import { logOpenRouterCall } from './openRouterLogger.js';

function parseResponse(response) {
  if(!response?.usage?.cost) console.log(response);
  console.log('OpenRouter API call cost:', response?.usage);
  return { 
    cost: response?.usage?.cost,
    prompt_tokens: response?.usage?.prompt_tokens,
    completion_tokens: response?.usage?.completion_tokens,
    data: JSON.parse(response.choices[0].message.content) 
  };
}

export async function summarizeSources({ openrouter, text, question }) {
  const prompt = `
    You are a search result analyst.
    Based on the following search results for the query "${question}",
    provide a list of relevant sources with their full weblink with a concise summary for each source.
  `;

  const params = {
    model: 'openai/gpt-oss-120b:nitro',
    messages: [
      { role: 'system', content: prompt },
      { role: 'user', content: text },
    ],
    reasoning: { effort: 'low' },
    response_format: {
      type: 'json_schema',
      json_schema: {
        name: 'search_summaries',
        strict: true,
        schema: {
          type: 'object',
          required: ['sources'],
          additionalProperties: false,
          properties: {
            sources: {
              type: 'array',
              items: {
                type: 'object',
                required: ['url', 'summary'],
                additionalProperties: false,
                properties: {
                  url: { type: 'string', description: 'Full URL of the source' },
                  summary: { type: 'string', description: 'Concise summary of the content' },
                },
              },
            },
          },
        },
      },
    },
    stream: false,
  };

  // Using direct fetch API instead of OpenRouter SDK
  const apiKey = process.env.OPENROUTER_API_KEY;
  const fetchResponse = await fetch('https://openrouter.ai/api/v1/chat/completions', {
    method: 'POST',
    headers: {
      Authorization: `Bearer ${apiKey}`,
      'Content-Type': 'application/json',
    },
    body: JSON.stringify(params),
  });
  const response = await fetchResponse.json();
  await logOpenRouterCall('summarizeSources', text, params, response);
  return parseResponse(response);
}

export async function rephraseQuestion({ question, previousClarification, originalQuestion }) {

  if(previousClarification) {
    const prompt = `
      You are a search query expert. You are given a question and you return
      a search query for a web search engine that would return the best results to answer the question. 
      Do NOT restrict the query using site: operator.
      Also give a list of 2 supplementary search queries to deepen the search. 
      Today is the date of ${new Date().toLocaleDateString()}. 
      The user has provided this clarification "${previousClarification}" to the original question: ` + originalQuestion;

    const params = {
      model: 'openai/gpt-5.4-mini',
      messages: [
        { role: 'system', content: prompt },
        { role: 'user', content: question },
      ],
      reasoning: { effort: 'none' },
      stream: false,
      response_format: {
        type: 'json_schema', json_schema: { 
          name: 'queries', strict: true, schema: {
            required: [ 'query', 'supplementaryQueries'], type: 'object', additionalProperties: false, properties: {
              query: { type: 'string' },
              supplementaryQueries: { type: 'array', items: { type: 'string' } },
      } } } } 
    };

    const apiKey = process.env.OPENROUTER_API_KEY;
    const fetchResponse = await fetch('https://openrouter.ai/api/v1/chat/completions', {
      method: 'POST',
      headers: {
        Authorization: `Bearer ${apiKey}`,
        'Content-Type': 'application/json',
      },
      body: JSON.stringify(params),
    });
    const response = await fetchResponse.json();
    await logOpenRouterCall('rephraseQuestion', question,params, response);
    return parseResponse(response);
  }


  const prompt = `
    You are a search query expert. You are given a question and you return
    a search query for a web search engine that would return the best results to answer the question. 
    Do NOT restrict the query using site: operator.
    Also give a list of 2 supplementary search queries to deepen the search. 
    Today is the date of ${new Date().toLocaleDateString()}. 
    The user cannot ask questions that a web search engine cannot answer. 
    Like "Who are you". 
    If the question is ambiguous or unsuited for a web search, you can ask for clarification.
    ${previousClarification ? `The user has provided this clarification to the original question: "${previousClarification}". Use this clarification to refine the search query.` : ''}
  `;

  const params = {
    model: 'openai/gpt-5.4-mini',
    messages: [
      { role: 'system', content: prompt },
      { role: 'user', content: question },
    ],
    reasoning: { effort: 'none' },
    stream: false,
    response_format: {
      type: 'json_schema', json_schema: { 
        name: 'queries', strict: true, schema: {
          required: ['needsClarification', 'clarification', 'query', 'supplementaryQueries'], type: 'object', additionalProperties: false, properties: {
            needsClarification: { type: 'boolean', description: 'Indicates if the question is ambiguous and needs clarification' },
            clarification: { type: 'string', description: 'If needsClarification is true, this field contains the clarification question to ask the user. Otherwise, it is an empty string.' },
            query: { type: 'string' },
            supplementaryQueries: { type: 'array', items: { type: 'string' } },
    } } } } 
  };

  const apiKey = process.env.OPENROUTER_API_KEY;
  const fetchResponse = await fetch('https://openrouter.ai/api/v1/chat/completions', {
    method: 'POST',
    headers: {
      Authorization: `Bearer ${apiKey}`,
      'Content-Type': 'application/json',
    },
    body: JSON.stringify(params),
  });
  const response = await fetchResponse.json();
  await logOpenRouterCall('rephraseQuestion', question,params, response);
  return parseResponse(response);
}

export async function summarizeFinalAnswer({ openrouter, text, question }) {
  const prompt = `
    You are a search result analyst. Today is the date of ${new Date().toLocaleDateString()}.
    Based on the following search results for the query "${question}",
    Summarize the search results to answer the original query. Use Emoji and HTML. Tags allowed: <b>, <i>, <u>, <pre>, <ul>, <li>, <span style="color:...">, <p> <div> <hr/>
    Also provide the most relevant sources. Answer in the language of the question. You may suggest followup searched to the user.
  `;

  const params = {
    model: 'openai/gpt-oss-120b:nitro',
    messages: [
      { role: 'system', content: prompt },
      { role: 'user', content: text },
    ],
    reasoning: { effort: 'low' },
    response_format: {
      type: 'json_schema',
      json_schema: {
        name: 'response',
        strict: true,
        schema: {
          type: 'object',
          required: ['fullAnswerHTMLSnippet', 'mostRelevantSources', 'suggestedSearches'],
          properties: {
            fullAnswerHTMLSnippet: { type: 'string' },
            mostRelevantSources: { type: 'array', items: { type: 'string' } },
            suggestedSearches: { type: 'array', items: { type: 'string' } },
          },
        },
      },
    },
    stream: false,
  };

  // Using direct fetch API instead of OpenRouter SDK
  const apiKey = process.env.OPENROUTER_API_KEY;
  const fetchResponse = await fetch('https://openrouter.ai/api/v1/chat/completions', {
    method: 'POST',
    headers: {
      Authorization: `Bearer ${apiKey}`,
      'Content-Type': 'application/json',
    },
    body: JSON.stringify(params),
  });
  const response = await fetchResponse.json();
  
  await logOpenRouterCall('summarizeFinalAnswer', text, params, response);
  
  return parseResponse(response);
}