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import gradio as gr
import os
import time
from multi_agent_chatbot import multi_agent_chatbot
# Chatbot demo with multimodal input (text, markdown, LaTeX, code blocks, image, audio, & video). Plus shows support for streaming text.
multi_agent_chatbot = multi_agent_chatbot()
def print_like_dislike(x: gr.LikeData):
print(x.index, x.value, x.liked)
def add_text(history, text):
history = history + [(text, None)]
return history, gr.Textbox(value="", interactive=False)
def add_file(history, file):
history = history + [((file.name,), None)]
return history
def bot(history):
# print(history[-1][0][0])
# print(history[-1][0])
# print(type(history[-1][0]))
# response = "**That's cool!**"
response = multi_agent_chatbot.respond(history[-1][0])
history[-1][1] = ""
for character in response:
history[-1][1] += character
time.sleep(0.05)
yield history
with gr.Blocks() as demo:
gr.Markdown("<h1 style='text-align: center; color: #ffffff; font-size: 40px;'> 🏡 🤖 Garden Whisperer AI - Your personal kitchen gardening assistant (POC)")
chatbot = gr.Chatbot(
[],
elem_id="chatbot",
height=800,
bubble_full_width=False,
avatar_images=(None, (os.path.join(os.path.dirname(__file__), "assets//avatar.png"))),
)
with gr.Row():
txt = gr.Textbox(
scale=4,
show_label=False,
placeholder="Enter text and press enter, or upload an image",
container=False,
)
btn = gr.UploadButton("📁", file_types=["image", "video", "audio"])
txt_msg = txt.submit(add_text, [chatbot, txt], [chatbot, txt], queue=False).then(
bot, chatbot, chatbot, api_name="bot_response"
)
txt_msg.then(lambda: gr.Textbox(interactive=True), None, [txt], queue=False)
file_msg = btn.upload(add_file, [chatbot, btn], [chatbot], queue=False).then(
bot, chatbot, chatbot
)
chatbot.like(print_like_dislike, None, None)
demo.queue()
if __name__ == "__main__":
demo.launch()
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