ALwrity/docs/SIF/SIF_AGENTS_TEAM_ARCHITECTURE.md

SIF AI Agents Team - Architecture & Capabilities

Last Updated: 2025-03-01 Component: Semantic Intelligence Framework (SIF) Agents

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🧠 Executive Summary

The SIF Agents Team is a multi-agent system built on top of the Semantic Intelligence Framework (SIF). Unlike generic AI assistants, these agents are "grounded" in a shared semantic index (txtai) containing the user's content, competitor data, and search console metrics.

Each agent acts as a specialized "Department Head," continuously monitoring the index to surface insights, propose tasks, and execute workflows autonomously.

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🏗️ Architecture

The "Committee" Model

Instead of a single "God Mode" AI, we use a committee of specialized agents orchestrated by a central Manager.

graph TD
    A[User / Dashboard] -->|Requests| B(Orchestrator)
    B -->|Delegates| C[Strategy Architect]
    B -->|Delegates| D[Content Strategist]
    B -->|Delegates| E[SEO Specialist]
    B -->|Delegates| F[Social Manager]
    B -->|Delegates| G[Competitor Analyst]
    
    C & D & E & F & G -->|Reads/Writes| H[(SIF Semantic Index)]
    H -->|Syncs| I[Google Search Console]
    H -->|Syncs| J[Competitor Content]

Shared Brain (SIF Index)

All agents share the same memory (the SIF Index).

• Example: If the Competitor Analyst indexes a new rival blog post, the Content Strategist immediately sees it as a "Content Gap" without needing a manual update.

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🤖 The Agent Roster

1. Strategy Architect Agent (Lead)

• Role: The "VP of Content." Responsible for high-level direction.
• Key Capabilities:
  • Pillar Discovery: Clusters content to find de-facto pillars.
  • Strategy Health: Warns when content deviates from core goals.
  • Planning: Proposes quarterly themes based on performance.
• SIF Integration: Queries txtai for cluster density and topic coherence.

2. Content Strategist Agent (Creative)

• Role: The "Editor-in-Chief." Focuses on what to write next.
• Key Capabilities:
  • Gap Analysis: Identifies topics competitors cover but you don't.
  • Trend Spotting: Detects rising keywords in the industry.
  • Brief Generation: Creates detailed outlines for writers.
• SIF Integration: Compares user vector space vs. competitor vector space.

3. SEO Specialist Agent (Technical)

• Role: The "Technical SEO." Ensures visibility and health.
• Key Capabilities:
  • Rank Monitoring: Watches SERP movements for key pages.
  • Health Checks: Flags 404s, slow pages, or missing meta tags.
  • Opportunity Finding: "Low hanging fruit" (e.g., high impression, low CTR).
• SIF Integration: Analyzes GSC performance data mapped to content embeddings.

4. Social Manager Agent (Engagement)

• Role: The "Social Media Manager." Handles distribution and community.
• Key Capabilities:
  • Repurposing: Turns blog posts into LinkedIn threads/Tweets.
  • Schedule Optimization: Predicts best times to post.
  • Engagement: Drafts replies to high-value comments.
• SIF Integration: Matches social trends to existing content library.

5. Competitor Analyst Agent (Intelligence)

• Role: The "Spy." Watches the market 24/7.
• Key Capabilities:
  • Change Detection: Alerts when a competitor updates their pricing or homepage.
  • Counter-Strategy: Suggests moves to block competitor launches.
• SIF Integration: Continuously indexes competitor sitemaps into the shared brain.

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🛠️ Technical Implementation

Base Agent Interface

All agents inherit from BaseALwrityAgent and implement standard methods:

class SpecializedAgent(BaseALwrityAgent):
    async def propose_daily_tasks(self, context) -> List[TaskProposal]:
        # Domain specific logic
        pass

    async def analyze_sif_data(self, query) -> Dict[str, Any]:
        # Semantic search logic
        pass

Task Proposal Protocol

Agents don't just "chat"; they submit structured TaskProposal objects:

• Title: Actionable name.
• Priority: High/Medium/Low.
• Reasoning: "Why?" (e.g., "Because competitor X did Y").
• Source: Agent Name (displayed in UI).

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📊 UI Visibility

The agents are visible to the user in three key areas:

1. Team Huddle Widget: Real-time status (Active/Thinking) in the Main Dashboard.
2. Today's Tasks: Each task card shows the agent's badge and reasoning.
3. SEO Dashboard: Insights are tagged with "Identified by [Agent Name]".

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🤝 Team Huddle (System Contract)

The Team Huddle is the canonical operational surface for multi-agent coordination. It must stay consistent across dashboard widget, notifications, and the full activity view.

Event/Data Contract

All orchestration updates are emitted as typed records under a shared schema:

• status
  • agent_id, state, started_at, last_heartbeat_at, run_id?
  • State enum: idle, running, blocked, waiting_approval, degraded.
• run
  • run_id, workflow_type, trigger, started_at, ended_at, duration_ms, outcome
  • Trigger enum: scheduled, manual, event_driven.
• event
  • event_id, run_id, agent_id, event_type, severity, summary, created_at, metadata
  • Event type enum: insight, task, system, handoff.
• alert
  • alert_id, event_id, threshold_key, threshold_value, observed_value, created_at, is_acknowledged
• approval
  • approval_id, run_id, action_label, requested_by, requested_at, expires_at, approval_state
  • Approval state enum: pending, approved, rejected, expired.

Refresh + Stream Semantics

• Primary transport is SSE with incremental delivery for each record type.
• Clients bootstrap with latest N (default 50) records, then subscribe for deltas.
• On disconnect: exponential backoff reconnect; if retries exhausted, switch to 15-second polling.
• Feed ordering is deterministic by created_at DESC, tie-broken by event_id.
• Duplicate prevention uses idempotency key = event_id (status events key by agent_id + last_heartbeat_at).

Latency SLOs

• P50 ingest-to-UI: <= 2s for status/event.
• P95 ingest-to-UI: <= 5s for all non-bulk events.
• Critical alert propagation: <= 3s P95.
• Approval decision reflection: <= 2s P95.

Failure + Fallback Behavior

• If ingestion pipeline lags, emit synthetic system event with severity warning to inform users.
• If an agent misses two heartbeat windows, transition status to degraded and suspend dependent handoffs.
• If schema validation fails, route to dead-letter queue and emit sanitized system placeholder event.
• If transport unavailable, UI remains functional in read-only cached mode with manual refresh controls.

User Detail Tiers + Security Constraints

• Tier 1: Summary — agent, summary, timestamp, severity.
• Tier 2: Operational — run context, thresholds, workflow outcome, approval state.
• Tier 3: Diagnostic — trace/correlation IDs, retry counters, raw sanitized metadata.
• Role mapping:
  • Workspace Member -> Tier 1
  • Analyst/Editor -> Tier 1-2
  • Admin/Owner -> Tier 1-3
• Security rules:
  • Secrets, credentials, API keys, and personal identifiers are redacted before persistence.
  • Tier 3 data is never included in default exports or external webhook mirrors.
  • Approval actions require explicit authorization and audit logging of actor + timestamp.

Acceptance Criteria: View Full Team Activity

• The "View Full Team Activity" control navigates from widget to a dedicated timeline route and preserves filters.
• The timeline supports filtering by agent, event type, severity, status, and approval state.
• Minimum visible fields per row:
  • event_id, created_at, agent_id, event_type, severity, summary
  • run_id, workflow_type, outcome
  • alert_id (when present), approval_id + approval_state (when present)
• Row expansion reveals Tier 2 details; Tier 3 panel is visible only for admin/owner roles.
• Inline interactions:
  1. Acknowledge/unacknowledge alerts.
  2. Approve/reject pending approval requests.
  3. Jump from event row to related task/insight detail.
• Navigation continuity: returning to dashboard restores previous Team Huddle scroll position and active filters.

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🚀 Future Roadmap

• Inter-Agent Chat: Allow agents to debate strategy (e.g., SEO Agent vs. Creative Agent).
• Auto-Execution: Allow agents to perform tasks (e.g., fix a broken link) with user approval.
• Voice Interface: Daily standup meeting via voice.