fixed sticky sidebar

.streamlit/config.toml

@@ -0,0 +1,2 @@
+[theme]
+base="light"

app.py

@@ -17,7 +17,6 @@ load_dotenv()
 Groq_Token = os.environ["GROQ_API_KEY"]
 hf_token = os.environ["HF_TOKEN"]
 models = {"llama3":"llama3-70b-8192","mixtral": "mixtral-8x7b-32768", "llama2": "llama2-70b-4096", "gemma": "gemma-7b-it"}
-shape_file = os.getenv("SHAPE_FILE")
 
 self_path = os.path.dirname(os.path.abspath(__file__))
 
@@ -36,7 +35,6 @@ st.write(
 )
 
 # Displaying the centered title
-st.markdown("<h2 class='title'>VayuBuddy</h2>", unsafe_allow_html=True)
 st.markdown("<div style='text-align:center; padding: 20px;'>VayuBuddy makes pollution monitoring easier by bridging the gap between users and datasets.<br>No coding required—just meaningful insights at your fingertips!</div>", unsafe_allow_html=True)
 
 # Center-aligned instruction text with bold formatting
@@ -52,12 +50,14 @@ st.markdown("<div style='text-align:center;'>Choose a query from <b>Select a pro
 # inference_server = "https://api-inference.huggingface.co/models/codellama/CodeLlama-13b-hf"
 # inference_server = "https://api-inference.huggingface.co/models/pandasai/bamboo-llm"
 
-image_path = "IITGN_Logo.png"  
+image_path = "IITGN_Logo.png"
 
     # Display images and text in three columns with specified ratios
-col1, col2, col3 = st.sidebar.columns((1.4, 2, 2))  
+col1, col2, col3 = st.sidebar.columns((1.0, 2, 1.0))  
 with col2:
     st.image(image_path, use_column_width=True)
+    st.markdown("<h1 class='title'>VayuBuddy</h1>", unsafe_allow_html=True)
+    
     
 model_name = st.sidebar.selectbox("Select LLM:", ["llama3","mixtral", "gemma"])
 
@@ -181,6 +181,9 @@ if prompt == 'Custom Prompt':
     prompt = st.chat_input("Ask me anything about air quality!", key=1000)
     if prompt :
         show = True
+else:
+    # placeholder for chat input
+    st.chat_input("Select 'Select a Prompt' -> 'Custom Prompt' in the sidebar to ask your own questions.", key=1000, disabled=True)
 
 if "last_prompt" in st.session_state:
     last_prompt = st.session_state["last_prompt"]
@@ -221,7 +224,7 @@ df = pd.read_csv("Data.csv")
 df["Timestamp"] = pd.to_datetime(df["Timestamp"])
 
 import geopandas as gpd
-india = gpd.read_file(f"{shape_file}") 
+india = gpd.read_file("https://gist.githubusercontent.com/jbrobst/56c13bbbf9d97d187fea01ca62ea5112/raw/e388c4cae20aa53cb5090210a42ebb9b765c0a36/india_states.geojson")
 india.loc[india['ST_NM'].isin(['Ladakh', 'Jammu & Kashmir']), 'ST_NM'] = 'Jammu and Kashmir'
 import uuid
 # df.dtypes

test.ipynb

@@ -0,0 +1,114 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "DriverError",
+     "evalue": "None: No such file or directory",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mCPLE_OpenFailedError\u001b[0m                      Traceback (most recent call last)",
+      "File \u001b[0;32mfiona/ogrext.pyx:136\u001b[0m, in \u001b[0;36mfiona.ogrext.gdal_open_vector\u001b[0;34m()\u001b[0m\n",
+      "File \u001b[0;32mfiona/_err.pyx:291\u001b[0m, in \u001b[0;36mfiona._err.exc_wrap_pointer\u001b[0;34m()\u001b[0m\n",
+      "\u001b[0;31mCPLE_OpenFailedError\u001b[0m: None: No such file or directory",
+      "\nDuring handling of the above exception, another exception occurred:\n",
+      "\u001b[0;31mDriverError\u001b[0m                               Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[1], line 10\u001b[0m\n\u001b[1;32m      7\u001b[0m df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mTimestamp\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mto_datetime(df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mTimestamp\u001b[39m\u001b[38;5;124m\"\u001b[39m])\n\u001b[1;32m      9\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mgeopandas\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mgpd\u001b[39;00m\n\u001b[0;32m---> 10\u001b[0m india \u001b[38;5;241m=\u001b[39m \u001b[43mgpd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread_file\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mNone\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m \n\u001b[1;32m     11\u001b[0m india\u001b[38;5;241m.\u001b[39mloc[india[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mST_NM\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m.\u001b[39misin([\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mLadakh\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mJammu & Kashmir\u001b[39m\u001b[38;5;124m'\u001b[39m]), \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mST_NM\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mJammu and Kashmir\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m     12\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01muuid\u001b[39;00m\n",
+      "File \u001b[0;32m/opt/anaconda3/envs/zeel_py311/lib/python3.11/site-packages/geopandas/io/file.py:297\u001b[0m, in \u001b[0;36m_read_file\u001b[0;34m(filename, bbox, mask, rows, engine, **kwargs)\u001b[0m\n\u001b[1;32m    294\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    295\u001b[0m         path_or_bytes \u001b[38;5;241m=\u001b[39m filename\n\u001b[0;32m--> 297\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_read_file_fiona\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    298\u001b[0m \u001b[43m        \u001b[49m\u001b[43mpath_or_bytes\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfrom_bytes\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbbox\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbbox\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmask\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmask\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrows\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrows\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\n\u001b[1;32m    299\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    301\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    302\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124munknown engine \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mengine\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
+      "File \u001b[0;32m/opt/anaconda3/envs/zeel_py311/lib/python3.11/site-packages/geopandas/io/file.py:338\u001b[0m, in \u001b[0;36m_read_file_fiona\u001b[0;34m(path_or_bytes, from_bytes, bbox, mask, rows, where, **kwargs)\u001b[0m\n\u001b[1;32m    335\u001b[0m     reader \u001b[38;5;241m=\u001b[39m fiona\u001b[38;5;241m.\u001b[39mopen\n\u001b[1;32m    337\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m fiona_env():\n\u001b[0;32m--> 338\u001b[0m     \u001b[38;5;28;01mwith\u001b[39;00m \u001b[43mreader\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpath_or_bytes\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mas\u001b[39;00m features:\n\u001b[1;32m    339\u001b[0m         crs \u001b[38;5;241m=\u001b[39m features\u001b[38;5;241m.\u001b[39mcrs_wkt\n\u001b[1;32m    340\u001b[0m         \u001b[38;5;66;03m# attempt to get EPSG code\u001b[39;00m\n",
+      "File \u001b[0;32m/opt/anaconda3/envs/zeel_py311/lib/python3.11/site-packages/fiona/env.py:457\u001b[0m, in \u001b[0;36mensure_env_with_credentials.<locals>.wrapper\u001b[0;34m(*args, **kwds)\u001b[0m\n\u001b[1;32m    454\u001b[0m     session \u001b[38;5;241m=\u001b[39m DummySession()\n\u001b[1;32m    456\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m env_ctor(session\u001b[38;5;241m=\u001b[39msession):\n\u001b[0;32m--> 457\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mf\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwds\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m/opt/anaconda3/envs/zeel_py311/lib/python3.11/site-packages/fiona/__init__.py:292\u001b[0m, in \u001b[0;36mopen\u001b[0;34m(fp, mode, driver, schema, crs, encoding, layer, vfs, enabled_drivers, crs_wkt, allow_unsupported_drivers, **kwargs)\u001b[0m\n\u001b[1;32m    289\u001b[0m     path \u001b[38;5;241m=\u001b[39m parse_path(fp)\n\u001b[1;32m    291\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m mode \u001b[38;5;129;01min\u001b[39;00m (\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124ma\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124m\"\u001b[39m):\n\u001b[0;32m--> 292\u001b[0m     colxn \u001b[38;5;241m=\u001b[39m \u001b[43mCollection\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    293\u001b[0m \u001b[43m        \u001b[49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    294\u001b[0m \u001b[43m        \u001b[49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    295\u001b[0m \u001b[43m        \u001b[49m\u001b[43mdriver\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdriver\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    296\u001b[0m \u001b[43m        \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mencoding\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    297\u001b[0m \u001b[43m        \u001b[49m\u001b[43mlayer\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlayer\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    298\u001b[0m \u001b[43m        \u001b[49m\u001b[43menabled_drivers\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43menabled_drivers\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    299\u001b[0m \u001b[43m        \u001b[49m\u001b[43mallow_unsupported_drivers\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mallow_unsupported_drivers\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    300\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\n\u001b[1;32m    301\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    302\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m mode \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mw\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m    303\u001b[0m     colxn \u001b[38;5;241m=\u001b[39m Collection(\n\u001b[1;32m    304\u001b[0m         path,\n\u001b[1;32m    305\u001b[0m         mode,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    314\u001b[0m         \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs\n\u001b[1;32m    315\u001b[0m     )\n",
+      "File \u001b[0;32m/opt/anaconda3/envs/zeel_py311/lib/python3.11/site-packages/fiona/collection.py:243\u001b[0m, in \u001b[0;36mCollection.__init__\u001b[0;34m(self, path, mode, driver, schema, crs, encoding, layer, vsi, archive, enabled_drivers, crs_wkt, ignore_fields, ignore_geometry, include_fields, wkt_version, allow_unsupported_drivers, **kwargs)\u001b[0m\n\u001b[1;32m    241\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmode \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m    242\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msession \u001b[38;5;241m=\u001b[39m Session()\n\u001b[0;32m--> 243\u001b[0m     \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msession\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstart\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    244\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmode \u001b[38;5;129;01min\u001b[39;00m (\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124ma\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mw\u001b[39m\u001b[38;5;124m\"\u001b[39m):\n\u001b[1;32m    245\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msession \u001b[38;5;241m=\u001b[39m WritingSession()\n",
+      "File \u001b[0;32mfiona/ogrext.pyx:588\u001b[0m, in \u001b[0;36mfiona.ogrext.Session.start\u001b[0;34m()\u001b[0m\n",
+      "File \u001b[0;32mfiona/ogrext.pyx:143\u001b[0m, in \u001b[0;36mfiona.ogrext.gdal_open_vector\u001b[0;34m()\u001b[0m\n",
+      "\u001b[0;31mDriverError\u001b[0m: None: No such file or directory"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "plt.rcParams.update({'font.size': 12, 'figure.dpi': 600})\n",
+    "\n",
+    "df = pd.read_csv(\"Data.csv\")\n",
+    "df[\"Timestamp\"] = pd.to_datetime(df[\"Timestamp\"])\n",
+    "\n",
+    "import geopandas as gpd\n",
+    "india = gpd.read_file(f\"None\")\n",
+    "india.loc[india['ST_NM'].isin(['Ladakh', 'Jammu & Kashmir']), 'ST_NM'] = 'Jammu and Kashmir'\n",
+    "import uuid\n",
+    "# df.dtypes\n",
+    "# Timestamp    datetime64[ns]\n",
+    "# station              object\n",
+    "# PM2.5               float64\n",
+    "# PM10                float64\n",
+    "# address              object\n",
+    "# city                 object\n",
+    "# latitude            float64\n",
+    "# longitude           float64\n",
+    "# state                object\n",
+    "# dtype: object\n",
+    "\n",
+    "# Plot the monthly average PM2.5 for the year 2023.\n",
+    "# <your code here>\n",
+    "\n",
+    "\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "plt.rcParams.update({'font.size': 12, 'figure.dpi': 600})\n",
+    "\n",
+    "df = pd.read_csv(\"Data.csv\")\n",
+    "df[\"Timestamp\"] = pd.to_datetime(df[\"Timestamp\"])\n",
+    "\n",
+    "import geopandas as gpd\n",
+    "india = gpd.read_file(f\"None\") \n",
+    "india.loc[india['ST_NM'].isin(['Ladakh', 'Jammu & Kashmir']), 'ST_NM'] = 'Jammu and Kashmir'\n",
+    "\n",
+    "# Plot the monthly average PM2.5 for the year 2023.\n",
+    "df_2023 = df[df['Timestamp'].dt.year == 2023]\n",
+    "monthly_avg_pm25 = df_2023.resample('M', on='Timestamp')['PM2.5'].mean()\n",
+    "\n",
+    "fig, ax = plt.subplots(figsize=(10, 6))\n",
+    "monthly_avg_pm25.plot(kind='bar')\n",
+    "ax.set_title('Monthly Average PM2.5 in 2023')\n",
+    "ax.set_xlabel('Month')\n",
+    "ax.set_ylabel('Average PM2.5 (µg/m³)')\n",
+    "ax.axhline(y=60, color='r', linestyle='--', label='India Guideline')\n",
+    "ax.axhline(y=15, color='b', linestyle='--', label='WHO Guideline')\n",
+    "plt.legend()\n",
+    "plt.tight_layout()\n",
+    "\n",
+    "uuid_str = str(uuid.uuid4())\n",
+    "answer = f'plot_{uuid_str}.png'\n",
+    "plt.savefig(answer)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "zeel_py311",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
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+}