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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 \"@draht/ai\";\nimport type { Static, TSchema } from \"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 *   `tool_execution_end` is emitted in tool completion order after each tool is finalized,\n *   while tool-result message artifacts are emitted later in assistant source order.\n */\nexport type ToolExecutionMode = \"sequential\" | \"parallel\";\n\n/**\n * Controls how many queued user messages are injected when the agent loop reaches a queue drain point.\n *\n * - \"all\": drain and inject every queued message at that point.\n * - \"one-at-a-time\": drain and inject only the oldest queued message, leaving the rest queued for later drain points.\n */\nexport type QueueMode = \"all\" | \"one-at-a-time\";\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 * - `terminate`: if provided, replaces the early-termination hint\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\t/**\n\t * Hint that the agent should stop after the current tool batch.\n\t * Early termination only happens when every finalized tool result in the batch sets this to true.\n\t */\n\tterminate?: 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/** Context passed to `shouldStopAfterTurn`. */\nexport interface ShouldStopAfterTurnContext {\n\t/** The assistant message that completed the turn. */\n\tmessage: AssistantMessage;\n\t/** Tool result messages passed to the preceding `turn_end` event. */\n\ttoolResults: ToolResultMessage[];\n\t/** Current agent context after the turn's assistant message and tool results have been appended. */\n\tcontext: AgentContext;\n\t/** Messages that this loop invocation will return if it exits at this point. Prompt runs include the initial prompt messages; continuation runs do not include pre-existing context messages. */\n\tnewMessages: AgentMessage[];\n}\n\n/** Replacement runtime state used by the agent loop before starting another provider request. */\nexport interface AgentLoopTurnUpdate {\n\t/** Context for the next provider request. */\n\tcontext?: AgentContext;\n\t/** Model for the next provider request. */\n\tmodel?: Model<any>;\n\t/** Thinking level for the next provider request. */\n\tthinkingLevel?: ThinkingLevel;\n}\n\nexport interface PrepareNextTurnContext extends ShouldStopAfterTurnContext {}\n\nexport interface AgentLoopConfig extends SimpleStreamOptions {\n\tmodel: Model<any>;\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 * Called after each turn fully completes and `turn_end` has been emitted.\n\t *\n\t * If it returns true, the loop emits `agent_end` and exits before polling steering or follow-up queues,\n\t * without starting another LLM call. The current assistant response and any tool executions finish normally.\n\t *\n\t * Use this to request a graceful stop after the current turn, e.g. before context gets too full.\n\t *\n\t * Contract: must not throw or reject. Throwing interrupts the low-level agent loop without producing a normal event sequence.\n\t */\n\tshouldStopAfterTurn?: (context: ShouldStopAfterTurnContext) => boolean | Promise<boolean>;\n\n\t/**\n\t * Called after `turn_end` and before the loop decides whether another provider request should start.\n\t * Return replacement context/model/thinking state to affect the next turn in this run.\n\t * Return undefined to keep using the current context/config.\n\t */\n\tprepareNextTurn?: (\n\t\tcontext: PrepareNextTurnContext,\n\t) => AgentLoopTurnUpdate | undefined | Promise<AgentLoopTurnUpdate | 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, unless `shouldStopAfterTurn` exits first.\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 *   emit `tool_execution_end` in tool completion order after each tool is finalized,\n\t *   then emit tool-result message artifacts later in assistant source order\n\t *\n\t * Default: \"parallel\"\n\t */\n\ttoolExecution?: ToolExecutionMode;\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 `tool_execution_end` and tool-result message 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 * - `terminate` replaces the early-termination hint\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 selected model families. Use model thinking-level metadata\n * from @draht/ai to detect support for a concrete model.\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 \"@mariozechner/agent\" {\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 * Public agent state.\n *\n * `tools` and `messages` use accessor properties so implementations can copy\n * assigned arrays before storing them.\n */\nexport interface AgentState {\n\t/** System prompt sent with each model request. */\n\tsystemPrompt: string;\n\t/** Active model used for future turns. */\n\tmodel: Model<any>;\n\t/** Requested reasoning level for future turns. */\n\tthinkingLevel: ThinkingLevel;\n\t/** Available tools. Assigning a new array copies the top-level array. */\n\tset tools(tools: AgentTool<any>[]);\n\tget tools(): AgentTool<any>[];\n\t/** Conversation transcript. Assigning a new array copies the top-level array. */\n\tset messages(messages: AgentMessage[]);\n\tget messages(): AgentMessage[];\n\t/**\n\t * True while the agent is processing a prompt or continuation.\n\t *\n\t * This remains true until awaited `agent_end` listeners settle.\n\t */\n\treadonly isStreaming: boolean;\n\t/** Partial assistant message for the current streamed response, if any. */\n\treadonly streamingMessage?: AgentMessage;\n\t/** Tool call ids currently executing. */\n\treadonly pendingToolCalls: ReadonlySet<string>;\n\t/** Error message from the most recent failed or aborted assistant turn, if any. */\n\treadonly errorMessage?: string;\n}\n\n/** Final or partial result produced by a tool. */\nexport interface AgentToolResult<T> {\n\t/** Text or image content returned to the model. */\n\tcontent: (TextContent | ImageContent)[];\n\t/** Arbitrary structured details for logs or UI rendering. */\n\tdetails: T;\n\t/**\n\t * Hint that the agent should stop after the current tool batch.\n\t * Early termination only happens when every finalized tool result in the batch sets this to true.\n\t */\n\tterminate?: boolean;\n}\n\n/** Callback used by tools to stream partial execution updates. */\nexport type AgentToolUpdateCallback<T = any> = (partialResult: AgentToolResult<T>) => void;\n\n/** Tool definition used by the agent runtime. */\nexport interface AgentTool<TParameters extends TSchema = TSchema, TDetails = any> extends Tool<TParameters> {\n\t/** Human-readable label for UI display. */\n\tlabel: string;\n\t/**\n\t * Optional compatibility shim for raw tool-call arguments before schema validation.\n\t * Must return an object that matches `TParameters`.\n\t */\n\tprepareArguments?: (args: unknown) => Static<TParameters>;\n\t/** Execute the tool call. Throw on failure instead of encoding errors in `content`. */\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\t/**\n\t * Per-tool execution mode override.\n\t * - \"sequential\": this tool must execute one at a time with other tool calls.\n\t * - \"parallel\": this tool can execute concurrently with other tool calls.\n\t *\n\t * If omitted, the default execution mode applies.\n\t */\n\texecutionMode?: ToolExecutionMode;\n}\n\n/** Context snapshot passed into the low-level agent loop. */\nexport interface AgentContext {\n\t/** System prompt included with the request. */\n\tsystemPrompt: string;\n\t/** Transcript visible to the model. */\n\tmessages: AgentMessage[];\n\t/** Tools available for this run. */\n\ttools?: AgentTool<any>[];\n}\n\n/**\n * Events emitted by the Agent for UI updates.\n *\n * `agent_end` is the last event emitted for a run, but awaited `Agent.subscribe()`\n * listeners for that event are still part of run settlement. The agent becomes\n * idle only after those listeners finish.\n */\nexport type AgentEvent =\n\t// Agent lifecycle\n\t| { type: \"agent_start\" }\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"]}