basic AI analytics

assets/js/main.js

@@ -55,26 +55,40 @@ document.addEventListener('DOMContentLoaded', function () {
         spinner.classList.remove('d-none');
         submitButton.disabled = true;
 
-        // --- FAKE LOADER FOR DEMO --- 
-        // In the next step, we will replace this with a real AJAX call to the backend.
-        setTimeout(() => {
+        const formData = new FormData(uploadForm);
+
+        // Show loading state
+        resultsSection.style.display = 'block';
+        analysisOutput.innerHTML = `
+            <div class="text-center p-5">
+                <div class="spinner-border text-primary" role="status">
+                    <span class="visually-hidden">Loading...</span>
+                </div>
+                <p class="mt-3">AI is analyzing your data, this may take a moment...</p>
+            </div>
+        `;
+        resultsSection.scrollIntoView({ behavior: 'smooth' });
+
+        fetch('upload.php', {
+            method: 'POST',
+            body: formData
+        })
+        .then(response => response.json())
+        .then(data => {
+            if (data.success) {
+                analysisOutput.innerHTML = data.analysis;
+            } else {
+                analysisOutput.innerHTML = `<div class="alert alert-danger">${data.error || 'An unknown error occurred.'}</div>`;
+            }
+        })
+        .catch(error => {
+            console.error('Error:', error);
+            analysisOutput.innerHTML = `<div class="alert alert-danger">An error occurred while communicating with the server.</div>`;
+        })
+        .finally(() => {
             // Hide spinner and re-enable button
             spinner.classList.add('d-none');
             submitButton.disabled = false;
-
-            // Show results section with a placeholder message
-            resultsSection.style.display = 'block';
-            analysisOutput.innerHTML = `
-                <div class="text-center p-5">
-                    <div class="spinner-border text-primary" role="status">
-                        <span class="visually-hidden">Loading...</span>
-                    </div>
-                    <p class="mt-3">AI is analyzing your data... This will be implemented in the next step.</p>
-                </div>
-            `;
-            // Scroll to results
-            resultsSection.scrollIntoView({ behavior: 'smooth' });
-
-        }, 2000);
+        });
     });
 });

upload.php

@@ -0,0 +1,100 @@
+<?php
+header('Content-Type: application/json');
+
+require_once __DIR__ . '/ai/LocalAIApi.php';
+
+function return_error($message) {
+    echo json_encode(['success' => false, 'error' => $message]);
+    exit;
+}
+
+// 1. Handle File Upload
+if (!isset($_FILES['csv_file']) || $_FILES['csv_file']['error'] !== UPLOAD_ERR_OK) {
+    return_error('File upload error. Please try again. Code: ' . ($_FILES['csv_file']['error'] ?? 'Unknown'));
+}
+
+$file = $_FILES['csv_file'];
+$tmpPath = $file['tmp_name'];
+
+// 2. Validate File Type (Basic Check)
+$fileType = mime_content_type($tmpPath);
+$fileName = $file['name'];
+$fileExtension = strtolower(pathinfo($fileName, PATHINFO_EXTENSION));
+
+if ($fileType !== 'text/csv' && $fileType !== 'text/plain' && $fileExtension !== 'csv') {
+    return_error('Invalid file type. Please upload a valid CSV file.');
+}
+
+// 3. Read CSV Header and First 2 Rows
+$dataSample = '';
+$handle = fopen($tmpPath, 'r');
+if (!$handle) {
+    return_error('Failed to open the uploaded file.');
+}
+
+$lineCount = 0;
+while (($row = fgetcsv($handle)) !== false && $lineCount < 3) {
+    $dataSample .= implode(',', array_map(function($cell) {
+        return '"' . addslashes($cell) . '"';
+    }, $row)) . "\n";
+    $lineCount++;
+}
+fclose($handle);
+
+if (empty($dataSample)) {
+    return_error('The CSV file appears to be empty or could not be read.');
+}
+
+// 4. Prepare Prompt for AI
+$prompt = <<<PROMPT
+You are an expert data analyst. A user has uploaded a CSV file for analysis.
+Below is the header and the first two rows of the data.
+
+Your task is to perform a brief analysis and return the output in **HTML format**.
+
+**Data Sample:**
+```csv
+{$dataSample}
+```
+
+**Instructions:**
+1.  **Briefly Describe the Data:** In a paragraph, describe what the data appears to be about. Identify the likely data type for each column (e.g., Text, Number, Date).
+2.  **Suggest Charts & Visualizations:** In a bulleted list, suggest 2-3 relevant charts or visualizations that could be created from this data. For each suggestion, briefly explain what insight it would provide. Use `<ul>` and `<li>` tags.
+3.  **Suggest Key Statistics:** In a bulleted list, suggest 2-3 key statistical calculations (e.g., average, sum, distribution) that would be meaningful for this dataset. Use `<ul>` and `<li>` tags.
+
+Structure your response using HTML tags like `<h4>`, `<p>`, and `<ul>`.
+PROMPT;
+
+
+// 5. Call AI API
+try {
+    $resp = LocalAIApi::createResponse(
+        [
+            'input' => [
+                ['role' => 'system', 'content' => 'You are a helpful data analysis assistant.'],
+                ['role' => 'user', 'content' => $prompt],
+            ],
+        ]
+    );
+
+    if (empty($resp['success'])) {
+        $errorMsg = 'AI API Error: ' . ($resp['error'] ?? 'Unknown error');
+        error_log($errorMsg);
+        return_error('Failed to get a response from the AI. Please try again later.');
+    }
+
+    $aiText = LocalAIApi::extractText($resp);
+
+    if (empty($aiText)) {
+        $decoded = LocalAIApi::decodeJsonFromResponse($resp);
+        $aiText = $decoded ? '<pre>' . htmlspecialchars(json_encode($decoded, JSON_PRETTY_PRINT)) . '</pre>' : 'The AI returned an empty response.';
+    }
+
+    echo json_encode(['success' => true, 'analysis' => $aiText]);
+
+} catch (Exception $e) {
+    error_log('Exception in AI call: ' . $e->getMessage());
+    return_error('An unexpected error occurred while processing the file with AI.');
+}
+
+