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Technical Requirements Document (TRD): AI Agent Orchestration Platform (v1.0 - Core)

1. Introduction

This document outlines the technical design, architecture, and specifications for implementing the AI Agent Orchestration Platform v1.0, as defined in the PRD (agent_platform_prd). It details the chosen technology stack, component interactions, data models, APIs, and non-functional technical requirements. The architecture is designed for extensibility, interoperability (via open standards like Agent2Agent/A2A), multi-modal agent support, edge computing capabilities, federated collaboration, and a vibrant agent ecosystem/marketplace.

2. System Architecture Overview

The platform follows a modular monolithic or microservices-oriented approach (initial choice TBD, leaning towards modular monolith for v1.0 simplicity) comprising several key components:

  • Frontend: Single Page Application (SPA) providing the user interface with support for multi-modal visualization and AR/VR interfaces.
  • Backend API: Serves the frontend, manages business logic, interacts with the database and orchestrator.
  • Orchestration Engine: Manages workflow execution lifecycle (Temporal.io preferred) with support for edge deployment and federated execution.
  • Agent Execution Runtimes: Environments where agent code runs (Docker initially, A2A/Open Agent Protocol for interoperability) with support for multi-modal agents (text, vision, audio, sensor data).
  • Database: Stores persistent state with support for edge-compatible storage and federated data sharing.
  • Observability Stack: Collects and visualizes logs and metrics (Langfuse/Trulens for LLM tracing, Arize, PromptLayer, Grafana, Prometheus, Loki, OpenTelemetry for system observability) with AI-driven anomaly detection and self-optimization.
  • Marketplace & Registry: Agent registry and public/private marketplace for agents, templates, and plugins with comprehensive monetization and quality assurance.
  • Security & Compliance: Enterprise-grade auth (SSO, OIDC, SAML), audit logging, compliance (GDPR, SOC2, HIPAA, PCI-DSS), zero-trust execution, and secure multi-party computation.
  • Multi-Tenancy: Namespaces/workspaces for SaaS deployments and data isolation with cross-organization collaboration capabilities.
  • Edge Computing Framework: Support for deploying and managing agents at the edge with offline operation capabilities.
  • Federated Learning & Collaboration: Framework for secure cross-organization workflows and privacy-preserving computation.

Architecture Diagram (ASCII)

[User] -> [Frontend (React)] <-> [Backend API (FastAPI)] <-> [Temporal.io]
                |                       |                  |-> [Edge Deployment]
                |                       |                  |-> [Federated Execution]
                |                       |
                |                       |-> [PostgreSQL/Edge Storage]
                |                       |-> [Agent Runner: Docker/API/A2A/Multi-Modal]
                |                       |-> [Observability: Prometheus/Grafana/AI-Driven]
                |                       |-> [Marketplace & Monetization]
                |                       |-> [Security & Compliance: GDPR/HIPAA/PCI]
                |                       |-> [Federated Learning Framework]
                |
                |-> [AR/VR Interface] <-|

3. Technology Stack (v1.0)

  • Frontend:
  • Framework: React (v18+)
  • Visual Builder: React Flow (v11+)
  • UI Library: Material UI (MUI) v5+ (or Ant Design)
  • State Management: Zustand
  • API Client: Axios + React Query (TanStack Query) v5+
  • Language: TypeScript
  • Multi-Modal Visualization: Three.js, D3.js
  • AR/VR Support: A-Frame, React Three Fiber
  • Adaptive UI: Responsive design with role-based component rendering
  • Backend API:
  • Framework: Python (v3.11+) with FastAPI
  • API Spec: OpenAPI 3.x (auto-generated by FastAPI)
  • Database ORM: SQLAlchemy v2+ with Alembic for migrations
  • Authentication: JWT with OAuth2/OIDC flow, SSO, SAML
  • Language: Python
  • Multi-Modal Processing: OpenCV, PyTorch, TensorFlow, Whisper
  • Federated APIs: gRPC, Protocol Buffers
  • Edge Compatibility: Lightweight API modules for edge deployment
  • Database:
  • Primary: PostgreSQL (v15+)
  • Edge Storage: SQLite, LevelDB
  • Federated Data: CockroachDB, distributed PostgreSQL
  • Secure Computation: Encrypted query processing, homomorphic encryption libraries
  • Orchestration Engine:
  • Core: Temporal.io (Self-hosted cluster or Temporal Cloud)
  • SDK: Temporal Python SDK
  • Edge Support: Lightweight Temporal worker for edge devices
  • Federated Orchestration: Cross-organization workflow coordination
  • Self-Optimization: AI-driven workflow optimization and resource allocation
  • Agent Execution:
  • Runtime: Docker Engine, WebAssembly for edge
  • Integration: Temporal Activities will use Docker Python SDK (docker-py) to start/manage containers. Kubernetes for cloud, lightweight containers for edge.
  • A2A/Open Agent Protocol: Support for agent interoperability and cross-platform execution.
  • Multi-Modal Agents: Framework for vision, audio, sensor data processing
  • IoT & Robotics: Integration with ROS (Robot Operating System), MQTT
  • AR/VR Agents: Integration with AR/VR frameworks and devices
  • Observability:
  • LLM Tracing: Langfuse SDK (Python), Trulens SDK (Python), Arize, PromptLayer - integrated within agent execution logic/adapters.
  • System Metrics: Prometheus
  • System Logging: Loki (or Elasticsearch)
  • Visualization: Grafana
  • Instrumentation: OpenTelemetry SDKs (Python for backend/activities, potentially JS for frontend) exporting to a collector.
  • AI-Driven Analytics: Anomaly detection, predictive scaling, self-healing
  • Multi-Modal Monitoring: Vision, audio, sensor data visualization
  • Edge Telemetry: Lightweight telemetry for edge devices with offline buffering
  • Marketplace & Registry:
  • Agent registry and plugin/agent marketplace (public/private).
  • Monetization Framework: Payment processing, revenue sharing, subscription management
  • Quality Assurance: Automated testing, compliance verification, security scanning
  • Community Governance: Decentralized governance for marketplace policies
  • Developer Tools: SDKs and development kits for building marketplace-ready agents
  • Infrastructure:
  • Deployment: Docker containers, managed via Docker Compose for local dev/simple deployments. Kubernetes for cloud scaling.
  • Edge Deployment: WebAssembly, lightweight containers for resource-constrained environments
  • CI/CD: GitHub Actions (or similar) with edge-specific deployment pipelines.
  • Secret Management: Integration with HashiCorp Vault (or cloud provider equivalent).
  • Mesh Networking: Support for agent collaboration across distributed edge nodes

4. Component Design & Interactions

  • Frontend <-> Backend: RESTful API calls over HTTPS using JSON payloads. Authentication via JWT Bearer tokens, SSO, SAML. React Query for data fetching/caching. WebSocket connection potentially for real-time updates (future, maybe basic polling for v1.0).
  • Backend <-> Database: SQLAlchemy ORM for CRUD operations on PostgreSQL. Alembic for schema migrations.
  • Backend <-> Orchestrator (Temporal):
  • Backend uses Temporal Client (Python SDK) to:
    • Start new workflow executions based on user requests/translated visual definitions.
    • Query the status of workflow executions.
    • Signal workflows (e.g., for HITL approvals).
    • Deploy/update workflow definitions (if managed dynamically).
  • Orchestrator (Temporal) <-> Agent Execution:
  • Temporal Workflows define the logic flow.
  • Temporal Activities encapsulate interaction with the outside world, including agent execution.
  • DockerRunActivity: Takes image name, command, inputs (env vars, volume mounts). Uses docker-py to run the container, monitors it, retrieves logs/outputs.
  • ApiCallActivity: Takes URL, method, headers, body. Uses httpx to make the call, returns response.
  • A2A/Open Agent Protocol Activity: Enables cross-platform agent interoperability.
  • Activities implement retry policies defined in the workflow.
  • Activities integrate Langfuse/Trulens/Arize/PromptLayer SDKs where appropriate (e.g., before/after LLM calls within an agent if the activity wraps that logic, or if the agent container itself is instrumented).
  • Activities emit logs and metrics via OpenTelemetry/standard logging.
  • Orchestrator (Temporal) <-> HITL:
  • Workflow reaches an HITL step.
  • An Activity notifies the Backend API (e.g., via direct API call or a shared DB flag) that input is needed, providing context and a task ID.
  • The Workflow uses workflow.wait_for_signal(...) to pause execution.
  • User interacts via Frontend -> Backend API -> Backend signals the waiting Temporal Workflow with the human's decision/input. Support for multi-step reviews, escalation, and comms integration (Slack, email).
  • Marketplace & Registry:
  • Backend exposes APIs for agent registration, discovery, and sharing via a public/private marketplace.
  • Monetization APIs for payment processing, subscription management, and revenue sharing.
  • Quality assurance pipeline for automated testing and compliance verification.
  • Community governance framework for decentralized marketplace management.
  • Observability Integration:
  • Backend, Temporal Workers/Activities instrumented with OpenTelemetry SDK.
  • Logs formatted (e.g., JSON) and shipped to Loki/Elasticsearch.
  • Metrics exposed for Prometheus scraping or pushed to a gateway.
  • Langfuse/Trulens/Arize/PromptLayer integration as described above.
  • AI-driven analytics for anomaly detection, predictive scaling, and self-healing.
  • Multi-modal monitoring for vision, audio, and sensor data visualization.
  • Edge Computing Framework:
  • Edge deployment manager for distributing workflows to edge devices.
  • Offline operation support with local storage and synchronization.
  • Resource optimization for constrained environments.
  • Mesh networking for agent collaboration across distributed nodes.
  • Federated Learning & Collaboration:
  • Secure multi-party computation for privacy-preserving data sharing.
  • Cross-organization workflow coordination with access controls.
  • Federated learning framework for distributed model training.
  • Zero-knowledge proofs for verification without revealing sensitive data.

5. API Endpoints (Examples)

  • POST /auth/token: Login, get JWT.
  • GET /users/me: Get current user info.
  • GET /workflows: List workflows.
  • POST /workflows: Create new workflow (takes definition_json).
  • GET /workflows/{workflow_id}: Get workflow details.
  • PUT /workflows/{workflow_id}: Update workflow definition.
  • DELETE /workflows/{workflow_id}: Delete workflow.
  • POST /workflows/{workflow_id}/run: Trigger a workflow run (takes inputs_json).
  • GET /runs: List all workflow runs (filterable by workflow_id, status).
  • GET /runs/{run_id}: Get details of a specific run (including task statuses, graph state).
  • GET /runs/{run_id}/tasks/{task_instance_id}/logs: Get logs for a specific task instance.
  • GET /hitl/tasks: Get HITL tasks assigned to the current user.
  • GET /hitl/tasks/{hitl_task_id}: Get details of a specific HITL task.
  • POST /hitl/tasks/{hitl_task_id}/complete: Submit decision/input for an HITL task.
  • GET /agents: List available agents in registry/marketplace.
  • POST /agents: Register a new agent.
  • GET /marketplace: Browse marketplace items.

Multi-Modal Agent APIs

  • POST /agents/vision: Process image/video data with vision agents.
  • POST /agents/audio: Process audio data with speech/sound agents.
  • POST /agents/sensor: Process IoT sensor data with specialized agents.
  • POST /agents/ar-vr: Interact with AR/VR environments.

Edge Computing APIs

  • GET /edge/devices: List registered edge devices.
  • POST /edge/deploy: Deploy workflows to edge devices.
  • GET /edge/status: Get status of edge deployments.
  • POST /edge/sync: Synchronize data from edge devices.

Federated Collaboration APIs

  • GET /federation/organizations: List federated organizations.
  • POST /federation/workflows: Create cross-organization workflows.
  • GET /federation/compute: Initiate secure multi-party computation.
  • POST /federation/learning: Manage federated learning tasks.

Marketplace & Monetization APIs

  • GET /marketplace/subscriptions: List user subscriptions.
  • POST /marketplace/purchase: Purchase marketplace items.
  • GET /marketplace/earnings: View creator earnings.
  • POST /marketplace/payouts: Request creator payouts.

AI-Driven Platform APIs

  • GET /ai/optimize: Get workflow optimization suggestions.
  • GET /ai/anomalies: Detect anomalies in workflow execution.
  • POST /ai/self-heal: Trigger self-healing for failing workflows.
  • GET /ai/analytics: Get AI-driven performance analytics.

6. Data Models (Tables)

  • users: id, username, hashed_password, email, roles, etc.
  • workflows: id, name, description, creator_id, created_at, updated_at, definition_json (from React Flow), orchestrator_workflow_id (reference).
  • workflow_runs: id, workflow_id, status, start_time, end_time, inputs_json, trigger_info, orchestrator_run_id.
  • task_instances: id, workflow_run_id, task_node_id (from visual graph), status, start_time, end_time, inputs_json, outputs_json, logs_reference, attempt_count, orchestrator_activity_id.
  • hitl_tasks: id, workflow_run_id, task_instance_id, status (pending, completed), assignee_ref, instructions, context_json, decision_json, completed_at, escalation_path, comms_integration.
  • secrets_metadata: id, name, description, secret_manager_ref, associated_entity (user/workflow). (Actual secrets stored in Vault/etc).
  • agents_registry: id, name, type, config_json, owner_id, marketplace_visibility, version, metadata, supported_modalities, etc.
  • marketplace_items: id, type (agent/template/plugin), description, owner_id, visibility, downloads, ratings, pricing_model, subscription_details, etc.

Multi-Modal Agent Tables

  • vision_agents: id, agent_id, supported_formats, model_details, capabilities, performance_metrics, etc.
  • audio_agents: id, agent_id, supported_formats, language_support, capabilities, performance_metrics, etc.
  • sensor_agents: id, agent_id, supported_protocols, sensor_types, data_formats, capabilities, etc.
  • ar_vr_agents: id, agent_id, supported_platforms, interaction_modes, rendering_capabilities, etc.

Edge Computing Tables

  • edge_devices: id, name, device_type, capabilities, status, last_sync, resource_constraints, etc.
  • edge_deployments: id, device_id, workflow_id, deployment_status, version, sync_status, etc.
  • edge_telemetry: id, device_id, metrics_json, collected_at, synced_at, etc.

Federated Collaboration Tables

  • federated_organizations: id, name, api_endpoint, public_key, trust_level, capabilities, etc.
  • federated_workflows: id, name, participating_orgs, access_controls, workflow_definition, etc.
  • secure_computations: id, computation_type, participants, status, result_access, etc.
  • federated_learning_tasks: id, model_type, participants, aggregation_method, status, etc.

Marketplace & Monetization Tables

  • subscriptions: id, user_id, item_id, plan_type, start_date, end_date, status, payment_details, etc.
  • transactions: id, user_id, item_id, amount, currency, status, transaction_date, etc.
  • creator_earnings: id, creator_id, item_id, amount, currency, period, status, etc.
  • payouts: id, creator_id, amount, currency, status, payout_date, payment_details, etc.

AI-Driven Platform Tables

  • workflow_optimizations: id, workflow_id, suggestions_json, applied_status, performance_impact, etc.
  • anomaly_detections: id, workflow_id, run_id, anomaly_type, severity, detected_at, resolution_status, etc.
  • self_healing_actions: id, workflow_id, run_id, action_type, triggered_at, success_status, etc.
  • performance_analytics: id, entity_id, entity_type, metrics_json, period_start, period_end, etc.

7. Security & Compliance

  • JWT/OAuth2, SSO, SAML
  • Audit logging, encrypted secrets
  • GDPR/SOC2/HIPAA/PCI-DSS controls
  • Zero-trust architecture with strong isolation for agents and data
  • Secure multi-party computation for privacy-preserving collaboration
  • Homomorphic encryption for secure data processing
  • Zero-knowledge proofs for verification without revealing sensitive data
  • Industry-specific compliance modules for healthcare, finance, etc.
  • Advanced audit and forensics capabilities
  • Secure enclaves for trusted execution environments

8. Non-Functional Requirements (Technical Implementation)

  • Scalability: Temporal architecture supports horizontal scaling of workers. Backend API should be stateless for scaling. Database requires appropriate indexing. Initial target: Handle hundreds of concurrent workflows, thousands of agent executions, and multi-tenant isolation. Edge deployment framework scales to thousands of distributed devices.
  • Reliability: Leverage Temporal's guarantees for activity retries and workflow persistence. Implement proper error handling in backend and activities. Support offline operation and resilient mesh networking for edge deployments. AI-driven self-healing for automated recovery from failures.
  • Security: Secure JWT handling, HTTPS enforced, input validation (Pydantic in FastAPI), secure secret injection into agent runtimes (via Temporal/adapter layer, not direct env vars if possible), dependency scanning, SSO/SAML, audit logging, compliance (GDPR, SOC2, HIPAA, PCI-DSS), zero-trust execution, secure multi-party computation, homomorphic encryption, and secure enclaves.
  • Maintainability: Use clear coding standards, type hinting (Python/TypeScript), modular design, automated testing (unit, integration), proper documentation. AI-assisted code generation and documentation. Comprehensive CI/CD pipelines for all components including edge deployments.
  • Performance: API response times < 500ms for typical requests. Workflow step latency depends on agent execution time, but orchestration overhead should be minimal. Optimize database queries. Edge-optimized components for resource-constrained environments. AI-driven performance optimization and predictive scaling.
  • Extensibility: Support plugins, marketplace, and open APIs for community-driven growth. Comprehensive SDK for multi-modal agent development. Edge device integration framework. Federated collaboration APIs.
  • AI-Driven UX: Enable AI-assisted workflow suggestions, auto-completion, and intelligent diagnostics. Adaptive interfaces based on user skill level and preferences. Multi-modal interaction support including voice, vision, and AR/VR.
  • Multi-Modal Support: Process and orchestrate text, vision, audio, sensor data, and AR/VR interactions with specialized agents and visualization tools.
  • Edge Computing: Support resource-constrained environments with offline operation, efficient synchronization, and mesh networking capabilities.
  • Federated Collaboration: Enable secure cross-organization workflows with privacy-preserving computation, federated learning, and zero-knowledge verification.

This TRD provides the technical blueprint for v1.0 and beyond, focusing on establishing a robust foundation using Temporal, FastAPI, React, Docker, A2A protocol, LLMOps, advanced observability, extensibility, and compliance, while benchmarking against leading platforms and open standards. The expanded scope includes multi-modal agent support, edge computing capabilities, federated collaboration, AI-driven self-optimization, and comprehensive marketplace monetization, positioning the platform as the definitive solution for AI agent orchestration across industries, modalities, and deployment environments.