Create app.py

app.py

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+import gradio as gr
+from datetime import datetime
+from enum import Enum
+from pymongo import MongoClient
+import PIL
+import google.generativeai as genai
+import re
+from langchain_groq import ChatGroq
+from langchain.agents import AgentExecutor, create_tool_calling_agent
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_core.tools import tool
+
+# MongoDB connection
+client = MongoClient('mongodb://miniproject:[email protected]:27017,ac-yzyqqis-shard-00-01.iv8gz1x.mongodb.net:27017,ac-yzyqqis-shard-00-02.iv8gz1x.mongodb.net:27017/?ssl=true&replicaSet=atlas-ayivip-shard-0&authSource=admin&retryWrites=true&w=majority')
+db = client['Final_Year_Project']
+collection = db['Patients']
+
+# Langchain Groq API setup
+groq_api_key = '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'
+llm_agent = ChatGroq(api_key=groq_api_key, model='llama-3.3-70b-versatile', temperature=0.1)
+
+# Set up the prompt template
+prompt = ChatPromptTemplate.from_messages(
+    [
+        (
+            "system",
+            f"You Are an AI Assistant which helps to manage the reminders for Patients. It is currently {datetime.now()}.",
+        ),
+        ("human", "{input}"),
+        ("placeholder", "{agent_scratchpad}"),
+    ]
+)
+
+# Enum for reminder status
+class ReminderStatus(Enum):
+    ACTIVE = "Active"
+    COMPLETED = "Completed"
+    CANCELLED = "Cancelled"
+
+# Tool for saving user data to MongoDB
+@tool
+def save_user_data(user_id: str, patient_name: str, dr_name: str, prescription_date: datetime,
+                   age: int, sex: str, medicines: list, notification_type: str = "Push",
+                   notification_time: int = 30, status: ReminderStatus = ReminderStatus.ACTIVE):
+    reminder = {
+        "user_id": user_id,
+        "patient_name": patient_name,
+        "dr_name": dr_name,
+        "prescription_date": prescription_date.isoformat(),
+        "age": age,
+        "sex": sex,
+        "medicines": medicines,
+        "notification": {
+            "type": notification_type,
+            "time_before": notification_time
+        },
+        "status": status.value,
+        "created_at": datetime.now()
+    }
+    
+    result = collection.insert_one(reminder)
+    return result.inserted_id
+
+tools = [save_user_data]
+agent = create_tool_calling_agent(llm_agent, tools, prompt)
+agent_executor = AgentExecutor(agent=agent, tools=tools)
+
+# API key for Google Generative AI
+genai.configure(api_key="AIzaSyCltTyFKRtgLQBR9BwX0q9e2aDW9BwwUfo")
+
+# Function to process the image and generate text using Google AI
+def extract_and_store_text(file, user_id):
+    try:
+        # Open the image using PIL
+        image = PIL.Image.open(file)
+
+        # Generate text using Google Generative AI
+        mod = genai.GenerativeModel(model_name="gemini-2.0-flash")
+        text = mod.generate_content(contents=["Extract all text from this image, including medication names, dosages, instructions, patient information, and any other relevant medical details if this is a prescription. If the image is not a prescription, return only 'None'.", image])
+        
+        pattern = r'[_*]+\s*'
+        data_str = re.sub(pattern, '', text.text)
+        
+        if not text.text:
+            return "No relevant text found"
+        
+        else:
+            res = agent_executor.invoke({"input": f'Add this Data to Mongo DB for user with user_id {user_id} DATA : {str(data_str)}'})
+            ans = collection.find_one({'user_id': user_id}, {'_id': 0})
+            return str(ans)
+    
+    except Exception as e:
+        return str(e)
+
+# Gradio interface
+def gradio_interface(file, user_id):
+    return extract_and_store_text(file, user_id)
+
+# Define Gradio Inputs and Outputs
+inputs = [
+    gr.File(label="Upload Image"),
+    gr.Textbox(label="User ID", value="101")  # Default user ID
+]
+outputs = gr.Textbox(label="Response")
+
+# Create Gradio Interface
+interface = gr.Interface(
+    fn=gradio_interface, 
+    inputs=inputs, 
+    outputs=outputs,
+    title="Patient Reminder System", 
+    description="Extracts and stores patient prescription details from images."
+)
+
+if __name__ == "__main__":
+    interface.launch()