mirror of
https://gitlab.rlp.net/proj-wise2526-video2document/video2document.git
synced 2026-06-15 18:01:52 +02:00
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7 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| e661aefbe8 | |||
| ed94928953 | |||
| 8adf470f18 | |||
| f858f2edbb | |||
| 05c04aaef2 | |||
| 84cc94aa34 | |||
| 16f319f89f |
@@ -141,7 +141,7 @@ electron.ipcMain.on("file_submit", async (event, args) => {
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console.log("\n\n Running the Video to Audio Extractor");
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// This code handles the Video to Audio extraction module call
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await mapFunctions.get("module-handler").function(args.video.module, {inputVideoPath: args.video.inputVideoPath, outputType: args.video.outputType}).then(resp => {
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await mapFunctions.get("module-handler").function(args.video.module, {inputVideoPath: args.video.inputVideoPath, outputType: mapFunctions.get(args.transcription.module).audioformat}).then(resp => {
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console.log(resp);
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audiopath = resp
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curstep++
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@@ -194,6 +194,24 @@ electron.ipcMain.on("file_submit", async (event, args) => {
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})
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}
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// TODO actually implement this functionality
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// Module to get the first few lines for each speaker to send to the frontend
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// await mapFunctions.get("speaker-getter-idfk").function(transcriptpath).then(resp => {
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// console.log(resp);
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// transcriptpath = resp
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// curstep++
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// mainWindow.webContents.send("progress", {curstep:curstep, totalsteps:totalsteps})
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// // {
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// // speakerA: {source: "Pfad zur Audio File"},
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// // speakerB:.....
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// // }
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mainWindow.webContents.send("speakers", {speakerA:"pfad1", speakerB:"pfad2"})
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// }).catch(err => {
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// mainWindow.webContents.send("error", err)
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// return
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// })
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} catch (error) {
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console.log(error);
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Generated
-2
@@ -299,7 +299,6 @@
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"resolved": "https://registry.npmjs.org/@types/node/-/node-24.9.2.tgz",
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"integrity": "sha512-uWN8YqxXxqFMX2RqGOrumsKeti4LlmIMIyV0lgut4jx7KQBcBiW6vkDtIBvHnHIquwNfJhk8v2OtmO8zXWHfPA==",
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"license": "MIT",
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"peer": true,
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"dependencies": {
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"undici-types": "~7.16.0"
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}
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@@ -2535,7 +2534,6 @@
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"integrity": "sha512-jl1vZzPDinLr9eUt3J/t7V6FgNEw9QjvBPdysz9KfQDD41fQrC2Y4vKQdiaUpFT4bXlb1RHhLpp8wtm6M5TgSw==",
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"dev": true,
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"license": "Apache-2.0",
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"peer": true,
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"bin": {
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"tsc": "bin/tsc",
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"tsserver": "bin/tsserver"
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@@ -4,9 +4,10 @@ if (!fs.existsSync(outputDir)) {
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fs.mkdirSync(outputDir, { recursive: true }); // Create output directory if it doesn't exist
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}
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const ai = new genai.GoogleGenAI({
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apiKey: process.env.GOOGLE_API_KEY // Ensure Google API key is set in environment variables: export GOOGLE_API_KEY="your_api_key_here"
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});
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// Ensure Google API key is set in environment variables: export GOOGLE_API_KEY="your_api_key_here"
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const GEMINI_API_KEY = process.env.GOOGLE_API_KEY; // Ensure Google API key is set in environment variables: export GOOGLE_API_KEY="your_api_key_here"
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const GEMINI_URL = "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent"; //URL for the REST call, used model and action
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module.exports = {
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name: "llm-gemini",
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@@ -31,19 +32,39 @@ module.exports = {
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createDocumentFromTranscript: async function(transcriptPath, documentTypePath, language = "en") { // default language is English
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try {
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const transcript = await fs.promises.readFile(transcriptPath, "utf-8");
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const documentType = await fs.promises.readFile(documentTypePath, "utf-8");
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const transcript = await fs.promises.readFile(transcriptPath, "utf-8"); //read transcript file from Path
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const documentType = await fs.promises.readFile(documentTypePath, "utf-8"); //read document type from Path
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const promptText = `${documentType}, in language ${language}, transcript:\n\n${transcript}`; //combine doc type, language and transcript - Change prompt here if needed
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const promptText = `${documentType}, in language ${language}, transcript:\n\n${transcript}`;
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const response = await ai.models.generateContent({
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model: "gemini-2.5-flash", // Specify the Gemini model to use
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contents: promptText // Input prompt for content generation
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// --- REST CALL ---
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const response = await fetch(`${GEMINI_URL}?key=${GEMINI_API_KEY}`, { //safe model response in variable
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method: "POST",
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headers: {
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"Content-Type": "application/json"
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},
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body: JSON.stringify({
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contents: [
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{
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parts: [
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{ text: promptText } // Input prompt for content generation
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]
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}
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]
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})
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});
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const output = response.text || ""; // Get generated text from response or default to empty string (if null)
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if (!response.ok) { //ok is true when a responce was successfull
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const text = await response.text();
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throw new Error(`Gemini API error (${response.status}): ${text}`);
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}
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const outPath = path.join(outputDir, "test.md"); // Output file path & name TO BE DONE to make dynamic out of input transcript name
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const data = await response.json();
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// Get generated text from response or default to empty string (if null)
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const output = data?.candidates?.[0]?.content?.parts?.[0]?.text || "";
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let inputTranscriptName = path.basename(transcriptPath, path.extname(transcriptPath)); // Name for the output file
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console.log(inputTranscriptName);
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const outPath = path.join(outputDir, `${inputTranscriptName}.md`); // Output file path & name to make naming dynamic. Pulled from input transcript name
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fs.writeFileSync(outPath, output, "utf8"); // Write output to file
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console.log("Generated document written to:", outPath);
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@@ -89,6 +89,7 @@ module.exports = {
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name: 'assembly',
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type: 'transcription',
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displayname: 'AssemblyAI',
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audioformat: "mp3",
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async function(audioFileName) {
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return new Promise(async (resolve, reject) => {
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