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from flask import Flask, jsonify, request, send_from_directory
from backend.utils import (
generate_counseling_response,
generate_medication_response,
classify_diabetes,
classify_medicine,
get_llama_response
)
import os
app = Flask(__name__, static_folder='frontend', template_folder='frontend')
# Serve the main HTML file for the frontend
@app.route('/')
def index():
return send_from_directory(app.static_folder, 'index.html')
# Serve the CSS files
@app.route('/styles.css')
def styles():
return send_from_directory(app.static_folder, 'styles.css')
# Serve the JavaScript files
@app.route('/script.js')
def script():
return send_from_directory(app.static_folder, 'script.js')
# Route for Counseling Model
@app.route('/api/counseling', methods=['POST'])
def counseling():
data = request.json
question = data.get('question')
if not question:
return jsonify({"error": "Question is required."}), 400
response = generate_counseling_response(question)
return jsonify({"response": response})
# Route for Medication Info Model
@app.route('/api/medication', methods=['POST'])
def medication():
data = request.json
question = data.get('question')
if not question:
return jsonify({"error": "Question is required."}), 400
response = generate_medication_response(question)
return jsonify({"response": response})
# Route for Diabetes Classification
@app.route('/api/diabetes_classification', methods=['POST'])
def diabetes_classification():
data = request.json
# Extract input features
glucose = data.get('glucose')
bmi = data.get('bmi')
age = data.get('age')
# Validate input data
if glucose is None or bmi is None or age is None:
return jsonify({"error": "Please provide glucose, bmi, and age."}), 400
result = classify_diabetes(glucose, bmi, age)
return jsonify({"result": result})
# Route for Medicine Classification
@app.route('/api/medicine_classification', methods=['POST'])
def medicine_classification():
data = request.json
# Extract input features
age = data.get('age')
gender = data.get('gender')
blood_type = data.get('blood_type')
medical_condition = data.get('medical_condition')
test_results = data.get('test_results')
# Validate input data
if not (age and gender and blood_type and medical_condition and test_results):
return jsonify({"error": "Please provide Age, Gender, Blood Type, Medical Condition, and Test Results."}), 400
# Prepare the new data as a DataFrame
new_data = {
'Age': [int(age)],
'Gender': [gender],
'Blood Type': [blood_type],
'Medical Condition': [medical_condition],
'Test Results': [test_results]
}
# Call the classification function
medicine = classify_medicine(new_data)
return jsonify({"medicine": medicine[0]})
# Route for General Chat (Llama 3.1 API using Groq Cloud)
@app.route('/api/general', methods=['POST'])
def general_chat():
data = request.json
question = data.get('question')
if not question:
return jsonify({"error": "Question is required."}), 400
# Get formatted response from LLaMA 3.1 hosted on Groq Cloud
llama_response = get_llama_response(question)
return jsonify({"response": llama_response})
if __name__ == '__main__':
app.run(debug=True)
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