On May 1st 2023, with Bangalore at 12.979N, 77.592E I get a distance to the Sun of 1.007313284 AU or 150691922.3 km. You will get slightly different numbers if you used a slightly different lat/long, or if you didn't include the light-time correction that the .observe() method uses here.

from skyfield.api import Loader, Topos
import numpy as np
import matplotlib.pyplot as plt

load = Loader('~/Documents/fishing/SkyData') # avoid multiple copies of large files
ts = load.timescale()
eph = load('de421.bsp')

earth, sun, moon = [eph[x] for x in ('earth', 'sun', 'moon')]

latlon = 12.979, 77.592
bangalore = Topos(latitude_degrees = latlon[0],
                  longitude_degrees = latlon[1])

days = np.arange(1, 31)

times = ts.utc(2023, 5, days, 0, 0, 0) # 2023-05-01 00:00-2023-05-30 00:00

sun_astrometric = (earth + bangalore).at(times).observe(sun)

both = sun_astrometric.distance().au, sun_astrometric.distance().km

i_annotate = [0, 4, 9, 14, 19, 24, 29]

annots = [[str(val) for val in thing[i_annotate].round(n)]
          for (thing, n) in zip(both, (9, 1))]

annots = np.array(annots)

fig, axes = plt.subplots(2, 1)

goodies = axes, both, ('AU', 'km'), annots

for ax, distance, label, anns in zip(*goodies):
    ax.plot(days, distance)
    for ann, day, dist in zip(anns, days[i_annotate], distance[i_annotate]):
        ax.annotate(ann, (day, dist))
        ax.plot(day, dist, 'ok')
    ax.set_ylabel(label, fontsize=12)

axes[1].set_xlabel('days in May 2023', fontsize=12)

suptitle = ('distance from Bangalore (' + str(latlon) +
            ' to the Sun May 2023 (00:00)')

plt.suptitle(suptitle)

fig.subplots_adjust(left=0.13, right=0.86)
             
plt.show()

On May 1st 2023, with Bangalore at 12.979N, 77.592E I get a distance to the Sun of 1.007313284 AU or 150691922.3 km. You will get slightly different numbers if you used a slightly different lat/lon, or if you included the light-time correction, I didn't use Skyfield's 'apparent()' method that does a few more corrections.

from skyfield.api import Loader, Topos
import numpy as np
import matplotlib.pyplot as plt

load = Loader('~/Documents/fishing/SkyData') # avoid multiple copies of large files
ts = load.timescale()
eph = load('de421.bsp')

earth, sun, moon = [eph[x] for x in ('earth', 'sun', 'moon')]

latlon = 12.979, 77.592
bangalore = Topos(latitude_degrees = latlon[0],
                  longitude_degrees = latlon[1])

days = np.arange(1, 31)

times = ts.utc(2023, 5, days, 0, 0, 0) # 2023-05-01 00:00-2023-05-30 00:00

sun_astrometric = (earth + bangalore).at(times).observe(sun)

both = sun_astrometric.distance().au, sun_astrometric.distance().km

i_annotate = [0, 4, 9, 14, 19, 24, 29]

annots = [[str(val) for val in thing[i_annotate].round(n)]
          for (thing, n) in zip(both, (9, 1))]

annots = np.array(annots)

fig, axes = plt.subplots(2, 1)

goodies = axes, both, ('AU', 'km'), annots

for ax, distance, label, anns in zip(*goodies):
    ax.plot(days, distance)
    for ann, day, dist in zip(anns, days[i_annotate], distance[i_annotate]):
        ax.annotate(ann, (day, dist))
        ax.plot(day, dist, 'ok')
    ax.set_ylabel(label, fontsize=12)

axes[1].set_xlabel('days in May 2023', fontsize=12)

suptitle = ('distance from Bangalore ' + str(latlon) +
            ' to the Sun May 2023 (00:00)')

plt.suptitle(suptitle)

fig.subplots_adjust(left=0.13, right=0.86)
             
plt.show()