import { AbstractAgent, BaseEvent, RunAgentInput } from "@ag-ui/client";
import { BaseChatModel } from "@langchain/core/language_models/chat_models";
import { AIMessage, AIMessageChunk, BaseMessage, BaseMessageChunk } from "@langchain/core/messages";
import { DynamicStructuredTool } from "@langchain/core/tools";
import { IterableReadableStream } from "@langchain/core/utils/stream";
import { Observable } from "rxjs";

//#region src/streaming.d.ts
/**
 * LangChain response types that can be returned from chainFn
 */
type LangChainResponse = string | AIMessage | AIMessageChunk | BaseMessageChunk | IterableReadableStream<BaseMessageChunk> | IterableReadableStream<AIMessageChunk>;
//#endregion
//#region src/agent.d.ts
/**
 * Parameters passed to chainFn callback
 */
interface ChainFnParams {
  /**
   * Converted LangChain messages
   */
  messages: BaseMessage[];
  /**
   * Converted LangChain tools
   */
  tools: DynamicStructuredTool[];
  /**
   * Application state (can be edited via state tools)
   */
  state?: any;
  /**
   * Application context
   */
  context: Array<{
    description: string;
    value: string;
  }>;
  /**
   * Thread ID
   */
  threadId: string;
  /**
   * Run ID
   */
  runId: string;
  /**
   * Per-request HTTP headers forwarded from the runtime (e.g. x-aimock-context).
   * Undefined when no headers are set on the agent instance.
   */
  headers?: Record<string, string>;
}
/**
 * Configuration for advanced usage with custom LangChain logic
 */
interface LangChainAgentChainFnConfig {
  /**
   * Custom function that handles LangChain execution
   * This allows full control over chains, graphs, and custom logic
   */
  chainFn: (params: ChainFnParams) => Promise<LangChainResponse> | LangChainResponse;
}
/**
 * Configuration for simple usage with direct model
 */
interface LangChainAgentModelConfig {
  /**
   * LangChain chat model instance
   */
  model: BaseChatModel;
  /**
   * Optional system prompt
   */
  prompt?: string;
  /**
   * Options to pass to bindTools()
   */
  bindToolsOptions?: Record<string, any>;
}
/**
 * Dual configuration: either chainFn OR model
 */
type LangChainAgentConfig = LangChainAgentChainFnConfig | LangChainAgentModelConfig;
/**
 * LangChain Agent - bridges AG-UI and LangChain ecosystems
 *
 * Supports two usage patterns:
 *
 * 1. Advanced (chainFn): Full control over LangChain execution
 * ```typescript
 * new LangChainAgent({
 *   chainFn: async ({ messages, tools }) => {
 *     const model = new ChatOpenAI({ model: "gpt-4" });
 *     return model.bindTools(tools).stream(messages);
 *   }
 * })
 * ```
 *
 * 2. Simple (model): Direct model usage with automatic plumbing
 * ```typescript
 * new LangChainAgent({
 *   model: new ChatOpenAI({ model: "gpt-4" }),
 *   prompt: "You are a helpful assistant"
 * })
 * ```
 */
declare class LangChainAgent extends AbstractAgent {
  private config;
  private abortController?;
  /**
   * Per-request HTTP headers to forward to the underlying LLM provider.
   * Set by CopilotKit Runtime via configureAgentForRequest() to propagate
   * x-aimock-context, x-aimock-strict, x-test-id, and other forwarded headers.
   */
  headers?: Record<string, string>;
  constructor(config: LangChainAgentConfig);
  run(input: RunAgentInput): Observable<BaseEvent>;
  /**
   * Build system prompt with context and state
   */
  private buildSystemPrompt;
  clone(): LangChainAgent;
  abortRun(): void;
}
//#endregion
export { ChainFnParams, LangChainAgent, LangChainAgentChainFnConfig, LangChainAgentConfig, LangChainAgentModelConfig };
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