File size: 5,171 Bytes
4737b79 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 |
import gradio as gr
import os
import plotly.express as px
# Chatbot demo with multimodal input (text, markdown, LaTeX, code blocks, image, audio, & video). Plus shows support for streaming text.
def random_plot():
df = px.data.iris()
fig = px.scatter(
df,
x="sepal_width",
y="sepal_length",
color="species",
size="petal_length",
hover_data=["petal_width"],
)
return fig
def print_like_dislike(x: gr.LikeData):
print(x.index, x.value, x.liked)
def random_bokeh_plot():
from bokeh.models import ColumnDataSource, Whisker
from bokeh.plotting import figure
from bokeh.sampledata.autompg2 import autompg2 as df
from bokeh.transform import factor_cmap, jitter, factor_mark
classes = list(sorted(df["class"].unique()))
p = figure(
height=400,
x_range=classes,
background_fill_color="#efefef",
title="Car class vs HWY mpg with quintile ranges",
)
p.xgrid.grid_line_color = None
g = df.groupby("class")
upper = g.hwy.quantile(0.80)
lower = g.hwy.quantile(0.20)
source = ColumnDataSource(data=dict(base=classes, upper=upper, lower=lower))
error = Whisker(
base="base",
upper="upper",
lower="lower",
source=source,
level="annotation",
line_width=2,
)
error.upper_head.size = 20
error.lower_head.size = 20
p.add_layout(error)
p.circle(
jitter("class", 0.3, range=p.x_range),
"hwy",
source=df,
alpha=0.5,
size=13,
line_color="white",
color=factor_cmap("class", "Light6", classes),
)
return p
def random_matplotlib_plot():
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
countries = ["USA", "Canada", "Mexico", "UK"]
months = ["January", "February", "March", "April", "May"]
m = months.index("January")
r = 3.2
start_day = 30 * m
final_day = 30 * (m + 1)
x = np.arange(start_day, final_day + 1)
pop_count = {"USA": 350, "Canada": 40, "Mexico": 300, "UK": 120}
df = pd.DataFrame({"day": x})
for country in countries:
df[country] = x ** (r) * (pop_count[country] + 1)
fig = plt.figure()
plt.plot(df["day"], df[countries].to_numpy())
plt.title("Outbreak in " + "January")
plt.ylabel("Cases")
plt.xlabel("Days since Day 0")
plt.legend(countries)
return fig
def add_message(history, message):
for x in message["files"]:
history.append(((x,), None))
if message["text"] is not None:
history.append((message["text"], None))
return history, gr.MultimodalTextbox(value=None, interactive=False)
def bot(history, response_type):
if response_type == "plot":
history[-1][1] = gr.Plot(random_plot())
elif response_type == "bokeh_plot":
history[-1][1] = gr.Plot(random_bokeh_plot())
elif response_type == "matplotlib_plot":
history[-1][1] = gr.Plot(random_matplotlib_plot())
elif response_type == "gallery":
history[-1][1] = gr.Gallery(
[os.path.join("files", "avatar.png"), os.path.join("files", "avatar.png")]
)
elif response_type == "image":
history[-1][1] = gr.Image(os.path.join("files", "avatar.png"))
elif response_type == "video":
history[-1][1] = gr.Video(os.path.join("files", "world.mp4"))
elif response_type == "audio":
history[-1][1] = gr.Audio(os.path.join("files", "audio.wav"))
elif response_type == "audio_file":
history[-1][1] = (os.path.join("files", "audio.wav"), "description")
elif response_type == "image_file":
history[-1][1] = (os.path.join("files", "avatar.png"), "description")
elif response_type == "video_file":
history[-1][1] = (os.path.join("files", "world.mp4"), "description")
elif response_type == "txt_file":
history[-1][1] = (os.path.join("files", "sample.txt"), "description")
else:
history[-1][1] = "Cool!"
return history
fig = random_plot()
with gr.Blocks(fill_height=True) as demo:
chatbot = gr.Chatbot(
elem_id="chatbot",
bubble_full_width=False,
scale=1,
)
response_type = gr.Radio(
[
"audio_file",
"image_file",
"video_file",
"txt_file",
"plot",
"matplotlib_plot",
"bokeh_plot",
"image",
"text",
"gallery",
"video",
"audio",
],
value="text",
label="Response Type",
)
chat_input = gr.MultimodalTextbox(
interactive=True,
placeholder="Enter message or upload file...",
show_label=False,
)
chat_msg = chat_input.submit(
add_message, [chatbot, chat_input], [chatbot, chat_input]
)
bot_msg = chat_msg.then(
bot, [chatbot, response_type], chatbot, api_name="bot_response"
)
bot_msg.then(lambda: gr.MultimodalTextbox(interactive=True), None, [chat_input])
chatbot.like(print_like_dislike, None, None)
demo.queue()
if __name__ == "__main__":
demo.launch()
|