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