Multiple AI models implemented - chatgpt, llama

scripts/show-models.js

@@ -0,0 +1,47 @@
+const fs = require('fs');
+const path = require('path');
+
+//node show-models.js, remember to set SAIA_API_KEY in your environment before running the script
+
+const SAIA_API_KEY = process.env.SAIA_API_KEY;
+const SAIA_MODELS_URL = "https://chat-ai.academiccloud.de/v1/models";
+
+// Script to list available models
+(async () => {
+    if (!SAIA_API_KEY) {
+        console.error("ERROR: SAIA_API_KEY environment variable is not set!");
+        process.exit(1);
+    }
+
+    console.log("Fetching available models from SAIA...\n");
+
+    try {
+        const response = await fetch(SAIA_MODELS_URL, {
+            method: "GET",
+            headers: {
+                "Authorization": `Bearer ${SAIA_API_KEY}`,
+                "Accept": "application/json"
+            }
+        });
+
+        if (!response.ok) {
+            const text = await response.text();
+            throw new Error(`SAIA API error (${response.status}): ${text}`);
+        }
+
+        const data = await response.json();
+        
+        console.log("Available models:");
+        console.log(JSON.stringify(data, null, 2));
+        
+        if (data.data && Array.isArray(data.data)) {
+            console.log("\n\nModel IDs:");
+            data.data.forEach(model => {
+                console.log(`- ${model.id}`);
+            });
+        }
+
+    } catch (error) {
+        console.error("Error fetching models:", error);
+    }
+})();

services/modules/llm-chat_gpt/chatgpt.js

@@ -1,24 +1,26 @@
+const fs = require('fs');
+const path = require('path');
+
 const outputDir = path.join(__dirname, "../../../storage/documents"); //  path for output directory
 
 if (!fs.existsSync(outputDir)) {
     fs.mkdirSync(outputDir, { recursive: true }); // Create output directory if it doesn't exist
 }
 
-// Ensure Chat GPT API key is set in environment variables: export CHAT_GPT_API_KEY="your_api_key_here"
+// Ensure SAIA API key is set in environment variables: export SAIA_API_KEY="your_api_key_here"
-// NOTE: Using standard OPENAI_API_KEY instead because the API expects this env variable
+const SAIA_API_KEY = process.env.SAIA_API_KEY; // Ensure SAIA API key is set in environment variables
-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
+const SAIA_URL = "https://chat-ai.academiccloud.de/v1/chat/completions"; //URL for the REST call, used model and action
 
-module.exports = {
+const module_exports = {
-    name: "llm-chat_gpt",
+    name: "llm-saia_openai_gpt",
     type: "llm",
-    displayname: "Chat GPT",
+    displayname: "SAIA OpenAI GPT OSS 120B",
-    description: "Generates documents using Chat GPT",
+    description: "Generates documents using OpenAI GPT OSS 120B via SAIA platform",
 
     async function(parameter) {
         try {
-            console.log("Chat GPT module invoked with parameters:", parameter);
+            console.log("SAIA OpenAI 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
@@ -27,7 +29,7 @@ module.exports = {
             );
 
         } catch (error) {
-            console.error("Error in Chat GPT module:", error);
+            console.error("Error in SAIA OpenAI GPT module:", error);
         }
     },
 
@@ -38,29 +40,32 @@ module.exports = {
             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, {
+            const response = await fetch(SAIA_URL, {
                 method: "POST",
                 headers: {
-                    "Authorization": `Bearer ${OPENAI_API_KEY}`,
+                    "Authorization": `Bearer ${SAIA_API_KEY}`,
+                    "Accept": "application/json",
                     "Content-Type": "application/json"
                 },
                 body: JSON.stringify({
-                    model: "gpt-4.1",
+                    model: "openai-gpt-oss-120b",
                     messages: [
+                        { role: "system", content: "You are a helpful assistant that generates documents from transcripts." },
                         { role: "user", content: promptText }
-                    ]
+                    ],
+                    temperature: 0
                 })
             });
 
-            if (!response.ok) { //ok is true when a responce was successfull
+            if (!response.ok) { //ok is true when a response was successful
                 const text = await response.text();
-                throw new Error(`Chat GPT API error (${response.status}): ${text}`);
+                throw new Error(`SAIA API error (${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
+            // SAIA uses OpenAI-compatible structure: 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 
@@ -72,7 +77,55 @@ module.exports = {
             console.log("Generated document written to:", outPath);
 
         } catch (error) {
-            console.error("Error generating Chat GPT content:", error);
+            console.error("Error generating SAIA content:", error);
         }
     }
 };
+
+module.exports = module_exports;
+
+// CLI Mode: Allow direct execution
+if (require.main === module) {
+    (async () => {
+        const args = process.argv.slice(2);
+        
+        if (args.length < 2) {
+            console.error("Usage: node llm-openai-gpt.js <transcriptPath> <documentTypePath> [language]");
+            console.error("Example: node llm-openai-gpt.js ./transcript.json ./docType.json de");
+            process.exit(1);
+        }
+
+        const [transcriptPath, documentTypePath, language] = args;
+
+        // Check if API key is set
+        if (!SAIA_API_KEY) {
+            console.error("ERROR: SAIA_API_KEY environment variable is not set!");
+            console.error("Please set it with: export SAIA_API_KEY='your_api_key_here'");
+            process.exit(1);
+        }
+
+        // Check if files exist
+        if (!fs.existsSync(transcriptPath)) {
+            console.error(`ERROR: Transcript file not found: ${transcriptPath}`);
+            process.exit(1);
+        }
+
+        if (!fs.existsSync(documentTypePath)) {
+            console.error(`ERROR: Document type file not found: ${documentTypePath}`);
+            process.exit(1);
+        }
+
+        console.log("Starting document generation...");
+        console.log(`Transcript: ${transcriptPath}`);
+        console.log(`Document Type: ${documentTypePath}`);
+        console.log(`Language: ${language || 'en (default)'}`);
+        
+        await module_exports.createDocumentFromTranscript(
+            transcriptPath,
+            documentTypePath,
+            language || 'en'
+        );
+        
+        console.log("Done!");
+    })();
+}

services/modules/llm-llama/llm-llama.js

@@ -0,0 +1,123 @@
+const fs = require('fs');
+const path = require('path');
+
+const outputDir = path.join(__dirname, "../../../storage/documents");
+
+if (!fs.existsSync(outputDir)) {
+    fs.mkdirSync(outputDir, { recursive: true });
+}
+
+const SAIA_API_KEY = process.env.SAIA_API_KEY;
+const SAIA_URL = "https://chat-ai.academiccloud.de/v1/chat/completions";
+
+const module_exports = {
+    name: "llm-saia_llama_3.3",
+    type: "llm",
+    displayname: "SAIA Llama 3.3 70B",
+    description: "Generates documents using Llama 3.3 70B Instruct via SAIA platform",
+
+    async function(parameter) {
+        try {
+            console.log("SAIA Llama 3.3 70B module invoked with parameters:", parameter);
+
+            await this.createDocumentFromTranscript(
+                parameter.inputTranscriptPath,
+                parameter.documentTypePath,
+                parameter.language
+            );
+
+        } catch (error) {
+            console.error("Error in SAIA Llama 3.3 70B module:", error);
+        }
+    },
+
+    createDocumentFromTranscript: async function(transcriptPath, documentTypePath, language = "en") {
+        try {
+            const transcript = await fs.promises.readFile(transcriptPath, "utf-8");
+            const documentType = await fs.promises.readFile(documentTypePath, "utf-8");
+            const promptText = `${documentType}, in language ${language}, transcript:\n\n${transcript}`;
+
+            // --- REST CALL ---
+            const response = await fetch(SAIA_URL, {
+                method: "POST",
+                headers: {
+                    "Authorization": `Bearer ${SAIA_API_KEY}`,
+                    "Accept": "application/json",
+                    "Content-Type": "application/json"
+                },
+                body: JSON.stringify({
+                    model: "llama-3.3-70b-instruct",  // Korrekter Modellname!
+                    messages: [
+                        { role: "system", content: "You are a helpful assistant that generates documents from transcripts." },
+                        { role: "user", content: promptText }
+                    ],
+                    temperature: 0
+                })
+            });
+
+            if (!response.ok) {
+                const text = await response.text();
+                throw new Error(`SAIA API error (${response.status}): ${text}`);
+            }
+
+            const data = await response.json();
+            const output = data.choices?.[0]?.message?.content || "";
+
+            let inputTranscriptName = path.basename(transcriptPath, path.extname(transcriptPath));
+            console.log(inputTranscriptName);
+
+            const outPath = path.join(outputDir, `${inputTranscriptName}.md`);
+            fs.writeFileSync(outPath, output, "utf8");
+
+            console.log("Generated document written to:", outPath);
+
+        } catch (error) {
+            console.error("Error generating SAIA content:", error);
+        }
+    }
+};
+
+module.exports = module_exports;
+
+if (require.main === module) {
+    (async () => {
+        const args = process.argv.slice(2);
+        
+        if (args.length < 2) {
+            console.error("Usage: node llm-llama-3.3.js <transcriptPath> <documentTypePath> [language]");
+            console.error("Example: node llm-llama-3.3.js ./transcript.json ./docType.json de");
+            process.exit(1);
+        }
+
+        const [transcriptPath, documentTypePath, language] = args;
+
+        if (!SAIA_API_KEY) {
+            console.error("ERROR: SAIA_API_KEY environment variable is not set!");
+            console.error("Please set it with: export SAIA_API_KEY='your_api_key_here'");
+            process.exit(1);
+        }
+
+        if (!fs.existsSync(transcriptPath)) {
+            console.error(`ERROR: Transcript file not found: ${transcriptPath}`);
+            process.exit(1);
+        }
+
+        if (!fs.existsSync(documentTypePath)) {
+            console.error(`ERROR: Document type file not found: ${documentTypePath}`);
+            process.exit(1);
+        }
+
+        console.log("Starting document generation...");
+        console.log(`Transcript: ${transcriptPath}`);
+        console.log(`Document Type: ${documentTypePath}`);
+        console.log(`Language: ${language || 'en (default)'}`);
+        
+        await module_exports.createDocumentFromTranscript(
+            transcriptPath,
+            documentTypePath,
+            language || 'en'
+        );
+        
+        console.log("Done!");
+    })();
+}