Update app.py

app.py

@@ -237,25 +237,9 @@ import uuid
 
 {new_line.join(['# '+line for line in prompt.strip().split(new_line)])}
 """
-                query = f"""I have a pandas dataframe data of PM2.5 and PM10.
-                * The columns are 'Timestamp', 'station', 'PM2.5', 'PM10', 'address', 'city', 'latitude', 'longitude',and 'state'.
-                * Frequency of data is daily.
-                * `pollution` generally means `PM2.5`.
-                * You already have df, so don't read the csv file 
-                * Don't print anything, but save result in a variable `answer` and make it global.
-                * Unless explicitly mentioned, don't consider the result as a plot.
-                * PM2.5 guidelines: India: 60, WHO: 15.
-                * PM10 guidelines: India: 100, WHO: 50.
-				* If result is a plot, show the India and WHO guidelines in the plot.
-                * If result is a plot make it in tight layout, save it and save path in `answer`. Example: `answer='plot.png'`. Use uuid to save the plot.
-                * If result is a plot, rotate x-axis tick labels by 45 degrees,
-                * If result is not a plot, save it as a string in `answer`. Example: `answer='The city is Mumbai'`
-                * I have a geopandas.geodataframe india containining the coordinates required to plot Indian Map with states.
-                * If the query asks you to plot on India Map, use that geodataframe to plot and then add more points as per the requirements using the similar code as follows : v = ax.scatter(df['longitude'], df['latitude']). If the colorbar is required, use the following code : plt.colorbar(v)
-                * If the query asks you to plot on India Map plot the India Map in Beige color 
-                * Whenever you do any sort of aggregation, report the corresponding standard deviation, standard error and the number of data points for that aggregation.
-                * Whenever you're reporting a floating point number, round it to 2 decimal places.
-                * Always report the unit of the data. Example: `The average PM2.5 is 45.67 µg/m³`
+                with open("system_prompt.txt") as f:
+                    system_prompt = f.read().strip()
+                query = f"""{system_prompt}
                 
                 Complete the following code.