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primitives for NebulaOS (Agent, Workflow, Providers)","maintainers":[{"name":"starya","email":"services@starya.ai"}],"readme":"# @starya/nebulaos-core\n\nThe core of NebulaOS for building AI Agents and complex Workflows. This package provides the essential primitives for orchestration, state management, and model abstraction.\n\n## Installation\n\n```bash\npnpm add @starya/nebulaos-core\n```\n\n---\n\n## โœจ Features Overview\n\n### ๐Ÿค– Agent System\n- โœ… **Multi-Step Reasoning** - Automatic tool calling loops with configurable max steps\n- โœ… **Streaming Support** - Real-time token streaming with `executeStream()`\n- โœ… **Tool Calling** - Function calling with Zod schema validation\n- โœ… **Parallel Tool Execution** - Execute multiple tools simultaneously\n- โœ… **Structured Outputs** - JSON mode with schema validation\n- โœ… **Memory Management** - Pluggable memory implementations (InMemory, Redis, etc.)\n- โœ… **Dynamic Instructions** - Template interpolation with `{{variables}}` and per-execution context\n- โœ… **Request/Response Interceptors** - Middleware for RAG, sanitization, etc.\n- โœ… **Multimodal Support** - Text + Images (via ContentPart[])\n- โœ… **Execution Metadata** - Attach custom key-value pairs for tracking and filtering\n\n### ๐Ÿ”„ Workflow Orchestration\n- โœ… **Fluent API** - Declarative workflow definition (`.start().step().finish()`)\n- โœ… **Branching & Parallel** - Conditional paths and concurrent execution\n- โœ… **State Persistence** - Save/resume workflow state (requires state store)\n- โœ… **Retry Policies** - Exponential/Linear backoff with configurable attempts\n- โœ… **Input/Output Validation** - Zod schema validation at boundaries\n- โœ… **Queue Integration** - Async workflow execution (requires queue adapter)\n- โœ… **Event-Driven** - Lifecycle events for monitoring and logging\n\n### ๐Ÿ“Š Observability & Tracing\n- โœ… **Distributed Tracing** - Automatic trace/span propagation via AsyncLocalStorage\n- โœ… **Event System** - Rich lifecycle events (`execution:start`, `llm:call`, `tool:result`, etc.)\n- โœ… **Correlation IDs** - Track requests across nested operations\n- โœ… **Structured Logging** - Beautiful console logs with ANSI colors and metadata trees\n- โœ… **Log Levels** - Configurable (debug, info, warn, error)\n- โœ… **Custom Loggers** - Implement `ILogger` for Datadog, CloudWatch, etc.\n- โœ… **PII Masking** - GDPR/LGPD compliance with pluggable masking\n\n### ๐Ÿงช Testing & Quality\n- โœ… **Provider Compliance Suite** - Reusable test suite for model providers\n- โœ… **Mock Implementations** - MockProvider, MockStateStore for unit tests\n- โœ… **Integration Tests** - Live API tests with real providers\n- โœ… **Type Safety** - Full TypeScript support with strict typing\n- โœ… **Test Coverage** - Comprehensive unit and integration tests\n\n### ๐Ÿ”Œ Provider System\n- โœ… **Provider Abstraction** - IModel interface for any LLM (OpenAI, Anthropic, etc.)\n- โœ… **Token Usage Tracking** - Automatic accumulation across multi-step flows\n- โœ… **Streaming Protocol** - Unified chunk types (content_delta, tool_call_start, etc.)\n- โœ… **Error Handling** - Graceful degradation and retry logic\n\n---\n\n## ๐Ÿ†• Recent Updates\n\n### v0.0.2 - Execution Metadata\n- **Execution Metadata**: Attach custom key-value pairs to executions via `execute({ metadata: {...} })`\n- **UI Filtering**: Filter executions by metadata key/value in the NebulaOS Console\n- **API Support**: Query executions with `?metadataKey=...&metadataValue=...`\n\n### v0.0.1 - Distributed Tracing & Stream Parity\n- **Distributed Tracing**: Automatic trace/span propagation across Agent โ†’ Workflow โ†’ Tool chains\n- **executeStream() Parity**: Full feature parity with execute() including token tracking, events, and max steps fallback\n- **Enhanced Logging**: Color-coded terminal output with hierarchical metadata display\n- **Response Interceptors**: Now run only on final responses (not intermediate tool calls)\n- **Test Coverage**: Expanded to 22 unit tests + 7 integration tests\n\n---\n\n## Core Components\n\n### Delivering tool-step text immediately\n\nFor separate text messages during a synchronous execution, pass an awaited callback:\n\n```typescript\nconst result = await agent.execute({\n input: \"Schedule my appointment\",\n onIntermediateResponse: async (text) => {\n await sendMessage(text);\n },\n});\nif (result.content) await sendMessage(result.content);\n```\n\nEach complete tool-step text passes output processors before delivery. The SDK\nawaits delivery before executing that step's tools or making another LLM call.\nRejected text is not sent; retry also postpones the rejected step's tools.\nThe final answer is returned normally, without repeating intermediate messages.\nJSON mode ignores this callback; `executeStream()` is unchanged.\n\nMessages already sent cannot be recalled if a later step fails. SDK memory is\nstill persisted atomically at successful completion, so consumers should record\nintermediate deliveries in the callback. Without the callback, intermediate text\nis accumulated and validated together with the final text before returning.\n\n### 1. Agent (`Agent`)\n\nThe main class that manages the lifecycle of AI interaction.\n\n### Key Features\n* **Memory-First**: Every agent requires a memory implementation (e.g., `InMemory`) to maintain context.\n* **Interceptors**: Middleware to modify requests and responses.\n * **Request Interceptors**: Run before each LLM call. Useful for context injection (RAG).\n * **Response Interceptors**: Run **only on the final response** (or when there are no tool calls), ideal for output sanitization and formatting.\n* **Streaming**: Native support for text and tool call streaming.\n* **Observability**: Integrated event-based logging system with PII Masking support (GDPR/LGPD).\n\n### Complete Example\n\n```typescript\nimport { Agent, InMemory, Tool, z } from \"@starya/nebulaos-core\";\nimport { OpenAI } from \"@starya/nebulaos-openai\";\n\n// 1. Tools\nconst calculator = new Tool({\n id: \"calculator\",\n description: \"Adds two numbers\",\n inputSchema: z.object({ a: z.number(), b: z.number() }),\n handler: async (ctx, input) => ({ result: input.a + input.b })\n});\n\n// 2. Agent\nconst agent = new Agent({\n name: \"financial-assistant\",\n model: new OpenAI({\n apiKey: process.env.OPENAI_API_KEY!,\n model: \"gpt-4o\"\n }),\n memory: new InMemory(),\n instructions: \"You help with financial calculations.\",\n tools: [calculator],\n logLevel: \"info\", // Detailed console logs\n interceptors: {\n response: [\n async (res) => {\n // Format final output to uppercase (example)\n if (res.content) res.content = res.content.toUpperCase();\n return res;\n }\n ]\n }\n});\n\n// 3. Execution\nawait agent.addMessage({ role: \"user\", content: \"How much is 10 + 20?\" });\nconst result = await agent.execute({\n metadata: { userId: \"user-123\", channel: \"api\" } // Optional: attach tracking metadata\n});\nconsole.log(result.content);\n```\n\n---\n\n## ๐Ÿ“ Dynamic Instructions\n\nInstructions support template interpolation with `{{variable}}` syntax. Variables can be provided at config time, runtime, or during execution.\n\n### Basic Usage\n\n```typescript\nconst agent = new Agent({\n id: \"support-agent\",\n name: \"support-agent\",\n model: provider,\n memory: new InMemory(),\n instructions: `Voce e {{persona}}. Cliente: {{client.name}}. Plano: {{client.plan}}.`\n});\n\nawait agent.addMessage({ role: \"user\", content: \"Oi\" });\nawait agent.execute({\n variables: {\n persona: \"Veri\",\n client: { name: \"Joao\", plan: \"Premium\" }\n }\n});\n// System prompt: \"Voce e Veri. Cliente: Joao. Plano: Premium.\"\n```\n\n### InstructionConfig with Defaults\n\nUse `{ template, defaults }` format for default values that can be overridden:\n\n```typescript\nconst agent = new Agent({\n id: \"assistant\",\n name: \"assistant\",\n model: provider,\n memory: new InMemory(),\n instructions: {\n template: `Voce e {{persona}}. Modo: {{mode}}.`,\n defaults: { persona: \"Assistente\", mode: \"normal\" }\n }\n});\n\n// Uses defaults\nawait agent.execute();\n// System prompt: \"Voce e Assistente. Modo: normal.\"\n\n// Override specific variables\nawait agent.execute({ variables: { mode: \"urgente\" } });\n// System prompt: \"Voce e Assistente. Modo: urgente.\"\n```\n\n### Loading from Files\n\nUse `Instruction.fromFileSync()` or `Instruction.fromFile()` for external templates:\n\n```typescript\nimport { Instruction } from \"@nebulaos/core\";\n\nconst agent = new Agent({\n id: \"agent\",\n name: \"agent\",\n model: provider,\n memory: new InMemory(),\n instructions: {\n template: Instruction.fromFileSync(\"./prompts/agent.md\"),\n defaults: { language: \"pt-BR\" }\n }\n});\n```\n\n### Runtime Variables (Skills)\n\nSkills can modify instructions during execution using `setVariable()`:\n\n```typescript\n// Inside a skill or tool\nagent.setVariable(\"mode\", \"urgente\");\nagent.setVariables({ client: { name: \"Maria\" } });\n\n// Read variables\nconst mode = agent.getVariable(\"mode\"); // \"urgente\"\nconst all = agent.getVariables(); // { mode: \"urgente\", client: { ... } }\n\n// Clear all runtime variables\nagent.clearVariables();\n```\n\n### Variable Priority\n\nVariables are merged with the following priority (higher overrides lower):\n\n1. **Config defaults** (`instructions.defaults`)\n2. **Runtime variables** (`setVariable()` / `setVariables()`)\n3. **Execution variables** (`execute({ variables })`)\n\n---\n\n## ๐Ÿท๏ธ Execution Metadata\n\nAttach custom metadata to agent executions for tracking, filtering, and debugging. Metadata is persisted with the execution and can be used to search/filter executions in the UI.\n\n### Basic Usage\n\n```typescript\nconst result = await agent.execute(\"Process this order\", {\n metadata: {\n environment: \"production\",\n userId: \"user-123\",\n orderId: \"ORD-456\",\n channel: \"whatsapp\"\n }\n});\n```\n\n### Use Cases\n\n| Use Case | Example Metadata |\n|----------|------------------|\n| **Multi-tenant** | `{ tenantId: \"acme-corp\", workspaceId: \"ws-1\" }` |\n| **Request tracking** | `{ requestId: \"req-abc\", sessionId: \"sess-xyz\" }` |\n| **A/B testing** | `{ experiment: \"new-prompt-v2\", variant: \"B\" }` |\n| **Environment** | `{ environment: \"staging\", region: \"us-east-1\" }` |\n| **Business context** | `{ customerId: \"C-123\", orderId: \"ORD-456\" }` |\n\n### With Streaming\n\nMetadata works the same way with `executeStream()`:\n\n```typescript\nconst stream = agent.executeStream({\n metadata: { streamId: \"live-chat-001\", channel: \"widget\" }\n});\n\nfor await (const chunk of stream) {\n // Process chunks...\n}\n```\n\n### Filtering in the UI\n\nOnce metadata is attached, you can filter executions in the NebulaOS Console:\n\n- **By key**: Find all executions with `environment` key\n- **By key-value**: Find executions where `environment = \"production\"`\n\n### API Filtering\n\n```bash\n# Filter by metadata key and value\nGET /execution?metadataKey=environment&metadataValue=production\n\n# Filter by key only (check if key exists)\nGET /execution?metadataKey=orderId\n```\n\n### Best Practices\n\n1. **Use consistent keys** across your application for easier filtering\n2. **Keep metadata small** - it's stored as JSONB, avoid large objects\n3. **Use strings for values** when possible - easier to filter\n4. **Don't store sensitive data** - metadata may appear in logs and UI\n\n### Supported Value Types\n\n| Type | Behavior |\n|------|----------|\n| `string`, `number`, `boolean` | Converted directly |\n| `null` | Converted to `\"null\"` |\n| `undefined` | Placeholder kept as-is (`{{key}}`) |\n| `object`, `array` | JSON stringified |\n\n### Nested Paths\n\nAccess nested object properties with dot notation:\n\n```typescript\ninstructions: \"Cliente: {{client.profile.name}}, Empresa: {{client.company.name}}\"\n\n// With variables:\n{\n client: {\n profile: { name: \"Joao\" },\n company: { name: \"Acme Corp\" }\n }\n}\n// Result: \"Cliente: Joao, Empresa: Acme Corp\"\n```\n\n---\n\n## ๐Ÿ”„ Workflow (`Workflow`)\n\nOrchestrator for long-running and complex processes, supporting persistence, retries, and validation.\n\n### Features\n* **Fluent API**: Declarative definition (`.start().step().branch().finish()`).\n* **State Persistence**: Saves the state of each step (requires `stateStore`).\n* **Resilience**: Configurable Retry Policies (Exponential, Linear).\n* **Type-Safe**: Input and output validation with Zod.\n\n### Workflow Example\n\n```typescript\nimport { Workflow, MockStateStore } from \"@starya/nebulaos-core\";\nimport { z } from \"zod\";\n\nconst workflow = new Workflow({\n id: \"order-processing\",\n stateStore: new MockStateStore(), // Or real implementation (Redis/Postgres)\n retryPolicy: {\n maxAttempts: 3,\n backoff: \"exponential\",\n initialDelay: 1000\n }\n})\n.start(async ({ input }) => {\n console.log(\"Validating order\", input);\n return input;\n})\n.step(\"payment\", async ({ input }) => {\n // Payment logic\n return { status: \"paid\", id: input.id };\n})\n.finish(async ({ input }) => {\n return { message: `Order ${input.id} processed successfully` };\n});\n\n// Execution\nconst result = await workflow.run({ id: 123, total: 500 });\n```\n\n---\n\n## ๐Ÿ›ก๏ธ Logging & Observability\n\nThe Core emits rich events during execution (`execution:start`, `llm:call`, `tool:result`).\n\n### Configuration\nThe default logger (`ConsoleLogger`) can be configured via `logLevel`. For production, you can implement the `ILogger` interface to send logs to Datadog, CloudWatch, etc.\n\n### PII Masking (Privacy)\nProtect sensitive data in logs by configuring a `piiMasker`.\n\n```typescript\nconst agent = new Agent({\n // ...\n piiMasker: {\n mask: (text) => text.replace(/\\d{3}\\.\\d{3}\\.\\d{3}-\\d{2}/g, \"***\") // Example mask\n }\n});\n```\n\n---\n\n## ๐Ÿงช Testing & Compliance\n\n### Package Tests\n```bash\npnpm test\n```\n\n### Provider Compliance Suite\nIf you are creating a new Provider (e.g., Anthropic), use the compliance suite to ensure full compatibility.\n\n```typescript\nimport { runProviderComplianceTests } from \"@starya/nebulaos-core/test-utils\";\n\nrunProviderComplianceTests(() => new MyNewProvider(...), { runLiveTests: true });\n```\n","readmeFilename":"README.md"}