> ## Documentation Index > Fetch the complete documentation index at: https://docs.nevermined.app/llms.txt > Use this file to discover all available pages before exploring further. # Publishing Static Resources > Publish and manage static resources with access control This guide explains how to publish static resources (files, datasets) using the Nevermined Payments Python SDK. ## Overview Static resources are files or datasets that users can access through payment plans. Unlike AI agents that process requests, static resources are downloadable content such as: * Documents (PDFs, reports) * Datasets (CSV, JSON files) * Media files (images, videos) * Software packages ## Register Static Resource Agents Static resources are registered as a special type of agent with file endpoints: ```python theme={null} from payments_py.common.types import AgentMetadata, AgentAPIAttributes # Resource metadata resource_metadata = AgentMetadata( name="Premium Dataset Collection", description="A curated collection of ML training datasets", tags=["dataset", "machine-learning", "premium"] ) # Static file endpoints resource_api = AgentAPIAttributes( endpoints=[ {"GET": "https://storage.example.com/datasets/training-data.csv"}, {"GET": "https://storage.example.com/datasets/validation-data.csv"}, {"GET": "https://storage.example.com/datasets/test-data.csv"} ], agent_definition_url="https://storage.example.com/datasets/manifest.json" ) # Register with a payment plan result = payments.agents.register_agent( agent_metadata=resource_metadata, agent_api=resource_api, payment_plans=[plan_id] ) print(f"Resource ID: {result['agentId']}") ``` ## Using Wildcards for Multiple Files When you have multiple files that follow a pattern, you can use wildcard URLs: ```python theme={null} # Single wildcard for dynamic file names resource_api = AgentAPIAttributes( endpoints=[ # Matches: /files/report-001.pdf, /files/report-2024.pdf, etc. {"GET": "https://storage.example.com/files/report-*.pdf"}, # Matches: /data/dataset_v1.csv, /data/dataset_v2.csv, etc. {"GET": "https://storage.example.com/data/dataset_*.csv"} ], agent_definition_url="https://storage.example.com/manifest.json" ) ``` ### Wildcard Patterns | Pattern | Matches | | -------------- | ------------------------------- | | `*.pdf` | Any PDF file | | `report-*.pdf` | report-001.pdf, report-2024.pdf | | `data/*.csv` | All CSV files in data folder | | `v*/data.json` | v1/data.json, v2/data.json | ## Complete Example: Dataset Publishing ```python theme={null} from payments_py import Payments, PaymentOptions from payments_py.common.types import AgentMetadata, AgentAPIAttributes, PlanMetadata from payments_py.plans import get_erc20_price_config, get_fixed_credits_config # Initialize payments = Payments.get_instance( PaymentOptions(nvm_api_key="nvm:your-key", environment="sandbox") ) ERC20_TOKEN = "0x75faf114eafb1BDbe2F0316DF893fd58CE46AA4d" builder_address = payments.account_address # 1. Create a plan for the dataset plan_result = payments.plans.register_credits_plan( plan_metadata=PlanMetadata( name="Dataset Access Plan", description="Access to premium ML datasets" ), price_config=get_erc20_price_config(100, ERC20_TOKEN, builder_address), credits_config=get_fixed_credits_config(10) # 10 downloads ) plan_id = plan_result['planId'] # 2. Register the dataset resource dataset_result = payments.agents.register_agent( agent_metadata=AgentMetadata( name="ML Training Datasets", description="High-quality labeled datasets for machine learning", tags=["dataset", "ml", "training", "labeled"] ), agent_api=AgentAPIAttributes( endpoints=[ {"GET": "https://storage.example.com/datasets/images/*.zip"}, {"GET": "https://storage.example.com/datasets/text/*.jsonl"}, {"GET": "https://storage.example.com/datasets/audio/*.tar.gz"} ], agent_definition_url="https://storage.example.com/datasets/catalog.json" ), payment_plans=[plan_id] ) print(f"Dataset Resource ID: {dataset_result['agentId']}") ``` ## Example: Document Repository ```python theme={null} # Publishing a document repository doc_result = payments.agents.register_agent( agent_metadata=AgentMetadata( name="Research Papers Collection", description="Exclusive research papers and technical reports", tags=["research", "papers", "technical"] ), agent_api=AgentAPIAttributes( endpoints=[ # Specific documents {"GET": "https://docs.example.com/papers/whitepaper-2024.pdf"}, {"GET": "https://docs.example.com/papers/research-findings.pdf"}, # Wildcard for quarterly reports {"GET": "https://docs.example.com/reports/q*-report.pdf"}, # All supplementary materials {"GET": "https://docs.example.com/supplementary/*.zip"} ], agent_definition_url="https://docs.example.com/index.json" ), payment_plans=[plan_id] ) ``` ## Example: Software Distribution ```python theme={null} # Publishing software packages software_result = payments.agents.register_agent( agent_metadata=AgentMetadata( name="Premium Software Tools", description="Professional development tools and utilities", tags=["software", "tools", "professional"] ), agent_api=AgentAPIAttributes( endpoints=[ # Version-specific downloads {"GET": "https://releases.example.com/tool/v*/tool-*.zip"}, # Platform-specific binaries {"GET": "https://releases.example.com/tool/latest/tool-linux-*.tar.gz"}, {"GET": "https://releases.example.com/tool/latest/tool-macos-*.dmg"}, {"GET": "https://releases.example.com/tool/latest/tool-windows-*.exe"}, # Documentation {"GET": "https://releases.example.com/tool/docs/*.pdf"} ], agent_definition_url="https://releases.example.com/tool/manifest.json" ), payment_plans=[plan_id] ) ``` ## Accessing Static Resources For details on how subscribers access static resources using x402 access tokens, see [Request Validation](/docs/api-reference/python/validation-module). ## Best Practices 1. **Use descriptive metadata**: Include clear names, descriptions, and tags for discoverability 2. **Organize files logically**: Use consistent URL patterns that work well with wildcards 3. **Version your resources**: Include version numbers in URLs for easy updates 4. **Provide a manifest**: Create a JSON manifest at the `agent_definition_url` listing all available files 5. **Set appropriate credits**: Consider the value and size of files when setting credit costs ## Next Steps Order plans and check balances Access resources with tokens