Similar to the Gemini LLM we now have a ChatGPT REST call. The API Key is still missing

This commit is contained in:
MikeHughes-BIN
2025-12-04 10:58:50 +01:00
parent 05c04aaef2
commit 425e24853e
+77 -7
View File
@@ -1,8 +1,78 @@
module.exports = { const outputDir = path.join(__dirname, "../../../storage/documents"); // path for output directory
name:"chatgpt", // Unique name for our function that will later be used to get the function from the map via "mapFunctions.get("example").function()"
type:"llm", // value used to differentiate each module to order them in the UI if (!fs.existsSync(outputDir)) {
displayname:"ChatGPT", // The displayname used within the UI fs.mkdirSync(outputDir, { recursive: true }); // Create output directory if it doesn't exist
async function(parameter){
// TODO add code to actually send the transcript to ChatGPT and get a response back
}
} }
// Ensure Chat GPT API key is set in environment variables: export CHAT_GPT_API_KEY="your_api_key_here"
// NOTE: Using standard OPENAI_API_KEY instead because the API expects this env variable
const OPENAI_API_KEY = process.env.OPENAI_API_KEY; // Ensure Chat GPT API key is set in environment variables: export OPENAI_API_KEY="your_api_key_here"
const CHAT_GPT_URL = "https://api.openai.com/v1/chat/completions"; //URL for the REST call, used model and action
module.exports = {
name: "llm-chat_gpt",
type: "llm",
displayname: "Chat GPT",
description: "Generates documents using Chat GPT",
async function(parameter) {
try {
console.log("Chat GPT module invoked with parameters:", parameter);
await this.createDocumentFromTranscript( //Call the function to create document with transcript, document type and language
parameter.inputTranscriptPath, // Path to input transcript file
parameter.documentTypePath, // Path to document type file which is chosen in the front end by the user
parameter.language // Language for the document which is chosen in the front end by the user
);
} catch (error) {
console.error("Error in Chat GPT module:", error);
}
},
createDocumentFromTranscript: async function(transcriptPath, documentTypePath, language = "en") { // default language is English
try {
const transcript = await fs.promises.readFile(transcriptPath, "utf-8"); //read transcript file from Path
const documentType = await fs.promises.readFile(documentTypePath, "utf-8"); //read document type from Path
const promptText = `${documentType}, in language ${language}, transcript:\n\n${transcript}`; //combine doc type, language and transcript - Change prompt here if needed
// --- REST CALL ---
const response = await fetch(CHAT_GPT_URL, {
method: "POST",
headers: {
"Authorization": `Bearer ${OPENAI_API_KEY}`,
"Content-Type": "application/json"
},
body: JSON.stringify({
model: "gpt-4.1",
messages: [
{ role: "user", content: promptText }
]
})
});
if (!response.ok) { //ok is true when a responce was successfull
const text = await response.text();
throw new Error(`Chat GPT API error (${response.status}): ${text}`);
}
const data = await response.json();
// Get generated text from response or default to empty string (if null)
// FIX: Chat Completions API uses data.choices[x].message.content
const output = data.choices?.[0]?.message?.content || "";
let inputTranscriptName = path.basename(transcriptPath, path.extname(transcriptPath)); // Name for the output file
console.log(inputTranscriptName);
const outPath = path.join(outputDir, `${inputTranscriptName}.md`); // Output file path & name to make naming dynamic. Pulled from input transcript name
fs.writeFileSync(outPath, output, "utf8"); // Write output to file
console.log("Generated document written to:", outPath);
} catch (error) {
console.error("Error generating Chat GPT content:", error);
}
}
};