From 4581e62f05397b7f508f9677169943e46c8f52e2 Mon Sep 17 00:00:00 2001
From: Swapnali Kudale <sskudale@mun.ca>
Date: Sun, 12 Apr 2026 22:18:35 -0230
Subject: [PATCH 1/4] Update CSV UI

---
 app/frontend/templates/index.html | 46 +++++++++++++++++++++++++++++--
 1 file changed, 43 insertions(+), 3 deletions(-)

diff --git a/app/frontend/templates/index.html b/app/frontend/templates/index.html
index 29653d8..2b28708 100644
--- a/app/frontend/templates/index.html
+++ b/app/frontend/templates/index.html
@@ -32,8 +32,13 @@ <h1 class="hero-title">
       </h1>
       <p class="hero-sub">Analyse customer reviews instantly </p>
     </section>
-
-    <div class="panel">
+      <!-- Tabs -->
+    <div class="tabs">
+      <button class="tab active" data-tab="single">Single Review</button>
+      <button class="tab" data-tab="batch">Batch CSV Upload</button>
+    </div>
+ <!-- Single Review Panel -->
+    <div class="panel" id="panel-single">
       <div class="input-group">
         <label class="input-label">Review Text</label>
         <textarea
@@ -98,6 +103,41 @@ <h1 class="hero-title">
         </div>
       </div>
     </div>
+    <!-- Batch Panel -->
+    <div class="panel hidden" id="panel-batch">
+      <div class="upload-zone" id="uploadZone">
+        <div class="upload-icon">📂</div>
+        <p class="upload-title">Drag & drop your CSV file here</p>
+        <p class="upload-sub">or click to browse · Max 10 MB · Must have a <code>text</code> column</p>
+        <input type="file" id="csvFile" accept=".csv" class="file-input" />
+      </div>
+      <p class="file-hint" id="fileHint"></p>
+
+      <button class="btn-primary" id="batchBtn" onclick="runBatch()">
+        <span class="btn-text">Analyse CSV</span>
+        <span class="btn-spinner hidden" id="batchSpinner">⟳</span>
+      </button>
+      <p class="error-msg hidden" id="batchError"></p>
+
+      <div class="batch-results hidden" id="batchResults">
+        <div class="batch-summary" id="batchSummary"></div>
+        <div class="table-wrap">
+          <table class="results-table" id="resultsTable">
+            <thead>
+              <tr>
+                <th>#</th>
+                <th>Review (truncated)</th>
+                <th>Verdict</th>
+                <th>Fake %</th>
+              </tr>
+            </thead>
+            <tbody id="resultsBody"></tbody>
+          </table>
+        </div>
+        <button class="btn-secondary" id="downloadBtn" onclick="downloadCSV()">⬇ Download Results CSV</button>
+      </div>
+    </div>
+
   </main>
 
   <footer class="footer">
@@ -106,4 +146,4 @@ <h1 class="hero-title">
 
   <script src="/static/js/script.js"></script>
 </body>
-</html>
+</html>
\ No newline at end of file

From 7976d51a2aee8d327c639046556f6829c6b04ae8 Mon Sep 17 00:00:00 2001
From: Swapnali Kudale <sskudale@mun.ca>
Date: Sun, 12 Apr 2026 22:20:55 -0230
Subject: [PATCH 2/4] Add CSS of CSV

---
 app/frontend/static/css/style.css | 129 +++++++++++++++++++++++++++++-
 1 file changed, 128 insertions(+), 1 deletion(-)

diff --git a/app/frontend/static/css/style.css b/app/frontend/static/css/style.css
index 62dda65..bba1661 100644
--- a/app/frontend/static/css/style.css
+++ b/app/frontend/static/css/style.css
@@ -108,6 +108,30 @@ body {
   max-width: 460px;
   margin: 0 auto;
 }
+/* ── Tabs ────────────────────────────────────────────────────── */
+.tabs {
+  display: flex;
+  gap: .5rem;
+  margin-bottom: 1.5rem;
+  border-bottom: 1px solid var(--border);
+  padding-bottom: 0;
+}
+.tab {
+  background: none;
+  border: none;
+  color: var(--text-muted);
+  font-family: var(--font-body);
+  font-size: .9rem;
+  font-weight: 500;
+  padding: .6rem 1.2rem;
+  cursor: pointer;
+  border-bottom: 2px solid transparent;
+  margin-bottom: -1px;
+  transition: color .2s, border-color .2s;
+}
+.tab:hover { color: var(--text); }
+.tab.active { color: var(--accent); border-bottom-color: var(--accent); }
+
 
 .panel {
   background: var(--bg2);
@@ -220,6 +244,34 @@ body {
   font-size: 1.1rem;
   animation: spin 1s linear infinite;
 }
+.btn-secondary {
+  display: flex;
+  align-items: center;
+  justify-content: center;
+  gap: 0.6rem;
+
+  width: 100%;
+  padding: 1rem;              /* bigger */
+  margin-top: 0.5rem;
+
+  background: var(--accent);  /* green */
+  color: #0a0e1a;
+
+  font-family: var(--font-body);
+  font-size: 1.05rem;         /* slightly bigger text */
+  font-weight: 600;
+
+  border: none;
+  border-radius: 10px;
+  cursor: pointer;
+
+  transition: opacity 0.2s, transform 0.15s;
+}
+
+.btn-secondary:hover {
+  opacity: 0.9;
+  transform: translateY(-1px);
+}
 @keyframes spin { to { transform: rotate(360deg); } }
 
 .error-msg {
@@ -306,6 +358,81 @@ body {
   font-size: .7rem;
   color: var(--text-muted);
 }
+/* ── Upload zone ─────────────────────────────────────────────── */
+.upload-zone {
+  border: 2px dashed var(--border);
+  border-radius: var(--radius);
+  padding: 2.5rem 1.5rem;
+  text-align: center;
+  cursor: pointer;
+  transition: border-color .2s, background .2s;
+  position: relative;
+}
+.upload-zone:hover, .upload-zone.dragover {
+  border-color: var(--accent);
+  background: var(--accent-dim);
+}
+.upload-icon { font-size: 2.5rem; margin-bottom: .8rem; }
+.upload-title { font-size: 1rem; font-weight: 500; margin-bottom: .3rem; }
+.upload-sub { font-size: .82rem; color: var(--text-muted); }
+.upload-sub code { font-family: var(--font-mono); font-size: .78rem; color: var(--accent); }
+.file-input {
+  position: absolute; inset: 0; opacity: 0; cursor: pointer; width: 100%; height: 100%;
+}
+.file-hint { font-size: .82rem; color: var(--accent); font-family: var(--font-mono); }
+
+/* ── Batch results ───────────────────────────────────────────── */
+.batch-results { display: flex; flex-direction: column; gap: 1rem; }
+.batch-summary {
+  font-size: .9rem;
+  color: var(--text-muted);
+  background: var(--bg3);
+  border-radius: 8px;
+  padding: .75rem 1rem;
+}
+.batch-summary strong { color: var(--text); }
+.batch-summary .fake-count { color: var(--fake); }
+.batch-summary .genuine-count { color: var(--genuine); }
+
+.table-wrap {
+  overflow-x: auto;
+  border-radius: 10px;
+  border: 1px solid var(--border);
+  max-height: 360px;
+  overflow-y: auto;
+}
+.results-table { width: 100%; border-collapse: collapse; font-size: .85rem; }
+.results-table thead { position: sticky; top: 0; z-index: 2; }
+.results-table th {
+  background: var(--bg3);
+  color: var(--text-muted);
+  font-weight: 600;
+  font-size: .72rem;
+  letter-spacing: .07em;
+  text-transform: uppercase;
+  padding: .7rem 1rem;
+  text-align: left;
+  border-bottom: 1px solid var(--border);
+}
+.results-table td {
+  padding: .65rem 1rem;
+  border-bottom: 1px solid var(--border);
+  vertical-align: middle;
+}
+.results-table tr:last-child td { border-bottom: none; }
+.results-table tr:hover td { background: rgba(255,255,255,0.02); }
+.verdict-badge {
+  display: inline-block;
+  font-family: var(--font-mono);
+  font-size: .72rem;
+  font-weight: 600;
+  letter-spacing: .06em;
+  padding: .2rem .6rem;
+  border-radius: 6px;
+}
+.verdict-badge.fake { background: var(--fake-dim); color: var(--fake); }
+.verdict-badge.genuine { background: var(--genuine-dim); color: var(--genuine); }
+
 
 .footer {
   text-align: center;
@@ -315,4 +442,4 @@ body {
   border-top: 1px solid var(--border);
 }
 
-.hidden { display: none !important; }
+.hidden { display: none !important; }
\ No newline at end of file

From 56ad566632315fe40b697748521af19bf551aefb Mon Sep 17 00:00:00 2001
From: Swapnali Kudale <sskudale@mun.ca>
Date: Sun, 12 Apr 2026 22:22:17 -0230
Subject: [PATCH 3/4] Update JS for CSV

---
 app/frontend/static/js/script.js | 161 +++++++++++++++++++++++++++++--
 1 file changed, 155 insertions(+), 6 deletions(-)

diff --git a/app/frontend/static/js/script.js b/app/frontend/static/js/script.js
index 855b532..0e16e84 100644
--- a/app/frontend/static/js/script.js
+++ b/app/frontend/static/js/script.js
@@ -1,9 +1,21 @@
-const API = '';
+const API = window.location.origin;
+
+// ── Tab switching ────────────────────────────────────────────────────────────
+
+document.querySelectorAll('.tab').forEach(tab => {
+  tab.addEventListener('click', () => {
+    document.querySelectorAll('.tab').forEach(t => t.classList.remove('active'));
+    document.querySelectorAll('.panel').forEach(p => p.classList.add('hidden'));
+    tab.classList.add('active');
+
+    const targetPanel = document.getElementById(`panel-${tab.dataset.tab}`);
+    if (targetPanel) {
+      targetPanel.classList.remove('hidden');
+    }
+  });
+});
+
 
-function showError(el, msg) {
-  el.textContent = msg;
-  el.classList.remove('hidden');
-}
 
 function hideError(el) {
   el.textContent = '';
@@ -115,6 +127,143 @@ async function analyzeReview() {
   }
 }
 
+
+const uploadZone = document.getElementById('uploadZone');
+const csvFile = document.getElementById('csvFile');
+const fileHint = document.getElementById('fileHint');
+
+uploadZone.addEventListener('dragover', e => { e.preventDefault(); uploadZone.classList.add('dragover'); });
+uploadZone.addEventListener('dragleave', () => uploadZone.classList.remove('dragover'));
+uploadZone.addEventListener('drop', e => {
+  e.preventDefault();
+  uploadZone.classList.remove('dragover');
+  const file = e.dataTransfer.files[0];
+  if (file) setFile(file);
+});
+csvFile.addEventListener('change', () => {
+  if (csvFile.files[0]) setFile(csvFile.files[0]);
+});
+
+function setFile(file) {
+  const dt = new DataTransfer();
+  dt.items.add(file);
+  csvFile.files = dt.files;
+  fileHint.textContent = `📄 ${file.name} (${(file.size / 1024).toFixed(1)} KB)`;
+}
+
+// ── Batch upload ──────────────────────────────────────────────────────────────
+
+let _batchResults = [];
+
+async function runBatch() {
+  const errEl = document.getElementById('batchError');
+  const btn = document.getElementById('batchBtn');
+  const spinner = document.getElementById('batchSpinner');
+  const btnText = btn.querySelector('.btn-text');
+  const batchResultsEl = document.getElementById('batchResults');
+
+  hideError(errEl);
+  batchResultsEl.classList.add('hidden');
+  _batchResults = [];
+
+  const file = csvFile.files[0];
+  if (!file) {
+    showError(errEl, 'Please select a CSV file first.');
+    return;
+  }
+
+  btn.disabled = true;
+  spinner.classList.remove('hidden');
+  btnText.textContent = 'Analysing…';
+
+  try {
+    // ✅ FIX: CREATE formData HERE
+    const formData = new FormData();
+    formData.append('file', file);
+    formData.append('model_version', 'v3');
+
+    const res = await fetch(`${API}/batch`, {
+      method: 'POST',
+      body: formData
+    });
+
+    const data = await res.json();
+
+    if (!res.ok) {
+      showError(errEl, data.error || 'Batch prediction failed.');
+      return;
+    }
+
+    _batchResults = data.results || [];
+    renderBatch(data);
+
+  } catch (e) {
+    showError(errEl, e.message || 'Cannot connect to server.');
+  } finally {
+    btn.disabled = false;
+    spinner.classList.add('hidden');
+    btnText.textContent = 'Analyse CSV';
+  }
+}
+
+function renderBatch(data) {
+  const results = data.results;
+  const fakeCount = results.filter(r => r.label === 'fake').length;
+  const genuineCount = results.length - fakeCount;
+
+  document.getElementById('batchSummary').innerHTML =
+    `Processed <strong>${results.length}</strong> reviews — ` +
+    `<span class="fake-count">⚠ ${fakeCount} fake</span> · ` +
+    `<span class="genuine-count">✓ ${genuineCount} genuine</span>`;
+
+  const tbody = document.getElementById('resultsBody');
+  tbody.innerHTML = '';
+  results.forEach((r, i) => {
+    const tr = document.createElement('tr');
+    const preview = (r.text || '').slice(0, 80) + ((r.text || '').length > 80 ? '…' : '');
+    tr.innerHTML = `
+      <td style="color:var(--text-muted);font-family:var(--font-mono)">${i + 1}</td>
+      <td title="${escapeHtml(r.text || '')}">${escapeHtml(preview)}</td>
+      <td><span class="verdict-badge ${r.label}">${r.label.toUpperCase()}</span></td>
+      <td style="font-family:var(--font-mono)">${r.fake_percent}%</td>
+    `;
+    tbody.appendChild(tr);
+  });
+
+  document.getElementById('batchResults').classList.remove('hidden');
+}
+
+function downloadCSV() {
+  if (!_batchResults.length) return;
+  const headers = ['text', 'label', 'fake_probability'];
+  const rows = _batchResults.map(r =>
+    headers.map(h => JSON.stringify(r[h] ?? '')).join(',')
+  );
+  const csv = [headers.join(','), ...rows].join('\n');
+  const blob = new Blob([csv], { type: 'text/csv' });
+  const url = URL.createObjectURL(blob);
+  const a = document.createElement('a');
+  a.href = url;
+  a.download = 'fake_review_results.csv';
+  a.click();
+  URL.revokeObjectURL(url);
+}
+
+// ── Utilities ─────────────────────────────────────────────────────────────────
+
+function showError(el, msg) {
+  el.textContent = msg;
+  el.classList.remove('hidden');
+}
+
+function escapeHtml(str) {
+  return String(str)
+    .replace(/&/g, '&amp;')
+    .replace(/</g, '&lt;')
+    .replace(/>/g, '&gt;')
+    .replace(/"/g, '&quot;');
+}
+
 document.getElementById('analyzeBtn')?.addEventListener('click', analyzeReview);
 document.getElementById('reviewText')?.addEventListener('keydown', (e) => {
   if (e.key === 'Enter' && !e.shiftKey) {
@@ -123,4 +272,4 @@ document.getElementById('reviewText')?.addEventListener('keydown', (e) => {
   }
 });
 
-checkHealth();
+checkHealth();
\ No newline at end of file

From 2de351f354c96967611e98cb824f343927a61e6f Mon Sep 17 00:00:00 2001
From: Swapnali Kudale <sskudale@mun.ca>
Date: Sun, 12 Apr 2026 22:23:54 -0230
Subject: [PATCH 4/4] Update CSV

---
 app/backend/app.py | 152 ++++++++++++++++++++++++++++++++++++++++-----
 1 file changed, 137 insertions(+), 15 deletions(-)

diff --git a/app/backend/app.py b/app/backend/app.py
index 08411d1..5f24077 100644
--- a/app/backend/app.py
+++ b/app/backend/app.py
@@ -1,7 +1,9 @@
+import io
 import os
 import sys
 import time
 
+import pandas as pd
 from flask import Flask, jsonify, render_template, request
 
 # Add project root to import path for direct script execution.
@@ -11,13 +13,17 @@
 
 PHASE1_DIR = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
 
-from app.ml.predict import predict_single, predict_single_v3
+from app.ml.predict import (
+    predict_batch as ml_predict_batch,
+    predict_batch_v3,
+    predict_single,
+    predict_single_v3,
+)
 
 MAX_TEXT_LENGTH = 10000
 
 
 def first_existing_path(paths):
-    # Return the first existing path from a list, else the first candidate.
     for path in paths:
         if os.path.exists(path):
             return path
@@ -25,8 +31,8 @@ def first_existing_path(paths):
 
 
 def models_dir_from_version(model_version):
-    # Map API model version selector to local artifact directory.
     version = str(model_version or "v3").strip().lower()
+
     if version in {"v1", "phase1-v1"}:
         return first_existing_path(
             [
@@ -34,6 +40,7 @@ def models_dir_from_version(model_version):
                 os.path.join(PHASE1_DIR, "models_v1"),
             ]
         )
+
     if version in {"v2", "phase1-v2"}:
         return first_existing_path(
             [
@@ -41,6 +48,7 @@ def models_dir_from_version(model_version):
                 os.path.join(PHASE1_DIR, "models_v2"),
             ]
         )
+
     if version in {"v3", "phase1-v3"}:
         return first_existing_path(
             [
@@ -48,21 +56,24 @@ def models_dir_from_version(model_version):
                 os.path.join(PHASE1_DIR, "models_v3"),
             ]
         )
+
     return None
 
 
 def parse_payload(payload):
-    # Validate and normalize shared request payload fields.
     if payload is None:
         raise ValueError("Invalid JSON body")
+
     if "text" not in payload:
         raise ValueError("Missing required field: text")
 
     text = payload.get("text")
     if not isinstance(text, str):
         raise TypeError("Field text must be a string")
+
     if len(text.strip()) == 0:
         raise ValueError("Field text must be non-empty")
+
     if len(text) > MAX_TEXT_LENGTH:
         raise OverflowError(f"Field text exceeds max length {MAX_TEXT_LENGTH}")
 
@@ -78,12 +89,13 @@ def parse_payload(payload):
 
 
 def run_prediction_for_version(version, text, rating, helpful_vote, verified_purchase):
-    # Run prediction for one model version and return UI-ready fields.
     models_dir = models_dir_from_version(version)
     if models_dir is None:
         raise ValueError("model_version must be 'v1', 'v2', or 'v3'")
 
-    if str(version).strip().lower() in {"v3", "phase1-v3"}:
+    version_str = str(version).strip().lower()
+
+    if version_str in {"v3", "phase1-v3"}:
         result = predict_single_v3(
             text=text,
             rating=rating,
@@ -106,28 +118,139 @@ def run_prediction_for_version(version, text, rating, helpful_vote, verified_pur
 
 
 def create_app():
-    # Create Flask app and define API routes.
     template_dir = os.path.abspath(
         os.path.join(os.path.dirname(__file__), "..", "frontend", "templates")
     )
     static_dir = os.path.abspath(
         os.path.join(os.path.dirname(__file__), "..", "frontend", "static")
     )
-    app = Flask(__name__, template_folder=template_dir, static_folder=static_dir, static_url_path="/static")
+
+    app = Flask(
+        __name__,
+        template_folder=template_dir,
+        static_folder=static_dir,
+        static_url_path="/static",
+    )
 
     @app.get("/")
     def home():
-        # Render the web tester UI for direct prediction checks.
         return render_template("index.html")
 
     @app.get("/health")
     def health():
-        # Return simple health status for monitoring.
         return jsonify({"status": "ok"}), 200
 
+    @app.post("/batch")
+    def batch_predict():
+        if "file" not in request.files:
+            return jsonify({"error": "Missing CSV file upload"}), 400
+
+        file = request.files["file"]
+        if not file or not file.filename:
+            return jsonify({"error": "Please choose a CSV file"}), 400
+
+        if not file.filename.lower().endswith(".csv"):
+            return jsonify({"error": "Only CSV files are supported"}), 400
+
+        try:
+            df = pd.read_csv(file)
+        except Exception as ex:
+            return jsonify({"error": f"Could not read CSV: {str(ex)}"}), 400
+
+        if "text" not in df.columns:
+            return jsonify({"error": "CSV must contain a text column"}), 400
+
+        try:
+            texts = df["text"].fillna("").astype(str).tolist()
+            ratings = (
+                pd.to_numeric(df["rating"], errors="coerce").fillna(0.0).tolist()
+                if "rating" in df.columns
+                else [0.0] * len(df)
+            )
+            helpful_votes = (
+                pd.to_numeric(df["helpful_vote"], errors="coerce").fillna(0.0).tolist()
+                if "helpful_vote" in df.columns
+                else [0.0] * len(df)
+            )
+            verified_purchase = (
+                pd.to_numeric(df["verified_purchase"], errors="coerce")
+                .fillna(0)
+                .astype(int)
+                .tolist()
+                if "verified_purchase" in df.columns
+                else [0] * len(df)
+            )
+
+            model_version = str(request.form.get("model_version", "v3")).strip().lower() or "v3"
+            models_dir = models_dir_from_version(model_version)
+            if models_dir is None:
+                return jsonify({"error": "model_version must be 'v1', 'v2', or 'v3'"}), 400
+
+            if model_version == "v3":
+                results = predict_batch_v3(
+                    texts=texts,
+                    ratings=ratings,
+                    helpful_votes=helpful_votes,
+                    verified_purchase=verified_purchase,
+                    models_dir=models_dir,
+                )
+            else:
+                results = ml_predict_batch(
+                    texts=texts,
+                    ratings=ratings,
+                    helpful_votes=helpful_votes,
+                    verified_purchase=verified_purchase,
+                    models_dir=models_dir,
+                )
+
+            formatted_results = []
+            fake_count = 0
+            genuine_count = 0
+
+            for item in results:
+                label = str(item.get("label", "genuine")).lower()
+                fake_probability = round(float(item.get("fake_probability", 0.0)) * 100.0, 2)
+
+                if label == "fake":
+                    fake_count += 1
+                else:
+                    genuine_count += 1
+
+                formatted_results.append(
+                    {
+                        "text": item.get("text", ""),
+                        "label": label,
+                        "fake_probability": fake_probability,
+                        "fake_percent": fake_probability,
+                        "threshold": round(float(item.get("threshold", 0.5)) * 100.0, 2),
+                        "model_version": item.get("model_version", model_version),
+                    }
+                )
+
+            csv_output = io.StringIO()
+            pd.DataFrame(formatted_results).to_csv(csv_output, index=False)
+
+            return jsonify(
+                {
+                    "summary": {
+                        "total_reviews": len(formatted_results),
+                        "fake_count": fake_count,
+                        "genuine_count": genuine_count,
+                        "manual_review_count": 0,
+                    },
+                    "results": formatted_results,
+                    "csv_data": csv_output.getvalue(),
+                    "count": len(formatted_results),
+                }
+            ), 200
+
+        except FileNotFoundError:
+            return jsonify({"error": "Model artifacts not found. Train the model first."}), 500
+        except Exception as ex:
+            return jsonify({"error": f"Batch prediction failed: {str(ex)}"}), 500
+
     @app.post("/predict")
     def predict():
-        # Validate request payload and return fake probability prediction.
         started = time.time()
 
         if not request.is_json:
@@ -152,14 +275,12 @@ def predict():
         except Exception as ex:
             return jsonify({"error": f"Prediction failed: {str(ex)}"}), 500
 
-        # Add lightweight latency info to simplify local acceptance checks.
         elapsed_ms = (time.time() - started) * 1000.0
         result["latency_ms"] = round(elapsed_ms, 2)
         return jsonify(result), 200
 
     @app.post("/predict_all")
     def predict_all():
-        # Return predictions from all model versions for agreement checking.
         if not request.is_json:
             return jsonify({"error": "Request must be JSON"}), 400
 
@@ -174,6 +295,7 @@ def predict_all():
         try:
             predictions = {}
             labels = []
+
             for version in ["v1", "v2", "v3"]:
                 pred = run_prediction_for_version(
                     version=version,
@@ -188,6 +310,7 @@ def predict_all():
             disagreement = len(set(labels)) > 1
             majority_label = max(set(labels), key=labels.count) if labels else "unknown"
             recommendation = "manual_review" if disagreement else majority_label
+
             return jsonify(
                 {
                     "predictions": predictions,
@@ -208,6 +331,5 @@ def predict_all():
 
 
 if __name__ == "__main__":  # pragma: no cover
-    # Run local development server.
     port = int(os.environ.get("PORT", "8000"))
-    app.run(host="0.0.0.0", port=port, debug=False)
+    app.run(host="0.0.0.0", port=port, debug=False)
\ No newline at end of file