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Create app.py
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app.py
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import streamlit as st
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# Create a Streamlit app
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st.title("AI Symptom Checker")
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st.write("Please enter your symptoms:")
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# Create a text input field
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symptoms_input = st.text_input("Symptoms:", value="", max_chars=500)
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# Create a button to trigger the API call
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submit_button = st.button("Check Symptoms")
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# Define the Google Gemini API call function
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def call_gemini_api(symptoms, api_key):
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client = build('gemini', 'v1', developerKey=api_key)
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request = {
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'query': symptoms,
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'languageCode': 'en-US',
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'maxResults': 10
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}
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response = client.health().symptomChecker().query(body=request).execute()
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results = response.get('results', [])
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return results
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# Define the response processing function
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def process_response(results):
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top_results = results[:3]
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response_list = []
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for result in top_results:
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condition_name = result.get('condition', {}).get('name')
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probability = result.get('probability')
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response_string = f"**{condition_name}**: {probability:.2f}%"
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response_list.append(response_string)
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return response_list
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# Define the main function to call the API and process the response
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def check_symptoms(symptoms, api_key):
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results = call_gemini_api(symptoms, api_key)
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response_list = process_response(results)
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return response_list
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# Get the API key from the environment variables
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api_key = st.secrets["AIzaSyBKkDeuMYrYSvwiRX4eyqJ8Vy8xfVwPfGQ"]
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# Call the main function when the button is clicked
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if submit_button:
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symptoms = symptoms_input
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response_list = check_symptoms(symptoms, api_key)
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st.write("Possible conditions:")
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for response in response_list:
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st.write(response)
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