import { performance } from "node:perf_hooks";
import { prisma } from "../db.js";
import { anthropicClient, openaiClient, xaiClient } from "./providers.js";
import { buildToolLogMessageData, runToolAwareOpenAIChatStream, type ToolExecutionEvent } from "./chat-tools.js";
import { buildAnthropicConversationMessage, getAnthropicSystemPrompt } from "./message-content.js";
import type { MultiplexRequest, Provider } from "./types.js";

export type StreamEvent =
  | { type: "meta"; chatId: string; callId: string; provider: Provider; model: string }
  | { type: "tool_call"; event: ToolExecutionEvent }
  | { type: "delta"; text: string }
  | { type: "done"; text: string; usage?: { inputTokens?: number; outputTokens?: number; totalTokens?: number } }
  | { type: "error"; message: string };

function getChatIdOrCreate(chatId?: string) {
  if (chatId) return Promise.resolve(chatId);
  return prisma.chat.create({ data: {}, select: { id: true } }).then((c) => c.id);
}

export async function* runMultiplexStream(req: MultiplexRequest): AsyncGenerator<StreamEvent> {
  const t0 = performance.now();
  const chatId = await getChatIdOrCreate(req.chatId);

  const call = await prisma.llmCall.create({
    data: {
      chatId,
      provider: req.provider as any,
      model: req.model,
      request: req as any,
    },
    select: { id: true },
  });

  await prisma.$transaction([
    prisma.chat.update({
      where: { id: chatId },
      data: {
        lastUsedProvider: req.provider as any,
        lastUsedModel: req.model,
      },
    }),
    prisma.chat.updateMany({
      where: { id: chatId, initiatedProvider: null },
      data: {
        initiatedProvider: req.provider as any,
        initiatedModel: req.model,
      },
    }),
  ]);

  yield { type: "meta", chatId, callId: call.id, provider: req.provider, model: req.model };

  let text = "";
  let usage: StreamEvent extends any ? any : never;
  let raw: unknown = { streamed: true };
  let toolMessages: ReturnType<typeof buildToolLogMessageData>[] = [];

  try {
    if (req.provider === "openai" || req.provider === "xai") {
      const client = req.provider === "openai" ? openaiClient() : xaiClient();
      for await (const ev of runToolAwareOpenAIChatStream({
        client,
        model: req.model,
        messages: req.messages,
        temperature: req.temperature,
        maxTokens: req.maxTokens,
        logContext: {
          provider: req.provider,
          model: req.model,
          chatId,
        },
      })) {
        if (ev.type === "delta") {
          text += ev.text;
          yield { type: "delta", text: ev.text };
          continue;
        }

        if (ev.type === "tool_call") {
          toolMessages.push(buildToolLogMessageData(chatId, ev.event));
          yield { type: "tool_call", event: ev.event };
          continue;
        }

        raw = ev.result.raw;
        usage = ev.result.usage;
        text = ev.result.text;
      }
    } else if (req.provider === "anthropic") {
      const client = anthropicClient();

      const system = getAnthropicSystemPrompt(req.messages);
      const msgs = req.messages.filter((message) => message.role !== "system").map((message) => buildAnthropicConversationMessage(message));

      const stream = await client.messages.create({
        model: req.model,
        system,
        max_tokens: req.maxTokens ?? 1024,
        temperature: req.temperature,
        messages: msgs as any,
        stream: true,
      });

      for await (const ev of stream as any as AsyncIterable<any>) {
        // Anthropic streaming events include content_block_delta with text_delta
        if (ev?.type === "content_block_delta" && ev?.delta?.type === "text_delta") {
          const delta = ev.delta.text ?? "";
          if (delta) {
            text += delta;
            yield { type: "delta", text: delta };
          }
        }
        // capture usage if present on message_delta
        if (ev?.type === "message_delta" && ev?.usage) {
          usage = {
            inputTokens: ev.usage.input_tokens,
            outputTokens: ev.usage.output_tokens,
            totalTokens:
              (ev.usage.input_tokens ?? 0) + (ev.usage.output_tokens ?? 0),
          };
        }
        // some streams end with message_stop
      }
      raw = { streamed: true, provider: "anthropic" };
    } else {
      throw new Error(`unknown provider: ${req.provider}`);
    }

    const latencyMs = Math.round(performance.now() - t0);

    await prisma.$transaction(async (tx) => {
      if (toolMessages.length) {
        await tx.message.createMany({
          data: toolMessages.map((message) => ({
            chatId: message.chatId,
            role: message.role as any,
            content: message.content,
            name: message.name,
            metadata: message.metadata as any,
          })),
        });
      }
      await tx.message.create({
        data: { chatId, role: "assistant" as any, content: text },
      });
      await tx.llmCall.update({
        where: { id: call.id },
        data: {
          response: raw as any,
          latencyMs,
          inputTokens: usage?.inputTokens,
          outputTokens: usage?.outputTokens,
          totalTokens: usage?.totalTokens,
        },
      });
    });

    yield { type: "done", text, usage };
  } catch (e: any) {
    const latencyMs = Math.round(performance.now() - t0);
    await prisma.llmCall.update({
      where: { id: call.id },
      data: {
        error: e?.message ?? String(e),
        latencyMs,
      },
    });
    yield { type: "error", message: e?.message ?? String(e) };
  }
}