197 lines
13 KiB
Python
197 lines
13 KiB
Python
"""Built-in Co4E agent personas (ported from nova-platform).
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Built-ins are code constants — always available in the palette / sidebar /
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parallel sub-agent picker, never saved to disk. Kept Qt-free for testing."""
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from __future__ import annotations
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from dataclasses import dataclass
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from typing import List, Optional
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from pathlib import Path
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from .co4e import (
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Edge, Node, Step, Workflow, get_workflow, save_workflow,
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)
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@dataclass
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class BuiltinAgent:
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slug: str
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name: str
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role: str
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icon: str
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instructions: str
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permission_preset: str = "inherit"
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# 14 built-in agent personas (name / role / read-only where the job is analysis).
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BUILTIN_AGENTS: List[BuiltinAgent] = [
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BuiltinAgent("business-analyst", "Business Analyst", "ANALYST", "file",
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"Analyze the requirement/RFP. Extract goals, scope, stakeholders, constraints and "
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"acceptance criteria. Output a clear, structured requirements breakdown.", "read-only"),
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BuiltinAgent("slide-craft", "Slide Craft — RFP to Proposal", "PRESENTER", "eye",
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"Turn the input into a persuasive proposal/slide outline: executive summary, win "
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"themes, solution, plan, and pricing structure. Output ready-to-slide sections."),
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BuiltinAgent("project-manager", "Project Manager", "PM", "schedule",
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"Plan delivery: break work into milestones and tasks with owners, dependencies and a "
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"realistic timeline. Flag risks and mitigations."),
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BuiltinAgent("solution-architect", "Solution Architect", "ARCHITECT", "server",
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"Design the solution architecture: components, data flow, technology choices and the "
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"list of files/modules to create or change. Justify key decisions."),
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BuiltinAgent("dba-expert", "DBA Expert", "DBA", "database",
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"Design/optimize the database: schema, indexes, migrations and queries. Ensure "
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"integrity, performance and safe rollout."),
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BuiltinAgent("security-auditor", "Security Auditor", "SECURITY", "shield",
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"Review for security issues: authn/authz, injection, secrets, data exposure and unsafe "
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"dependencies. List findings by severity with concrete fixes.", "read-only"),
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BuiltinAgent("pdf-to-markdown", "PDF to Markdown", "CONVERTER", "file",
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"Convert the provided document faithfully to clean, well-structured Markdown, "
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"preserving headings, tables and lists.", "read-only"),
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BuiltinAgent("migration-expert", "Migration Expert", "MIGRATION", "link",
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"Plan and perform the migration: assess the source, map to the target, produce "
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"step-by-step migration scripts and a verification/rollback plan."),
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BuiltinAgent("reviewer", "Reviewer", "REVIEWER", "check",
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"Critically review the work for correctness, completeness and quality. Give specific, "
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"actionable feedback; approve only when it genuinely meets the goal.", "read-only"),
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BuiltinAgent("backend-dev", "Backend Dev", "BACKEND", "server",
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"Implement the backend: APIs, business logic, data access and tests. Write clean, "
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"working code in the working folder."),
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BuiltinAgent("reverse-engineering", "Reverse Engineering", "REVERSE", "search",
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"Analyze the existing code/binary to explain how it works: structure, key flows and "
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"behavior. Produce a clear technical write-up.", "read-only"),
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BuiltinAgent("cloud-expert", "Cloud Expert", "CLOUD", "cloud",
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"Design/operate the cloud setup: infrastructure, deployment, scaling, cost and "
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"reliability. Provide IaC or concrete configuration."),
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BuiltinAgent("frontend-dev", "Frontend Dev", "FRONTEND", "workspaces",
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"Implement the frontend/UI: components, state and styling. Write clean, working code "
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"and match the design intent."),
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BuiltinAgent("tester", "Tester", "QA", "beaker",
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"Test what was built: write and run meaningful tests, report pass/fail and file clear "
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"defects with reproduction steps."),
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# ---- Delivery-lifecycle personas, one per bundled skill (see skill_library
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# and DELIVERY_LIFECYCLE_FLOW). Each pairs with an attached skill of the same
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# topic; the built-in flow chains all four end-to-end. ----
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BuiltinAgent("requirement-analyst", "Requirement Analyst", "ANALYST", "file",
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"Act as an expert Business Analyst. Do NOT jump to solution or code. Extract business "
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"goal, current issue, expected outcome, scope, constraints, data and stakeholders; "
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"classify requirements (functional/non-functional/data/integration/security/operation/"
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"UI-UX/AI-agent/business/constraint); write acceptance criteria; list open questions. "
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"Mark missing info as `Need Confirm` instead of assuming. Save the requirement "
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"artifacts to the workspace. Keep requirement IDs traceable.", "full"),
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BuiltinAgent("solution-designer", "Solution Designer", "ARCHITECT", "server",
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"Act as an expert Solution Architect. Map each requirement to solution components; "
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"propose at least two options when uncertain and recommend one; define architecture, "
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"workflow, data model, integration, security/governance, deployment and risks; prepare "
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"a WBS-level scope and ADR decisions. Save the design artifacts to the workspace. Keep "
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"every decision traceable to requirement IDs or documented assumptions.", "full"),
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BuiltinAgent("build-implementer", "Build Implementer", "BUILDER", "beaker",
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"Act as an expert Tech Lead. Break the design into small executable tasks with "
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"dependencies and done criteria; enforce coding, security, logging and error-handling "
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"rules; prepare a test plan and review checklist; implement in the working folder and "
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"verify against acceptance criteria. Never hardcode secrets. Keep tasks/changes/tests "
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"traceable to requirement IDs.", "full"),
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BuiltinAgent("demo-preparer", "Demo Preparer", "PRESENTER", "eye",
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"Act as an expert Demo Director / Presales consultant. Start from the business story, "
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"not features. Prepare demo goal, audience, before/after storyline, happy-path + "
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"edge-case + failure/fallback scenarios, speaker script, data & environment checklists, "
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"customer Q&A and next actions. Then ACTUALLY SET UP THE DEMO ENVIRONMENT AND RUN THE "
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"APP in the workspace: create/prepare the runtime (venv + install dependencies or the "
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"documented setup), start the app/build, and verify it launches and the happy-path "
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"works — capturing the exact run commands and any fixes into a runbook. Save the demo "
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"artifacts to the workspace. Never expose credentials or sensitive data; keep claims "
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"aligned with what you actually ran and verified.", "full"),
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BuiltinAgent("security-agent", "Security Agent", "SECURITY", "shield",
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"Act as an expert Security Reviewer / governance auditor. Assess the prompt, attached "
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"content, tool/action, design or code against security rules: prompt injection, "
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"secret/credential exposure, destructive or out-of-scope actions, RBAC/least "
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"privilege, injection, data exposure, unsafe dependencies, audit and data "
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"classification. Report findings by severity with concrete fixes and give a clear "
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"ALLOW / ALLOW-WITH-CONDITIONS / BLOCK verdict — default to BLOCK when uncertain. "
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"Never expose secrets or protected source code.", "read-only"),
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]
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BUILTIN_AGENTS_BY_NAME = {a.name: a for a in BUILTIN_AGENTS}
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BUILTIN_AGENTS_BY_SLUG = {a.slug: a for a in BUILTIN_AGENTS}
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def step_from_builtin(name: str, instructions: str = "") -> Step:
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"""A Step persona seeded from a built-in agent name (fallback to a generic
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step if the name is unknown, e.g. a since-removed built-in)."""
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a = BUILTIN_AGENTS_BY_NAME.get(name)
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if a is None:
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return Step(label=name or "New Step", instructions=instructions)
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return Step(label=a.name, agent_slug=a.slug, role=a.role, icon=a.icon,
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instructions=instructions or a.instructions,
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permission_preset=a.permission_preset)
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# ---- Built-in end-to-end flow: Analyze → Design → Build → Demo -----------
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# Stable id so the built-in flow is refreshed (not duplicated) across upgrades.
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DELIVERY_LIFECYCLE_FLOW_ID = "wf-builtin-delivery-lifecycle"
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# (builtin agent name, attached skill name, permission preset, x position, per-step
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# handoff context). All steps run with full workspace access + auto self-verify;
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# each consumes the previous step's output (the runner threads it automatically),
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# so a single raw requirement flows through to a demo end-to-end.
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_LIFECYCLE_STEPS = [
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("Requirement Analyst", "Analyze Requirement", "full", 0.0,
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"FIRST step of the delivery pipeline. The raw requirement / RFP / meeting "
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"notes are provided as THIS step's attachment or in the input. Analyze it per "
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"the attached skill and SAVE the requirement artifacts (REQ_SPEC, scope "
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"matrix, acceptance criteria, open questions) into the workspace. If nothing "
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"was provided, clearly state what input you need and stop."),
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("Solution Designer", "Solution Design", "full", 260.0,
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"Use the requirement breakdown from the previous step (provided above) as your "
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"input. Produce and SAVE the solution-design artifacts (architecture, option "
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"comparison, data model, security design, WBS, ADRs). Keep every decision "
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"traceable to the requirement IDs."),
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("Build Implementer", "Build Implementation", "full", 520.0,
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"Use the requirements + solution design from the previous steps. IMPLEMENT the "
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"solution in the workspace with real, working code and tests; then run/verify "
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"it. Save the code, test plan and a short verification report. Keep changes "
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"traceable to the requirement IDs."),
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("Demo Preparer", "Demo Preparation", "full", 780.0,
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"Use everything produced by the previous steps. Prepare and SAVE a compelling, "
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"safe demo of what was built: goal, before/after story, happy-path + edge-case "
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"+ fallback scenarios, speaker script, data & environment checklists, Q&A and "
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"next actions. Keep claims aligned with what was actually verified."),
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]
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def build_delivery_lifecycle_flow() -> Workflow:
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"""A ready-to-run Co4E flow chaining the four delivery-lifecycle agents (skills
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01–04), each carrying its matching bundled skill + a handoff context, so a raw
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requirement runs FULLY end-to-end: Analyze Requirement → Solution Design →
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Build Implementation → Demo Preparation. Every step has full workspace access
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and auto self-verifies before advancing."""
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nodes: List[Node] = []
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for i, (agent_name, skill_name, preset, x, ctx) in enumerate(_LIFECYCLE_STEPS):
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step = step_from_builtin(agent_name)
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step.permission_preset = preset
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step.skills = [skill_name] # resolved to full skill text by the runner's skill_map
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step.context = ctx # per-step handoff guidance
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step.self_verify = True # quality gate before the next step
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nodes.append(Node(id=f"n-lc-{i}", x=x, y=0.0, data=step))
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edges = [Edge(id=f"e-lc-{i}", source=nodes[i].id, target=nodes[i + 1].id)
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for i in range(len(nodes) - 1)]
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return Workflow(id=DELIVERY_LIFECYCLE_FLOW_ID,
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name="Req2 Demo",
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is_template=False, nodes=nodes, edges=edges)
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def seed_builtin_flows(seeded_ids=None, directory: Optional[Path] = None) -> List[str]:
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"""Ensure the built-in Co4E flow is present + current in the user's workflow
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store on every launch, so it ALWAYS shows up in the Flow sidebar.
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It is (re)written to its latest definition unconditionally — the canonical
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built-in flow is treated like the built-in agents/skills (always available).
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To customise it, Duplicate it in the Flow sidebar (the copy is yours and is
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never overwritten). Returns the ids newly seeded THIS call (for the caller to
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persist — informational only, since presence no longer depends on it)."""
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already = set(seeded_ids or [])
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newly: List[str] = []
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fid = DELIVERY_LIFECYCLE_FLOW_ID
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save_workflow(build_delivery_lifecycle_flow(), directory) # always ensure present + current
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if fid not in already:
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newly.append(fid)
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return newly
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