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agents: tools, adapter, integrator, and investigator.","maintainers":[{"name":"zachagarrett","email":"zach@very.coffee"}],"readme":"# @khoralabs/memories-agents\n\nMemory agents built on `@khoralabs/memories-node` and [`@khoralabs/agent-capabilities`](https://github.com/khoralabs/agent-capabilities). There is no package root export — import the surface you need.\n\n## Entrypoints\n\n| Export | Role | AI SDK? |\n|--------|------|---------|\n| `./tools` | `memorySearchToolkit`, session helpers, framework-free `MemorySearchAgentExecutor` type, embedding re-exports | No |\n| `./adapter` | Zod expanded-memory wire, identity, instructions, message builders | No |\n| `./integrator` | Zod plan wire, identity, instructions, merge-slice helpers | No |\n| `./integrator/wire` | Durable integrate-memory event wire + write-scope policy | No |\n| `./investigator` | Zod answer wire, identity, instructions, message builders | No |\n| `./ai-sdk` | ToolLoop clients/sessions, `Output` wrappers, `toolLoopMemorySearchExecutor`, AI-shaped specs | **Yes** (optional peers) |\n\nLayout mirrors [`memories-node` persistence](../node/src/persistence/IMPLEMENTORS.md): core contracts on the first entrypoints; optional runtime adapter on `./ai-sdk`.\n\n**Optional peers** (install when importing `./ai-sdk`): `ai` ^7, `@khoralabs/agent-capabilities-ai-sdk` ^0.2.\n\n`./ai-sdk` host-facing `model` / `chatModel` args are **`string` model IDs** (serializable). Pass a gateway/provider id such as `\"openai/gpt-5\"` — do not put AI SDK Gateway class instances in durable Workflow step args; resolve provider models inside the host step when you need an instance.\n\n## Migration (0.10)\n\n| Was | Now |\n|-----|-----|\n| `model: LanguageModel` / `chatModel: LanguageModel` on `./ai-sdk` clients, specs, sessions | `model: string` / `chatModel: string` |\n\n## Migration (0.8)\n\n| Was | Now |\n|-----|-----|\n| `MemoryAdapterClient` from `./adapter` | `@khoralabs/memories-agents/ai-sdk` |\n| `MemoryIntegratorClient` / `processLogicalMemoryWithIntegrator` from `./integrator` | `./ai-sdk` |\n| `MemoryInvestigatorClient` from `./investigator` | `./ai-sdk` |\n| `toolLoopMemorySearchExecutor`, `buildMemorySearchAgentSpec`, `createMemorySearchToolLoopAgent*` from `./tools` | `./ai-sdk` |\n| `memoryAdapterExpandedOutput`, `investigatorAnswerOutput`, `integratorPlanOutputFromOntology` | `./ai-sdk` |\n| Zod schemas / `parse*` / identities / instructions / wire | unchanged on core entrypoints |\n\n## Tools (core)\n\n`memorySearchToolkit` is an `@khoralabs/agent-capabilities` toolkit. Session env (client, namespace, embeddings) is injected via context helpers — not constructor args:\n\n```ts\nimport {\n  memorySearchToolkit,\n  buildMemorySearchToolkitContext,\n} from \"@khoralabs/memories-agents/tools\";\n\nconst toolkitCtx = buildMemorySearchToolkitContext({\n  client,\n  namespace: \"app/user-1\",\n  embeddingModel,\n  additionalNamespaces: [\"app/shared\"],\n});\n// Compose memorySearchToolkit into a registry / tool loop with toolkitCtx\n```\n\n`memory_search` runs hybrid lexical + vector search (via node helpers) and can attach a provenance `root_hex` snapshot for cited answers.\n\n## Agents (AI SDK)\n\n```ts\nimport {\n  MemoryInvestigatorClient,\n  MemoryIntegratorClient,\n  MemoryAdapterClient,\n} from \"@khoralabs/memories-agents/ai-sdk\";\n\nconst investigator = new MemoryInvestigatorClient({\n  registry,\n  namespace: \"app/user-1\",\n  model: \"openai/gpt-5\", // string model id (serializable)\n  client,\n  embeddingModel,\n});\n\nconst { answer } = await investigator.investigate({\n  question: \"What commitments mention Project X?\",\n  maxSteps: 12,\n});\n```\n\nTypical pipeline: **adapter** (raw domain → draft) → **integrator** (draft → merged graph memories) → **investigator** / **tools** (read path). Graph connectivity after integrate can use `@khoralabs/memories-node/autolink`.\n\nWire sessions with `createAgentRegistry` and tool loops from `@khoralabs/agent-capabilities`. See the [root README](../../README.md) for composition context and [`../README.md`](../README.md) for the search pipeline these agents call.\n\n## Custom runners (WorkflowAgent)\n\nBuilt-in AI SDK clients default to `ToolLoopAgent` via `toolLoopMemorySearchExecutor` from `./ai-sdk`. For durable, resumable loops ([WorkflowAgent](https://ai-sdk.dev/docs/agents/workflow-agent)), build a spec and supply a custom executor — this package does not depend on `@ai-sdk/workflow`.\n\n```ts\nimport { WorkflowAgent, isStepCount } from \"@ai-sdk/workflow\"; // host dependency\nimport { getWritable } from \"workflow\";\nimport {\n  buildMemoryInvestigatorAgentSpec,\n  type MemorySearchAgentSpec,\n} from \"@khoralabs/memories-agents/ai-sdk\";\nimport type { MemorySearchAgentExecutor } from \"@khoralabs/memories-agents/tools\";\n\nconst workflowExecutor: MemorySearchAgentExecutor = {\n  async run(spec, { messages, abortSignal }) {\n    const s = spec as MemorySearchAgentSpec;\n    const agent = new WorkflowAgent({\n      id: s.id,\n      model: s.model,\n      tools: s.tools,\n      instructions: s.instructions,\n      prepareStep: s.prepareStep,\n    });\n    const result = await agent.stream({\n      messages,\n      output: s.output,\n      stopWhen: isStepCount(s.maxSteps),\n      writable: getWritable(),\n      abortSignal,\n    });\n    return {\n      output: result.output,\n      messages: result.messages,\n    };\n  },\n};\n```\n\nUse `buildMemoryInvestigatorAgentSpec` (or adapter/integrator equivalents) from `./ai-sdk` when constructing the AI-shaped spec for the session.\nLower-level wiring:\n\n- `./tools` — `MemorySearchAgentExecutor`, toolkit + session context helpers\n- `./ai-sdk` — `buildMemory*AgentSpec`, `toolLoopMemorySearchExecutor`, clients\n- `./integrator` — `mergeSearchPhaseMessages` moved to `./ai-sdk`\n\n**Serialization constraint:** `MemorySearchEnv` holds non-serializable handles (`memoriesClient`, `Map`/`Set` caches, live tool closures). Durable workflow steps that mark tool `execute` with durable step directives must rehydrate clients from serializable `toolsContext` / `runtimeContext`, or run tools without step durability (durable agent loop, in-memory tool calls). That rehydration is host responsibility — not provided here. Keep `model` as a string id in serializable step args; resolve provider/`LanguageModel` instances inside the host step if required.\n","readmeFilename":"README.md"}