langchain/dist/agents/middleware/hitl.cjs.map

Typescript bindings for langchain

{"version":3,"file":"hitl.cjs","names":["z","options: NonNullable<HumanInTheLoopMiddlewareConfig>","toolCall: ToolCall","config: InterruptOnConfig","state: AgentBuiltInState","runtime: Runtime<unknown>","description: string","actionRequest: ActionRequest","reviewConfig: ReviewConfig","decision: Decision","ToolMessage","createMiddleware","AIMessage","resolvedConfigs: Record<string, InterruptOnConfig>","interruptToolCalls: ToolCall[]","autoApprovedToolCalls: ToolCall[]","actionRequests: ActionRequest[]","reviewConfigs: ReviewConfig[]","hitlRequest: HITLRequest","revisedToolCalls: ToolCall[]","artificialToolMessages: ToolMessage[]","jumpTo: JumpToTarget | undefined"],"sources":["../../../src/agents/middleware/hitl.ts"],"sourcesContent":["/* eslint-disable @typescript-eslint/no-explicit-any */\nimport { z } from \"zod/v3\";\nimport { AIMessage, ToolMessage, ToolCall } from \"@langchain/core/messages\";\nimport {\n  InferInteropZodInput,\n  interopParse,\n} from \"@langchain/core/utils/types\";\nimport { interrupt } from \"@langchain/langgraph\";\n\nimport { createMiddleware } from \"../middleware.js\";\nimport type { AgentBuiltInState, Runtime } from \"../runtime.js\";\nimport type { JumpToTarget } from \"../constants.js\";\n\nconst DescriptionFunctionSchema = z\n  .function()\n  .args(\n    z.custom<ToolCall>(), // toolCall\n    z.custom<AgentBuiltInState>(), // state\n    z.custom<Runtime<unknown>>() // runtime\n  )\n  .returns(z.union([z.string(), z.promise(z.string())]));\n\n/**\n * Function type that dynamically generates a description for a tool call approval request.\n *\n * @param toolCall - The tool call being reviewed\n * @param state - The current agent state\n * @param runtime - The agent runtime context\n * @returns A string description or Promise that resolves to a string description\n *\n * @example\n * ```typescript\n * import { type DescriptionFactory, type ToolCall } from \"langchain\";\n *\n * const descriptionFactory: DescriptionFactory = (toolCall, state, runtime) => {\n *   return `Please review: ${toolCall.name}(${JSON.stringify(toolCall.args)})`;\n * };\n * ```\n */\nexport type DescriptionFactory = z.infer<typeof DescriptionFunctionSchema>;\n\n/**\n * The type of decision a human can make.\n */\nconst ALLOWED_DECISIONS = [\"approve\", \"edit\", \"reject\"] as const;\nconst DecisionType = z.enum(ALLOWED_DECISIONS);\nexport type DecisionType = z.infer<typeof DecisionType>;\n\nconst InterruptOnConfigSchema = z.object({\n  /**\n   * The decisions that are allowed for this action.\n   */\n  allowedDecisions: z.array(DecisionType),\n  /**\n   * The description attached to the request for human input.\n   * Can be either:\n   * - A static string describing the approval request\n   * - A callable that dynamically generates the description based on agent state,\n   *   runtime, and tool call information\n   *\n   * @example\n   * Static string description\n   * ```typescript\n   * import type { InterruptOnConfig } from \"langchain\";\n   *\n   * const config: InterruptOnConfig = {\n   *   allowedDecisions: [\"approve\", \"reject\"],\n   *   description: \"Please review this tool execution\"\n   * };\n   * ```\n   *\n   * @example\n   * Dynamic callable description\n   * ```typescript\n   * import type {\n   *   AgentBuiltInState,\n   *   Runtime,\n   *   DescriptionFactory,\n   *   ToolCall,\n   *   InterruptOnConfig\n   * } from \"langchain\";\n   *\n   * const formatToolDescription: DescriptionFactory = (\n   *   toolCall: ToolCall,\n   *   state: AgentBuiltInState,\n   *   runtime: Runtime<unknown>\n   * ) => {\n   *   return `Tool: ${toolCall.name}\\nArguments:\\n${JSON.stringify(toolCall.args, null, 2)}`;\n   * };\n   *\n   * const config: InterruptOnConfig = {\n   *   allowedDecisions: [\"approve\", \"edit\"],\n   *   description: formatToolDescription\n   * };\n   * ```\n   */\n  description: z.union([z.string(), DescriptionFunctionSchema]).optional(),\n  /**\n   * JSON schema for the arguments associated with the action, if edits are allowed.\n   */\n  argsSchema: z.record(z.any()).optional(),\n});\nexport type InterruptOnConfig = z.input<typeof InterruptOnConfigSchema>;\n\n/**\n * Represents an action with a name and arguments.\n */\nexport interface Action {\n  /**\n   * The type or name of action being requested (e.g., \"add_numbers\").\n   */\n  name: string;\n  /**\n   * Key-value pairs of arguments needed for the action (e.g., {\"a\": 1, \"b\": 2}).\n   */\n  args: Record<string, any>;\n}\n\n/**\n * Represents an action request with a name, arguments, and description.\n */\nexport interface ActionRequest {\n  /**\n   * The name of the action being requested.\n   */\n  name: string;\n  /**\n   * Key-value pairs of arguments needed for the action (e.g., {\"a\": 1, \"b\": 2}).\n   */\n  args: Record<string, any>;\n  /**\n   * The description of the action to be reviewed.\n   */\n  description?: string;\n}\n\n/**\n * Policy for reviewing a HITL request.\n */\nexport interface ReviewConfig {\n  /**\n   * Name of the action associated with this review configuration.\n   */\n  actionName: string;\n  /**\n   * The decisions that are allowed for this request.\n   */\n  allowedDecisions: DecisionType[];\n  /**\n   * JSON schema for the arguments associated with the action, if edits are allowed.\n   */\n  argsSchema?: Record<string, any>;\n}\n\n/**\n * Request for human feedback on a sequence of actions requested by a model.\n *\n * @example\n * ```ts\n * const hitlRequest: HITLRequest = {\n *   actionRequests: [\n *     { name: \"send_email\", args: { to: \"user@example.com\", subject: \"Hello\" } }\n *   ],\n *   reviewConfigs: [\n *     {\n *       actionName: \"send_email\",\n *       allowedDecisions: [\"approve\", \"edit\", \"reject\"],\n *       description: \"Please review the email before sending\"\n *     }\n *   ]\n * };\n * const response = interrupt(hitlRequest);\n * ```\n */\nexport interface HITLRequest {\n  /**\n   * A list of agent actions for human review.\n   */\n  actionRequests: ActionRequest[];\n  /**\n   * Review configuration for all possible actions.\n   */\n  reviewConfigs: ReviewConfig[];\n}\n\n/**\n * Response when a human approves the action.\n */\nexport interface ApproveDecision {\n  type: \"approve\";\n}\n\n/**\n * Response when a human edits the action.\n */\nexport interface EditDecision {\n  type: \"edit\";\n  /**\n   * Edited action for the agent to perform.\n   * Ex: for a tool call, a human reviewer can edit the tool name and args.\n   */\n  editedAction: Action;\n}\n\n/**\n * Response when a human rejects the action.\n */\nexport interface RejectDecision {\n  type: \"reject\";\n  /**\n   * The message sent to the model explaining why the action was rejected.\n   */\n  message?: string;\n}\n\n/**\n * Union of all possible decision types.\n */\nexport type Decision = ApproveDecision | EditDecision | RejectDecision;\n\n/**\n * Response payload for a HITLRequest.\n */\nexport interface HITLResponse {\n  /**\n   * The decisions made by the human.\n   */\n  decisions: Decision[];\n}\n\nconst contextSchema = z.object({\n  /**\n   * Mapping of tool name to allowed reviewer responses.\n   * If a tool doesn't have an entry, it's auto-approved by default.\n   *\n   * - `true` -> pause for approval and allow approve/edit/reject decisions\n   * - `false` -> auto-approve (no human review)\n   * - `InterruptOnConfig` -> explicitly specify which decisions are allowed for this tool\n   */\n  interruptOn: z\n    .record(z.union([z.boolean(), InterruptOnConfigSchema]))\n    .optional(),\n  /**\n   * Prefix used when constructing human-facing approval messages.\n   * Provides context about the tool call being reviewed; does not change the underlying action.\n   *\n   * Note: This prefix is only applied for tools that do not provide a custom\n   * `description` via their {@link InterruptOnConfig}. If a tool specifies a custom\n   * `description`, that per-tool text is used and this prefix is ignored.\n   */\n  descriptionPrefix: z.string().default(\"Tool execution requires approval\"),\n});\nexport type HumanInTheLoopMiddlewareConfig = InferInteropZodInput<\n  typeof contextSchema\n>;\n\n/**\n * Creates a Human-in-the-Loop (HITL) middleware for tool approval and oversight.\n *\n * This middleware intercepts tool calls made by an AI agent and provides human oversight\n * capabilities before execution. It enables selective approval workflows where certain tools\n * require human intervention while others can execute automatically.\n *\n * A invocation result that has been interrupted by the middleware will have a `__interrupt__`\n * property that contains the interrupt request.\n *\n * ```ts\n * import { type HITLRequest, type HITLResponse } from \"langchain\";\n * import { type Interrupt } from \"langchain\";\n *\n * const result = await agent.invoke(request);\n * const interruptRequest = result.__interrupt__?.[0] as Interrupt<HITLRequest>;\n *\n * // Examine the action requests and review configs\n * const actionRequests = interruptRequest.value.actionRequests;\n * const reviewConfigs = interruptRequest.value.reviewConfigs;\n *\n * // Create decisions for each action\n * const resume: HITLResponse = {\n *   decisions: actionRequests.map((action, i) => {\n *     if (action.name === \"calculator\") {\n *       return { type: \"approve\" };\n *     } else if (action.name === \"write_file\") {\n *       return {\n *         type: \"edit\",\n *         editedAction: { name: \"write_file\", args: { filename: \"safe.txt\", content: \"Safe content\" } }\n *       };\n *     }\n *     return { type: \"reject\", message: \"Action not allowed\" };\n *   })\n * };\n *\n * // Resume with decisions\n * await agent.invoke(new Command({ resume }), config);\n * ```\n *\n * ## Features\n *\n * - **Selective Tool Approval**: Configure which tools require human approval\n * - **Multiple Decision Types**: Approve, edit, or reject tool calls\n * - **Asynchronous Workflow**: Uses LangGraph's interrupt mechanism for non-blocking approval\n * - **Custom Approval Messages**: Provide context-specific descriptions for approval requests\n *\n * ## Decision Types\n *\n * When a tool requires approval, the human operator can respond with:\n * - `approve`: Execute the tool with original arguments\n * - `edit`: Modify the tool name and/or arguments before execution\n * - `reject`: Provide a manual response instead of executing the tool\n *\n * @param options - Configuration options for the middleware\n * @param options.interruptOn - Per-tool configuration mapping tool names to their settings\n * @param options.interruptOn[toolName].allowedDecisions - Array of decision types allowed for this tool (e.g., [\"approve\", \"edit\", \"reject\"])\n * @param options.interruptOn[toolName].description - Custom approval message for the tool. Can be either a static string or a callable that dynamically generates the description based on agent state, runtime, and tool call information\n * @param options.interruptOn[toolName].argsSchema - JSON schema for the arguments associated with the action, if edits are allowed\n * @param options.descriptionPrefix - Default prefix for approval messages (default: \"Tool execution requires approval\"). Only used for tools that do not define a custom `description` in their InterruptOnConfig.\n *\n * @returns A middleware instance that can be passed to `createAgent`\n *\n * @example\n * Basic usage with selective tool approval\n * ```typescript\n * import { humanInTheLoopMiddleware } from \"langchain\";\n * import { createAgent } from \"langchain\";\n *\n * const hitlMiddleware = humanInTheLoopMiddleware({\n *   interruptOn: {\n *     // Interrupt write_file tool and allow edits or approvals\n *     \"write_file\": {\n *       allowedDecisions: [\"approve\", \"edit\"],\n *       description: \"⚠️ File write operation requires approval\"\n *     },\n *     // Auto-approve read_file tool\n *     \"read_file\": false\n *   }\n * });\n *\n * const agent = createAgent({\n *   model: \"openai:gpt-4\",\n *   tools: [writeFileTool, readFileTool],\n *   middleware: [hitlMiddleware]\n * });\n * ```\n *\n * @example\n * Handling approval requests\n * ```typescript\n * import { type HITLRequest, type HITLResponse, type Interrupt } from \"langchain\";\n * import { Command } from \"@langchain/langgraph\";\n *\n * // Initial agent invocation\n * const result = await agent.invoke({\n *   messages: [new HumanMessage(\"Write 'Hello' to output.txt\")]\n * }, config);\n *\n * // Check if agent is paused for approval\n * if (result.__interrupt__) {\n *   const interruptRequest = result.__interrupt__?.[0] as Interrupt<HITLRequest>;\n *\n *   // Show tool call details to user\n *   console.log(\"Actions:\", interruptRequest.value.actionRequests);\n *   console.log(\"Review configs:\", interruptRequest.value.reviewConfigs);\n *\n *   // Resume with approval\n *   const resume: HITLResponse = {\n *     decisions: [{ type: \"approve\" }]\n *   };\n *   await agent.invoke(\n *     new Command({ resume }),\n *     config\n *   );\n * }\n * ```\n *\n * @example\n * Different decision types\n * ```typescript\n * import { type HITLResponse } from \"langchain\";\n *\n * // Approve the tool call as-is\n * const resume: HITLResponse = {\n *   decisions: [{ type: \"approve\" }]\n * };\n *\n * // Edit the tool arguments\n * const resume: HITLResponse = {\n *   decisions: [{\n *     type: \"edit\",\n *     editedAction: { name: \"write_file\", args: { filename: \"safe.txt\", content: \"Modified\" } }\n *   }]\n * };\n *\n * // Reject with feedback\n * const resume: HITLResponse = {\n *   decisions: [{\n *     type: \"reject\",\n *     message: \"File operation not allowed in demo mode\"\n *   }]\n * };\n * ```\n *\n * @example\n * Production use case with database operations\n * ```typescript\n * const hitlMiddleware = humanInTheLoopMiddleware({\n *   interruptOn: {\n *     \"execute_sql\": {\n *       allowedDecisions: [\"approve\", \"edit\", \"reject\"],\n *       description: \"🚨 SQL query requires DBA approval\\nPlease review for safety and performance\"\n *     },\n *     \"read_schema\": false,  // Reading metadata is safe\n *     \"delete_records\": {\n *       allowedDecisions: [\"approve\", \"reject\"],\n *       description: \"⛔ DESTRUCTIVE OPERATION - Requires manager approval\"\n *     }\n *   },\n *   descriptionPrefix: \"Database operation pending approval\"\n * });\n * ```\n *\n * @example\n * Using dynamic callable descriptions\n * ```typescript\n * import { type DescriptionFactory, type ToolCall } from \"langchain\";\n * import type { AgentBuiltInState, Runtime } from \"langchain/agents\";\n *\n * // Define a dynamic description factory\n * const formatToolDescription: DescriptionFactory = (\n *   toolCall: ToolCall,\n *   state: AgentBuiltInState,\n *   runtime: Runtime<unknown>\n * ) => {\n *   return `Tool: ${toolCall.name}\\nArguments:\\n${JSON.stringify(toolCall.args, null, 2)}`;\n * };\n *\n * const hitlMiddleware = humanInTheLoopMiddleware({\n *   interruptOn: {\n *     \"write_file\": {\n *       allowedDecisions: [\"approve\", \"edit\"],\n *       // Use dynamic description that can access tool call, state, and runtime\n *       description: formatToolDescription\n *     },\n *     // Or use an inline function\n *     \"send_email\": {\n *       allowedDecisions: [\"approve\", \"reject\"],\n *       description: (toolCall, state, runtime) => {\n *         const { to, subject } = toolCall.args;\n *         return `Email to ${to}\\nSubject: ${subject}\\n\\nRequires approval before sending`;\n *       }\n *     }\n *   }\n * });\n * ```\n *\n * @remarks\n * - Tool calls are processed in the order they appear in the AI message\n * - Auto-approved tools execute immediately without interruption\n * - Multiple tools requiring approval are bundled into a single interrupt request\n * - The middleware operates in the `afterModel` phase, intercepting before tool execution\n * - Requires a checkpointer to maintain state across interruptions\n *\n * @see {@link createAgent} for agent creation\n * @see {@link Command} for resuming interrupted execution\n * @public\n */\nexport function humanInTheLoopMiddleware(\n  options: NonNullable<HumanInTheLoopMiddlewareConfig>\n) {\n  const createActionAndConfig = async (\n    toolCall: ToolCall,\n    config: InterruptOnConfig,\n    state: AgentBuiltInState,\n    runtime: Runtime<unknown>\n  ): Promise<{\n    actionRequest: ActionRequest;\n    reviewConfig: ReviewConfig;\n  }> => {\n    const toolName = toolCall.name;\n    const toolArgs = toolCall.args;\n\n    // Generate description using the description field (str or callable)\n    const descriptionValue = config.description;\n    let description: string;\n    if (typeof descriptionValue === \"function\") {\n      description = await descriptionValue(toolCall, state, runtime);\n    } else if (descriptionValue !== undefined) {\n      description = descriptionValue;\n    } else {\n      description = `${\n        options.descriptionPrefix ?? \"Tool execution requires approval\"\n      }\\n\\nTool: ${toolName}\\nArgs: ${JSON.stringify(toolArgs, null, 2)}`;\n    }\n\n    /**\n     * Create ActionRequest with description\n     */\n    const actionRequest: ActionRequest = {\n      name: toolName,\n      args: toolArgs,\n      description,\n    };\n\n    /**\n     * Create ReviewConfig\n     */\n    const reviewConfig: ReviewConfig = {\n      actionName: toolName,\n      allowedDecisions: config.allowedDecisions,\n    };\n\n    if (config.argsSchema) {\n      reviewConfig.argsSchema = config.argsSchema;\n    }\n\n    return { actionRequest, reviewConfig };\n  };\n\n  const processDecision = (\n    decision: Decision,\n    toolCall: ToolCall,\n    config: InterruptOnConfig\n  ): { revisedToolCall: ToolCall | null; toolMessage: ToolMessage | null } => {\n    const allowedDecisions = config.allowedDecisions;\n    if (decision.type === \"approve\" && allowedDecisions.includes(\"approve\")) {\n      return { revisedToolCall: toolCall, toolMessage: null };\n    }\n\n    if (decision.type === \"edit\" && allowedDecisions.includes(\"edit\")) {\n      const editedAction = decision.editedAction;\n\n      /**\n       * Validate edited action structure\n       */\n      if (!editedAction || typeof editedAction.name !== \"string\") {\n        throw new Error(\n          `Invalid edited action for tool \"${toolCall.name}\": name must be a string`\n        );\n      }\n      if (!editedAction.args || typeof editedAction.args !== \"object\") {\n        throw new Error(\n          `Invalid edited action for tool \"${toolCall.name}\": args must be an object`\n        );\n      }\n\n      return {\n        revisedToolCall: {\n          type: \"tool_call\",\n          name: editedAction.name,\n          args: editedAction.args,\n          id: toolCall.id,\n        },\n        toolMessage: null,\n      };\n    }\n\n    if (decision.type === \"reject\" && allowedDecisions.includes(\"reject\")) {\n      /**\n       * Validate that message is a string if provided\n       */\n      if (\n        decision.message !== undefined &&\n        typeof decision.message !== \"string\"\n      ) {\n        throw new Error(\n          `Tool call response for \"${\n            toolCall.name\n          }\" must be a string, got ${typeof decision.message}`\n        );\n      }\n\n      // Create a tool message with the human's text response\n      const content =\n        decision.message ??\n        `User rejected the tool call for \\`${toolCall.name}\\` with id ${toolCall.id}`;\n\n      const toolMessage = new ToolMessage({\n        content,\n        name: toolCall.name,\n        tool_call_id: toolCall.id!,\n        status: \"error\",\n      });\n\n      return { revisedToolCall: toolCall, toolMessage };\n    }\n\n    const msg = `Unexpected human decision: ${JSON.stringify(\n      decision\n    )}. Decision type '${decision.type}' is not allowed for tool '${\n      toolCall.name\n    }'. Expected one of ${JSON.stringify(\n      allowedDecisions\n    )} based on the tool's configuration.`;\n    throw new Error(msg);\n  };\n\n  return createMiddleware({\n    name: \"HumanInTheLoopMiddleware\",\n    contextSchema,\n    afterModel: {\n      canJumpTo: [\"model\"],\n      hook: async (state, runtime) => {\n        const config = interopParse(contextSchema, {\n          ...options,\n          ...(runtime.context || {}),\n        });\n        if (!config) {\n          return;\n        }\n\n        const { messages } = state;\n        if (!messages.length) {\n          return;\n        }\n\n        /**\n         * Don't do anything if the last message isn't an AI message with tool calls.\n         */\n        const lastMessage = [...messages]\n          .reverse()\n          .find((msg) => AIMessage.isInstance(msg)) as AIMessage;\n        if (!lastMessage || !lastMessage.tool_calls?.length) {\n          return;\n        }\n\n        /**\n         * If the user omits the interruptOn config, we don't do anything.\n         */\n        if (!config.interruptOn) {\n          return;\n        }\n\n        /**\n         * Resolve per-tool configs (boolean true -> all decisions allowed; false -> auto-approve)\n         */\n        const resolvedConfigs: Record<string, InterruptOnConfig> = {};\n        for (const [toolName, toolConfig] of Object.entries(\n          config.interruptOn\n        )) {\n          if (typeof toolConfig === \"boolean\") {\n            if (toolConfig === true) {\n              resolvedConfigs[toolName] = {\n                allowedDecisions: [...ALLOWED_DECISIONS],\n              };\n            }\n          } else if (toolConfig.allowedDecisions) {\n            resolvedConfigs[toolName] = toolConfig as InterruptOnConfig;\n          }\n        }\n\n        const interruptToolCalls: ToolCall[] = [];\n        const autoApprovedToolCalls: ToolCall[] = [];\n\n        for (const toolCall of lastMessage.tool_calls) {\n          if (toolCall.name in resolvedConfigs) {\n            interruptToolCalls.push(toolCall);\n          } else {\n            autoApprovedToolCalls.push(toolCall);\n          }\n        }\n\n        /**\n         * No interrupt tool calls, so we can just return.\n         */\n        if (!interruptToolCalls.length) {\n          return;\n        }\n\n        /**\n         * Create action requests and review configs for all tools that need approval\n         */\n        const actionRequests: ActionRequest[] = [];\n        const reviewConfigs: ReviewConfig[] = [];\n\n        for (const toolCall of interruptToolCalls) {\n          const interruptConfig = resolvedConfigs[toolCall.name]!;\n\n          /**\n           * Create ActionRequest and ReviewConfig using helper method\n           */\n          const { actionRequest, reviewConfig } = await createActionAndConfig(\n            toolCall,\n            interruptConfig,\n            state,\n            runtime\n          );\n          actionRequests.push(actionRequest);\n          reviewConfigs.push(reviewConfig);\n        }\n\n        /**\n         * Create single HITLRequest with all actions and configs\n         */\n        const hitlRequest: HITLRequest = {\n          actionRequests,\n          reviewConfigs,\n        };\n\n        /**\n         * Send interrupt and get response\n         */\n        const hitlResponse = (await interrupt(hitlRequest)) as HITLResponse;\n        const decisions = hitlResponse.decisions;\n\n        /**\n         * Validate that decisions is a valid array before checking length\n         */\n        if (!decisions || !Array.isArray(decisions)) {\n          throw new Error(\n            \"Invalid HITLResponse: decisions must be a non-empty array\"\n          );\n        }\n\n        /**\n         * Validate that the number of decisions matches the number of interrupt tool calls\n         */\n        if (decisions.length !== interruptToolCalls.length) {\n          throw new Error(\n            `Number of human decisions (${decisions.length}) does not match number of hanging tool calls (${interruptToolCalls.length}).`\n          );\n        }\n\n        const revisedToolCalls: ToolCall[] = [...autoApprovedToolCalls];\n        const artificialToolMessages: ToolMessage[] = [];\n        const hasRejectedToolCalls = decisions.some(\n          (decision) => decision.type === \"reject\"\n        );\n\n        /**\n         * Process each decision using helper method\n         */\n        for (let i = 0; i < decisions.length; i++) {\n          const decision = decisions[i]!;\n          const toolCall = interruptToolCalls[i]!;\n          const interruptConfig = resolvedConfigs[toolCall.name]!;\n\n          const { revisedToolCall, toolMessage } = processDecision(\n            decision,\n            toolCall,\n            interruptConfig\n          );\n\n          if (\n            revisedToolCall &&\n            /**\n             * If any decision is a rejected, we are going back to the model\n             * with only the tool calls that were rejected as we don't know\n             * the results of the approved/updated tool calls at this point.\n             */\n            (!hasRejectedToolCalls || decision.type === \"reject\")\n          ) {\n            revisedToolCalls.push(revisedToolCall);\n          }\n          if (toolMessage) {\n            artificialToolMessages.push(toolMessage);\n          }\n        }\n\n        /**\n         * Update the AI message to only include approved tool calls\n         */\n        if (AIMessage.isInstance(lastMessage)) {\n          lastMessage.tool_calls = revisedToolCalls;\n        }\n\n        const jumpTo: JumpToTarget | undefined = hasRejectedToolCalls\n          ? \"model\"\n          : undefined;\n        return {\n          messages: [lastMessage, ...artificialToolMessages],\n          jumpTo,\n        };\n      },\n    },\n  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