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import { AZURE_DEPLOYMENT_ID, OPENAI_API_HOST, OPENAI_API_TYPE, OPENAI_API_VERSION, OPENAI_ORGANIZATION } from './pages/api/llm';
import { createParser } from 'eventsource-parser';

export class OpenAIError extends Error {
  constructor(message, type, param, code) {
    super(message);
    this.name = 'OpenAIError';
    this.type = type;
    this.param = param;
    this.code = code;
  }
}

export const OpenAIStream = async (
  model,
  systemPrompt,
  temperature,
  key,
  messages
) => {
  let url = `${OPENAI_API_HOST}/v1/chat/completions`;
  if (OPENAI_API_TYPE === 'azure') {
    url = `${OPENAI_API_HOST}/openai/deployments/${AZURE_DEPLOYMENT_ID}/chat/completions?api-version=${OPENAI_API_VERSION}`;
  }
  const res = await fetch(url, {
    headers: {
      'Content-Type': 'application/json',
      ...(OPENAI_API_TYPE === 'openai' && {
        Authorization: `Bearer ${key ? key : process.env.OPENAI_API_KEY}`
      }),
      ...(OPENAI_API_TYPE === 'azure' && {
        'api-key': `${key ? key : process.env.OPENAI_API_KEY}`
      }),
      ...((OPENAI_API_TYPE === 'openai' && OPENAI_ORGANIZATION) && {
        'OpenAI-Organization': OPENAI_ORGANIZATION,
      }),
    },
    method: 'POST',
    body: JSON.stringify({
      ...(OPENAI_API_TYPE === 'openai' && {model: model.id}),
      messages: [
        {
          role: 'system',
          content: systemPrompt,
        },
        ...messages,
      ],
      max_tokens: 1000,
      temperature: temperature,
      stream: true,
    }),
  });

  const encoder = new TextEncoder();
  const decoder = new TextDecoder();

  if (res.status !== 200) {
    const result = await res.json();
    if (result.error) {
      throw new OpenAIError(
        result.error.message,
        result.error.type,
        result.error.param,
        result.error.code,
      );
    } else {
      throw new Error(
        `OpenAI API returned an error: ${
          decoder.decode(result?.value) || result.statusText
        }`,
      );
    }
  }

  const stream = new ReadableStream({
    async start(controller) {
      const onParse = async (event) => {
        if (event.type === 'event') {
          const data = event.data;

          try {
            const json = JSON.parse(data);
            if (json.choices[0].finish_reason === "stop") {
              controller.close();
              return;
            } else if (json.choices[0].finish_reason === "function_call") {
                const fnName = json.choices[0].message.function_call.name;
                const args = json.choices[0].message.function_call.arguments;
            
                const fn = functions[fnName];
                const result = await fn(...Object.values(JSON.parse(args)));
            
                console.log(`Function call: ${fnName}, Arguments: ${args}`);
                console.log(`Calling Function ${fnName} Result: ` + result);
            
                messages.push({
                    role: "assistant",
                    content: "",
                    function_call: {
                    name: fnName,
                    arguments: args,
                    },
                });
            
                messages.push({
                    role: "function",
                    name: fnName,
                    content: JSON.stringify({ result: result }),
                });
                }
            const text = json.choices[0].delta.content;
            const queue = encoder.encode(text);
            controller.enqueue(queue);
          } catch (e) {
            controller.error(e);
          }
        }
      };

      const parser = createParser(onParse);

      for await (const chunk of res.body) {
        parser.feed(decoder.decode(chunk));
      }
    },
  });

  return stream;
};