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Application File

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  1. app.py +55 -0
app.py ADDED
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+ import os
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+ import streamlit as st
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+ import keyfile as kf
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+ from langchain.llms import OpenAI
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+ from langchain import PromptTemplate, LLMChain
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+
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+ # Set up the Streamlit app
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+ st.title("Patient Symptom Analyzer")
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+
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+ # Input field for OpenAI API Key
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+ api_key = kf.OPENKEY
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+
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+ # Check if API key is provided
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+ if api_key:
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+ os.environ["OPENAI_API_KEY"] = api_key
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+
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+ # Initialize the OpenAI LLM
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+ llm = OpenAI(temperature=0.7, max_tokens=1500)
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+
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+ # Input field for patient symptoms
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+ symptoms = st.text_area("Enter the patient's symptoms:")
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+
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+ # Generate Report button
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+ if st.button("Generate Report"):
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+ if symptoms:
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+ # Define the prompt template
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+ prompt = PromptTemplate(
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+ input_variables=["symptoms"],
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+ template="""
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+ Given the following patient symptoms: {symptoms},
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+ provide general information including:
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+
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+ 1. Common conditions associated with these symptoms (without making a diagnosis).
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+ 2. General advice on seeking professional medical help.
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+ 3. Preventive measures to maintain health.
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+
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+ Do not provide specific medical diagnoses or treatments. Emphasize the importance of consulting a healthcare professional for proper diagnosis and treatment.
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+ """
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+ )
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+
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+ # Create the LLMChain with the prompt
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+ chain = LLMChain(llm=llm, prompt=prompt)
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+
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+ # Generate the report
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+ with st.spinner("Generating report..."):
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+ try:
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+ report = chain.run(symptoms)
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+ st.success("Report generated successfully.")
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+ st.write(report)
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+ except Exception as e:
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+ st.error(f"An error occurred: {e}")
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+ else:
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+ st.warning("Please enter the patient's symptoms.")
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+ else:
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+ st.warning("Please enter your OpenAI API Key.")