import { Injectable } from "@nestjs/common";
import type { LLMProvider } from "./llm-provider.js";
import type { GenerationContext, GeneratedResponse } from "./types.js";
import { buildMessages } from "./prompt-builder.js";
import { extractActions } from "./action-markup.js";

interface OpenAiCompatibleChoice {
  message?: { content?: string };
  delta?: { content?: string };
}
interface OpenAiCompatibleResponse {
  choices?: OpenAiCompatibleChoice[];
}

function baseUrl(): string {
  return process.env.CLAUDE_BASE_URL ?? "http://localhost:3000/api/v1";
}

function apiKey(): string {
  const key = process.env.CLAUDE_API_KEY;
  if (!key) {
    throw new Error("CLAUDE_API_KEY 未設定，LLM_PROVIDER=claude 需要這個環境變數才能呼叫真實 API");
  }
  return key;
}

function model(): string {
  return process.env.CLAUDE_MODEL ?? "claude-sonnet-4-5";
}

async function requestChatCompletion(body: Record<string, unknown>): Promise<Response> {
  const res = await fetch(`${baseUrl()}/chat/completions`, {
    method: "POST",
    headers: {
      "Content-Type": "application/json",
      Authorization: `Bearer ${apiKey()}`,
    },
    body: JSON.stringify(body),
  });
  if (!res.ok) {
    const text = await res.text().catch(() => "");
    throw new Error(`ClaudeProvider 呼叫失敗（HTTP ${res.status}）：${text.slice(0, 500)}`);
  }
  return res;
}

// R-3：把 F-2 的空殼換成真的呼叫。這個部署走 CLIProxy（分散式派工代理，見
// gitea.jsc.idv.tw/jiantw83/CLIProxy）提供的 OpenAI 相容端點，而不是直連
// api.anthropic.com——底層仍是 Claude，只是多一層派工代理，對這個介面
// （LLMProvider.generate/stream）完全透明，切換供應商不需要動任何呼叫端程式碼。
@Injectable()
export class ClaudeProvider implements LLMProvider {
  async generate(context: GenerationContext): Promise<GeneratedResponse> {
    const res = await requestChatCompletion({
      model: model(),
      messages: buildMessages(context),
      stream: false,
    });
    const json = (await res.json()) as OpenAiCompatibleResponse;
    const text = json.choices?.[0]?.message?.content ?? "";
    if (!text) {
      throw new Error("ClaudeProvider 回應內容為空（choices[0].message.content 缺失）");
    }
    return { text, actions: extractActions(text) };
  }

  async *stream(context: GenerationContext): AsyncIterable<string> {
    const res = await requestChatCompletion({
      model: model(),
      messages: buildMessages(context),
      stream: true,
    });
    if (!res.body) {
      throw new Error("ClaudeProvider 串流回應沒有 body");
    }
    const reader = res.body.getReader();
    const decoder = new TextDecoder();
    let buffer = "";
    while (true) {
      const { done, value } = await reader.read();
      if (done) break;
      buffer += decoder.decode(value, { stream: true });
      const lines = buffer.split("\n");
      buffer = lines.pop() ?? "";
      for (const line of lines) {
        const trimmed = line.trim();
        if (!trimmed.startsWith("data:")) continue;
        const payload = trimmed.slice("data:".length).trim();
        if (payload === "[DONE]") return;
        let chunk: OpenAiCompatibleResponse;
        try {
          chunk = JSON.parse(payload);
        } catch {
          continue;
        }
        const delta = chunk.choices?.[0]?.delta?.content;
        if (delta) yield delta;
      }
    }
  }
}