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* Copyright 2025 © BeeAI a Series of LF Projects, LLC\n * SPDX-License-Identifier: Apache-2.0\n */\n\nimport { AgentError, BaseAgent } from \"@/agents/base.js\";\nimport {\n AnyTool,\n DynamicTool,\n StringToolOutput,\n Tool,\n ToolError,\n ToolOutput,\n} from \"@/tools/base.js\";\nimport { BaseMemory } from \"@/memory/base.js\";\nimport { AgentMeta } from \"@/agents/types.js\";\nimport { Emitter } from \"@/emitter/emitter.js\";\nimport type {\n ToolCallingAgentExecutionConfig,\n ToolCallingAgentTemplates,\n ToolCallingAgentCallbacks,\n ToolCallingAgentRunInput,\n ToolCallingAgentRunOptions,\n ToolCallingAgentRunOutput,\n ToolCallingAgentRunState,\n} from \"@/agents/toolCalling/types.js\";\nimport { GetRunContext } from \"@/context.js\";\nimport { ChatModel } from \"@/backend/chat.js\";\nimport { shallowCopy } from \"@/serializer/utils.js\";\nimport { UnconstrainedMemory } from \"@/memory/unconstrainedMemory.js\";\nimport { AssistantMessage, SystemMessage, ToolMessage, UserMessage } from \"@/backend/message.js\";\nimport { isEmpty, isString } from \"remeda\";\nimport { RetryCounter } from \"@/internals/helpers/counter.js\";\nimport { mapObj, omitUndefined } from \"@/internals/helpers/object.js\";\nimport { Cache } from \"@/cache/decoratorCache.js\";\nimport { PromptTemplate } from \"@/template.js\";\nimport {\n ToolCallingAgentSystemPrompt,\n ToolCallingAgentTaskPrompt,\n} from \"@/agents/toolCalling/prompts.js\";\nimport { z, ZodSchema } from \"zod\";\nimport { Logger } from \"@/logger/logger.js\";\n\nexport type ToolCallingAgentTemplateFactory = (\n template: ToolCallingAgentTemplates[K],\n) => ToolCallingAgentTemplates[K];\n\nexport interface ToolCallingAgentInput {\n llm: ChatModel;\n memory: BaseMemory;\n tools: AnyTool[];\n meta?: Omit;\n templates?: Partial<{\n [K in keyof ToolCallingAgentTemplates]:\n | ToolCallingAgentTemplates[K]\n | ToolCallingAgentTemplateFactory;\n }>;\n execution?: ToolCallingAgentExecutionConfig;\n saveIntermediateSteps?: 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Use RequirementAgent instead.\",\n );\n }\n\n static {\n this.register();\n }\n\n protected async _run(\n input: ToolCallingAgentRunInput,\n options: ToolCallingAgentRunOptions = {},\n run: GetRunContext,\n ): Promise {\n const tempMessageKey = \"tempMessage\" as const;\n const execution = {\n maxRetriesPerStep: 3,\n totalMaxRetries: 20,\n maxIterations: 10,\n ...omitUndefined(this.input.execution ?? {}),\n ...omitUndefined(options.execution ?? {}),\n };\n\n const state: ToolCallingAgentRunState = {\n memory: new UnconstrainedMemory(),\n result: undefined,\n iteration: 0,\n };\n await state.memory.add(\n new SystemMessage(\n this.templates.system.render({\n role: undefined,\n instructions: undefined,\n }),\n ),\n );\n await state.memory.addMany(this.memory.messages);\n\n if (input.prompt) {\n const userMessage = new UserMessage(\n this.templates.task.render({\n prompt: input.prompt,\n context: input.context,\n expectedOutput: isString(input.expectedOutput) ? input.expectedOutput : undefined,\n }),\n );\n await state.memory.add(userMessage);\n }\n\n const globalRetriesCounter = new RetryCounter(execution.totalMaxRetries || 1, AgentError);\n\n const usePlainResponse = !input.expectedOutput || !(input.expectedOutput instanceof ZodSchema);\n const finalAnswerToolSchema = usePlainResponse\n ? z.object({\n response: z.string().describe(String(input.expectedOutput ?? \"\")),\n })\n : (input.expectedOutput as ZodSchema);\n\n const finalAnswerTool = new DynamicTool({\n name: \"final_answer\",\n description: \"Sends the final answer to the user\",\n inputSchema: finalAnswerToolSchema,\n handler: async (input) => {\n const result = usePlainResponse ? input.response : JSON.stringify(input);\n state.result = new AssistantMessage(result);\n return new StringToolOutput(\"Message has been sent\");\n },\n });\n\n const tools = [...this.input.tools, finalAnswerTool];\n let forceFinalAnswer = false;\n\n while (!state.result) {\n state.iteration++;\n if (state.iteration > (execution.totalMaxRetries ?? Infinity)) {\n throw new AgentError(\n `Agent was not able to resolve the task in ${state.iteration} iterations.`,\n );\n }\n\n await run.emitter.emit(\"start\", { state });\n const response = await this.input.llm.create({\n messages: state.memory.messages.slice(),\n tools,\n toolChoice: forceFinalAnswer ? finalAnswerTool : tools.length > 1 ? \"required\" : tools[0],\n stream: false,\n });\n await state.memory.addMany(response.messages);\n\n const toolCallMessages = response.getToolCalls();\n for (const toolCall of toolCallMessages) {\n try {\n const tool = tools.find((tool) => tool.name === toolCall.toolName);\n if (!tool) {\n throw new AgentError(`Tool ${toolCall.toolName} does not exist!`);\n }\n\n const toolInput: any = toolCall.input;\n const toolResponse: ToolOutput = await tool.run(toolInput).context({\n state,\n toolCallMsg: toolCall,\n [Tool.contextKeys.Memory]: this.memory,\n });\n await state.memory.add(\n new ToolMessage({\n type: \"tool-result\",\n toolCallId: toolCall.toolCallId,\n toolName: toolCall.toolName,\n output: { type: \"text\", value: toolResponse.getTextContent() },\n }),\n );\n } catch (e) {\n if (e instanceof ToolError) {\n globalRetriesCounter.use(e);\n await state.memory.add(\n new ToolMessage({\n type: \"tool-result\",\n toolCallId: toolCall.toolCallId,\n toolName: toolCall.toolName,\n output: { type: \"error-text\", value: e.explain() },\n }),\n );\n } else {\n throw e;\n }\n }\n }\n\n // handle empty messages for some models\n const textMessages = response.getTextMessages();\n if (isEmpty(toolCallMessages) && isEmpty(textMessages)) {\n await state.memory.add(new AssistantMessage(\"\\n\", { [tempMessageKey]: true }));\n } else {\n await state.memory.deleteMany(\n state.memory.messages.filter((msg) => msg.meta[tempMessageKey]),\n );\n }\n\n // Fallback for providers that do not support structured outputs\n if (!isEmpty(textMessages) && isEmpty(toolCallMessages)) {\n forceFinalAnswer = true;\n tools.length = 0;\n tools.push(finalAnswerTool);\n }\n\n await run.emitter.emit(\"success\", { state });\n }\n\n if (this.input.saveIntermediateSteps) {\n this.memory.reset();\n await this.memory.addMany(state.memory.messages.slice(1));\n } else {\n await this.memory.addMany(state.memory.messages.slice(-2));\n }\n return { memory: state.memory, result: state.result };\n }\n\n get meta(): AgentMeta {\n const tools = this.input.tools.slice();\n\n if (this.input.meta) {\n return { ...this.input.meta, tools };\n }\n\n return {\n name: \"ToolCalling\",\n tools,\n description: \"ToolCallingAgent that uses tools to accomplish the task.\",\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 @Cache({ enumerable: false })\n protected get templates(): ToolCallingAgentTemplates {\n const overrides = this.input.templates ?? {};\n const defaultTemplates: ToolCallingAgentTemplates = {\n system: ToolCallingAgentSystemPrompt,\n task: ToolCallingAgentTaskPrompt,\n } as const;\n\n return mapObj(defaultTemplates)(\n (key, defaultTemplate: ToolCallingAgentTemplates[typeof key]) => {\n const override = overrides[key] ?? defaultTemplate;\n if (override instanceof PromptTemplate) {\n return override;\n }\n return override(defaultTemplate) ?? defaultTemplate;\n },\n );\n }\n\n createSnapshot() {\n return {\n ...super.createSnapshot(),\n input: shallowCopy(this.input),\n emitter: this.emitter,\n };\n }\n\n set memory(memory: BaseMemory) {\n this.input.memory = memory;\n }\n\n get memory() {\n return this.input.memory;\n }\n}\n"]}