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LICENSE IN LICENSE.md","description":"Easier to use Agentic Framework for multi-turn LLM flows.","maintainers":[{"name":"picoflow","email":"dev@picoflow.io"}],"readme":"# PicoFlow Core (`@picoflow/core`)\n\nPicoFlow is a TypeScript framework for durable, multi-turn LLM workflows. It\nmodels an application as named `Flow` and `Step` classes: a flow declares the\navailable stages and default model, while each step owns its prompt, typed\ntools, state, and conversation memory. PicoFlow runs the model/tool loop,\npersists one versioned session document, and resumes the active step on a\nlater request.\n\nIt is designed for assistants with explicit stages and consequential tools—for\nexample intake, search, validation, comparison, and confirmation—not merely a\nsingle stateless prompt-and-response call.\n\n## Install\n\n```bash\nnpm install @picoflow/core\n# or\nyarn add @picoflow/core\n```\n\n`@picoflow/core` requires Node.js 22.5 or later. It publishes both ESM and\nCommonJS entry points; TypeScript ESM applications should use\n`\"module\": \"NodeNext\"`, `\"moduleResolution\": \"NodeNext\"`, and explicit\n`.js` extensions in relative imports. To use the legacy `@Tool` and `@Tools`\nmethod decorators, enable `experimentalDecorators` and\n`emitDecoratorMetadata` in `tsconfig.json`.\n\nPicoFlow is license-gated at runtime. For a free evaluation key, including\nenterprise prototyping, request one through the [PicoFlow Evaluation and\nCommercial License](https://www.picoflow.io/license/). Then set `PICOFLOW_KEY`\nin the service environment before a flow reaches its first model or tool turn.\n\n## The programming model\n\n```ts\nimport {\n  Flow,\n  Step,\n  TerminateSessionStep,\n  direct,\n  go,\n  stay,\n} from \"@picoflow/core\";\n\nclass SupportFlow extends Flow {\n  protected configModel() {\n    return {\n      provider: \"openai\",\n      name: \"gpt-4o-mini\",\n      params: { temperature: 0.2 },\n      retryAttempts: 3,\n    } as const;\n  }\n\n  protected defineSteps(): Step[] {\n    return [\n      new CollectEmailStep(this).useMemory(\"support\"),\n      new TerminateSessionStep(this).useMemory(\"end\"),\n    ];\n  }\n}\n```\n\nThe first step returned by `defineSteps()` is the initial step unless the flow\noverrides `initialStep()`. Every possible destination must be registered in\nthat method. A conventional step provides a prompt, tool definitions, and\ndecorated handlers; the handler validates business input and returns an\nexplicit outcome:\n\n```ts\nreturn go(TerminateSessionStep);       // activate another registered step\nreturn stay(\"Explain the correction\"); // remain in this step\nreturn direct({ status: \"ok\" });       // return without another model call\nreturn finish(\"The conversation is complete.\"); // return and complete the session\n```\n\nThe model may choose a declared tool, but it does not choose the route. Your\ntool or application code returns `go(...)`, `stay(...)`, `direct(...)`, or `finish(...)`.\nThat keeps validation and control flow in the same place.\n\n## What PicoFlow provides\n\n- A shared model and tool-calling runtime with explicit flow and per-step model\n  policy.\n- Provider adapters registered at application bootstrap; built-in adapters\n  cover OpenAI, experimental local Codex OAuth (`openai-auth`), Azure OpenAI,\n  Google, Anthropic, DeepSeek, Moonshot, Z.AI, Ollama, and OpenRouter. Custom\n  adapters support other compatible endpoints.\n- One versioned session document containing the active step, per-step JSON\n  state, named memory, context, execution records, errors, and token totals.\n- Bundled memory, SQLite, MongoDB, and Azure Cosmos DB stores. Durable stores\n  use revision compare-and-swap; the engine also serializes same-session turns\n  within a process.\n- Flow-owned restore policy, scoped memory, nested/sequential/parallel step\n  composition, structured outputs, and direct text, JSON, or file responses.\n- Typed `DecisionStep` routing, classification, and review. This release uses\n  Jev AI through TypeSafe as its initial decision provider.\n\nPicoFlow does not impose an HTTP framework. Create a `FlowEngine`, register\nyour flows and provider adapters, then call `engine.run(...)` from the web\nframework or worker you already use.\n\n## Typed decisions with Jev AI\n\nThis release adds `DecisionStep` for fast, typed non-generative decisions such\nas request routing, eligibility classification, and response review. It uses\nJev AI through TypeSafe as the initial provider and returns typed `Choice`,\n`Score`, or `Noul` evidence to application code. Use ordinary `Step` classes\nfor conversational collection and `LogicStep` or application code for policy,\nvalidation, and irreversible actions.\n\nRegister the decision provider alongside chat-model providers when creating the\nengine, then configure decision policy in `Flow.configDecision()` or override\nit with `.useDecision()` on a particular step. PicoFlow keeps the public\n`DecisionStep` API provider-neutral, so applications retain their question\nschemas, thresholds, routing, fallbacks, and side-effect boundaries if another\ndecision provider is introduced later. See the\n[DecisionStep reference](https://www.picoflow.io/docs/reference/decision-step/)\nfor setup and examples.\n\n## Model failure handling\n\n`Step.shouldRetryLlmError()` and `Flow.shouldRetryLlmError()` can decide\nwhether a thrown model invocation error uses another configured attempt.\nReturning `undefined` delegates from Step to Flow to the framework default.\n`Step.checkResponse()` remains the hook for completed candidates: `true`\nretries and `false` accepts.\n\nAfter attempts end, `Step.onLlmError()` may return a safe message, route to\nanother Step, or use `retryWithModel({ provider, name, params })` for a\ntemporary alternate model on the same Step. Returning `null` delegates to\n`Flow.onLlmError()`. The context distinguishes invocation errors, empty\nresponses, and responses rejected by `checkResponse()`. Provider refusals go\nto `Step.onLlmBlocked()` first, then `Flow.onLlmBlocked()` if the Step returns\n`null`; caller cancellation always propagates. These hooks do not repeat\ncompleted tool calls.\n\n## Start here\n\n- [Installation and runtime requirements](https://www.picoflow.io/docs/get-started/installation/)\n- [Build your first flow](https://www.picoflow.io/docs/get-started/first-flow/)\n- [Flow lifecycle and session restoration](https://www.picoflow.io/docs/concepts/flow-lifecycle/)\n- [Routing outcomes](https://www.picoflow.io/docs/concepts/routing/)\n- [Models and providers](https://www.picoflow.io/docs/concepts/models-and-providers/)\n- [Session stores](https://www.picoflow.io/docs/reference/session-stores/)\n- [PicoFlow versus a direct LangGraph implementation](https://www.picoflow.io/docs/get-started/why-picoflow/)\n- [Working demo application](https://github.com/picoflowio/pico-demo)\n\n## License\n\nPicoFlow is proprietary and commercially licensed. It is not released under an\nopen-source license. Internal, non-production evaluation is free with a license\nkey, including enterprise prototyping; production\nuse requires commercial terms. See the [PicoFlow Evaluation and Commercial License](https://www.picoflow.io/license/)\nfor the current terms.\n\nCopyright (c) 2026 picoflow.io\n","readmeFilename":"README.md"}