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DevAll Backend User Guide (English)

This landing page helps operators, workflow authors, and extension developers find the right documentation for DevAll backend components. Use the table below as your navigation map; drill into the linked chapters for full procedures and examples.

1. Documentation Map

Topic Highlights
Web UI Quick Start Frontend interface operations, workflow execution, human review, troubleshooting.
Workflow Authoring YAML structure, node types, provider/edge conditions, template export, CLI execution.
Graph Execution Logic DAG/cyclic graph execution, Tarjan cycle detection, super node construction, recursive cycle execution.
Dynamic Parallel Execution Map/Tree modes, split strategies, parallel processing and hierarchical reduction.
Memory Module Memory list architecture, built-in simple/file/blackboard behaviors, embedding config, troubleshooting.
Thinking Module Reasoning enhancement, self-reflection mode, extending custom thinking modes.
Tooling Module Function/MCP modes, context injection, built-in function catalog, MCP launch patterns.
Node Types Reference Agent, Python, Human, Subgraph, Passthrough, Literal, Loop Counter node configurations.
Attachment & Artifact APIs Upload/list/download endpoints, manifest schema, cleanup strategies, security constraints.
FIELD_SPECS Standard Field metadata contract that powers UI forms and template export—required reading before customizing modules.
Config Schema API Contract /api/config/schema(*) request examples and breadcrumbs protocol (mostly for frontend/IDE integrations).

2. Product Overview (Backend Focus)

  • Workflow orchestration engine: Parses YAML DAGs, coordinates model, python, tooling, and human nodes inside a shared context, and writes node outputs into WareHouse/<session>/.
  • Provider abstraction: The runtime/node/agent/providers/ layer encapsulates OpenAI, Gemini, and other APIs so each node can swap models, base URLs, credentials, plus optional thinking and memories settings.
  • Real-time observability: FastAPI + WebSocket streams node states, stdout/stderr, and artifact events to the Web UI, while structured logs land in logs/ for centralized collection.
  • Run asset management: Every execution creates an isolated session; attachments, Python workspace, context snapshots, and summary outputs are downloadable for later review.

3. Architecture & Execution Flow

  1. Entry: Web UI and CLI call the FastAPI server exposed via server_main.py (e.g., /api/workflow/execute).
  2. Validation/queueing: WorkflowRunService validates YAML, creates a session, prepares code_workspace/attachments/, then hands the DAG to the scheduler in workflow/.
  3. Execution: Node executors resolve dependencies, propagate context, call tools, and retrieve memories; MemoryManager, ToolingConfig, and ThinkingManager trigger inside agent nodes as needed.
  4. Observability: WebSocket pushes states, logs, and artifact events; JSON logs stay in logs/, and WareHouse/ stores run assets.
  5. Cleanup & download: After completion you can bundle the session for download or fetch files individually via the attachment APIs; retention policies are deployment-specific.

4. Role-based Navigation

5. Glossary

  • Session: Unique ID (timestamp + name) for a single run, used across the Web UI, backend, and WareHouse/.
  • code_workspace: Shared directory for Python nodes at WareHouse/<session>/code_workspace/, synchronized with relevant attachments.
  • Attachment: Files uploaded by users or generated during runs; list/download via REST or WebSocket APIs.
  • Memory Store / Attachment: Stores define persistence backends; memory attachments describe how agent nodes read/write those stores across phases.
  • Tooling: Execution environment bound to agent nodes (Function or MCP implementations).

If you spot gaps or outdated instructions, open an issue/PR or edit the docs directly (remember to keep Chinese and English versions in sync).