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from transformers import pipeline
import gradio as gr
from fastapi import FastAPI
from gradio_client import Client
from typing import Union
import uvicorn
app = FastAPI()
chatbot = pipeline(model="Kaludi/Customer-Support-Assistant-V2")
def print_like_dislike(x: gr.LikeData):
print(x.index, x.value, x.liked)
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 DS_chatbot(message,history):
conversation = chatbot(message)
return conversation[0]['generated_text']
'''io = gr.ChatInterface(DS_chatbot, title=" Customer Service Bot", description="Enter your query.")'''
with gr.Blocks() as demo:
chat_bot = gr.Chatbot(
[],
elem_id="Customer Service Bot",
bubble_full_width=False,
)
chat_input = gr.MultimodalTextbox(interactive=True, file_types=["image"], placeholder="Enter message or upload file...", show_label=False)
chat_msg = chat_input.submit(add_message, [chat_bot, chat_input], [chat_bot, chat_input])
bot_msg = chat_msg.then(DS_chatbot, chat_bot, chat_bot, api_name="bot_response")
bot_msg.then(lambda: gr.MultimodalTextbox(interactive=True), None, [chat_input])
chat_bot.like(print_like_dislike, None, None)
@app.get("/")
async def read_main():
return {"message": "Append /gradio to the url to see gradio the interface"
,"message2": "Append /hello/{any_name} to get a greeting"}
@app.get("/hello/{name}")
async def read_name(name: Union[str, None] = None):
return { "Hey!": name}
# Mount the Gradio app onto the FastAPI app
app = gr.mount_gradio_app(app, demo, path='/gradio')
if __name__ == "__main__":
uvicorn.run(app, host="0.0.0.0", port=7860)
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