Fix finetuning methods

Frontend/src/App.js

@@ -1,13 +1,12 @@
 // src/App.jsx
 import React, { useState, useEffect } from 'react';
-import { BrowserRouter as Router, Routes, Route, useNavigate } from 'react-router-dom';
+import { BrowserRouter as Router, Routes, Route } from 'react-router-dom';
 import Navbar from './components/Navbar';
 import LandingPage from './pages/AppLanding';
 import DetectHardwarePage from './pages/DetectHardwarePage';
 import FinetuneSettings from './pages/FinetuningSettingsPage';
 import Loading from './pages/Loading';
 import TechnicalDetailsPage from './pages/TechnicalDetailsPage';
-import ListModels from './pages/ListModels';
 import './index.css';
 import ListAllModels from "./pages/ListAllModels";
 

Frontend/src/components/Navbar.jsx

@@ -85,10 +85,6 @@ const Navbar = ({ appName = "ModelForge" }) => {
     );
   };
 
-  // We're removing the footer since it's not in the screenshot
-  const renderFooter = () => {
-    return null;
-  };
 
   return (
     <>

Frontend/src/pages/FinetuningSettingsPage.jsx

@@ -1,11 +1,11 @@
 import React, { useState, useEffect } from 'react';
 import { useNavigate } from 'react-router-dom';
-import { config, getSystemInfo, uploadDataset, startTraining } from '../services/api';
+import { config, getSystemInfo, validateDatasetPath, startTraining } from '../services/api';
 
 const FinetuneSettings = ({ defaultValues, updateSettings }) => {
   const navigate = useNavigate();
   const [showAdvanced, setShowAdvanced] = useState(false);
-  const [selectedFile, setSelectedFile] = useState(null);
+  const [datasetPath, setDatasetPath] = useState('');
   const [formState, setFormState] = useState({});
   const [settingsUpdated, setSettingsUpdated] = useState(false);
   const [activeTooltip, setActiveTooltip] = useState(null);
@@ -67,7 +67,6 @@ const FinetuneSettings = ({ defaultValues, updateSettings }) => {
         };
 
         console.log("Merged form state:", mergedState);
-        defaultValues = mergedState;
         setFormState(mergedState);
       } catch (err) {
         console.error("Error fetching settings:", err);
@@ -95,9 +94,8 @@ const FinetuneSettings = ({ defaultValues, updateSettings }) => {
     }
   }, [defaultValues]);
 
-  const handleFileChange = (e) => {
-    const file = e.target.files[0];
-    setSelectedFile(file);
+  const handleDatasetPathChange = (e) => {
+    setDatasetPath(e.target.value);
   };
 
   const handleInputChange = (e) => {
@@ -144,16 +142,16 @@ const FinetuneSettings = ({ defaultValues, updateSettings }) => {
         return;
       }
 
-      // Step 1: Upload dataset if provided
-      if (selectedFile) {
-        console.log("Uploading dataset...");
-        const uploadResponse = await uploadDataset(selectedFile, formState);
-        console.log("Dataset uploaded:", uploadResponse);
-        
-        // Update form state with the uploaded file path
-        formState.dataset = uploadResponse.file_path;
+      // Step 1: Validate dataset path
+      if (datasetPath.trim()) {
+        console.log("Validating dataset path...");
+        const validateResponse = await validateDatasetPath(datasetPath.trim());
+        console.log("Dataset validated:", validateResponse);
+
+        // Update form state with the validated file path
+        formState.dataset = validateResponse.file_path;
       } else {
-        throw new Error("Please select a dataset file");
+        throw new Error("Please enter the path to your dataset file");
       }
 
       // Step 2: Prepare training configuration
@@ -240,7 +238,7 @@ const FinetuneSettings = ({ defaultValues, updateSettings }) => {
     learning_rate: "How quickly the model adapts to new information",
     per_device_train_batch_size: "How many examples are processed at once",
     max_seq_length: "Maximum text length the model can handle",
-    dataset_file: "Your training examples in JSON format",
+    dataset_file: "Path to your local training data file (JSON or JSONL format)",
     lora_r: "Controls model capacity and training speed",
     lora_alpha: "Controls how much the model changes during training",
     quantization: "Reduces model size to fit in memory",
@@ -496,39 +494,21 @@ const FinetuneSettings = ({ defaultValues, updateSettings }) => {
 
             <div className="col-span-full">
               <Tooltip id="dataset_file">
-                <label htmlFor="dataset_file" className="block text-sm font-medium text-gray-400 mb-1">
-                  Dataset File
+                <label htmlFor="dataset_path" className="block text-sm font-medium text-gray-400 mb-1">
+                  Dataset File Path
                 </label>
               </Tooltip>
-              <div className="flex items-center">
-                <label className="w-full flex items-center justify-center px-4 py-2 border border-gray-700 rounded-lg cursor-pointer bg-gray-900 hover:bg-gray-800 transition">
-                  <svg
-                    xmlns="http://www.w3.org/2000/svg"
-                    className="h-5 w-5 mr-2 text-gray-400"
-                    fill="none"
-                    viewBox="0 0 24 24"
-                    stroke="currentColor"
-                  >
-                    <path
-                      strokeLinecap="round"
-                      strokeLinejoin="round"
-                      strokeWidth={2}
-                      d="M7 16a4 4 0 01-.88-7.903A5 5 0 1115.9 6L16 6a5 5 0 011 9.9M15 13l-3-3m0 0l-3 3m3-3v12"
-                    />
-                  </svg>
-                  <span className="text-white">Upload Dataset</span>
-                  <input
-                    type="file"
-                    id="dataset_file"
-                    name="dataset_file"
-                    accept=".json,.jsonl"
-                    className="hidden"
-                    onChange={handleFileChange}
-                  />
-                </label>
-              </div>
+              <input
+                type="text"
+                id="dataset_path"
+                name="dataset_path"
+                placeholder="C:\path\to\your\dataset.json"
+                value={datasetPath}
+                onChange={handleDatasetPathChange}
+                className="bg-gray-900 border border-gray-700 rounded-lg p-3 w-full text-white focus:border-orange-500 focus:outline-none"
+              />
               <p className="mt-2 text-sm text-gray-400">
-                {selectedFile ? selectedFile.name : 'No file selected'}
+                Enter the full path to your local JSON or JSONL dataset file
               </p>
             </div>
           </div>

Frontend/src/pages/ListModels.jsx

@@ -1,6 +1,5 @@
 import React from 'react';
 import { useState, useEffect } from 'react';
-import { Link, useLocation } from 'react-router-dom';
 
 const ListModelsPage = () => {
   const [models, setModels] = useState([]);

Frontend/src/pages/Loading.jsx

@@ -21,16 +21,6 @@ const Loading = () => {
     "Starting training loop...",
     "Training in progress..."
   ];
-
-  // Function to manually set idle status (for demo purposes)
-  const setTrainingComplete = () => {
-    setIsIdle(true);
-    setProgress(100);
-    setCurrentStep(steps.length - 1);
-    if (statusIntervalRef.current) {
-      clearInterval(statusIntervalRef.current);
-    }
-  };
 
   // Function to check backend status
   useEffect(() => {
@@ -112,19 +102,19 @@ const Loading = () => {
       const modelPathResponse = await fetch(`${config.baseURL}/playground/model_path`, {
         method: 'GET'
       });
-  
+
       if (!modelPathResponse.ok) {
         throw new Error('Failed to get model path');
       }
-  
+
       // Extract the model path from the response
       const modelPathData = await modelPathResponse.json();
       const modelPath = modelPathData.model_path;
-  
+
       console.log("Received model path:", modelPath);
-  
+
       // Now send POST request with the model path
-      const response = await fetch(`${config.baseURL}/playground/new`, {
+      await fetch(`${config.baseURL}/playground/new`, {
         method: 'POST',
         headers: {
           'Content-Type': 'application/json'
@@ -133,10 +123,10 @@ const Loading = () => {
           model_path: modelPath
         })
       });
-  
+
       // After successful POST request, redirect to homepage
       navigate('/');
-      
+
     } catch (error) {
       console.error('Error starting AI chat:', error);
       // Show an error message to the user

Frontend/src/pages/TechnicalDetailsPage.jsx

@@ -1,5 +1,4 @@
 import React, { useState } from 'react';
-import { Link } from 'react-router-dom';
 
 const TechnicalDetailsPage = () => {
   const [activeTab, setActiveTab] = useState('architecture');

Frontend/src/services/api.js

@@ -30,30 +30,26 @@ export const getSystemInfo = async () => {
 };
 
 /**
- * Upload dataset file
- * @param {File} file - Dataset file (JSON/JSONL)
- * @param {Object} settings - Training settings
- * @returns {Promise<Object>} Upload response
+ * Validate a local dataset file path
+ * @param {string} datasetPath - Local file path to the dataset
+ * @returns {Promise<Object>} Validation response with file_path
  */
-export const uploadDataset = async (file, settings) => {
+export const validateDatasetPath = async (datasetPath) => {
     try {
-        const formData = new FormData();
-        formData.append('json_file', file, file.name);
-        formData.append('settings', JSON.stringify(settings));
-
-        const response = await fetch(`${config.baseURL}/finetune/load_settings`, {
+        const response = await fetch(`${config.baseURL}/finetune/validate_dataset_path`, {
             method: 'POST',
-            body: formData,
+            headers: config.headers,
+            body: JSON.stringify({ dataset_path: datasetPath }),
         });
 
         if (!response.ok) {
             const errorData = await response.json().catch(() => ({}));
-            throw new Error(errorData.detail || `Upload failed: ${response.status}`);
+            throw new Error(errorData.detail || `Validation failed: ${response.status}`);
         }
 
         return await response.json();
     } catch (error) {
-        console.error('Error uploading dataset:', error);
+        console.error('Error validating dataset path:', error);
         throw error;
     }
 };

ModelForge/Frontend/build/asset-manifest.json

@@ -1,15 +1,15 @@
 {
   "files": {
     "main.css": "/static/css/main.9680427d.css",
-    "main.js": "/static/js/main.630cdb63.js",
+    "main.js": "/static/js/main.9df15fbf.js",
     "static/js/453.ad6eb26e.chunk.js": "/static/js/453.ad6eb26e.chunk.js",
     "index.html": "/index.html",
     "main.9680427d.css.map": "/static/css/main.9680427d.css.map",
-    "main.630cdb63.js.map": "/static/js/main.630cdb63.js.map",
+    "main.9df15fbf.js.map": "/static/js/main.9df15fbf.js.map",
     "453.ad6eb26e.chunk.js.map": "/static/js/453.ad6eb26e.chunk.js.map"
   },
   "entrypoints": [
     "static/css/main.9680427d.css",
-    "static/js/main.630cdb63.js"
+    "static/js/main.9df15fbf.js"
   ]
 }

ModelForge/Frontend/build/index.html

@@ -1 +1 @@
-<!doctype html><html lang="en"><head><meta charset="utf-8"/><link rel="icon" href="/favicon.ico"/><meta name="viewport" content="width=device-width,initial-scale=1"/><meta name="theme-color" content="#000000"/><meta name="description" content="Web site created using create-react-app"/><link rel="apple-touch-icon" href="/logo192.png"/><link rel="manifest" href="/manifest.json"/><title>ModelForge</title><script defer="defer" src="/static/js/main.630cdb63.js"></script><link href="/static/css/main.9680427d.css" rel="stylesheet"></head><body><noscript>You need to enable JavaScript to run this app.</noscript><div id="root"></div></body></html>
+<!doctype html><html lang="en"><head><meta charset="utf-8"/><link rel="icon" href="/favicon.ico"/><meta name="viewport" content="width=device-width,initial-scale=1"/><meta name="theme-color" content="#000000"/><meta name="description" content="Web site created using create-react-app"/><link rel="apple-touch-icon" href="/logo192.png"/><link rel="manifest" href="/manifest.json"/><title>ModelForge</title><script defer="defer" src="/static/js/main.9df15fbf.js"></script><link href="/static/css/main.9680427d.css" rel="stylesheet"></head><body><noscript>You need to enable JavaScript to run this app.</noscript><div id="root"></div></body></html>

ModelForge/app.py

@@ -58,14 +58,15 @@ async def lifespan(app: FastAPI):
     lifespan=lifespan,
 )
 
+cors_origins_env = os.getenv("CORS_ORIGINS", "http://localhost:8000")
+origins = [origin.strip() for origin in cors_origins_env.split(",")]
 
-# CORS middleware
 app.add_middleware(
     CORSMiddleware,
-    allow_origins=["*"],
-    allow_credentials=True,
+    allow_origins=origins,
     allow_methods=["*"],
     allow_headers=["*"],
+    allow_credentials=True,
 )