Fixed Trinitey's name

AiMedTracker/backend/ai_funcs.py

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+# ai code - openrouter
+
+import requests
+import json
+import os
+import traceback
+from dotenv import load_dotenv
+
+# Load environment variables from .env file
+load_dotenv()
+
+# Get API key from environment variable
+OPENROUTER_API_KEY = os.getenv("OPENROUTER_API_KEY")
+OPENROUTER_API_URL = "https://openrouter.ai/api/v1/chat/completions"
+
+def generate_llm_response(prompt, model="openai/gpt-3.5-turbo"):
+    """
+    Generate a response using the OpenRouter API.
+
+    Args:
+        prompt (str): The input prompt for the LLM
+        model (str): The model to use (default: openai/gpt-3.5-turbo)
+
+    Returns:
+        str: The generated response
+    """
+    if not OPENROUTER_API_KEY:
+        print("Error: OPENROUTER_API_KEY environment variable not set")
+        return "Error: API key not configured. Please contact support."
+
+    headers = {
+        "Authorization": f"Bearer {OPENROUTER_API_KEY}",
+        "HTTP-Referer": "https://github.com/your-username/AiInteractionApp",
+        "X-Title": "AI Drug Interaction App",
+        "Content-Type": "application/json"
+    }
+
+    data = {
+        "model": model,
+        "messages": [
+            {"role": "system", "content": "You are a helpful AI assistant that provides information about drug interactions and medications."},
+            {"role": "user", "content": prompt}
+        ],
+        "temperature": 0.7,
+        "max_tokens": 1000,
+        "timeout": 120
+    }
+
+    try:
+        print(f"Sending prompt to OpenRouter API: {prompt[:200]}...")
+        print(f"Using model: {model}")
+
+        response = requests.post(
+            OPENROUTER_API_URL,
+            headers=headers,
+            json=data,
+            timeout=120
+        )
+
+        if response.status_code != 200:
+            error_msg = f"API Error: {response.status_code} - {response.text}"
+            print(error_msg)
+            return f"Error analyzing interaction: {error_msg}"
+
+        response_json = response.json()
+
+        if "choices" not in response_json or not response_json["choices"]:
+            print("No choices in response")
+            return "Error: No response from AI model. Please try again."
+
+        result = response_json["choices"][0]["message"]["content"]
+        print(f"Received response from OpenRouter API: {result[:200]}...")
+        return result
+
+    except requests.exceptions.Timeout:
+        print("Request timed out after 120 seconds")
+        return "Error: The AI model is taking longer than expected to respond. Please try again in a few moments."
+    except requests.exceptions.RequestException as e:
+        print(f"Request error: {str(e)}")
+        return f"Error: Could not connect to AI service. Please try again."
+    except Exception as e:
+        print(f"Unexpected error: {str(e)}")
+        print(f"Full traceback: {traceback.format_exc()}")
+        return "Error: An unexpected error occurred. Please try again."
+
+def analyze_interaction(med1, med2):
+    """
+    Use LLM to analyze potential interactions between two medications.
+
+    Args:
+        med1 (str): First medication name
+        med2 (str): Second medication name
+
+    Returns:
+        str: Analysis of potential interactions
+    """
+    prompt = f"""Analyze the potential interactions between {med1} and {med2}.
+
+    Consider:
+    1. Common side effects when taken together
+    2. Potential drug interactions and their severity
+    3. Contraindications or warnings
+    4. Recommendations for patients taking both medications
+
+    Provide a concise, patient-friendly summary that explains:
+    - The main interaction concern
+    - Key warnings or precautions
+    - What patients should do if they're taking both medications
+
+    Format the response in a clear, easy-to-read manner with bullet points where appropriate.
+    Keep the response brief but informative."""
+
+    return generate_llm_response(prompt)
+
+def get_medication_info(medication):
+    """
+    Use LLM to get detailed information about a medication.
+
+    Args:
+        medication (str): Medication name
+
+    Returns:
+        str: Detailed information about the medication
+    """
+    prompt = f"""Provide detailed information about {medication}.
+    Include:
+    1. Common uses
+    2. Typical dosage
+    3. Common side effects
+    4. Important warnings
+    5. Drug interactions
+
+    Format the response in a clear, easy-to-read manner."""
+
+    return generate_llm_response(prompt)
+

AiMedTracker/backend/data/users.json

@@ -0,0 +1,11 @@
+{
+  "users": {
+    "u1": {
+      "email": "pat@example.com",
+      "password": "pass123",
+      "type": "patient",
+      "name": "Thomas Yang",
+      "medications": []
+    }
+  }
+}

AiMedTracker/backend/main.py

@@ -0,0 +1,207 @@
+from flask import Flask, request, jsonify
+from flask_cors import CORS
+import json
+import os
+import requests
+from user_funcs import create_user, verify_user, get_user, update_user, delete_user
+from ai_funcs import analyze_interaction, get_medication_info
+
+app = Flask(__name__)
+CORS(app)  # This allows your React frontend to make requests to this backend
+
+
+def normalize_name(name):
+    return name.strip().lower()
+
+def check_name(medication):
+    """
+    Check if a medication exists in the FDA database and return information.
+    """
+    medication = medication.strip().lower()
+    print(f"Checking medication: {medication}")
+
+    # Search for both generic and brand names
+    url = f"https://api.fda.gov/drug/label.json?search=openfda.generic_name:{medication}+OR+openfda.brand_name:{medication}&limit=1"
+    try:
+        response = requests.get(url)
+        response.raise_for_status()
+        data = response.json()
+
+        if "results" not in data or len(data["results"]) == 0:
+            print(f"Medication not found: {medication}")
+            return medication.capitalize() + " not found."
+
+        result = data["results"][0]
+        openfda = result.get("openfda", {})
+
+        # Get medication names
+        generic_names = openfda.get("generic_name", [])
+        brand_names = openfda.get("brand_name", [])
+
+        generic_name = generic_names[0] if generic_names else medication
+        brand_name = brand_names[0] if brand_names else ""
+
+        # Build response message
+        info = f"{generic_name.capitalize()} found."
+        if brand_name and brand_name.lower() != generic_name.lower():
+            info += f" Brand name: {brand_name}."
+
+        print(f"Medication found: {info}")
+        return info
+
+    except Exception as e:
+        print(f"Error checking FDA database: {str(e)}")
+        return medication.capitalize() + " not found (Error)."
+
+def check_if_medication_exists(medication):
+    """Simple helper function to check if a medication exists in the FDA database"""
+    medication = medication.strip().lower()
+    url = f"https://api.fda.gov/drug/label.json?search=openfda.generic_name:{medication}+OR+openfda.brand_name:{medication}&limit=1"
+    try:
+        response = requests.get(url)
+        if response.status_code != 200:
+            print(f"FDA API error: {response.status_code}")
+            return False
+
+        data = response.json()
+        if "results" not in data:
+            print("No results field in FDA API response")
+            return False
+
+        exists = len(data["results"]) > 0
+        print(f"Medication {medication} {'exists' if exists else 'does not exist'} in FDA database")
+        return exists
+    except Exception as e:
+        print(f"Error checking FDA database: {str(e)}")
+        return False
+
+
+@app.route('/api/check-interaction', methods=['POST'])
+def check_interaction():
+    data = request.get_json()
+    med1 = data.get('medication1', '').strip()
+    med2 = data.get('medication2', '').strip()
+
+    if not med1 or not med2:
+        return jsonify({'success': False, 'message': 'Both medications are required'})
+
+    # First check if medications exist in FDA database
+    med1_exists = check_if_medication_exists(med1)
+    med2_exists = check_if_medication_exists(med2)
+
+    if not med1_exists or not med2_exists:
+        return jsonify({
+            'success': False,
+            'message': 'One or both medications not found in FDA database'
+        })
+
+    # Use LLM to analyze the interaction
+    analysis = analyze_interaction(med1, med2)
+    print(f"AI Analysis result: {analysis}")
+
+    # Check if the analysis starts with "Error:" to indicate an error message
+    if analysis and analysis.startswith("Error:"):
+        return jsonify({
+            'success': False,
+            'message': analysis
+        })
+
+    if not analysis:
+        return jsonify({
+            'success': False,
+            'message': 'Error analyzing medication interaction'
+        })
+
+    # Return the analysis with success status
+    response = {
+        'success': True,
+        'message': 'Interaction analysis completed',
+        'analysis': analysis
+    }
+    print(f"Sending response: {response}")
+    return jsonify(response)
+
+
+@app.route('/api/check-medication', methods=['POST'])
+def check_medication():
+    data = request.json
+    medication = data.get('medicationName')
+
+    if not medication:
+        return jsonify({
+            "success": False,
+            "error": "Medication name is required"
+        }), 400
+
+    print(f"Received medication check request for: {medication}")
+    result = check_name(medication)
+
+    # Check if the result contains "not found" to determine if the medication exists
+    exists = "not found" not in result.lower()
+
+    response = {
+        "success": True,
+        "exists": exists,
+        "message": result
+    }
+
+    print(f"Sending response: {response}")
+    return jsonify(response)
+
+@app.route('/api/signup', methods=['POST'])
+def signup():
+    try:
+        data = request.get_json()
+        user = create_user(data)
+        return jsonify({"success": True, "user": user}), 201
+    except ValueError as e:
+        return jsonify({"success": False, "error": str(e)}), 400
+    except Exception as e:
+        return jsonify({"success": False, "error": "An error occurred during signup"}), 500
+
+@app.route('/api/login', methods=['POST'])
+def login():
+    try:
+        data = request.get_json()
+        user = verify_user(data['email'], data['password'])
+        if user:
+            return jsonify({"success": True, "user": user}), 200
+        return jsonify({"success": False, "error": "Invalid credentials"}), 401
+    except Exception as e:
+        return jsonify({"success": False, "error": "An error occurred during login"}), 500
+
+@app.route('/api/user/<email>', methods=['GET'])
+def get_user_profile(email):
+    try:
+        user = get_user(email)
+        if user:
+            # Remove password from response
+            user_copy = user.copy()
+            user_copy.pop('password', None)
+            return jsonify({"success": True, "user": user_copy}), 200
+        return jsonify({"success": False, "error": "User not found"}), 404
+    except Exception as e:
+        return jsonify({"success": False, "error": "An error occurred"}), 500
+
+@app.route('/api/user/<email>', methods=['PUT'])
+def update_user_profile(email):
+    try:
+        data = request.get_json()
+        user = update_user(email, data)
+        return jsonify({"success": True, "user": user}), 200
+    except ValueError as e:
+        return jsonify({"success": False, "error": str(e)}), 400
+    except Exception as e:
+        return jsonify({"success": False, "error": "An error occurred"}), 500
+
+@app.route('/api/user/<email>', methods=['DELETE'])
+def delete_user_profile(email):
+    try:
+        if delete_user(email):
+            return jsonify({"success": True}), 200
+        return jsonify({"success": False, "error": "User not found"}), 404
+    except Exception as e:
+        return jsonify({"success": False, "error": "An error occurred"}), 500
+
+if __name__ == '__main__':
+    app.run(debug=True, port=5001)

AiMedTracker/backend/requirements.txt

@@ -0,0 +1,4 @@
+flask==3.0.2
+flask-cors==4.0.0
+requests==2.31.0
+python-dotenv==1.0.0 

AiMedTracker/backend/text.txt

@@ -0,0 +1 @@
+