diff --git a/main.py b/main.py
new file mode 100644
index 0000000..0669d7f
--- /dev/null
+++ b/main.py
@@ -0,0 +1,38 @@
+from jinja2 import Environment, FileSystemLoader
+from weasyprint import HTML
+import matplotlib.pyplot as plt
+import os
+
+# 1. Generate a chart with matplotlib
+os.makedirs("static/charts", exist_ok=True)
+chart_path = "static/charts/resp_chart.png"
+
+plt.plot([1, 2, 3, 4], [1, 4, 2, 5], label="Breath Volume")
+plt.legend()
+plt.title("Respiratory Chart")
+plt.savefig(chart_path)
+plt.close()
+
+# 2. Patient data (this would usually come from your DB)
+patient_data = {
+    "name": "Keirstyn Moran",
+    "age": 34,
+    "height": 163,
+    "weight": 56
+}
+
+context = {
+    "patient": patient_data,
+    "indications": "No Respiratory Capacity Limitation",
+    "chart_path": chart_path
+}
+
+# 3. Render Jinja2 template
+env = Environment(loader=FileSystemLoader("templates"))
+template = env.get_template("report.html")
+html_out = template.render(context)
+
+# 4. Generate PDF
+HTML(string=html_out, base_url=".").write_pdf("lung_report.pdf")
+
+print("✅ Report generated: lung_report.pdf")
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diff --git a/pdf_generation.ipynb b/pdf_generation.ipynb
new file mode 100644
index 0000000..4bcc195
--- /dev/null
+++ b/pdf_generation.ipynb
@@ -0,0 +1,105 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "6eee3ddd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import camelot\n",
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "d95cd8b1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tables = camelot.read_pdf('data/KM6479696509 _ Keirstyn_Moran_SingleViewWithExplanation_2025-07-29.pdf')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "759fd46e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "all_dfs = []\n",
+    "\n",
+    "# Append each table's dataframe to the list\n",
+    "for table in tables:\n",
+    "    all_dfs.append(table.df)\n",
+    "\n",
+    "# Concatenate all dataframes into one\n",
+    "combined_df = pd.concat(all_dfs, ignore_index=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "e9c3b9f0",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "                                                   0 1 2 3  \\\n",
+      "0  ← FM →\\nLow Fat\\nHigh Fat\\nBody Composition Ch...         \n",
+      "1                                                            \n",
+      "2                                                            \n",
+      "3                                                            \n",
+      "4                                                            \n",
+      "5                                                            \n",
+      "6                                                            \n",
+      "\n",
+      "                                                   4 5  \n",
+      "0  muscle  mass  in  a  coordinate  system.  A  d...    \n",
+      "1                                                       \n",
+      "2                                                       \n",
+      "3                                                       \n",
+      "4                                                       \n",
+      "5                                                       \n",
+      "6                                                       \n"
+     ]
+    }
+   ],
+   "source": [
+    "print(combined_df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6bbc907f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "report_generation",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/templates/base.html b/templates/base.html
new file mode 100644
index 0000000..27ae3ca
--- /dev/null
+++ b/templates/base.html
@@ -0,0 +1,39 @@
+
+<!DOCTYPE html>
+<html>
+<head>
+  <meta charset="utf-8">
+  <title>Lung Report</title>
+  <!-- TailwindCSS via CDN -->
+  <script src="https://cdn.tailwindcss.com"></script>
+</head>
+<body class="p-10 font-sans">
+  <div class="bg-black text-white p-4 rounded-lg mb-6">
+    <h1 class="text-2xl font-bold">Lung Analysis Report</h1>
+  </div>
+
+  <div class="grid grid-cols-2 gap-4 mb-6">
+    <div><b>Name:</b> {{ patient.name }}</div>
+    <div><b>Age:</b> {{ patient.age }}</div>
+    <div><b>Height:</b> {{ patient.height }} cm</div>
+    <div><b>Weight:</b> {{ patient.weight }} kg</div>
+  </div>
+
+  <div class="mb-6">
+    <h2 class="text-xl font-semibold mb-2">Lung Function</h2>
+    <div class="w-full h-6 bg-gradient-to-r from-red-500 via-yellow-300 to-green-400 relative">
+      <div class="absolute top-[-5px] left-1/2 transform -translate-x-1/2
+                  w-0 h-0 border-l-[7px] border-r-[7px] border-b-[10px] border-black"></div>
+    </div>
+  </div>
+
+  <div class="bg-gray-100 p-4 rounded-lg mb-6">
+    <b>Indications:</b> {{ indications }}
+  </div>
+
+  <div>
+    <h2 class="text-xl font-semibold mb-2">Respiratory Chart</h2>
+    <img src="{{ chart_path }}" class="border rounded-lg shadow">
+  </div>
+</body>
+</html>
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