plano/demos/use_cases/credit_risk_case_copilot/config.yaml

version: v0.3.0

# Define the Risk Crew Agent service
agents:
  - id: risk_crew_agent
    #url: http://localhost:10530/v1/chat/completions
    url: http://host.docker.internal:10530/v1/chat/completions

# HTTP filter for PII redaction and prompt injection detection
filters:
  - id: pii_security_filter
    #url: http://localhost:10550/v1/tools/pii_security_filter
    url: http://host.docker.internal:10550/v1/tools/pii_security_filter
    type: http

# LLM providers with model routing
model_providers:
  - model: openai/gpt-4o
    access_key: $OPENAI_API_KEY
    default: true
  - model: openai/gpt-4o-mini
    access_key: $OPENAI_API_KEY

# ToDo: Debug model aliases
# Model aliases for semantic naming
model_aliases:
  risk_fast:
    target: openai/gpt-4o-mini
  risk_reasoning:
    target: openai/gpt-4o

# Listeners
listeners:
  # Agent listener for routing credit risk requests
  - type: agent
    name: credit_risk_service
    port: 8001
    router: plano_orchestrator_v1
    address: 0.0.0.0
    agents:
      - id: risk_crew_agent
        description: |
          Credit Risk Case Copilot Agent - Specialized AI system for credit risk assessment, policy compliance, and case management.

          CAPABILITIES:
          * Credit risk triage and assessment for loan applications
          * Multi-agent workflow using intake, scoring, policy, and memo agents
          * Risk band classification (LOW/MEDIUM/HIGH) with confidence scoring
          * Risk driver identification with supporting evidence from application data
          * Policy and compliance checks against lending standards
          * Document requirement identification based on risk profile
          * Bank-ready decision memo generation
          * Case creation with structured data capture
          * Handles missing data, thin files, and incomplete applications

          USE CASES:
          * "Analyze this loan application for credit risk"
          * "What is the risk assessment for this applicant?"
          * "Check policy compliance for this case"
          * "Create a decision memo for this application"
          * "What documents are needed for this loan?"
          * "Assess the credit risk and create a case"

          SECURITY & COMPLIANCE:
          * PII redaction for CNIC, phone numbers, emails
          * Prompt injection detection and mitigation
          * Audit trail with model usage and guardrail events
          * OpenTelemetry tracing for compliance monitoring

          When queries involve credit risk assessment, policy validation, document requirements, decision memos, or case creation for loan applications, route to this agent.
        filter_chain:
          - pii_security_filter

  # Model listener for internal LLM gateway (used by agents)
  - type: model
    name: llm_gateway
    address: 0.0.0.0
    port: 12000

  # Prompt listener for function calling
  - type: prompt
    name: prompt_functions
    address: 0.0.0.0
    port: 10000

# Endpoints for prompt targets
endpoints:
  case_service:
    #endpoint: localhost:10540
    endpoint: host.docker.internal:10540
    connect_timeout: 5s

# Prompt target for case creation
prompt_targets:
  - name: create_risk_case
    description: Create a new credit risk case in the case management system with validated loan application data
    parameters:
      - name: applicant_name
        description: Full name of the loan applicant
        required: true
        type: string
      - name: loan_amount
        description: Requested loan amount in currency
        required: true
        type: number
      - name: risk_band
        description: Risk classification (LOW, MEDIUM, or HIGH)
        required: true
        type: string
        enum: ["LOW", "MEDIUM", "HIGH"]
      - name: confidence
        description: Confidence score for risk assessment (0.0 to 1.0)
        required: true
        type: number
      - name: recommended_action
        description: Recommended action (APPROVE, CONDITIONAL_APPROVE, REFER, REJECT)
        required: true
        type: string
        enum: ["APPROVE", "CONDITIONAL_APPROVE", "REFER", "REJECT"]
      - name: required_documents
        description: List of required documents for case processing
        required: true
        type: array
      - name: policy_exceptions
        description: List of policy exceptions identified
        required: false
        type: array
      - name: notes
        description: Additional case notes or decision memo summary
        required: false
        type: string
    endpoint:
      name: case_service
      path: /cases
      http_method: POST

# OpenTelemetry tracing
tracing:
  random_sampling: 100