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Create app.py
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app.py
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import gradio as gr
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import json
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import os
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import openai
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INIT_PROMPT = """
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I would like to engage your services as an academic writing consultant to improve my writing.
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I will provide you with text that requires refinement, and you will enhance it with more academic language and sentence structures.
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The essence of the text should remain unaltered, including any LaTeX commands.
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I request that you provide only the improved version of the text without any further explanations.
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"""
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PREFIX_PROMPT = "Please refine the following text in academic English: \n"
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print(f'[INFO] Loading API key from env...')
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openai.api_key = os.getenv("OPENAI_API_KEY")
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if openai.api_key is None:
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print('[WARN] OPENAI_API_KEY key not found in env')
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def submit(x, simple=False):
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# everytime we restart a new conversation.
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if simple:
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results = openai.ChatCompletion.create(
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model="gpt-3.5-turbo",
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messages=[
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{"role": "user", "content": PREFIX_PROMPT + x},
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]
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)
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else:
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results = openai.ChatCompletion.create(
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model="gpt-3.5-turbo",
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messages=[
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{"role": "system", "content": INIT_PROMPT},
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{"role": "user", "content": PREFIX_PROMPT + x},
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]
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)
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total_tokens = results['usage']['total_tokens']
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cost = (total_tokens / 1000) * 0.002 # in dollar
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response = results['choices'][0]['message']['content']
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return response, cost
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print(f'[INFO] Starting Gradio APP...')
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with gr.Blocks() as app:
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gr.Markdown("### ChatGPT, please help to improve my paper writing!")
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# allow setting API key in gui
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with gr.Row():
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api_input = gr.Textbox(label="OPENAI_API_KEY", value=openai.api_key, lines=1)
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def save_api(x): openai.api_key = x
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api_input.change(save_api, api_input)
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simple_checkbox = gr.Checkbox(value=False, label='simple mode (only send the prefix prompt, 0.00142$ cheaper per query)')
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with gr.Row():
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text_input = gr.Textbox(label="Input", lines=10)
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with gr.Column():
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text_output = gr.Textbox(label="Output", lines=10)
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cost = gr.Number(label='cost of this query ($)')
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text_button = gr.Button("Submit")
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text_button.click(submit, inputs=[text_input, simple_checkbox], outputs=[text_output, cost])
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app.launch()
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