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import gradio as gr
import pandas as pd
import random
import time
from pandasai import PandasAI
from pandasai.llm.openai import OpenAI
import os
df = pd.DataFrame()
OPENAPI_KEY_VAL = ""
llm = ""
pandas_ai = ""
def process_file(file, OPENAPI_KEY):
global df, OPENAPI_KEY_VAL, llm, pandas_ai
df = pd.read_csv(file.name)
OPENAPI_KEY_VAL = OPENAPI_KEY
llm = OpenAI(api_token = OPENAPI_KEY_VAL)
pandas_ai = PandasAI(llm)
return df.head(2)
with gr.Blocks() as demo:
with gr.Row():
file = gr.inputs.File(type="file", label="Upload CSV")
key = gr.Textbox(placeholder="Paste OPENAI API KEY")
out = gr.DataFrame(type="pandas")
btn = gr.Button("Execute")
btn.click(fn=process_file, inputs=[file, key], outputs=out)
chatbot = gr.Chatbot()
msg = gr.Textbox()
clear = gr.Button("Clear")
def respond(message, chat_history):
bot_message = "Hi"
try:
bot_message = pandas_ai.run(df, prompt=message)
except Exception as e:
print(e)
bot_message = "I'm sorry, but as an AI language model, I am unable to provide a meaningful response to this question."
# bot_message = random.choice(["How are you?", "I love you", "I'm very hungry"])
chat_history.append((message, bot_message))
time.sleep(1)
return "", chat_history
msg.submit(respond, [msg, chatbot], [msg, chatbot])
clear.click(lambda: None, None, chatbot, queue=False)
demo.launch() |