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import gradio as gr |
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import time, os |
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from openai import OpenAI |
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api_key = os.environ["OPENAI_API_KEY_PUBLIC"] |
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class ask_me: |
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def __init__(self): |
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self.client = OpenAI(api_key=api_key) |
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self.thread = self.client.beta.threads.create() |
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def ask(self,question): |
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run = self.client.beta.threads.runs.create( |
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thread_id=self.thread.id, |
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assistant_id='asst_cqL6gztTsqBGDdkKegpcQ32Y', |
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instructions=question |
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) |
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while run.status in ['queued', 'in_progress', 'cancelling']: |
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time.sleep(1) |
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run = self.client.beta.threads.runs.retrieve( |
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thread_id=self.thread.id, |
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run_id=run.id |
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) |
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if run.status == 'completed': |
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messages = self.client.beta.threads.messages.list( |
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thread_id=self.thread.id |
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) |
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return messages.data[0].content[0].text.value |
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else: |
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return run.status |
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def clear(self): |
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self.thread = self.client.beta.threads.create() |
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return "New search is there." |
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def wait(): |
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time.sleep(1) |
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return "Waiting for the answer." |
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temp = ask_me() |
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with gr.Blocks(css="footer {visibility: hidden}") as demo: |
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with gr.Row(): |
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with gr.Column(scale=5): |
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search_box = gr.Textbox(label= "Your questions",value="How many MOF with Cu?",interactive = True) |
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with gr.Column(scale=2): |
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sub = gr.Button("Ask it!") |
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clear = gr.Button("New search") |
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with gr.Row(): |
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text = gr.Textbox(label= "Result",value="Answer is out there.") |
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sub.click(temp.ask,inputs=search_box,outputs=text) |
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clear.click(temp.clear,outputs=text) |
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demo.launch(debug=True) |
