matt HOFFNER
refactor to use openai functions
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import { Configuration, OpenAIApi } from "openai";
import { GoogleCustomSearch } from "openai-function-calling-tools";
export default async function handler(req, res) {
if (req.method !== 'POST') {
// Handle any other HTTP method
res.status(405).send({ error: 'Method Not Allowed', method: req.method });
return;
}
const QUESTION = req.body.question;
if (!QUESTION) {
res.status(400).send({ error: 'Question is missing in request body' });
return;
}
const configuration = new Configuration({
apiKey: process.env.OPENAI_API_KEY,
});
const openai = new OpenAIApi(configuration);
const messages = [
{
role: "user",
content: QUESTION,
},
];
const { googleCustomSearch, googleCustomSearchSchema } = new GoogleCustomSearch({
apiKey: process.env.GOOGLE_API_KEY,
googleCSEId: process.env.GOOGLE_CSE_ID,
});
const functions = {
googleCustomSearch,
};
const getCompletion = async (messages) => {
const response = await openai.createChatCompletion({
model: "gpt-3.5-turbo-0613",
messages,
functions: [googleCustomSearchSchema],
temperature: 0,
});
return response;
};
let response;
while (true) {
response = await getCompletion(messages);
if (response.data.choices[0].finish_reason === "stop") {
res.status(200).json({ result: response.data.choices[0].message.content });
break;
} else if (response.data.choices[0].finish_reason === "function_call") {
const fnName = response.data.choices[0].message.function_call.name;
const args = response.data.choices[0].message.function_call.arguments;
const fn = functions[fnName];
const result = await fn(...Object.values(JSON.parse(args)));
messages.push({
role: "assistant",
content: "",
function_call: {
name: fnName,
arguments: args,
},
});
messages.push({
role: "function",
name: fnName,
content: JSON.stringify({ result: result }),
});
}
}
}