Phase 4.2+4.3: YAML workflow spec + ACA protocol abstraction (v2026.07.19.10)
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QihuAI Design committed 2026-07-19 20:17:49 +08:00
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version: "1.0"
name: "Code Review Pipeline"
description: "Generate code → review → merge. A standard code-review workflow."
category: development
nodes:
- id: code_gen
type: llm
description: "Generate code based on requirements"
on_error: halt
config:
model: auto
system_prompt: "You are a senior software engineer. Write clean, production-ready code based on the user's requirements. Include comments and error handling."
- id: review
type: llm
description: "Review generated code for bugs and style"
on_error: continue
config:
model: auto
system_prompt: "You are a code reviewer. Analyze the provided code for bugs, style issues, performance problems, and security vulnerabilities. Provide specific, actionable feedback."
- id: merge
type: reduce
description: "Combine code with review feedback"
config:
strategy: concat
edges:
- from: code_gen
to: review
- from: code_gen
to: merge
- from: review
to: merge
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version: "1.0"
name: "Multi-Agent Debate"
description: "Two agents debate a topic from opposing perspectives, then a judge agent synthesizes the conclusion."
category: creativity
nodes:
- id: proponent
type: llm
description: "Argue in favor of the proposition"
on_error: continue
config:
model: auto
system_prompt: "You are a skilled debater. Argue strongly IN FAVOR of the given proposition. Use logic, evidence, and persuasive reasoning. Be passionate but fair."
- id: opponent
type: llm
description: "Argue against the proposition"
on_error: continue
config:
model: auto
system_prompt: "You are a skilled debater. Argue strongly AGAINST the given proposition. Use logic, evidence, and persuasive reasoning to find flaws in the proponent's case."
- id: judge
type: llm
description: "Evaluate both sides and reach a conclusion"
on_error: continue
config:
model: auto
system_prompt: "You are an impartial judge. Evaluate both arguments fairly. Identify the strongest points from each side. Provide a balanced conclusion and recommendation."
edges:
- from: proponent
to: judge
- from: opponent
to: judge
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version: "1.0"
name: "RAG Search Pipeline"
description: "Search knowledge base → augment with context → generate answer. Standard RAG pipeline."
category: productivity
nodes:
- id: search
type: llm
description: "Generate search queries and retrieve relevant context"
on_error: continue
config:
model: auto
system_prompt: "You are a search specialist. For the given question, identify 2-3 key search points. Then search the provided knowledge base for relevant information. Return the most relevant passages with source references."
- id: answer
type: llm
description: "Generate final answer with citations"
on_error: continue
config:
model: auto
system_prompt: "You are a knowledge assistant. Using the search results provided, generate a comprehensive answer. Always cite your sources. If information is insufficient, clearly state what is missing."
edges:
- from: search
to: answer
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version: "1.0"
name: "Research & Answer"
description: "Research topic → generate answer. Uses two LLM nodes for research and synthesis."
category: productivity
nodes:
- id: research
type: llm
description: "Search and gather information on the topic"
on_error: continue
config:
model: auto
system_prompt: "You are a thorough researcher. Search for key facts, data points, and relevant context about the given topic. Provide a comprehensive summary with citations."
- id: answer
type: llm
description: "Synthesize research into final answer"
on_error: continue
config:
model: auto
system_prompt: "You are a professional writer. Based on the research summary provided, craft a clear, well-structured answer for the user. Include key findings and actionable insights."
edges:
- from: research
to: answer