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* Copyright 2025 © BeeAI a Series of LF Projects, LLC\n * SPDX-License-Identifier: Apache-2.0\n */\n\nimport { BaseAgent } from \"@/agents/base.js\";\nimport { AnyTool } from \"@/tools/base.js\";\nimport { BaseMemory } from \"@/memory/base.js\";\nimport { AgentMeta } from \"@/agents/types.js\";\nimport { Emitter } from \"@/emitter/emitter.js\";\nimport { ChatModel } from \"@/backend/chat.js\";\nimport type { GetRunContext, MiddlewareType } from \"@/context.js\";\nimport { UnconstrainedMemory } from \"@/memory/unconstrainedMemory.js\";\nimport { Message, UserMessage } from \"@/backend/message.js\";\nimport { shallowCopy } from \"@/serializer/utils.js\";\nimport { mapObj } from \"@/internals/helpers/object.js\";\nimport { PromptTemplate } from \"@/template.js\";\nimport {\n RequirementAgentCallbacks,\n RequirementAgentExecutionConfig,\n RequirementAgentOutput,\n RequirementAgentRunInput,\n RequirementAgentRunOptions,\n RequirementAgentTemplates,\n} from \"./types.js\";\nimport {\n RequirementAgentSystemPrompt,\n RequirementAgentTaskPrompt,\n RequirementAgentToolErrorPrompt,\n RequirementAgentToolNoResultPrompt,\n} from \"./prompts.js\";\nimport { Requirement } from \"./requirements/requirement.js\";\nimport { RequirementAgentRunner } from \"./runner.js\";\nimport { ToolCallChecker, ToolCallCheckerConfig } from \"./utils/toolCallChecker.js\";\nimport { isDefined, isEmptyish, pickBy } from \"remeda\";\nimport { castArray } from \"@/internals/helpers/array.js\";\nimport type { RequiredExcept } from \"@/internals/types.js\";\n\nexport type RequirementAgentTemplateFactory = (\n template: RequirementAgentTemplates[K],\n) => RequirementAgentTemplates[K];\n\nexport interface RequirementAgentInput {\n llm: ChatModel;\n memory?: BaseMemory;\n tools?: AnyTool[];\n requirements?: Requirement[];\n name?: string;\n description?: string;\n role?: string;\n instructions?: string | string[];\n notes?: string | string[];\n toolCallChecker?: boolean | ToolCallCheckerConfig;\n finalAnswerAsTool?: boolean;\n saveIntermediateSteps?: boolean;\n execution?: RequirementAgentExecutionConfig;\n templates?: Partial<{\n [K in keyof RequirementAgentTemplates]:\n | RequirementAgentTemplates[K]\n | RequirementAgentTemplateFactory;\n }>;\n middlewares?: MiddlewareType[];\n}\n\ntype InternalRequirementAgentInput = RequiredExcept<\n RequirementAgentInput,\n | \"role\"\n | \"instructions\"\n | \"name\"\n | \"description\"\n | \"templates\"\n | \"notes\"\n | \"execution\"\n | \"middlewares\"\n>;\n\n/**\n * RequirementAgent - A declarative AI agent with rule-based constraints\n *\n * The RequirementAgent provides predictable, controlled execution behavior across\n * different language models through rule-based constraints (Requirements).\n * Requirements can be configured as strict or flexible as necessary, adapting to\n * task requirements while ensuring consistent execution regardless of the underlying\n * model's reasoning or tool-calling capabilities.\n */\nexport class RequirementAgent extends BaseAgent<\n RequirementAgentRunInput,\n RequirementAgentOutput,\n RequirementAgentRunOptions\n> {\n public readonly emitter = Emitter.root.child({\n namespace: [\"agent\", \"requirement\"],\n creator: this,\n });\n\n protected readonly input: InternalRequirementAgentInput;\n\n protected runner: new (\n ...args: ConstructorParameters\n ) => RequirementAgentRunner = RequirementAgentRunner;\n\n constructor(input: RequirementAgentInput) {\n super();\n this.input = {\n ...input,\n memory: input.memory || new UnconstrainedMemory(),\n tools: input.tools || [],\n requirements: input.requirements || [],\n saveIntermediateSteps: input.saveIntermediateSteps ?? true,\n finalAnswerAsTool: input.finalAnswerAsTool ?? true,\n toolCallChecker: input.toolCallChecker ?? true,\n };\n if (input.middlewares) {\n this.middlewares.push(...input.middlewares);\n }\n }\n\n static {\n this.register();\n }\n\n protected async _run(\n input: RequirementAgentRunInput,\n options: RequirementAgentRunOptions = {},\n run: GetRunContext,\n ): Promise {\n const execution: RequirementAgentExecutionConfig = {\n maxRetriesPerStep: 3,\n totalMaxRetries: 20,\n maxIterations: 20,\n ...this.input.execution,\n ...options.execution,\n };\n\n const toolCallChecker = this.createToolCallChecker();\n\n const runner = new this.runner(\n this.input.llm,\n execution,\n this.input.tools || [],\n this.input.requirements || [],\n input.expectedOutput || null,\n toolCallChecker,\n run,\n this.input.finalAnswerAsTool,\n this.templates,\n );\n\n // Process input messages\n const newMessages = this.processInput(input);\n await runner.addMessages([...this.memory.messages]);\n await runner.addMessages(newMessages);\n\n // Run the agent\n const finalState = await runner.run();\n\n // Update memory\n if (this.input.saveIntermediateSteps) {\n this.memory.reset();\n await this.memory.addMany(finalState.memory.messages);\n } else {\n await this.memory.addMany(newMessages);\n // Add last tool call pair\n const messages = finalState.memory.messages;\n const lastPair = messages.slice(-2);\n await this.memory.addMany(lastPair);\n }\n\n if (!finalState.answer) {\n throw new Error(\"Agent did not produce a final answer\");\n }\n\n return {\n result: finalState.answer,\n memory: finalState.memory,\n state: finalState,\n };\n }\n\n protected processInput(input: RequirementAgentRunInput): Message[] {\n if (!input.prompt) {\n return [];\n }\n\n const userMessage = new UserMessage(\n this.templates.task.render({\n prompt: input.prompt,\n context: input.context,\n expectedOutput: typeof input.expectedOutput === \"string\" ? input.expectedOutput : undefined,\n }),\n );\n\n return [userMessage];\n }\n\n protected createToolCallChecker(): ToolCallChecker {\n const config: ToolCallCheckerConfig = {};\n\n if (typeof this.input.toolCallChecker === \"object\") {\n Object.assign(config, this.input.toolCallChecker);\n }\n\n const checker = new ToolCallChecker(config);\n checker.enabled = this.input.toolCallChecker !== false;\n return checker;\n }\n\n get meta(): AgentMeta {\n const tools = this.input.tools || [];\n\n return {\n name: this.input.name ?? \"Requirement\",\n tools,\n description:\n this.input.description ??\n \"The RequirementAgent is a declarative AI agent implementation that provides predictable, \" +\n \"controlled execution behavior across different language models through rule-based constraints.\",\n ...(tools.length > 0 && {\n extraDescription: [\n `Tools that I can use to accomplish given task.`,\n ...tools.map((tool) => `Tool '${tool.name}': ${tool.description}.`),\n ].join(\"\\n\"),\n }),\n };\n }\n\n protected get templates(): RequirementAgentTemplates {\n const overrides = this.input.templates || {};\n const finalized = mapObj({\n system: RequirementAgentSystemPrompt,\n task: RequirementAgentTaskPrompt,\n toolError: RequirementAgentToolErrorPrompt,\n toolNoResult: RequirementAgentToolNoResultPrompt,\n } as RequirementAgentTemplates)((\n key,\n defaultTemplate: RequirementAgentTemplates[typeof key],\n ) => {\n const override = overrides[key] ?? defaultTemplate;\n if (override instanceof PromptTemplate) {\n return override;\n }\n return override(defaultTemplate) ?? defaultTemplate;\n });\n\n if (this.input.role || this.input.instructions || this.input.notes) {\n finalized.system.update({\n defaults: pickBy(\n {\n role: this.input.role,\n instructions: isEmptyish(this.input.instructions)\n ? undefined\n : castArray(this.input.instructions)\n .map((v) => `- ${v}`)\n .join(\"\\n\"),\n notes: isEmptyish(this.input.notes)\n ? undefined\n : castArray(this.input.notes)\n .map((v) => `- ${v}`)\n .join(\"\\n\"),\n },\n isDefined,\n ),\n });\n }\n\n return finalized;\n }\n\n createSnapshot() {\n return {\n ...super.createSnapshot(),\n input: shallowCopy(this.input),\n emitter: this.emitter,\n runner: this.runner,\n };\n }\n\n set memory(memory: BaseMemory) {\n this.input.memory = memory;\n }\n\n get memory(): BaseMemory {\n return this.input.memory!;\n }\n}\n"]}