Delete app.py
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app.py
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import os
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import gradio
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from groq import Groq
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from gradio import Textbox, Outputs
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# Initialize the GROQ client with your API key
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client = Groq(api_key=os.environ.get("GROQ_API_KEY"))
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# Initialize an empty conversation history list
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conversation_history = []
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def chatbot_with_submit(user_input):
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global conversation_history
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# If this is the first user input, provide the chatbot introduction message
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if not conversation_history:
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conversation_history.append({"role": "user", "content": "You are a medical chatbot and your name is Dr.BeeAi, Please provide information and advice on medical topics only. This includes questions related to symptoms, diagnoses, treatments, medications, and general health concerns. Please avoid responding to non-medical topics or questions that are not related to health or wellness."})
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# Add the user input to the conversation history
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conversation_history.append({"role": "user", "content": user_input})
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# Use GROQ Cloud API to generate a response
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chat_completion = client.chat.completions.create(
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messages=conversation_history,
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model="mixtral-8x7b-32768"
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)
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# Add the chatbot's response to the conversation history
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chatbot_reply = chat_completion.choices[0].message.content
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conversation_history.append({"role": "bot", "content": chatbot_reply})
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# Return the chatbot's response
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return chatbot_reply
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# You can keep the rest of the code for the Gradio interface as it is
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textbox = Textbox("Enter something:")
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output = Outputs("Here's the output:")
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interface_title = "Bee4Med Ai - GROQ"
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examples = [
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["What are the symptoms of a common cold?"],
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["How can I treat a migraine?"],
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["Is it safe to take aspirin while pregnant?"]
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]
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demo = gradio.Interface(
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fn=chatbot_with_submit,
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inputs=[my_input],
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outputs=my_output,
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title=interface_title,
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description=''' Warning: please consult a doctor in emergency situations, Our predictions may get wrong at times''',
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examples=examples
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)
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demo.launch()
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