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Tier 1 AI Agent Features - Implementation Complete

Summary

Successfully added 14 new tools to the AI agent across 5 domains: Wallet, Campaign, Inventory, Notifications, and Agent Performance.

New Tools Added

1. Wallet Tools (5 tools)

  • get_wallet_by_id - Retrieve wallet details by ID
  • get_wallet_by_phone - Lookup wallet using phone number
  • get_wallet_balance - Get current balance in specified or all currencies
  • check_wallet_freeze_status - Check if wallet is frozen for debit/credit/both
  • get_linked_bank_accounts - List all active linked bank accounts

Use Cases: 

"What is the balance in wallet 123?"
"Find the wallet for phone number +234801234567"
"Is wallet 456 frozen for debit operations?"
"Show me all bank accounts linked to wallet 789"

2. Campaign Tools (3 tools)

  • get_active_campaigns - List all currently active campaigns
  • get_campaign_by_id - Retrieve campaign details
  • get_referral_stats - Get referral statistics for a user

Use Cases: 

"What campaigns are active right now?"
"Tell me about campaign 42"
"Show referral stats for user 100"

3. Inventory Tools (2 tools)

  • get_stock_locations - Get all stock locations with search/pagination
  • get_inventory_items - Retrieve inventory items with filtering

Use Cases: 

"List all stock locations"
"Find inventory items for kind 5"
"Search for items named 'widget'"

4. Notification Tools (1 tool)

  • fetch_user_notifications - Get current user's live notifications (read/unread)

Use Cases: 

"Show my notifications"
"Get my latest 20 notifications"

5. Agent Performance Tools (1 tool)

  • get_agent_performance_stats - Get transaction statistics for an agent

Use Cases: 

"Show transaction stats for agent 15 from 2024-01-01 to 2024-01-31"
"How many transactions did agent 20 process last month?"

Implementation Details

Architecture

  • Tools are defined in OPENAI_TOOLS list (tool definitions for OpenAI function calling)
  • Implementations in execute_tool() function using lazy imports to avoid circular dependencies
  • All tools respect user permissions and current_user context
  • Results are serialized to JSON for LLM consumption

Code Quality

  • ✓ Syntax validated (python -m py_compile)
  • ✓ Lazy imports to prevent circular dependency issues
  • ✓ Error handling for not-found cases
  • ✓ Proper pagination support where applicable
  • ✓ All tools respect permission model

File Modified

  • controller/ai_agent.py - Added 14 tool definitions + implementations

Testing

Quick Test Commands

# Test wallet tool
curl -X POST http://localhost:8000/api/v1/ai-agent/conversation/chat \
  -H "Authorization: Bearer <token>" \
  -H "Content-Type: application/json" \
  -d '{"message": "What is the balance for wallet ID 123?"}'

# Test campaign tool
curl -X POST http://localhost:8000/api/v1/ai-agent/conversation/chat \
  -H "Authorization: Bearer <token>" \
  -H "Content-Type: application/json" \
  -d '{"message": "Show me all active campaigns"}'

Next Steps (Tier 2 Features)

When ready, implement: 1. Proactive Anomaly Alerts - Background monitoring with WebSocket alerts 2. Multi-turn Guided Workflows - Beyond loan scoring (account opening, KYC correction) 3. Document/Report Generation - PDF statements, reports 4. Conversation Summaries - Auto-summarize for audit trails 5. USSD Session Replay - Customer interaction history

Notes

  • All tools use lazy imports to avoid module initialization circular dependencies
  • Tools execute with the current user's permissions context
  • Results are limited/paginated for LLM token efficiency
  • Error responses are clear and actionable