* fix(threads): clean up local thread data after thread deletion
Delete DeerFlow-managed thread directories after the web UI removes a LangGraph thread.
This keeps local thread data in sync with conversation deletion and adds regression coverage for the cleanup flow.
* fix(threads): address thread cleanup review feedback
Encode thread cleanup URLs in the web client, keep cache updates explicit when no thread search data is cached, and return a generic 500 response from the cleanup endpoint while documenting the sanitized error behavior.
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* feat: add Claude Code OAuth and Codex CLI providers
Port of bytedance/deer-flow#1136 from @solanian's feat/cli-oauth-providers branch.\n\nCarries the feature forward on top of current main without the original CLA-blocked commit metadata, while preserving attribution in the commit message for review.
* fix: harden CLI credential loading
Align Codex auth loading with the current ~/.codex/auth.json shape, make Docker credential mounts directory-based to avoid broken file binds on hosts without exported credential files, and add focused loader tests.
* refactor: tighten codex auth typing
Replace the temporary Any return type in CodexChatModel._load_codex_auth with the concrete CodexCliCredential type after the credential loader was stabilized.
* fix: load Claude Code OAuth from Keychain
Match Claude Code's macOS storage strategy more closely by checking the Keychain-backed credentials store before falling back to ~/.claude/.credentials.json. Keep explicit file overrides and add focused tests for the Keychain path.
* fix: require explicit Claude OAuth handoff
* style: format thread hooks reasoning request
* docs: document CLI-backed auth providers
* fix: address provider review feedback
* fix: harden provider edge cases
* Fix deferred tools, Codex message normalization, and local sandbox paths
* chore: narrow PR scope to OAuth providers
* chore: remove unrelated frontend changes
* chore: reapply OAuth branch frontend scope cleanup
* fix: preserve upload guards with reasoning effort wiring
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* 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>
* 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 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
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>
* Adds Kubernetes sandbox provisioner support
* Improves Docker dev setup by standardizing host paths
Replaces hardcoded host paths with a configurable root directory,
making the development environment more portable and easier to use
across different machines. Automatically sets the root path if not
already defined, reducing manual setup steps.
* feat: adds docker-based dev environment
* docs: updates Docker command help
* fix local dev
* feat(sandbox): add Kubernetes-based sandbox provider for multi-instance support
* fix: skills path in k8s
* feat: add example config for k8s sandbox
* fix: docker config
* fix: load skills on docker dev
* feat: support sandbox execution to Kubernetes Deployment model
* chore: rename web service name
Updated documentation to accurately cover all backend subsystems including
subagents, memory, middleware chain, sandbox, MCP, skills, and gateway API.
Fixed broken MCP_SETUP.md link in root README.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add native Apple Container support for better performance on macOS while
maintaining full Docker compatibility. Enhance documentation with memory system
details, development guidelines, and sandbox setup instructions. Improve dev
experience with container image pre-pulling and unified cleanup tools.
Key changes:
- Auto-detect and prefer Apple Container on macOS with Docker fallback
- Add APPLE_CONTAINER.md with complete usage and troubleshooting guide
- Document memory system architecture in CLAUDE.md
- Add make setup-sandbox for pre-pulling container images
- Create cleanup-containers.sh for cross-runtime container cleanup
- Update all related documentation (README, SETUP, config examples)
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Add a root-level Makefile to manage frontend, backend, and nginx services:
- `make check` validates required dependencies (Node.js 22+, pnpm, uv, nginx)
- `make install` installs all project dependencies
- `make dev` starts all services with unified port 2026
- `make stop` and `make clean` for cleanup
Update nginx configuration:
- Change port from 8000 to 2026
- Add frontend upstream and routing (port 3000)
- Add /api/langgraph/* routing with path rewriting to LangGraph server
- Keep other /api/* routes to Gateway API
- Route non-API requests to frontend
Update frontend configuration:
- Use relative URLs through nginx proxy by default
- Support environment variables for direct backend access
- Construct full URL for LangGraph SDK compatibility
Clean up backend Makefile by removing nginx and serve targets.
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Add comprehensive MCP integration using langchain-mcp-adapters to enable
pluggable external tools from MCP servers.
Features:
- MCP server configuration via mcp_config.json
- Automatic lazy initialization for seamless use in both FastAPI and LangGraph Studio
- Support for multiple MCP servers (filesystem, postgres, github, brave-search, etc.)
- Environment variable resolution in configuration
- Tool caching mechanism for optimal performance
- Complete documentation and setup guide
Implementation:
- Add src/mcp module with client, tools, and cache components
- Integrate MCP config loading in AppConfig
- Update tool system to include MCP tools automatically
- Add eager initialization in FastAPI lifespan handler
- Add lazy initialization fallback for LangGraph Studio
Dependencies:
- Add langchain-mcp-adapters>=0.1.0
Documentation:
- Add MCP_SETUP.md with comprehensive setup guide
- Update CLAUDE.md with MCP system architecture
- Update config.example.yaml with MCP configuration notes
- Update README.md with MCP setup instructions
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Implement a skills framework that enables specialized workflows for
specific tasks (e.g., PDF processing, web page generation). Skills are
discovered from the skills/ directory and automatically mounted in
sandboxes with path mapping support.
- Add SkillsConfig for configuring skills path and container mount point
- Implement dynamic skill loading from SKILL.md files with YAML frontmatter
- Add path mapping in LocalSandbox to translate container paths to local paths
- Mount skills directory in AIO Docker sandbox containers
- Update lead agent prompt to dynamically inject available skills
- Add setup documentation and expand config.example.yaml
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
