import { addMessage, getHistoryString } from "@/utils/chatHistory";
import React, { useEffect } from "react";

export const useChatGpt = (message, promptId, chatHistory) => {
  // Send user meesage to api, meesage and prompt in body
  // then update state value with response
  //   console.log("Hook api call", message, promptId);
  const [data, setData] = React.useState("");
  const [isLoading, setIsLoading] = React.useState(false);
  const [isError, setIsError] = React.useState(false);
  const [history, setHistory] = React.useState(chatHistory);
  const [isSuccess, setIsSuccess] = React.useState(false);

  const fetchData = async () => {
    setIsLoading(true);
    try {
      const response = await fetch("/api/chatgpt", {
        method: "POST",
        headers: {
          "Content-Type": "application/json",
        },
        body: JSON.stringify({
          message,
          promptId,
          chatHistory: getHistoryString(chatHistory),
        }),
      }).then((res) => res.json());
      if (response.reply) {
        console.log("Hook api call response", response.reply);
        setData(response.reply);
        setIsSuccess(true);
        setHistory(addMessage(chatHistory, response.reply, "agent"));
      } else {
        setIsError(true);
      }
    } catch (error) {
      setIsError(true);
    }
    setIsLoading(false);
  };

  useEffect(() => {
    setIsError(false);
    setIsSuccess(false);
    if (message) {
      fetchData();
    }
  }, [message]);

  useEffect(() => {
    setHistory(chatHistory);
  }, [chatHistory]);

  useEffect(() => {
    if (promptId) {
      setIsError(false);
      setIsSuccess(false);
      setHistory([]);
    }
  }, [promptId]);

  return {
    data,
    isLoading,
    isError,
    history,
    isSuccess,
  };
};

import { useChatGpt } from "@/hook/useChatGpt";
import { addMessage } from "@/utils/chatHistory";
import { Button, TextField } from "@mui/material";
import React, { useEffect } from "react";
import { ChatHistoryFrame } from "./ChatHistoryFrame";

const promptId = "xxxxxx"; // 通過(guò)Prompt自動(dòng)生成獲取ID

export const ChatContainer = () => {
  const [pendingMessage, setPendingMessage] = React.useState("");
  const [message, setMessage] = React.useState("");
  const [chatHistory, setChatHistory] = React.useState([]);
  const { isLoading, history, isSuccess, isError } = useChatGpt(
    message,
    promptId,
    chatHistory
  );

  useEffect(() => {
    if (isSuccess || isError) {
      setMessage("");
    }
  }, [isSuccess, isError]);

  return (
    <div>
        <h1>MOVIE to emoji</h1>
      </a>
      <ChatHistoryFrame chatHistory={chatHistory} isLoading={isLoading} />
      <div>
        <TextField
          type="text"
          onChange={(e) => {
            setPendingMessage(e.target.value);
          }}
        />
        <Button
          style={{
            backgroundColor: "black",
            width: "80px",
          }}
          variant="contained"
          onClick={() => {
            setMessage(pendingMessage);
            setChatHistory(addMessage(history || [], pendingMessage, "user"));
          }}
        >
          Send
        </Button>
        <Button
          style={{
            color: "black",
            width: "80px",
            borderColor: "black",
          }}
          variant="outlined"
          onClick={() => {
            setMessage("");
            setChatHistory([]);
          }}
        >
          Clear
        </Button>
      </div>
    </div>
  );
};

import { PromptableApi } from "promptable";
import { Configuration, OpenAIApi } from "openai";
import GPT3Tokenizer from "gpt3-tokenizer";

const configuration = new Configuration({
  apiKey: process.env.OPENAI_API_KEY,
});
const openai = new OpenAIApi(configuration);
const tokenizer = new GPT3Tokenizer({ type: "gpt3" });

const chatgpt = async (req, res) => {
  const { message, promptId, chatHistory } = req.body;
  console.log("api call entry", message, promptId);
  if (!message) {
    res.status(400).json({ error: "Message is required" });
    return;
  }
  if (!promptId) {
    res.status(400).json({ error: "Prompt ID is required" });
    return;
  }
  // call prompt ai api and openai api
  const reply = await getReply(message, promptId, chatHistory || "");
  res.status(200).json({ reply });
  return;
};

const getReply = async (message, promptId, chatHistory) => {
  // get prompt from prompt ai api based on promptId
  if (!promptId) {
    throw new Error("Prompt ID is required");
  }
  const promptDeployment = await PromptableApi.getActiveDeployment({
    promptId: promptId,
  });
  console.log("prompt deployment", promptDeployment);
  if (!promptDeployment) {
    throw new Error("Prompt deployment not found");
  }
  // replace prompt with message

  const beforeChatHistory = promptDeployment.text.replace("{{input}}", message);

  const numTokens = countBPETokens(beforeChatHistory);
  const afterChatHistory = beforeChatHistory.replace(
    "{{chat history}}",
    chatHistory
  );

  const finalPromptText = leftTruncateTranscript(
    afterChatHistory,
    4000 - numTokens
  );

  const revisedPrompt = {
    ...promptDeployment,
    text: finalPromptText,
  };

  console.log("revised prompt", revisedPrompt);
  // call openai api
  const response = await openai.createCompletion({
    model: revisedPrompt.config.model,
    prompt: revisedPrompt.text,
    temperature: revisedPrompt.config.temperature,
    max_tokens: revisedPrompt.config.max_tokens,
    top_p: 1.0,
    frequency_penalty: 0.0,
    presence_penalty: 0.0,
    stop: revisedPrompt.config.stop,
  });
  console.log("openai response", response.data);
  if (response.data.choices && response.data.choices.length > 0) {
    return response.data.choices[0].text;
  } else {
    return "I'm sorry, I don't understand.";
  }
};

function countBPETokens(text) {
  const encoded = tokenizer.encode(text);
  return encoded.bpe.length;
}

function leftTruncateTranscript(text, maxTokens) {
  const encoded = tokenizer.encode(text);
  const numTokens = encoded.bpe.length;
  const truncated = encoded.bpe.slice(numTokens - maxTokens);
  const decoded = tokenizer.decode(truncated);
  return decoded;
}

export default chatgpt;

"dependencies": {
    "@emotion/react": "^11.10.5",
    "@emotion/styled": "^11.10.5",
    "@mui/material": "^5.11.6",
    "@next/font": "13.1.6",
    "eslint": "8.32.0",
    "eslint-config-next": "13.1.6",
    "gpt3-tokenizer": "^1.1.5",
    "next": "13.1.6",
    "openai": "^3.2.1",
    "promptable": "^0.0.5",
    "react": "18.2.0",
    "react-dom": "18.2.0"
  }

import axios from 'axios'

// 這里面的xxxxxxx是部署Prompt自動(dòng)生成的ID，這里我用xxxxxxx替換了
const { data } = await axios.get('https://promptable.ai/api/prompt/xxxxxxx/deployment/active')

const prompt = data.inputs?.reduce((acc, input) => {
  // Replace input.value with your value!
  return acc.replaceAll(`{{${input.name}}}, ${input.value}`)
}, data.text)

const res = await axios.get('https://openai.com/v1/completions', {
  data: {
    // your prompt
    prompt,

    // your model configs from promptable
    config: {
      ...data.config,
      // add any other configs here
    }
  }
})

// Your completion!
console.log(res.data.choices[0].text)