Aarushiar/pytorch-hackathon-support-env

1# OpenEnv Configuration for Customer Support Environment2# Compliant with OpenEnv specification for environment registration3 4name: support_ticket_environment5version: "1.0.0"  # REQUIRED: Semantic versioning6title: Customer Support Ticket Environment7description: Production-ready environment for customer support ticket resolution with multi-step reasoning, policy learning, and deterministic grading.8 9# ============================================================================10# OPENENV SPEC REQUIREMENTS11# ============================================================================12 13# Entrypoint specification (how the environment is accessed)14entrypoint:15  type: fastapi  # OpenEnv compatible async endpoint16  module: server.app        # Python module path17  app_name: app             # FastAPI app instance name18  host: "0.0.0.0"19  port: 800020  health_endpoint: /health  # Health check endpoint21  environment_endpoint: /env  # Environment endpoint (POST to step/reset)22 23# Observation schema (what agents receive from environment)24observation:25  type: object26  description: Environment state observation containing ticket information and context27  properties:28    done:29      type: boolean30      description: Whether the episode has terminated31    reward:32      type: number33      description: Reward signal from the last action34    metadata:35      type: object36      description: Dynamic state (satisfaction_score, frustration, SLA hours)37    ticket_id:38      type: string39      description: Unique ticket identifier40    customer_message:41      type: string42      description: Customer's issue description43    customer_tier:44      type: string45      enum: ["free", "pro", "enterprise"]46      description: Customer account tier47    priority:48      type: string49      enum: ["low", "medium", "high", "critical"]50      description: Ticket priority level51    category:52      type: string53      enum: ["billing", "technical", "account", "feature_request", "other"]54      description: Issue category55    sensor_data:56      type: object57      description: Business context (queue depth, KB match score, etc.)58    current_status:59      type: string60      description: Current ticket status61    reward_feedback:62      type: string63      description: Feedback on last action's reward64    conversation_history:65      type: array66      description: List of interaction history67    sla_deadline_hours:68      type: integer69      description: Hours remaining for SLA compliance70    steps_taken:71      type: integer72      description: Number of actions taken so far73    available_actions:74      type: array75      items:76        type: string77      description: Valid actions in current state78 79# Action schema (what agents can do)80action:81  type: object82  description: Agent action to take in the environment83  properties:84    action_type:85      type: string86      enum: [87        "request_more_info",88        "escalate_to_human",89        "suggest_knowledge_base",90        "assign_department",91        "close_resolved",92        "request_callback"93      ]94      description: Type of support workflow action95    parameters:96      type: object97      description: Action parameters (e.g., department='billing')98    reasoning:99      type: string100      description: Agent's reasoning for this action101  required:102    - action_type103    - parameters104    - reasoning105 106# Task definitions for grading107tasks:108  - id: 1109    name: billing_confused110    difficulty: easy111    description: Simple ticket classification and routing112    grader: Task1_Grader113    114  - id: 2115    name: technical_issue116    difficulty: medium117    description: Multi-step resolution with clarifications118    grader: Task2_Grader119    120  - id: 3121    name: complex_enterprise122    difficulty: hard123    description: Ambiguous issue requiring reasoning124    grader: Task3_Grader125 126# ============================================================================127# DEPLOYMENT CONFIGURATION128# ============================================================================129 130# Deployment type: 'space' for HF Spaces, 'service' for cloud services131type: space132 133# Runtime specification134runtime: fastapi135 136# Docker configuration137docker:138  # Root-level Dockerfile uses full project as build context139  dockerfile: Dockerfile140  context: .141  142# Health check configuration143health_check:144  endpoint: /health145  interval: 30146  timeout: 10147  retries: 3148  initial_delay: 5149 150# Maximum concurrent sessions for WebSocket support151max_concurrent_sessions: 10152 153# Enable web UI for testing154enable_web_ui: true155 156# Resource requirements for HF Spaces157resources:158  cpu: "2"159  memory: "4Gi"160  161# Metadata for registry and documentation162metadata:163  author: "Meta PyTorch"164  focus: "Customer Support"165  tasks: 3166  difficulty_levels: ["Easy", "Medium", "Hard"]167  version: "1.0.0"168  license: "BSD"169  keywords:170    - pytorch171    - environment172    - inference173    - optimization174    - reinforcement-learning175 176