DataFlow-WebUI

Reasoning-guided pipeline planner that generates standard DataFlow pipeline code

Reasoning-guided pipeline planner that generates standard DataFlow pipeline code. Use when the user asks to generate, create, or build a DataFlow pipeline, wants to process JSONL data with LLM operators, mentions PromptedGenerator / PromptedFilter / Text2MultiHopQAGenerator, or asks about DataFlow operator chains. Also use when user provides a .jsonl file and asks what pipeline to write.

DataFlow 开发专家上下文加载器。当用户在 DataFlow 仓库中进行开发时触发， 涵盖：新建算子/Pipeline/Prompt、诊断报错、规范审查、 以及感知仓库变更并建议更新知识库。 Trigger: user is developing in DataFlow repo, asks to create operator/pipeline/prompt, encounters errors, wants code review, or asks about operators.

Build production-grade DataFlow operator scaffolds (generate/filter/refine/eval) for Codex and coding agents. Trigger when users ask to create/new/scaffold operators, add OPERATOR_REGISTRY registration, generate DataFlowStorage-based CLI wrappers, or generate operator unit/registry/smoke tests.

Build reusable DataFlow prompt_template classes for existing operators with two-round AskUserQuestion intake, two-stage auditable outputs, and static acceptance checks. Trigger when users ask to generate/rewrite/optimize prompt_template or reuse operator logic with new prompt requirements.

DataFlow development expert context loader. Use when developing in the DataFlow repo: creating operators/pipelines/prompts, diagnosing errors, code review, or detecting repo changes to update the knowledge base. Trigger: user is developing in DataFlow repo, asks to create operator/pipeline/prompt, encounters errors, wants code review, or asks about operators.

Build production-grade DataFlow operator scaffolds (generate/filter/refine/eval). Use when users ask to create/new/scaffold operators, add OPERATOR_REGISTRY registration, generate DataFlowStorage-based CLI wrappers, or generate operator unit/registry/smoke tests.

Build reusable DataFlow prompt_template classes for existing operators with structured intake, two-stage auditable outputs, and static acceptance checks. Use when users ask to generate/rewrite/optimize prompt_template or reuse operator logic with new prompt requirements.