import {
	type GenerateContentConfig,
	type GenerateContentParameters,
	GoogleGenAI,
	type ThinkingConfig,
	type ThinkingLevel,
} from "@google/genai";
import { calculateCost } from "../models.js";
import type {
	Api,
	AssistantMessage,
	Context,
	Model,
	StreamFunction,
	StreamOptions,
	TextContent,
	ThinkingContent,
	ToolCall,
} from "../types.js";
import { AssistantMessageEventStream } from "../utils/event-stream.js";
import { sanitizeSurrogates } from "../utils/sanitize-unicode.js";
import { convertMessages, convertTools, mapStopReason, mapToolChoice } from "./google-shared.js";

export interface GoogleVertexOptions extends StreamOptions {
	toolChoice?: "auto" | "none" | "any";
	thinking?: {
		enabled: boolean;
		budgetTokens?: number; // -1 for dynamic, 0 to disable
		level?: ThinkingLevel;
	};
	project?: string;
	location?: string;
}

const API_VERSION = "v1";

// Counter for generating unique tool call IDs
let toolCallCounter = 0;

export const streamGoogleVertex: StreamFunction<"google-vertex"> = (
	model: Model<"google-vertex">,
	context: Context,
	options?: GoogleVertexOptions,
): AssistantMessageEventStream => {
	const stream = new AssistantMessageEventStream();

	(async () => {
		const output: AssistantMessage = {
			role: "assistant",
			content: [],
			api: "google-vertex" as Api,
			provider: model.provider,
			model: model.id,
			usage: {
				input: 0,
				output: 0,
				cacheRead: 0,
				cacheWrite: 0,
				totalTokens: 0,
				cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
			},
			stopReason: "stop",
			timestamp: Date.now(),
		};

		try {
			const project = resolveProject(options);
			const location = resolveLocation(options);
			const client = createClient(model, project, location);
			const params = buildParams(model, context, options);
			const googleStream = await client.models.generateContentStream(params);

			stream.push({ type: "start", partial: output });
			let currentBlock: TextContent | ThinkingContent | null = null;
			const blocks = output.content;
			const blockIndex = () => blocks.length - 1;
			for await (const chunk of googleStream) {
				const candidate = chunk.candidates?.[0];
				if (candidate?.content?.parts) {
					for (const part of candidate.content.parts) {
						if (part.text !== undefined) {
							const isThinking = part.thought === true;
							if (
								!currentBlock ||
								(isThinking && currentBlock.type !== "thinking") ||
								(!isThinking && currentBlock.type !== "text")
							) {
								if (currentBlock) {
									if (currentBlock.type === "text") {
										stream.push({
											type: "text_end",
											contentIndex: blocks.length - 1,
											content: currentBlock.text,
											partial: output,
										});
									} else {
										stream.push({
											type: "thinking_end",
											contentIndex: blockIndex(),
											content: currentBlock.thinking,
											partial: output,
										});
									}
								}
								if (isThinking) {
									currentBlock = { type: "thinking", thinking: "", thinkingSignature: undefined };
									output.content.push(currentBlock);
									stream.push({ type: "thinking_start", contentIndex: blockIndex(), partial: output });
								} else {
									currentBlock = { type: "text", text: "" };
									output.content.push(currentBlock);
									stream.push({ type: "text_start", contentIndex: blockIndex(), partial: output });
								}
							}
							if (currentBlock.type === "thinking") {
								currentBlock.thinking += part.text;
								currentBlock.thinkingSignature = part.thoughtSignature;
								stream.push({
									type: "thinking_delta",
									contentIndex: blockIndex(),
									delta: part.text,
									partial: output,
								});
							} else {
								currentBlock.text += part.text;
								stream.push({
									type: "text_delta",
									contentIndex: blockIndex(),
									delta: part.text,
									partial: output,
								});
							}
						}

						if (part.functionCall) {
							if (currentBlock) {
								if (currentBlock.type === "text") {
									stream.push({
										type: "text_end",
										contentIndex: blockIndex(),
										content: currentBlock.text,
										partial: output,
									});
								} else {
									stream.push({
										type: "thinking_end",
										contentIndex: blockIndex(),
										content: currentBlock.thinking,
										partial: output,
									});
								}
								currentBlock = null;
							}

							const providedId = part.functionCall.id;
							const needsNewId =
								!providedId || output.content.some((b) => b.type === "toolCall" && b.id === providedId);
							const toolCallId = needsNewId
								? `${part.functionCall.name}_${Date.now()}_${++toolCallCounter}`
								: providedId;

							const toolCall: ToolCall = {
								type: "toolCall",
								id: toolCallId,
								name: part.functionCall.name || "",
								arguments: part.functionCall.args as Record<string, any>,
								...(part.thoughtSignature && { thoughtSignature: part.thoughtSignature }),
							};

							output.content.push(toolCall);
							stream.push({ type: "toolcall_start", contentIndex: blockIndex(), partial: output });
							stream.push({
								type: "toolcall_delta",
								contentIndex: blockIndex(),
								delta: JSON.stringify(toolCall.arguments),
								partial: output,
							});
							stream.push({ type: "toolcall_end", contentIndex: blockIndex(), toolCall, partial: output });
						}
					}
				}

				if (candidate?.finishReason) {
					output.stopReason = mapStopReason(candidate.finishReason);
					if (output.content.some((b) => b.type === "toolCall")) {
						output.stopReason = "toolUse";
					}
				}

				if (chunk.usageMetadata) {
					output.usage = {
						input: chunk.usageMetadata.promptTokenCount || 0,
						output:
							(chunk.usageMetadata.candidatesTokenCount || 0) + (chunk.usageMetadata.thoughtsTokenCount || 0),
						cacheRead: chunk.usageMetadata.cachedContentTokenCount || 0,
						cacheWrite: 0,
						totalTokens: chunk.usageMetadata.totalTokenCount || 0,
						cost: {
							input: 0,
							output: 0,
							cacheRead: 0,
							cacheWrite: 0,
							total: 0,
						},
					};
					calculateCost(model, output.usage);
				}
			}

			if (currentBlock) {
				if (currentBlock.type === "text") {
					stream.push({
						type: "text_end",
						contentIndex: blockIndex(),
						content: currentBlock.text,
						partial: output,
					});
				} else {
					stream.push({
						type: "thinking_end",
						contentIndex: blockIndex(),
						content: currentBlock.thinking,
						partial: output,
					});
				}
			}

			if (options?.signal?.aborted) {
				throw new Error("Request was aborted");
			}

			if (output.stopReason === "aborted" || output.stopReason === "error") {
				throw new Error("An unknown error occurred");
			}

			stream.push({ type: "done", reason: output.stopReason, message: output });
			stream.end();
		} catch (error) {
			// Remove internal index property used during streaming
			for (const block of output.content) {
				if ("index" in block) {
					delete (block as { index?: number }).index;
				}
			}
			output.stopReason = options?.signal?.aborted ? "aborted" : "error";
			output.errorMessage = error instanceof Error ? error.message : JSON.stringify(error);
			stream.push({ type: "error", reason: output.stopReason, error: output });
			stream.end();
		}
	})();

	return stream;
};

function createClient(model: Model<"google-vertex">, project: string, location: string): GoogleGenAI {
	const httpOptions: { headers?: Record<string, string> } = {};

	if (model.headers) {
		httpOptions.headers = { ...model.headers };
	}

	const hasHttpOptions = Object.values(httpOptions).some(Boolean);

	return new GoogleGenAI({
		vertexai: true,
		project,
		location,
		apiVersion: API_VERSION,
		httpOptions: hasHttpOptions ? httpOptions : undefined,
	});
}

function resolveProject(options?: GoogleVertexOptions): string {
	const project = options?.project || process.env.GOOGLE_CLOUD_PROJECT || process.env.GCLOUD_PROJECT;
	if (!project) {
		throw new Error(
			"Vertex AI requires a project ID. Set GOOGLE_CLOUD_PROJECT/GCLOUD_PROJECT or pass project in options.",
		);
	}
	return project;
}

function resolveLocation(options?: GoogleVertexOptions): string {
	const location = options?.location || process.env.GOOGLE_CLOUD_LOCATION;
	if (!location) {
		throw new Error("Vertex AI requires a location. Set GOOGLE_CLOUD_LOCATION or pass location in options.");
	}
	return location;
}

function buildParams(
	model: Model<"google-vertex">,
	context: Context,
	options: GoogleVertexOptions = {},
): GenerateContentParameters {
	const contents = convertMessages(model, context);

	const generationConfig: GenerateContentConfig = {};
	if (options.temperature !== undefined) {
		generationConfig.temperature = options.temperature;
	}
	if (options.maxTokens !== undefined) {
		generationConfig.maxOutputTokens = options.maxTokens;
	}

	const config: GenerateContentConfig = {
		...(Object.keys(generationConfig).length > 0 && generationConfig),
		...(context.systemPrompt && { systemInstruction: sanitizeSurrogates(context.systemPrompt) }),
		...(context.tools && context.tools.length > 0 && { tools: convertTools(context.tools) }),
	};

	if (context.tools && context.tools.length > 0 && options.toolChoice) {
		config.toolConfig = {
			functionCallingConfig: {
				mode: mapToolChoice(options.toolChoice),
			},
		};
	} else {
		config.toolConfig = undefined;
	}

	if (options.thinking?.enabled && model.reasoning) {
		const thinkingConfig: ThinkingConfig = { includeThoughts: true };
		if (options.thinking.level !== undefined) {
			thinkingConfig.thinkingLevel = options.thinking.level;
		} else if (options.thinking.budgetTokens !== undefined) {
			thinkingConfig.thinkingBudget = options.thinking.budgetTokens;
		}
		config.thinkingConfig = thinkingConfig;
	}

	if (options.signal) {
		if (options.signal.aborted) {
			throw new Error("Request aborted");
		}
		config.abortSignal = options.signal;
	}

	const params: GenerateContentParameters = {
		model: model.id,
		contents,
		config,
	};

	return params;
}