Base Structure

{
  name: "flow_name (alphanumeric_underscore, unique identifier, e.g., 'document_analysis_flow')",
  version: "semantic_version (semver format, e.g., '1.0.0', '2.1.3-beta')",
  description: "flow_description (detailed explanation of what this flow accomplishes)",
  author: "author_contact (email or identifier, e.g., 'team@company.com')",
  variables: [
    {
      id: "variable_identifier (unique within flow, e.g., 'user_query', 'max_results')",
      default: "default_value (optional, any type matching the variable type)",
      type: "variable_type (enum: 'string'|'number'|'boolean'|'array'|'object'|'file')"
    }
  ],
  input: ["input_variable_names (array of variable IDs required at runtime)"],
  output: ["output_variable_names (array of variable IDs to return after execution)"],
  nodes: [
    "processing_nodes (array of FlowNode objects, see node documentation)"
  ]
}
 

import { FlowExecutor } from 'openflow-nodejs-sdk';
 
const executor = new FlowExecutor({
  concurrency: {
    global_limit: "max_concurrent_flows (integer, 1-50, default: 3)"
  },
  providers: {
    llm: {
      "provider_name (e.g., 'grok', 'openai', 'anthropic')": {
        apiKey: "api_key_credential (environment variable or direct key)",
        rate_limit: {
          concurrent_limit: "max_concurrent_requests (integer, 1-100, default: 3)",
          rps: "requests_per_second (integer, 1-1000, default: 8)",
          retry_strategy: {
            max_retries: "max_retry_attempts (integer, 0-10, default: 3)",
            backoff: "backoff_type (enum: 'exponential'|'linear'|'fixed')",
            base_delay: "base_delay_ms (integer, 100-10000, default: 1000)"
          }
        }
      }
    },
    vectorDB: {
      "vector_provider_name (e.g., 'pinecone', 'chroma', 'weaviate')": {
        provider: "provider_identifier (matches the key name)",
        index_name: "vector_index_name (provider-specific database/collection name)",
        apiKey: "vector_db_api_key (authentication credential)",
        rate_limit: {
          concurrent_limit: "max_concurrent_vector_operations (integer, 1-100, default: 5)",
          rps: "vector_requests_per_second (integer, 1-1000, default: 10)",
          retry_strategy: "retry_config (RetryStrategy object or null to disable)"
        }
      }
    },
    embeddings: {
      "embedding_provider_name (e.g., 'openai', 'cohere', 'huggingface')": {
        apiKey: "embedding_api_key (authentication credential)",
        rate_limit: {
          concurrent_limit: "max_concurrent_embedding_requests (integer, 1-100, default: 10)",
          rps: "embedding_requests_per_second (integer, 1-1000, default: 20)",
          retry_strategy: {
            max_retries: "embedding_max_retries (integer, 0-10, default: 2)",
            backoff: "embedding_backoff_strategy (enum: 'linear'|'exponential'|'fixed')",
            base_delay: "embedding_base_delay_ms (integer, 100-5000, default: 500)"
          }
        }
      }
    }
  },
  timeout: "global_timeout_ms (integer, 5000-300000, default: 30000)",
  logLevel: "logging_level (enum: 'debug'|'info'|'warn'|'error', default: 'warn')",
  tempDir: "temporary_directory_path (string, relative or absolute path, default: './of_tmp')"
});