Spaces:
Sleeping
Sleeping
File size: 3,132 Bytes
f5d22a4 153e9c1 b4b75a1 f5d22a4 3b24cdb f5d22a4 3b24cdb f5d22a4 3b24cdb 153e9c1 3b24cdb 153e9c1 3b24cdb f5d22a4 3b24cdb f5d22a4 3b24cdb f5d22a4 3b24cdb f5d22a4 3b24cdb 153e9c1 |
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 |
# Import Gradio for UI, along with other necessary libraries
import gradio as gr
from rag_app.agents.react_agent import agent_executor
if __name__ == "__main__":
# Function to add a new input to the chat history
def add_text(history, text):
# Append the new text to the history with a placeholder for the response
history = history + [(text, None)]
return history, ""
# Function representing the bot's response mechanism
def bot(history):
# Obtain the response from the 'infer' function using the latest input
response = infer(history[-1][0], history)
history[-1][1] = response['output']
return history
# Function to infer the response using the RAG model
def infer(question, history):
# Use the question and history to query the RAG model
#result = qa({"query": question, "history": history, "question": question})
try:
result = agent_executor.invoke(
{
"input": question,
"chat_history": history
}
)
return result
except Exception:
raise gr.Error("Model is Overloaded, Please retry later!")
def vote(data: gr.LikeData):
if data.liked:
print("You upvoted this response: ")
else:
print("You downvoted this response: ")
# CSS styling for the Gradio interface
css = """
#col-container {max-width: 700px; margin-left: auto; margin-right: auto;}
"""
# HTML content for the Gradio interface title
title = """
<div style="text-align:left;">
<p>Hello, I BotTina 2.0, your intelligent AI assistant. I can help you explore Wuerttembergische Versicherungs products.<br />
</div>
"""
# Building the Gradio interface
with gr.Blocks(theme=gr.themes.Soft()) as demo:
with gr.Column(elem_id="col-container"):
gr.HTML(title) # Add the HTML title to the interface
chatbot = gr.Chatbot([], elem_id="chatbot",
label="BotTina 2.0",
bubble_full_width=False,
avatar_images=(None, "https://dacodi-production.s3.amazonaws.com/store/87bc00b6727589462954f2e3ff6f531c.png"),
height=680,) # Initialize the chatbot component
chatbot.like(vote, None, None)
clear = gr.Button("Clear") # Add a button to clear the chat
# Create a row for the question input
with gr.Row():
question = gr.Textbox(label="Question", placeholder="Type your question and hit Enter ")
# Define the action when the question is submitted
question.submit(add_text, [chatbot, question], [chatbot, question], queue=False).then(
bot, chatbot, chatbot
)
# Define the action for the clear button
clear.click(lambda: None, None, chatbot, queue=False)
# Launch the Gradio demo interface
demo.queue().launch(share=False, debug=True) |