Merge branch 'develop' into 'feature/ui-test'

# Conflicts:
#   main.js

services/modules/llm-chat_gpt/chatgpt.js

@@ -8,7 +8,7 @@ if (!fs.existsSync(outputDir)) {
 }
 
 // Ensure SAIA API key is set in environment variables: export SAIA_API_KEY="your_api_key_here"
-const SAIA_API_KEY = process.env.SAIA_API_KEY; // Ensure SAIA API key is set in environment variables
+let SAIA_API_KEY // Ensure SAIA API key is set in environment variables
 const SAIA_URL = "https://chat-ai.academiccloud.de/v1/chat/completions"; // URL for the REST call, used model and action
 
 const module_exports = {
@@ -18,6 +18,7 @@ const module_exports = {
     description: "Generates documents using OpenAI GPT OSS 120B via SAIA platform",
 
     async function(parameter) {
+        SAIA_API_KEY = process.env.SAIA_API_KEY;
         return new Promise(async (resolve, reject) => {
             try {
                 // console.log("SAIA OpenAI GPT module invoked with parameters:", parameter);

services/modules/llm-gemini/gemini.js

@@ -8,7 +8,7 @@ if (!fs.existsSync(outputDir)) {
 }
 
 // Ensure Google API key is set in environment variables: export GOOGLE_API_KEY="your_api_key_here"
-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"
+let GEMINI_API_KEY; // Ensure Google API key is set in environment variables: export GOOGLE_API_KEY="your_api_key_here"
 const GEMINI_URL = "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent"; // URL for the REST call, used model and action
 
 const module_exports = {
@@ -18,6 +18,7 @@ const module_exports = {
     description: "Generates documents using Google Gemini LLM",
 
     async function(parameter) {
+        GEMINI_API_KEY = process.env.GOOGLE_API_KEY;
         return new Promise(async (resolve, reject) => {
             try {
                 // console.log("Gemini LLM module invoked with parameters:", parameter);

services/modules/quen3/qwen3.js

@@ -8,7 +8,7 @@ if (!fs.existsSync(outputDir)) {
 }
 
 // Ensure SAIA API key is set in environment variables: export SAIA_API_KEY="your_api_key_here"
-const SAIA_API_KEY = process.env.SAIA_API_KEY;
+let SAIA_API_KEY;
 const SAIA_URL = "https://chat-ai.academiccloud.de/v1/chat/completions"; // URL for the REST call, used model and action
 
 const module_exports = {
@@ -18,6 +18,7 @@ const module_exports = {
     description: "Generates documents using QWEN 3 235B via SAIA platform",
 
     async function(parameter) {
+        SAIA_API_KEY = process.env.SAIA_API_KEY;
         return new Promise(async (resolve, reject) => {
             try {
                 // console.log("SAIA QWEN 3 235B module invoked with parameters:", parameter);

services/modules/replace_speaker/replaceSpeaker.js

@@ -0,0 +1,79 @@
+const fs = require('fs');
+const path = require('path');
+
+const module_exports = {
+    name: "replace_speaker",
+    type: "processor",
+    displayname: "Speaker Name Replacer",
+    description: "Replaces speaker placeholder names with actual names based on a mapping in HTML files",
+
+    async function(speakerMapping) {
+        // Relativ von dieser Datei aus
+        const documentsDir = path.resolve(__dirname, '../../../storage/documents');
+        const inputHtmlPath = await this.getNewestFile(documentsDir, '.html');
+        
+        if (!inputHtmlPath) {
+            throw new Error(`No HTML files found in ${documentsDir}`);
+        }
+        
+        return await this.replaceNames(inputHtmlPath, speakerMapping);
+    },
+
+    getNewestFile: async function(dirPath, extension) {
+        try {
+            const files = await fs.promises.readdir(dirPath);
+            const filtered = files.filter(f => f.endsWith(extension));
+            
+            if (filtered.length === 0) return null;
+            
+            const filesWithStats = await Promise.all(
+                filtered.map(async (f) => {
+                    const fullPath = path.join(dirPath, f);
+                    const stats = await fs.promises.stat(fullPath);
+                    return { path: fullPath, time: stats.mtimeMs };
+                })
+            );
+            
+            return filesWithStats.reduce((newest, curr) => 
+                curr.time > newest.time ? curr : newest
+            ).path;
+        } catch (error) {
+            console.error("Error reading directory:", error);
+            throw error;
+        }
+    },
+
+    replaceNames: async function(inputHtmlPath, speakerMapping) {
+        try {
+            const htmlContent = await fs.promises.readFile(inputHtmlPath, "utf-8");
+
+            let outputContent = htmlContent;
+            Object.entries(speakerMapping).forEach(([placeholder, value]) => {
+                // Extract name if value is an object
+                const displayName = typeof value === 'string' ? value : value.name;
+                
+                // Normalize placeholder for matching (remove case sensitivity)
+                const normalizedPlaceholder = placeholder.toLowerCase();
+                
+                // Replace all variations: speakerA, SpeakerA, SPEAKERA, speaker_a, Speaker A, etc.
+                // Matches with optional spaces, underscores, and parentheses
+                const regex = new RegExp(
+                    `\\b[Ss]peaker\\s*[_-]?\\s*${placeholder.charAt(placeholder.length - 1)}\\b|\\b${placeholder}\\b`,
+                    'gi'
+                );
+                
+                outputContent = outputContent.replace(regex, displayName);
+            });
+
+            await fs.promises.writeFile(inputHtmlPath, outputContent, "utf-8");
+
+            return inputHtmlPath;
+
+        } catch (error) {
+            console.error("Error replacing speaker names:", error);
+            throw error;
+        }
+    }
+};
+
+module.exports = module_exports;

services/modules/transcription-local/parakeet.js

@@ -0,0 +1,54 @@
+// -----------------------------------------------------------
+//  Parakeet (Step 3A: spawn Python minimal integration)
+// -----------------------------------------------------------
+
+const fs = require("fs");
+const path = require("path");
+const { spawn } = require("child_process");
+
+module.exports = {
+    name: "parakeet",
+    type: "transcription",
+    displayname: "NVIDIA Parakeet",
+
+    async function(audioFilePath) {
+        console.log("🦜 [Parakeet] Starting test integration (spawn only)...");
+        console.log("🦜 Input audio:", audioFilePath);
+
+        // Check audio exists
+        if (!fs.existsSync(audioFilePath)) {
+            throw new Error("Audio file does not exist: " + audioFilePath);
+        }
+
+        // Output path in storage/transcripts
+        const sessionId = path.basename(audioFilePath).replace(/\.[^.]+$/, "");
+        const outputDir = path.join(__dirname, "../../../storage/transcripts");
+        fs.mkdirSync(outputDir, { recursive: true });
+
+        const outputPath = path.join(outputDir, `${sessionId}.json`);
+
+        // -------------------------------------------------------
+        // SPAWN PYTHON SCRIPT (step 3A — dummy script)
+        // -------------------------------------------------------
+        return new Promise((resolve, reject) => {
+            const python310 = "C:\\Users\\smith\\AppData\\Local\\Programs\\Python\\Python310\\python.exe";
+            const py = spawn(python310, [
+                path.join(__dirname, "parakeet_transcribe.py"),
+                audioFilePath,
+                outputPath
+            ]);
+
+            py.stdout.on("data", data => console.log("🦜 [Python]", data.toString().trim()));
+            py.stderr.on("data", data => console.error("🦜 [Python ERR]", data.toString().trim()));
+
+            py.on("close", code => {
+                if (code === 0) {
+                    console.log("🦜 [Parakeet] Done (spawn test). Output:", outputPath);
+                    resolve(outputPath);
+                } else {
+                    reject(new Error("Python script failed with exit code " + code));
+                }
+            });
+        });
+    }
+};

services/modules/transcription-local/parakeet_transcribe.py

@@ -0,0 +1,71 @@
+# -----------------------------------------------------------
+#  Parakeet Real Transcriber (NVIDIA NeMo + PyTorch GPU)
+# -----------------------------------------------------------
+
+import sys
+import json
+import soundfile as sf
+import torch
+from nemo.collections.asr.models import ASRModel
+
+# Args:
+#   sys.argv[1] = input audio path
+#   sys.argv[2] = output JSON path
+
+audio_path = sys.argv[1]
+output_path = sys.argv[2]
+
+print("🔥 Starting Parakeet model...")
+device = "cuda" if torch.cuda.is_available() else "cpu"
+print("🔥 Using device:", device)
+
+# -----------------------------------------------------------
+# Load Parakeet model (NVIDIA pretrained ASR)
+# -----------------------------------------------------------
+model = ASRModel.from_pretrained(model_name="nvidia/parakeet-ctc-0.6b")
+model = model.to(device)
+model.eval()
+
+# -----------------------------------------------------------
+# Load audio
+# -----------------------------------------------------------
+print("🎧 Loading audio:", audio_path)
+audio, sr = sf.read(audio_path)
+
+# model expects mono float32
+if len(audio.shape) > 1:
+    audio = audio.mean(axis=1)
+
+audio = audio.astype("float32")
+
+# -----------------------------------------------------------
+# Run inference
+# -----------------------------------------------------------
+print("🧠 Running inference...")
+with torch.no_grad():
+    hyp = model.transcribe([audio])[0]
+
+# Extract only the text
+if hasattr(hyp, "text"):
+    transcript = hyp.text
+else:
+    # fallback: convert to string (rare)
+    transcript = str(hyp)
+
+print("📄 Transcript:", transcript)
+
+# -----------------------------------------------------------
+# Save JSON format compatible with V2D pipeline
+# -----------------------------------------------------------
+result = {
+    "id": output_path.split("/")[-1].replace(".json", ""),
+    "tool": "nemo_parakeet",
+    "status": "completed",
+    "text": transcript,
+    "words": []  # Parakeet XS doesn’t return word timestamps
+}
+
+with open(output_path, "w", encoding="utf-8") as f:
+    json.dump(result, f, indent=2, ensure_ascii=False)
+
+print("✔ JSON saved at:", output_path)

services/modules/transcription-remote/assembly.js

@@ -1,4 +1,4 @@
-const API_KEY = process.env.ASSEMBLYAI_API_KEY;
+let API_KEY
 const BASE_URL = 'https://api.assemblyai.com/v2';
 
 //---------------------------------------------------Upload audio---------------------------------------------------
@@ -92,6 +92,7 @@ module.exports = {
   audioformat: "mp3",
 
   async function(audioFileName) {
+    API_KEY = process.env.ASSEMBLYAI_API_KEY;
     return new Promise(async (resolve, reject) => {
       try {
         // audioFileName ist nur "datei.mp3"