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type {\n\tAssistantMessage,\n\tAssistantMessageEvent,\n\tImageContent,\n\tMessage,\n\tModel,\n\tSimpleStreamOptions,\n\tstreamSimple,\n\tTextContent,\n\tTool,\n\tToolResultMessage,\n} from \"@dreb/ai\";\nimport type { Static, TSchema } from \"@sinclair/typebox\";\n\n/**\n * Stream function used by the agent loop.\n *\n * Contract:\n * - Must not throw or return a rejected promise for request/model/runtime failures.\n * - Must return an AssistantMessageEventStream.\n * - Failures must be encoded in the returned stream via protocol events and a\n *   final AssistantMessage with stopReason \"error\" or \"aborted\" and errorMessage.\n */\nexport type StreamFn = (\n\t...args: Parameters<typeof streamSimple>\n) => ReturnType<typeof streamSimple> | Promise<ReturnType<typeof streamSimple>>;\n\n/**\n * Configuration for how tool calls from a single assistant message are executed.\n *\n * - \"sequential\": each tool call is prepared, executed, and finalized before the next one starts.\n * - \"parallel\": tool calls are prepared sequentially, then allowed tools execute concurrently.\n *   Final tool results are still emitted in assistant source order.\n */\nexport type ToolExecutionMode = \"sequential\" | \"parallel\";\n\n/** A single tool call content block emitted by an assistant message. */\nexport type AgentToolCall = Extract<AssistantMessage[\"content\"][number], { type: \"toolCall\" }>;\n\n/**\n * Result returned from `beforeToolCall`.\n *\n * Returning `{ block: true }` prevents the tool from executing. The loop emits an error tool result instead.\n * `reason` becomes the text shown in that error result. If omitted, a default blocked message is used.\n */\nexport interface BeforeToolCallResult {\n\tblock?: boolean;\n\treason?: string;\n}\n\n/**\n * Partial override returned from `afterToolCall`.\n *\n * Merge semantics are field-by-field:\n * - `content`: if provided, replaces the tool result content array in full\n * - `details`: if provided, replaces the tool result details value in full\n * - `isError`: if provided, replaces the tool result error flag\n *\n * Omitted fields keep the original executed tool result values.\n * There is no deep merge for `content` or `details`.\n */\nexport interface AfterToolCallResult {\n\tcontent?: (TextContent | ImageContent)[];\n\tdetails?: unknown;\n\tisError?: boolean;\n}\n\n/** Context passed to `beforeToolCall`. */\nexport interface BeforeToolCallContext {\n\t/** The assistant message that requested the tool call. */\n\tassistantMessage: AssistantMessage;\n\t/** The raw tool call block from `assistantMessage.content`. */\n\ttoolCall: AgentToolCall;\n\t/** Validated tool arguments for the target tool schema. */\n\targs: unknown;\n\t/** Current agent context at the time the tool call is prepared. */\n\tcontext: AgentContext;\n}\n\n/** Context passed to `afterToolCall`. */\nexport interface AfterToolCallContext {\n\t/** The assistant message that requested the tool call. */\n\tassistantMessage: AssistantMessage;\n\t/** The raw tool call block from `assistantMessage.content`. */\n\ttoolCall: AgentToolCall;\n\t/** Validated tool arguments for the target tool schema. */\n\targs: unknown;\n\t/** The executed tool result before any `afterToolCall` overrides are applied. */\n\tresult: AgentToolResult<any>;\n\t/** Whether the executed tool result is currently treated as an error. */\n\tisError: boolean;\n\t/** Current agent context at the time the tool call is finalized. */\n\tcontext: AgentContext;\n}\n\n/** Atomic context/model replacement returned by `beforeLlmCall`. */\nexport interface BeforeLlmCallResult {\n\t/** Replacement messages for the upcoming request and subsequent loop iterations. */\n\tmessages?: AgentMessage[];\n\t/** Replacement model for the upcoming request and subsequent loop iterations. */\n\tmodel?: Model<any>;\n}\n\nexport interface AgentLoopConfig extends SimpleStreamOptions {\n\tmodel: Model<any>;\n\n\t/**\n\t * Called after loop guardrails pass and immediately before each LLM call.\n\t *\n\t * The callback sees a settled context. It may atomically replace the messages\n\t * and/or model used by the upcoming request and subsequent loop iterations.\n\t * Contract: low-level callers must not throw or reject; surface failures and\n\t * return `undefined` to keep the existing context. `Agent` converts a thrown\n\t * hook error into its normal visible assistant-error termination.\n\t */\n\tbeforeLlmCall?: (context: AgentContext, signal?: AbortSignal) => Promise<BeforeLlmCallResult | undefined>;\n\n\t/**\n\t * Converts AgentMessage[] to LLM-compatible Message[] before each LLM call.\n\t *\n\t * Each AgentMessage must be converted to a UserMessage, AssistantMessage, or ToolResultMessage\n\t * that the LLM can understand. AgentMessages that cannot be converted (e.g., UI-only notifications,\n\t * status messages) should be filtered out.\n\t *\n\t * Contract: must not throw or reject. Return a safe fallback value instead.\n\t * Throwing interrupts the low-level agent loop without producing a normal event sequence.\n\t *\n\t * @example\n\t * ```typescript\n\t * convertToLlm: (messages) => messages.flatMap(m => {\n\t *   if (m.role === \"custom\") {\n\t *     // Convert custom message to user message\n\t *     return [{ role: \"user\", content: m.content, timestamp: m.timestamp }];\n\t *   }\n\t *   if (m.role === \"notification\") {\n\t *     // Filter out UI-only messages\n\t *     return [];\n\t *   }\n\t *   // Pass through standard LLM messages\n\t *   return [m];\n\t * })\n\t * ```\n\t */\n\tconvertToLlm: (messages: AgentMessage[]) => Message[] | Promise<Message[]>;\n\n\t/**\n\t * Optional transform applied to the context before `convertToLlm`.\n\t *\n\t * Use this for operations that work at the AgentMessage level:\n\t * - Context window management (pruning old messages)\n\t * - Injecting context from external sources\n\t *\n\t * Contract: must not throw or reject. Return the original messages or another\n\t * safe fallback value instead.\n\t *\n\t * @example\n\t * ```typescript\n\t * transformContext: async (messages) => {\n\t *   if (estimateTokens(messages) > MAX_TOKENS) {\n\t *     return pruneOldMessages(messages);\n\t *   }\n\t *   return messages;\n\t * }\n\t * ```\n\t */\n\ttransformContext?: (messages: AgentMessage[], signal?: AbortSignal) => Promise<AgentMessage[]>;\n\n\t/**\n\t * Resolves an API key dynamically for each LLM call.\n\t *\n\t * Useful for short-lived OAuth tokens (e.g., GitHub Copilot) that may expire\n\t * during long-running tool execution phases.\n\t *\n\t * Contract: must not throw or reject. Return undefined when no key is available.\n\t */\n\tgetApiKey?: (provider: string) => Promise<string | undefined> | string | undefined;\n\n\t/**\n\t * Returns steering messages to inject into the conversation mid-run.\n\t *\n\t * Called after the current assistant turn finishes executing its tool calls.\n\t * If messages are returned, they are added to the context before the next LLM call.\n\t * Tool calls from the current assistant message are not skipped.\n\t *\n\t * Use this for \"steering\" the agent while it's working.\n\t *\n\t * Contract: must not throw or reject. Return [] when no steering messages are available.\n\t */\n\tgetSteeringMessages?: () => Promise<AgentMessage[]>;\n\n\t/**\n\t * Returns follow-up messages to process after the agent would otherwise stop.\n\t *\n\t * Called when the agent has no more tool calls and no steering messages.\n\t * If messages are returned, they're added to the context and the agent\n\t * continues with another turn.\n\t *\n\t * Use this for follow-up messages that should wait until the agent finishes.\n\t *\n\t * Contract: must not throw or reject. Return [] when no follow-up messages are available.\n\t */\n\tgetFollowUpMessages?: () => Promise<AgentMessage[]>;\n\n\t/**\n\t * Tool execution mode.\n\t * - \"sequential\": execute tool calls one by one\n\t * - \"parallel\": preflight tool calls sequentially, then execute allowed tools concurrently\n\t *\n\t * Default: \"parallel\"\n\t */\n\ttoolExecution?: ToolExecutionMode;\n\n\t/**\n\t * Called before each LLM call in the inner loop. If it returns false,\n\t * the loop exits cleanly as if no more tool calls were pending.\n\t *\n\t * Use this to enforce turn limits or other dynamic stopping conditions.\n\t * The callback is NOT called before the very first LLM call of a run —\n\t * only before subsequent calls triggered by tool results or steering.\n\t */\n\tshouldContinue?: () => boolean;\n\n\t/**\n\t * Maximum number of times to retry when a stream drops mid-response.\n\t * Retries only trigger on detected stream-drop errors (connection dropped before\n\t * the provider sent its terminal completion event). Other errors are not retried.\n\t *\n\t * Default: 3\n\t */\n\tstreamRetries?: number;\n\n\t/**\n\t * Base delay in milliseconds for exponential backoff between stream retries.\n\t * Actual delay is `baseDelay * 2^attempt` (e.g., 1000, 2000, 4000).\n\t *\n\t * Default: 1000\n\t */\n\tstreamRetryBaseDelayMs?: number;\n\n\t/**\n\t * Maximum number of times to retry when a turn ends with stopReason \"length\"\n\t * (the model reached its configured output limit mid-response). Each retry\n\t * discards the truncated partial and re-issues the request at the same\n\t * `maxTokens` limit. This is SEPARATE from `streamRetries`.\n\t *\n\t * Default: 2\n\t */\n\tlengthRetries?: number;\n\n\t/**\n\t * Called before a tool is executed, after arguments have been validated.\n\t *\n\t * Return `{ block: true }` to prevent execution. The loop emits an error tool result instead.\n\t * The hook receives the agent abort signal and is responsible for honoring it.\n\t */\n\tbeforeToolCall?: (context: BeforeToolCallContext, signal?: AbortSignal) => Promise<BeforeToolCallResult | undefined>;\n\n\t/**\n\t * Called after a tool finishes executing, before final tool events are emitted.\n\t *\n\t * Return an `AfterToolCallResult` to override parts of the executed tool result:\n\t * - `content` replaces the full content array\n\t * - `details` replaces the full details payload\n\t * - `isError` replaces the error flag\n\t *\n\t * Any omitted fields keep their original values. No deep merge is performed.\n\t * The hook receives the agent abort signal and is responsible for honoring it.\n\t */\n\tafterToolCall?: (context: AfterToolCallContext, signal?: AbortSignal) => Promise<AfterToolCallResult | undefined>;\n}\n\n/**\n * Thinking/reasoning level for models that support it.\n * Note: \"xhigh\" is only supported by OpenAI reasoning models that explicitly advertise extended reasoning (for example GPT-5.2+ and Codex GPT-5.3+).\n */\nexport type ThinkingLevel = \"off\" | \"minimal\" | \"low\" | \"medium\" | \"high\" | \"xhigh\" | \"max\";\n\n/**\n * Extensible interface for custom app messages.\n * Apps can extend via declaration merging:\n *\n * @example\n * ```typescript\n * declare module \"@dreb/agent-core\" {\n *   interface CustomAgentMessages {\n *     artifact: ArtifactMessage;\n *     notification: NotificationMessage;\n *   }\n * }\n * ```\n */\nexport interface CustomAgentMessages {\n\t// Empty by default - apps extend via declaration merging\n}\n\n/**\n * AgentMessage: Union of LLM messages + custom messages.\n * This abstraction allows apps to add custom message types while maintaining\n * type safety and compatibility with the base LLM messages.\n */\nexport type AgentMessage = Message | CustomAgentMessages[keyof CustomAgentMessages];\n\n/**\n * Agent state containing all configuration and conversation data.\n */\nexport interface AgentState {\n\tsystemPrompt: string;\n\tmodel: Model<any>;\n\tthinkingLevel: ThinkingLevel;\n\ttools: AgentTool<any>[];\n\tmessages: AgentMessage[]; // Can include attachments + custom message types\n\tisStreaming: boolean;\n\tstreamMessage: AgentMessage | null;\n\tpendingToolCalls: Set<string>;\n\terror?: string;\n}\n\nexport interface AgentToolResult<T> {\n\t// Content blocks supporting text and images\n\tcontent: (TextContent | ImageContent)[];\n\t// Details to be displayed in a UI or logged\n\tdetails: T;\n\t/**\n\t * When true, the agent loop will stop after processing all tool results\n\t * from the current assistant message. No further LLM call is made.\n\t *\n\t * Use this when a tool's result means the agent should yield control\n\t * (e.g., after launching background agents that will deliver results later).\n\t */\n\tendTurn?: boolean;\n}\n\n// Callback for streaming tool execution updates\nexport type AgentToolUpdateCallback<T = any> = (partialResult: AgentToolResult<T>) => void;\n\n// AgentTool extends Tool but adds the execute function\nexport interface AgentTool<TParameters extends TSchema = TSchema, TDetails = any> extends Tool<TParameters> {\n\t// A human-readable label for the tool to be displayed in UI\n\tlabel: string;\n\texecute: (\n\t\ttoolCallId: string,\n\t\tparams: Static<TParameters>,\n\t\tsignal?: AbortSignal,\n\t\tonUpdate?: AgentToolUpdateCallback<TDetails>,\n\t) => Promise<AgentToolResult<TDetails>>;\n}\n\n// AgentContext is like Context but uses AgentTool\nexport interface AgentContext {\n\tsystemPrompt: string;\n\tmessages: AgentMessage[];\n\ttools?: AgentTool<any>[];\n}\n\n/**\n * Events emitted by the Agent for UI updates.\n * These events provide fine-grained lifecycle information for messages, turns, and tool executions.\n */\nexport type AgentEvent =\n\t// Agent lifecycle\n\t| {\n\t\t\ttype: \"agent_start\";\n\t\t\tmodel?: { provider: string; id: string };\n\t\t\t/** Effective thinking level sent to the provider for this run. */\n\t\t\tthinkingLevel?: ThinkingLevel;\n\t  }\n\t| { type: \"agent_end\"; messages: AgentMessage[] }\n\t// Turn lifecycle - a turn is one assistant response + any tool calls/results\n\t| { type: \"turn_start\" }\n\t| { type: \"turn_end\"; message: AgentMessage; toolResults: ToolResultMessage[] }\n\t// Message lifecycle - emitted for user, assistant, and toolResult messages\n\t| { type: \"message_start\"; message: AgentMessage }\n\t// Only emitted for assistant messages during streaming\n\t| { type: \"message_update\"; message: AgentMessage; assistantMessageEvent: AssistantMessageEvent }\n\t| { type: \"message_end\"; message: AgentMessage }\n\t// Tool execution lifecycle\n\t| { type: \"tool_execution_start\"; toolCallId: string; toolName: string; args: any }\n\t| { type: \"tool_execution_update\"; toolCallId: string; toolName: string; args: any; partialResult: any }\n\t| { type: \"tool_execution_end\"; toolCallId: string; toolName: string; result: any; isError: boolean }\n\t// Stream reliability\n\t| {\n\t\t\ttype: \"stream_retry\";\n\t\t\tattempt: number;\n\t\t\tmaxAttempts: number;\n\t\t\terror: string;\n\t\t\t/** Partial assistant message discarded before retry, for debugging/instrumentation only. */\n\t\t\tdiscardedPartial?: AssistantMessage;\n\t  }\n\t// Emitted when a turn ends with stopReason \"length\" and is retried at the configured output limit.\n\t| {\n\t\t\ttype: \"length_retry\";\n\t\t\tattempt: number;\n\t\t\tmaxAttempts: number;\n\t\t\t/** The maxTokens limit used for both the truncated attempt and retry. */\n\t\t\tmaxTokens: number;\n\t\t\t/** Partial assistant message discarded before retry, for debugging/instrumentation only. */\n\t\t\tdiscardedPartial?: AssistantMessage;\n\t  };\n"]}