Function getLLMRequestChat

lib/queryLLM.ts:179–349

(
  messages: ChatGPTMessage[],
  params: ChatGPTParams = {},
  model: string,
)

}

function getLLMRequestChat(
  messages: ChatGPTMessage[],
  params: ChatGPTParams = {},
  model: string,
): {
  url: string;
  options: { method: string; headers: HeadersInit; body: string };
} {
  const isOpenAIModel = model.includes("gpt");
  const isMistralModel = model.includes("mistral");
  const isPhindModel = model.includes("Phind");
  const isAnthropicModel = model.includes("anthropic");
  const isGroqModel = model.startsWith("groq");
  const isOS = isOSModel(model);

  let key: string, url: string;
  if (isOpenAIModel) {
    key = process.env.OPENAI_API_KEY!;
    url = "https://api.openai.com/v1/chat/completions";
  } else if (isGroqModel) {
    key = process.env.GROQ_API_KEY!;
    url = "https://api.groq.com/openai/v1/chat/completions";
    model = model.split("/")[1];
  } else if (isMistralModel) {
    key = process.env.MISTRAL_API_KEY!;
    url = "https://api.mistral.ai/v1/chat/completions";
    delete defaultParams.frequency_penalty;
    delete defaultParams.presence_penalty;
    // Mistral doesn't know about function messages & is fussy about only replying to user messages!
    // Below stringify-parse is deepcopy
    messages = JSON.parse(JSON.stringify(messages)).map((m: ChatGPTMessage) =>
      m.role !== "function"
        ? { ...m }
        : { role: "user", content: `${m.name} output: ${m.content}` },
    );
  } else if (isAnthropicModel && model.includes("claude-instant")) {
    const prompt = GPTChatFormatToClaudeInstant(messages);
    const max_tokens_to_sample = params.max_tokens;
    const stop_sequences = params.stop;
    const localParams = { ...params };
    delete localParams.max_tokens;
    delete localParams.stop;
    return {
      url: "https://api.anthropic.com/v1/complete",
      options: {
        method: "POST",
        headers: {
          "x-api-key": process.env.ANTHROPIC_API_KEY ?? "",
          "Content-Type": "application/json",
          "anthropic-version": "2023-06-01",
        },
        body: JSON.stringify({
          ...localParams,
          max_tokens_to_sample,
          stop_sequences,
          model: model.split("/")[1],
          prompt: prompt,
        }),