VoiceRSSSummary/services/llm.ts

import { type ClientOptions, OpenAI } from "openai";
import { config, validateConfig } from "./config.js";

// Validate config on module load
validateConfig();

const clientOptions: ClientOptions = {
  apiKey: config.openai.apiKey,
  baseURL: config.openai.endpoint,
};
const openai = new OpenAI(clientOptions);

export async function openAI_ClassifyFeed(title: string): Promise<string> {
  if (!title || title.trim() === "") {
    throw new Error("Feed title is required for classification");
  }

  const prompt = `
以下のRSSフィードのタイトルを見て、適切なトピックカテゴリに分類してください。

フィードタイトル: ${title}

以下のカテゴリから1つを選択してください:
- テクノロジー
- ビジネス
- エンターテインメント
- スポーツ
- 科学
- 健康
- 政治
- 環境
- 教育
- その他

分類結果を上記カテゴリのいずれか1つだけ返してください。
`;

  try {
    const response = await openai.chat.completions.create({
      model: config.openai.modelName,
      messages: [{ role: "user", content: prompt.trim() }],
      temperature: 0.2,
      reasoning_effort: "low",
    });

    const category = response.choices[0]?.message?.content?.trim();
    if (!category) {
      console.warn("OpenAI returned empty category, using default");
      return "その他";
    }

    return category;
  } catch (error) {
    console.error("Error classifying feed:", error);
    throw new Error(
      `Failed to classify feed: ${error instanceof Error ? error.message : "Unknown error"}`,
    );
  }
}

export async function openAI_GeneratePodcastContent(
  title: string,
  items: Array<{
    title: string;
    link: string;
    content?: string;
    description?: string;
  }>,
): Promise<string> {
  if (!title || title.trim() === "") {
    throw new Error("Feed title is required for podcast content generation");
  }

  if (!items || items.length === 0) {
    throw new Error(
      "At least one news item is required for podcast content generation",
    );
  }

  // Validate items
  const validItems = items.filter((item) => item.title && item.link);
  if (validItems.length === 0) {
    throw new Error("No valid news items found (title and link required)");
  }

  // Build detailed article information including content
  const articleDetails = validItems
    .map((item, i) => {
      let articleInfo = `${i + 1}. タイトル: ${item.title}\nURL: ${item.link}`;

      // Add content if available
      const content = item.content || item.description;
      if (content && content.trim()) {
        // Limit content length to avoid token limits
        const maxContentLength = 2000;
        const truncatedContent =
          content.length > maxContentLength
            ? content.substring(0, maxContentLength) + "..."
            : content;
        articleInfo += `\n内容: ${truncatedContent}`;
      }

      return articleInfo;
    })
    .join("\n\n");

  const prompt = `
You are a professional podcaster. Create a detailed podcast script based on the provided feed title/topic, following these specific requirements:

**Content Requirements:**
- Provide detailed summaries and analysis based on the actual content of news articles
- Translate all news article titles to Japanese and introduce them at the beginning
- Create substantive commentary that adds value beyond just reading headlines
- Conclude with a comprehensive summary of the overall topic
- The podcast name must be "自動生成ポッドキャスト"

**Format Requirements:**
- Length: 1000-5000 characters (Japanese)
- Use natural, conversational Japanese language suitable for audio
- Write in a engaging podcast style with smooth transitions between topics
- There is only **one speaker** in the podcast, so use first-person perspective

**Technical Requirements:**
- Since this will be read by Japanese Text-to-Speech, convert ALL English words, abbreviations, and acronyms to katakana
- Examples: 
  - "AI" → "エーアイ"
  - "NASA" → "ナサ" 
  - "GitHub" → "ギットハブ"
  - "OpenAI" → "オープンエーアイ"
- Don't include any urls in the script.
- Don't include any non-Japanese characters in the script.
- Apply this conversion consistently throughout the script

**Structure:**
1. Opening with translated article titles
2. Detailed discussion of each news item with context and analysis
3. Overall topic summary and conclusion

Create a valuable, informative podcast script that utilizes the actual article content rather than just surface-level information.
`;

  const sendContent = `
  FeedTitle: ${title}
  Content:
${articleDetails}
`;

  try {
    const response = await openai.chat.completions.create({
      model: config.openai.modelName,
      messages: [
        { role: "system", content: prompt.trim() },
        { role: "user", content: sendContent.trim() },
      ],
      temperature: 0.4,
      max_completion_tokens: 1700,
      reasoning_effort: "medium",
    });

    const scriptText = response.choices[0]?.message?.content?.trim();
    if (!scriptText) {
      throw new Error("OpenAI returned empty podcast content");
    }

    return scriptText;
  } catch (error) {
    console.error("Error generating podcast content:", error);
    throw new Error(
      `Failed to generate podcast content: ${error instanceof Error ? error.message : "Unknown error"}`,
    );
  }
}

export async function openAI_ClassifyEpisode(
  title: string,
  description?: string,
  content?: string,
): Promise<string> {
  if (!title || title.trim() === "") {
    throw new Error("Episode title is required for classification");
  }

  // Build the text for classification based on available data
  let textForClassification = `タイトル: ${title}`;

  if (description && description.trim()) {
    textForClassification += `\n説明: ${description}`;
  }

  if (content && content.trim()) {
    const maxContentLength = 1500;
    const truncatedContent =
      content.length > maxContentLength
        ? content.substring(0, maxContentLength) + "..."
        : content;
    textForClassification += `\n内容: ${truncatedContent}`;
  }

  const prompt = `
以下のポッドキャストエピソードの情報を見て、適切なトピックカテゴリに分類してください。

${textForClassification}

以下のカテゴリから1つを選択してください:
- テクノロジー
- ビジネス
- エンターテインメント
- スポーツ
- 科学
- 健康
- 政治
- 環境
- 教育
- その他

エピソードの内容に最も適合するカテゴリを上記から1つだけ返してください。
`;

  try {
    const response = await openai.chat.completions.create({
      model: config.openai.modelName,
      messages: [{ role: "user", content: prompt.trim() }],
      temperature: 0.2,
      reasoning_effort: "low",
    });

    const category = response.choices[0]?.message?.content?.trim();
    if (!category) {
      console.warn("OpenAI returned empty episode category, using default");
      return "その他";
    }

    return category;
  } catch (error) {
    console.error("Error classifying episode:", error);
    throw new Error(
      `Failed to classify episode: ${error instanceof Error ? error.message : "Unknown error"}`,
    );
  }
}