import {
	type Content,
	FinishReason,
	FunctionCallingConfigMode,
	type GenerateContentConfig,
	type GenerateContentParameters,
	GoogleGenAI,
	type Part,
} from "@google/genai";
import { calculateCost } from "../models.js";
import type {
	Api,
	AssistantMessage,
	Context,
	Model,
	StopReason,
	StreamFunction,
	StreamOptions,
	TextContent,
	ThinkingContent,
	Tool,
	ToolCall,
} from "../types.js";
import { AssistantMessageEventStream } from "../utils/event-stream.js";
import { sanitizeSurrogates } from "../utils/sanitize-unicode.js";
import { validateToolArguments } from "../utils/validation.js";
import { transformMessages } from "./transorm-messages.js";

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

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

export const streamGoogle: StreamFunction<"google-generative-ai"> = (
	model: Model<"google-generative-ai">,
	context: Context,
	options?: GoogleOptions,
): AssistantMessageEventStream => {
	const stream = new AssistantMessageEventStream();

	(async () => {
		const output: AssistantMessage = {
			role: "assistant",
			content: [],
			api: "google-generative-ai" 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 client = createClient(model, options?.apiKey);
			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;
							}

							// Generate unique ID if not provided or if it's a duplicate
							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 }),
							};

							// Validate tool arguments if tool definition is available
							if (context.tools) {
								const tool = context.tools.find((t) => t.name === toolCall.name);
								if (tool) {
									toolCall.arguments = validateToolArguments(tool, toolCall);
								}
							}

							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 unkown error ocurred");
			}

			stream.push({ type: "done", reason: output.stopReason, message: output });
			stream.end();
		} catch (error) {
			for (const block of output.content) delete (block as any).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-generative-ai">, apiKey?: string): GoogleGenAI {
	if (!apiKey) {
		if (!process.env.GEMINI_API_KEY) {
			throw new Error(
				"Gemini API key is required. Set GEMINI_API_KEY environment variable or pass it as an argument.",
			);
		}
		apiKey = process.env.GEMINI_API_KEY;
	}
	return new GoogleGenAI({
		apiKey,
		httpOptions: model.headers ? { headers: model.headers } : undefined,
	});
}

function buildParams(
	model: Model<"google-generative-ai">,
	context: Context,
	options: GoogleOptions = {},
): 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) {
		config.thinkingConfig = {
			includeThoughts: true,
			...(options.thinking.budgetTokens !== undefined && { thinkingBudget: options.thinking.budgetTokens }),
		};
	}

	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;
}
function convertMessages(model: Model<"google-generative-ai">, context: Context): Content[] {
	const contents: Content[] = [];
	const transformedMessages = transformMessages(context.messages, model);

	for (const msg of transformedMessages) {
		if (msg.role === "user") {
			if (typeof msg.content === "string") {
				contents.push({
					role: "user",
					parts: [{ text: sanitizeSurrogates(msg.content) }],
				});
			} else {
				const parts: Part[] = msg.content.map((item) => {
					if (item.type === "text") {
						return { text: sanitizeSurrogates(item.text) };
					} else {
						return {
							inlineData: {
								mimeType: item.mimeType,
								data: item.data,
							},
						};
					}
				});
				const filteredParts = !model.input.includes("image") ? parts.filter((p) => p.text !== undefined) : parts;
				if (filteredParts.length === 0) continue;
				contents.push({
					role: "user",
					parts: filteredParts,
				});
			}
		} else if (msg.role === "assistant") {
			const parts: Part[] = [];

			for (const block of msg.content) {
				if (block.type === "text") {
					parts.push({ text: sanitizeSurrogates(block.text) });
				} else if (block.type === "thinking") {
					const thinkingPart: Part = {
						thought: true,
						thoughtSignature: block.thinkingSignature,
						text: sanitizeSurrogates(block.thinking),
					};
					parts.push(thinkingPart);
				} else if (block.type === "toolCall") {
					const part: Part = {
						functionCall: {
							id: block.id,
							name: block.name,
							args: block.arguments,
						},
					};
					if (block.thoughtSignature) {
						part.thoughtSignature = block.thoughtSignature;
					}
					parts.push(part);
				}
			}

			if (parts.length === 0) continue;
			contents.push({
				role: "model",
				parts,
			});
		} else if (msg.role === "toolResult") {
			// Build parts array with functionResponse and/or images
			const parts: Part[] = [];

			// Extract text and image content
			const textResult = msg.content
				.filter((c) => c.type === "text")
				.map((c) => (c as any).text)
				.join("\n");
			const imageBlocks = model.input.includes("image") ? msg.content.filter((c) => c.type === "image") : [];

			// Always add functionResponse with text result (or placeholder if only images)
			const hasText = textResult.length > 0;
			const hasImages = imageBlocks.length > 0;

			parts.push({
				functionResponse: {
					id: msg.toolCallId,
					name: msg.toolName,
					response: {
						result: hasText ? sanitizeSurrogates(textResult) : hasImages ? "(see attached image)" : "",
						isError: msg.isError,
					},
				},
			});

			// Add any images as inlineData parts
			for (const imageBlock of imageBlocks) {
				parts.push({
					inlineData: {
						mimeType: (imageBlock as any).mimeType,
						data: (imageBlock as any).data,
					},
				});
			}

			contents.push({
				role: "user",
				parts,
			});
		}
	}

	return contents;
}

function convertTools(tools: Tool[]): any[] | undefined {
	if (tools.length === 0) return undefined;
	return [
		{
			functionDeclarations: tools.map((tool) => ({
				name: tool.name,
				description: tool.description,
				parameters: tool.parameters as any, // TypeBox already generates JSON Schema
			})),
		},
	];
}

function mapToolChoice(choice: string): FunctionCallingConfigMode {
	switch (choice) {
		case "auto":
			return FunctionCallingConfigMode.AUTO;
		case "none":
			return FunctionCallingConfigMode.NONE;
		case "any":
			return FunctionCallingConfigMode.ANY;
		default:
			return FunctionCallingConfigMode.AUTO;
	}
}

function mapStopReason(reason: FinishReason): StopReason {
	switch (reason) {
		case FinishReason.STOP:
			return "stop";
		case FinishReason.MAX_TOKENS:
			return "length";
		case FinishReason.BLOCKLIST:
		case FinishReason.PROHIBITED_CONTENT:
		case FinishReason.SPII:
		case FinishReason.SAFETY:
		case FinishReason.IMAGE_SAFETY:
		case FinishReason.IMAGE_PROHIBITED_CONTENT:
		case FinishReason.RECITATION:
		case FinishReason.FINISH_REASON_UNSPECIFIED:
		case FinishReason.OTHER:
		case FinishReason.LANGUAGE:
		case FinishReason.MALFORMED_FUNCTION_CALL:
		case FinishReason.UNEXPECTED_TOOL_CALL:
		case FinishReason.NO_IMAGE:
			return "error";
		default: {
			const _exhaustive: never = reason;
			throw new Error(`Unhandled stop reason: ${_exhaustive}`);
		}
	}
}