feat(WP-0012): IHF Phase 11 — Advanced AI Federation

- Schema: AgentRegistration, ModelRoutingPolicy, AgentDelegation,
  CollectiveProposal, CollectiveProposalContribution, AiGovernancePolicy,
  AgentPerformanceRecord + ALTER TABLE agent_proposals
  (migration 1744156800; CHECK constraints on trust_level, status,
  consensus_status — GAAF compliant)

- Bridge: scripts/llm_bridge.py (llm-connect subprocess seam) +
  Application/Helper/AgentBridge.hs (callBridge, callAgent,
  checkGovernancePolicy, jsonArrayTexts)

- Routing: Application/Helper/ModelRouter.hs (resolveAgent,
  resolveAllAgents) + ModelRoutingPolicies CRUD

- Registry: AgentRegistrations CRUD (Index/Show/New/Edit/Performance),
  DeactivateAgentAction, ComputeAgentPerformanceAction

- Delegation: AgentDelegations controller + views, DelegateSubtaskAction
  with token budget enforcement at bridge call time

- Collective: CollectiveProposals controller + views,
  CreateCollectiveProposalAction (fan-out → synthesis → consensus detection)

- Governance: AiGovernancePolicies CRUD + ToggleAiGovernancePolicyAction;
  checkGovernancePolicy enforced at all 4 Phase 5 invocation points

- Phase 5 wiring: replaced callClaudeApi in Widgets, DecisionRecords,
  RequirementCandidates with resolveAgent + callAgent + token tracking

- llm-connect feature requests: ~/llm-connect/FEATURE_REQUESTS.md
  (FR-1 HTTP serve, FR-2 RoutingPolicy, FR-3 async, FR-4 BudgetTracker)

- GAAF scorecard: 3.61 (up from 3.56); Functional 3.4→3.6, Extensions 3.8→3.9

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

scripts/llm_bridge.py

@@ -0,0 +1,67 @@
+#!/usr/bin/env python3
+"""
+IHF llm-connect bridge — Phase 11 AI Federation (IHUB-WP-0012)
+
+Usage:
+    echo '{"provider":"openrouter","model":"...","prompt":"..."}' | python3 scripts/llm_bridge.py
+
+Input JSON fields:
+    provider      — openrouter | gemini | openai | claude-code (default: openrouter)
+    model         — model name string (provider-specific)
+    prompt        — the user prompt
+    systemPrompt  — optional system prompt
+    api_key       — optional; falls back to llm-connect env-var resolution
+    maxTokens     — max completion tokens (default: 2000)
+    temperature   — sampling temperature (default: 0.7)
+
+Output JSON (stdout, exit 0 on success):
+    content       — generated text
+    model         — model name actually used
+    tokensIn      — prompt token count
+    tokensOut     — completion token count
+    finishReason  — stop reason string
+
+Error JSON (stdout, exit 1 on LLMError):
+    error         — error message
+    errorType     — exception class name
+"""
+import sys
+import json
+import os
+
+sys.path.insert(0, os.path.expanduser("~/llm-connect"))
+
+from llm_connect import create_adapter, RunConfig
+from llm_connect.exceptions import LLMError
+
+
+def main() -> None:
+    req = json.load(sys.stdin)
+
+    try:
+        adapter = create_adapter(
+            provider=req.get("provider", "openrouter"),
+            model=req.get("model"),
+            api_key=req.get("api_key"),
+            system_prompt=req.get("systemPrompt"),
+        )
+        config = RunConfig(
+            model_name=req.get("model", ""),
+            temperature=req.get("temperature", 0.7),
+            max_tokens=req.get("maxTokens", 2000),
+        )
+        resp = adapter.execute_prompt(req["prompt"], config)
+        print(json.dumps({
+            "content": resp.content,
+            "model": resp.model,
+            "tokensIn": resp.usage.get("prompt_tokens", 0),
+            "tokensOut": resp.usage.get("completion_tokens", 0),
+            "finishReason": resp.finish_reason,
+        }))
+    except LLMError as e:
+        json.dump({"error": str(e), "errorType": type(e).__name__}, sys.stdout)
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()