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Sleeping
| import streamlit as st | |
| import groq | |
| from dotenv import load_dotenv | |
| import os | |
| load_dotenv() | |
| # Initialize the Groq client | |
| client = groq.Groq() | |
| GROQ_API_KEY = os.getenv("GROQ_API_KEY") | |
| # Available models | |
| MODELS = [ | |
| "mixtral-8x7b-32768", | |
| "gemma2-9b-it", | |
| "llama-3.2-1b-preview", | |
| ] | |
| # Default system prompt | |
| DEFAULT_SYSTEM_PROMPT = """You are an expert physiotherapist dedicated to helping users improve their well-being. | |
| Using the user's provided data, | |
| Send a brief, 2-line message to [patient name], personalized message that checks in on their condition or asks | |
| how they’ve been feeling lately, even though they haven’t taken a plan yet. | |
| The message should be warm, empathetic, and tailored to their persona, | |
| city or country, and specific needs. Focus on being kind, supportive, and motivating, | |
| while offering a helpful tip or insight that shows your genuine care for their health. | |
| Build trust by emphasizing that you’re here to help them at their pace, without any pressure, so they feel confident and reassured in reaching out whenever they’re ready.""" | |
| # Sidebar for system prompt | |
| st.sidebar.title("System Prompt") | |
| system_prompt = st.sidebar.text_area("Edit the system prompt here:", value=DEFAULT_SYSTEM_PROMPT, height=300) | |
| # Add a button to apply the system prompt | |
| if st.sidebar.button("Apply System Prompt"): | |
| st.session_state.system_prompt = system_prompt | |
| # Clear the chat history when a new prompt is applied | |
| st.session_state.messages = [{"role": "system", "content": system_prompt}] | |
| st.sidebar.success("System prompt applied successfully! Chat history cleared.") | |
| # Initialize system_prompt in session state if it doesn't exist | |
| if "system_prompt" not in st.session_state: | |
| st.session_state.system_prompt = DEFAULT_SYSTEM_PROMPT | |
| # Initialize chat history if it doesn't exist | |
| if "messages" not in st.session_state: | |
| st.session_state.messages = [{"role": "system", "content": st.session_state.system_prompt}] | |
| # Streamlit app | |
| st.title("Health Genie App") | |
| # Model selection | |
| selected_model = st.selectbox("Select a model", MODELS) | |
| # Add a Clear Conversation button | |
| if st.button("Clear Conversation"): | |
| st.session_state.messages = [{"role": "system", "content": st.session_state.system_prompt}] | |
| st.success("Conversation cleared!") | |
| # Predefined patient profiles | |
| patient_profiles = { | |
| "Patient 1": { | |
| "name": "John Doe", | |
| "age": 35, "gender": "Male", "height": 175, "weight": 80, "city": "New York", "country": "USA", | |
| "occupation": "Software Engineer", "chief_complaints": "Lower back pain", "pain_level": 6, | |
| "pain_duration": "2 weeks", "comorbidities": "None", "lifestyle": "Sedentary", | |
| "pain_history": "Started after long hours of sitting", "aggravating_factor": "Prolonged sitting", | |
| "relieving_factor": "Walking", "patient_goal": "Return to normal work routine", | |
| "joints": "Lumbar spine", "observations": "Reduced lumbar lordosis", | |
| "clinical_assessment": "Muscle spasm in lower back", "medical_reports": "X-ray shows no abnormalities", | |
| "provisional_diagnosis": "Mechanical low back pain", "treatment_plan": "Physical therapy and ergonomic adjustments", | |
| "precautions": "Avoid prolonged sitting", "remarks_physio": "Focus on core strengthening", | |
| "attitude": "Motivated", "patient_persona": "Tech-savvy, busy professional" | |
| }, | |
| "Patient 2": { | |
| "name": "Jane Smith", | |
| "age": 55, "gender": "Female", "height": 165, "weight": 70, "city": "London", "country": "UK", | |
| "occupation": "Teacher", "chief_complaints": "Knee pain", "pain_level": 7, | |
| "pain_duration": "3 months", "comorbidities": "Hypertension", "lifestyle": "Moderately active", | |
| "pain_history": "Gradual onset, worsening over time", "aggravating_factor": "Climbing stairs", | |
| "relieving_factor": "Rest and ice", "patient_goal": "Walk without pain", | |
| "joints": "Right knee", "observations": "Slight swelling", | |
| "clinical_assessment": "Crepitus on movement", "medical_reports": "MRI shows mild osteoarthritis", | |
| "provisional_diagnosis": "Osteoarthritis of the knee", "treatment_plan": "Physical therapy and weight management", | |
| "precautions": "Low-impact exercises only", "remarks_physio": "Gait training and knee stabilization exercises", | |
| "attitude": "Concerned", "patient_persona": "Dedicated educator, worried about mobility" | |
| }, | |
| "Patient 3": { | |
| "name": "Emily Brown", | |
| "age": 28, "gender": "Female", "height": 160, "weight": 55, "city": "Sydney", "country": "Australia", | |
| "occupation": "Graphic Designer", "chief_complaints": "Neck and shoulder pain", "pain_level": 5, | |
| "pain_duration": "1 month", "comorbidities": "Migraine", "lifestyle": "Active", | |
| "pain_history": "Started after increased workload", "aggravating_factor": "Long hours at computer", | |
| "relieving_factor": "Stretching", "patient_goal": "Work without discomfort", | |
| "joints": "Cervical spine, shoulder", "observations": "Forward head posture", | |
| "clinical_assessment": "Tight upper trapezius", "medical_reports": "No imaging done", | |
| "provisional_diagnosis": "Work-related musculoskeletal disorder", "treatment_plan": "Ergonomic assessment, posture correction", | |
| "precautions": "Regular breaks from computer work", "remarks_physio": "Focus on scapular stabilization", | |
| "attitude": "Proactive", "patient_persona": "Creative professional, health-conscious" | |
| }, | |
| "Patient 4": { | |
| "name": "Michael Johnson", | |
| "age": 45, "gender": "Male", "height": 180, "weight": 90, "city": "Toronto", "country": "Canada", | |
| "occupation": "Construction Worker", "chief_complaints": "Shoulder pain", "pain_level": 8, | |
| "pain_duration": "6 weeks", "comorbidities": "Type 2 Diabetes", "lifestyle": "Physically demanding job", | |
| "pain_history": "Injury while lifting heavy object", "aggravating_factor": "Overhead activities", | |
| "relieving_factor": "Rest and NSAIDs", "patient_goal": "Return to work full capacity", | |
| "joints": "Right shoulder", "observations": "Limited range of motion", | |
| "clinical_assessment": "Positive impingement tests", "medical_reports": "Ultrasound shows rotator cuff tendinopathy", | |
| "provisional_diagnosis": "Rotator cuff tendinopathy", "treatment_plan": "Physical therapy, gradual return to work", | |
| "precautions": "Avoid heavy lifting temporarily", "remarks_physio": "Rotator cuff strengthening program", | |
| "attitude": "Frustrated", "patient_persona": "Hardworking, eager to return to full duties" | |
| }, | |
| "Patient 5": { | |
| "name": "Anna Schmidt", | |
| "age": 62, "gender": "Female", "height": 170, "weight": 75, "city": "Berlin", "country": "Germany", | |
| "occupation": "Retired", "chief_complaints": "Hip pain", "pain_level": 6, | |
| "pain_duration": "4 months", "comorbidities": "Osteoporosis", "lifestyle": "Moderately active", | |
| "pain_history": "Gradual onset, worse in mornings", "aggravating_factor": "Prolonged walking", | |
| "relieving_factor": "Warm compress", "patient_goal": "Maintain independence in daily activities", | |
| "joints": "Left hip", "observations": "Antalgic gait", | |
| "clinical_assessment": "Reduced internal rotation", "medical_reports": "X-ray shows mild joint space narrowing", | |
| "provisional_diagnosis": "Early hip osteoarthritis", "treatment_plan": "Physical therapy, aquatic exercises", | |
| "precautions": "Fall prevention strategies", "remarks_physio": "Focus on hip mobility and strength", | |
| "attitude": "Determined", "patient_persona": "Active retiree, enjoys gardening" | |
| } | |
| } | |
| # Function to create a row of 3 inputs | |
| def create_input_row(col1_input, col2_input, col3_input): | |
| col1, col2, col3 = st.columns(3) | |
| with col1: | |
| val1 = col1_input() | |
| with col2: | |
| val2 = col2_input() | |
| with col3: | |
| val3 = col3_input() | |
| return val1, val2, val3 | |
| # Create buttons for patient profiles | |
| st.subheader("Quick Patient Profiles") | |
| cols = st.columns(5) | |
| for i, (profile_name, profile_data) in enumerate(patient_profiles.items()): | |
| if cols[i].button(profile_name): | |
| st.session_state.update(profile_data) | |
| user_name = st.session_state.get("name", "") # Update the name field | |
| # Create a form for user inputs | |
| with st.form(key='patient_info_form'): | |
| # User input rows | |
| name, age, gender = create_input_row( | |
| lambda: st.text_input("Patient Name", value=st.session_state.get("name", "")), | |
| lambda: st.number_input("Age", min_value=0, max_value=120, value=st.session_state.get("age", 30)), | |
| lambda: st.selectbox("Gender", ["Male", "Female", "Other"], index=["Male", "Female", "Other"].index(st.session_state.get("gender", "Male"))) | |
| ) | |
| height, weight, city = create_input_row( | |
| lambda: st.number_input("Height (cm)", min_value=0, max_value=300, value=st.session_state.get("height", 170)), | |
| lambda: st.number_input("Weight (kg)", min_value=0, max_value=500, value=st.session_state.get("weight", 70)), | |
| lambda: st.text_input("City/Town", value=st.session_state.get("city", "")) | |
| ) | |
| country, occupation, chief_complaints = create_input_row( | |
| lambda: st.text_input("Country", value=st.session_state.get("country", "")), | |
| lambda: st.text_input("Occupation", value=st.session_state.get("occupation", "")), | |
| lambda: st.text_area("Chief Complaints", value=st.session_state.get("chief_complaints", "")) | |
| ) | |
| pain_level, pain_duration, comorbidities = create_input_row( | |
| lambda: st.number_input("Pain Level", 0, 10, value=st.session_state.get("pain_level", 5)), | |
| lambda: st.text_input("Pain Duration", value=st.session_state.get("pain_duration", "")), | |
| lambda: st.text_area("Co-morbidities", value=st.session_state.get("comorbidities", "")) | |
| ) | |
| lifestyle, pain_history, aggravating_factor = create_input_row( | |
| lambda: st.text_area("Lifestyle", value=st.session_state.get("lifestyle", "")), | |
| lambda: st.text_area("History of this Pain", value=st.session_state.get("pain_history", "")), | |
| lambda: st.text_area("Aggravating Factor", value=st.session_state.get("aggravating_factor", "")) | |
| ) | |
| relieving_factor, patient_goal, joints = create_input_row( | |
| lambda: st.text_area("Relieving Factor", value=st.session_state.get("relieving_factor", "")), | |
| lambda: st.text_area("Patient Eventual Goal", value=st.session_state.get("patient_goal", "")), | |
| lambda: st.text_area("Joints", value=st.session_state.get("joints", "")) | |
| ) | |
| observations, clinical_assessment, medical_reports = create_input_row( | |
| lambda: st.text_area("Observations", value=st.session_state.get("observations", "")), | |
| lambda: st.text_area("Clinical Assessment", value=st.session_state.get("clinical_assessment", "")), | |
| lambda: st.text_area("Medical Reports Summary", value=st.session_state.get("medical_reports", "")) | |
| ) | |
| provisional_diagnosis, treatment_plan, precautions = create_input_row( | |
| lambda: st.text_area("Provisional Diagnosis", value=st.session_state.get("provisional_diagnosis", "")), | |
| lambda: st.text_area("Treatment Plan Advised", value=st.session_state.get("treatment_plan", "")), | |
| lambda: st.text_area("Precautions/Advice", value=st.session_state.get("precautions", "")) | |
| ) | |
| remarks_physio, attitude, patient_persona = create_input_row( | |
| lambda: st.text_area("Remarks for Physio", value=st.session_state.get("remarks_physio", "")), | |
| lambda: st.text_input("Attitude", value=st.session_state.get("attitude", "")), | |
| lambda: st.text_area("Patient Persona", value=st.session_state.get("patient_persona", "")) | |
| ) | |
| # Add the Apply button at the end of the form | |
| apply_button = st.form_submit_button(label='Apply') | |
| # Handle form submission | |
| if apply_button: | |
| # Update session state with new values | |
| st.session_state.update({ | |
| "name": name, | |
| "age": age, | |
| "gender": gender, | |
| "height": height, | |
| "weight": weight, | |
| "city": city, | |
| "country": country, | |
| "occupation": occupation, | |
| "chief_complaints": chief_complaints, | |
| "pain_level": pain_level, | |
| "pain_duration": pain_duration, | |
| "comorbidities": comorbidities, | |
| "lifestyle": lifestyle, | |
| "pain_history": pain_history, | |
| "aggravating_factor": aggravating_factor, | |
| "relieving_factor": relieving_factor, | |
| "patient_goal": patient_goal, | |
| "joints": joints, | |
| "observations": observations, | |
| "clinical_assessment": clinical_assessment, | |
| "medical_reports": medical_reports, | |
| "provisional_diagnosis": provisional_diagnosis, | |
| "treatment_plan": treatment_plan, | |
| "precautions": precautions, | |
| "remarks_physio": remarks_physio, | |
| "attitude": attitude, | |
| "patient_persona": patient_persona | |
| }) | |
| st.success("Patient information updated successfully!") | |
| # Display chat messages (excluding system message) | |
| for message in st.session_state.messages[1:]: | |
| with st.chat_message(message["role"]): | |
| st.markdown(message["content"]) | |
| # User input | |
| if prompt := st.chat_input("Type Anything to start"): | |
| # Prepare the user information | |
| user_info = f""" | |
| Name: {name} | |
| Age: {age}, Gender: {gender}, Height: {height} cm, Weight: {weight} kg | |
| Location: {city}, {country} | |
| Occupation: {occupation} | |
| Chief Complaints: {chief_complaints} | |
| Pain Level: {pain_level}, Pain Duration: {pain_duration} | |
| Co-morbidities: {comorbidities} | |
| Lifestyle: {lifestyle} | |
| Pain History: {pain_history} | |
| Aggravating Factor: {aggravating_factor} | |
| Relieving Factor: {relieving_factor} | |
| Patient Goal: {patient_goal} | |
| Joints: {joints} | |
| Observations: {observations} | |
| Clinical Assessment: {clinical_assessment} | |
| Medical Reports: {medical_reports} | |
| Provisional Diagnosis: {provisional_diagnosis} | |
| Treatment Plan: {treatment_plan} | |
| Precautions: {precautions} | |
| Remarks for Physio: {remarks_physio} | |
| Attitude: {attitude} | |
| Patient Persona: {patient_persona} | |
| """ | |
| # Update the system prompt with user information | |
| updated_system_prompt = f"{st.session_state.system_prompt}\n\nCurrent Patient Information:\n{user_info}" | |
| # Update the first message in the conversation (system prompt) | |
| st.session_state.messages[0] = {"role": "system", "content": updated_system_prompt} | |
| # Append the user's question | |
| st.session_state.messages.append({"role": "user", "content": prompt}) | |
| with st.chat_message("user"): | |
| st.markdown(prompt) | |
| # Generate response | |
| with st.chat_message("assistant"): | |
| message_placeholder = st.empty() | |
| full_response = "" | |
| for response in client.chat.completions.create( | |
| messages=st.session_state.messages, | |
| model=selected_model, | |
| stream=True, | |
| ): | |
| full_response += (response.choices[0].delta.content or "") | |
| message_placeholder.markdown(full_response + "▌") | |
| message_placeholder.markdown(full_response) | |
| st.session_state.messages.append({"role": "assistant", "content": full_response}) | |
| # Display a warning about API key | |
| st.sidebar.warning("Make sure to set your Groq API key as an environment variable named GROQ_API_KEY") |