com>
Co-authored-by: foreleven <4785594+foreleven@users.noreply.github.com>
* feat: u may ask
* chore: adjust code according to CR
* chore: adjust code according to CR
* ut: test for suggestions.py
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* fix(subagent): support async MCP tools in subagent executor
SubagentExecutor.execute() was synchronous and could not handle async-only tools like MCP tools. This caused failures when trying to use MCP tools within subagents.
Changes:
- Add _aexecute() async method using agent.astream() for async execution
- Refactor execute() to use asyncio.run() wrapping _aexecute()
- This allows subagents to use async tools (MCP) within ThreadPoolExecutor
* test(subagent): add unit tests for executor async/sync paths
Add comprehensive tests covering:
- Async _aexecute() with success/error cases
- Sync execute() wrapper using asyncio.run()
- Async tool (MCP) support verification
- Thread pool execution safety
* fix(subagent): subagent-test-circular-depend
- Use session-scoped fixture with delayed import to handle circular dependencies
without affecting other test modules
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
- replace with explicit runtime deps:
- regenerate after dependency changes
- make deterministic by patching
to avoid leaked global affecting expected paths
* feat(upload): implement optimistic UI for file uploads and enhance message handling
* feat(middleware): enhance file handling by collecting historical uploads from directory
* feat(thread-title): update page title handling for new threads and improve loading state
* feat(uploads-middleware): enhance file extraction by verifying file existence in uploads directory
* feat(thread-stream): update file path reference to use virtual_path for uploads
* feat(tests): add core behaviour tests for UploadsMiddleware
* feat(tests): remove unused pytest import from test_uploads_middleware_core_logic.py
* feat: enhance file upload handling and localization support
- Update UploadsMiddleware to validate filenames more robustly.
- Modify MessageListItem to parse uploaded files from raw content for backward compatibility.
- Add localization for uploading messages in English and Chinese.
- Introduce parseUploadedFiles utility to extract uploaded files from message content.
* fix(memory): prevent file upload events from persisting in long-term memory
Uploaded files are session-scoped and unavailable in future sessions.
Previously, upload interactions were recorded in memory, causing the
agent to search for non-existent files in subsequent conversations.
Changes:
- memory_middleware: skip human messages containing <uploaded_files>
and their paired AI responses from the memory queue
- updater: post-process generated memory to strip upload mentions
before saving to file
- prompt: instruct the memory LLM to ignore file upload events
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(memory): address Copilot review feedback on upload filtering
- memory_middleware: strip <uploaded_files> block from human messages
instead of dropping the entire turn; only skip the turn (and paired
AI response) when nothing remains after stripping
- updater: narrow the upload-scrubbing regex to explicit upload events
(avoids false-positive removal of "User works with CSV files" etc.);
also filter upload-event facts from the facts array
- prompt: move `import re` to module scope; skip upload-only human
messages (empty after stripping) rather than appending "User: "
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(memory): allow optional words between 'upload' and 'file' in scrub regex
The previous pattern required 'uploading file' with no intervening words,
so 'uploading a test file' was not matched and leaked into long-term memory.
Allow up to 3 modifier words between the verb and noun (e.g. 'uploading a
test file', 'uploaded the attachment').
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* test(memory): add unit tests for upload filtering in memory pipeline
Covers _filter_messages_for_memory and _strip_upload_mentions_from_memory
per Copilot review suggestion. 15 test cases verify:
- Upload-only turns (and paired AI responses) are excluded from memory queue
- User's real question is preserved when combined with an upload block
- Upload file paths are never present in filtered message content
- Intermediate tool messages are always excluded
- Multi-turn conversations: only the upload turn is dropped
- Multimodal (list-content) human messages are handled
- Upload-event sentences are removed from summaries and facts
- Legitimate file-related facts (CSV preferences, PDF exports) are preserved
- "uploading a test file" (words between verb and noun) is caught by regex
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* feat: add agent management functionality with creation, editing, and deletion
* feat: enhance agent creation and chat experience
- Added AgentWelcome component to display agent description on new thread creation.
- Improved agent name validation with availability check during agent creation.
- Updated NewAgentPage to handle agent creation flow more effectively, including enhanced error handling and user feedback.
- Refactored chat components to streamline message handling and improve user experience.
- Introduced new bootstrap skill for personalized onboarding conversations, including detailed conversation phases and a structured SOUL.md template.
- Updated localization files to reflect new features and error messages.
- General code cleanup and optimizations across various components and hooks.
* Refactor workspace layout and agent management components
- Updated WorkspaceLayout to use useLayoutEffect for sidebar state initialization.
- Removed unused AgentFormDialog and related edit functionality from AgentCard.
- Introduced ArtifactTrigger component to manage artifact visibility.
- Enhanced ChatBox to handle artifact selection and display.
- Improved message list rendering logic to avoid loading states.
- Updated localization files to remove deprecated keys and add new translations.
- Refined hooks for local settings and thread management to improve performance and clarity.
- Added temporal awareness guidelines to deep research skill documentation.
* feat: refactor chat components and introduce thread management hooks
* feat: improve artifact file detail preview logic and clean up console logs
* feat: refactor lead agent creation logic and improve logging details
* feat: validate agent name format and enhance error handling in agent setup
* feat: simplify thread search query by removing unnecessary metadata
* feat: update query key in useDeleteThread and useRenameThread for consistency
* feat: add isMock parameter to thread and artifact handling for improved testing
* fix: reorder import of setup_agent for consistency in builtins module
* feat: append mock parameter to thread links in CaseStudySection for testing purposes
* fix: update load_agent_soul calls to use cfg.name for improved clarity
* fix: update date format in apply_prompt_template for consistency
* feat: integrate isMock parameter into artifact content loading for enhanced testing
* docs: add license section to SKILL.md for clarity and attribution
* feat(agent): enhance model resolution and agent configuration handling
* chore: remove unused import of _resolve_model_name from agents
* feat(agent): remove unused field
* fix(agent): set default value for requested_model_name in _resolve_model_name function
* feat(agent): update get_available_tools call to handle optional agent_config and improve middleware function signature
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* feat: Add reasoning effort configuration support
* Add `reasoning_effort` parameter to model config and agent initialization
* Support reasoning effort levels (minimal/low/medium/high) for Doubao/GPT-5 models
* Add UI controls in input box for reasoning effort selection
* Update doubao-seed-1.8 example config with reasoning effort support
Fixes & Cleanup:
* Ensure UTF-8 encoding for file operations
* Remove unused imports
* fix: set reasoning_effort to None for unsupported models
* fix: unit test error
* Update frontend/src/components/workspace/input-box.tsx
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
add oauth schema to MCP server config (extensions_config.json)
support client_credentials and refresh_token grants
implement token manager with caching and pre-expiry refresh
inject OAuth Authorization header for MCP tool discovery and tool calls
extend MCP gateway config models to read/write OAuth settings
update docs and examples for OAuth configuration
add unit tests for token fetch/cache and header injection
* fix: use shell fallback instead of hardcoded /bin/zsh in LocalSandbox
Replace hardcoded /bin/zsh executable with dynamic shell detection
that falls back through /bin/zsh → /bin/bash → /bin/sh. This fixes
skill execution failures in Docker containers (python:3.12-slim)
where zsh is not available.
Closes#935
* Update backend/src/sandbox/local/local_sandbox.py
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
---------
Co-authored-by: atian8179 <atian8179@users.noreply.github.com>
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Validate that all dict-returning client methods conform to Gateway
Pydantic response models (ModelsListResponse, ModelResponse,
SkillsListResponse, SkillResponse, SkillInstallResponse,
McpConfigResponse, UploadResponse, MemoryConfigResponse,
MemoryStatusResponse). Pydantic ValidationError in CI catches
schema drift between client and Gateway with zero production coupling.
Also includes prior review fixes: enhanced client methods, expanded
unit tests (67→77), live integration test improvements, and updated
documentation.
Co-authored-by: greatmengqi <chenmengqi.0376@bytedance.com>
Add `DeerFlowClient` class that provides direct in-process access to
DeerFlow's agent and Gateway capabilities without requiring LangGraph
Server or Gateway API processes. This enables users to import and use
DeerFlow as a Python library.
Co-authored-by: greatmengqi <chenmengqi.0376@bytedance.com>
* feat: add Novita AI as optional LLM provider
Adds Novita AI (https://novita.ai) as an optional, OpenAI-compatible
LLM provider.
Changes:
- Added Novita model configuration example in config.example.yaml
- Added NOVITA_API_KEY to .env.example
Usage: Set NOVITA_API_KEY in your environment and use novita-gpt-4
as the model name.
* update correct model info
* Update README.md
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* fix: recover from stale model context after config model changes
* fix: fail fast on missing model config and expand model resolution tests
* fix: remove duplicate get_app_config imports
* fix: align model resolution tests with runtime imports
* Apply suggestions from code review
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* fix: remove duplicate model resolution test case
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Previously used before_model which returned {"messages": patches}, causing
LangGraph's add_messages reducer to append patches at the end of the message
list. This resulted in invalid ordering (ToolMessage after a HumanMessage)
that LLMs reject with tool call ID mismatch errors.
Switch to wrap_model_call/awrap_model_call to insert synthetic ToolMessages
immediately after each dangling AIMessage before the request reaches the LLM,
without persisting the patches to state.
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
* Enforces config env var checks and improves startup handling
Ensures critical environment variables are validated during config resolution,
raising clear errors if missing. Improves server startup reliability by
verifying that backend services are listening and by terminating on
misconfiguration at launch. Adds more robust feedback to developers when
API startup fails, reducing silent misconfigurations and speeding up
troubleshooting.
* Initial plan
* Implement suggestions from PR #892: fix env var checks and improve error logging
Co-authored-by: foreleven <4785594+foreleven@users.noreply.github.com>
---------
Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: foreleven <4785594+foreleven@users.noreply.github.com>
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* feat(subagents): make subagent timeout configurable via config.yaml
- Add SubagentsAppConfig supporting global and per-agent timeout_seconds
- Load subagents config section in AppConfig.from_file()
- Registry now applies config.yaml overrides without mutating builtin defaults
- Polling safety-net in task_tool is now dynamic (execution timeout + 60s buffer)
- Document subagents section in config.example.yaml
- Add make test command and enforce TDD policy in CLAUDE.md
- Add 38 unit tests covering config validation, timeout resolution, registry
override behavior, and polling timeout formula
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* feat(subagents): add logging for subagent timeout config and execution
- Log loaded timeout config (global default + per-agent overrides) on startup
- Log debug message in registry when config.yaml overrides a builtin timeout
- Include timeout in executor's async execution start log
- Log effective timeout and polling limit when a task is dispatched
- Fix UnboundLocalError: move max_poll_count assignment before logger.info
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* ci(backend): add lint step and run all unit tests via Makefile
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix lint
---------
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Unifies market analysis, data analysis, and consulting reporting into a comprehensive consulting-analysis skill, enabling a two-phase workflow from analysis framework design to professional report generation. Introduces a DuckDB-based data analysis utility for Excel/CSV files and a chart-visualization skill with a flexible JS interface and extensive chart type documentation. Removes the legacy market analysis skill to streamline report generation and improve extensibility for consulting and data-driven workflows.
