import gradio as gr
import pandas as pd
import os
import csv

# Path to the CSV files
patients_file_path = "patients.csv"
reports_file_path = "reports.csv"

def load_patient_data():
    """Load patient data from CSV."""
    try:
        patients_df = pd.read_csv(patients_file_path)
        expected_columns = ["Patient ID", "Patient Name", "Age", "Gender", "Contact Number"]
        if set(patients_df.columns) != set(expected_columns):
            raise ValueError("CSV columns do not match expected columns")
        return patients_df
    except FileNotFoundError:
        return pd.DataFrame(columns=["Patient ID", "Patient Name", "Age", "Gender", "Contact Number"])
    except pd.errors.EmptyDataError:
        return pd.DataFrame(columns=["Patient ID", "Patient Name", "Age", "Gender", "Contact Number"])
    except pd.errors.ParserError as e:
        print(f"Error parsing the CSV file: {e}")
        return pd.DataFrame(columns=["Patient ID", "Patient Name", "Age", "Gender", "Contact Number"])
    except ValueError as e:
        print(f"Error with CSV columns: {e}")
        return pd.DataFrame(columns=["Patient ID", "Patient Name", "Age", "Gender", "Contact Number"])

def get_patient_details(patient_id):
    """Retrieve the patient name based on Patient ID."""
    if not os.path.exists(patients_file_path):
        return "Patients file not found."
    
    with open(patients_file_path, mode='r') as file:
        reader = csv.DictReader(file)
        for row in reader:
            if str(row["Patient ID"]).strip() == str(patient_id).strip():
                return row["Patient Name"]
    return "Patient ID not found."

def autofill_patient_name(patient_id):
    """Auto-fill the patient Name."""
    return get_patient_details(patient_id)

def load_reports_data():
    """Load report data from CSV."""
    try:
        reports_df = pd.read_csv(reports_file_path)
        expected_columns = ["Report ID", "Patient ID", "Report File"]
        if set(reports_df.columns) != set(expected_columns):
            raise ValueError("CSV columns do not match expected columns")
        return reports_df
    except FileNotFoundError:
        return pd.DataFrame(columns=["Report ID", "Patient ID", "Report File"])
    except pd.errors.EmptyDataError:
        return pd.DataFrame(columns=["Report ID", "Patient ID", "Report File"])
    except pd.errors.ParserError as e:
        print(f"Error parsing the CSV file: {e}")
        return pd.DataFrame(columns=["Report ID", "Patient ID", "Report File"])
    except ValueError as e:
        print(f"Error with CSV columns: {e}")
        return pd.DataFrame(columns=["Report ID", "Patient ID", "Report File"])

def handle_file_upload(patient_id, file):
    """Handle file upload and save report details."""
    patient_name = get_patient_details(patient_id)
    if patient_name == "Patient ID not found":
        return f"Error: {patient_name}"
    
    if file is None:
        return "Error: No file uploaded"
    
    # Use the original file name
    original_filename = os.path.basename(file)  # Get the base name of the uploaded file
    sanitized_filename = original_filename.replace(" ", "_").lower()  # Sanitize file name for file system
    file_name = f"report_{patient_id}_{sanitized_filename}"
    file_path = f"reports/{file_name}"
    os.makedirs(os.path.dirname(file_path), exist_ok=True)
    
    # Copy the uploaded file to the destination path
    os.rename(file, file_path)
    
    # Load existing reports data
    reports_df = load_reports_data()
    
    # Add new report details (only the file name, not the full path)
    new_report = pd.DataFrame({
        "Report ID": [reports_df["Report ID"].max() + 1 if not reports_df.empty else 1],
        "Patient ID": [patient_id],
        "Report File": [file_name]  # Store the file name with the original file name
    })
    
    # Append new report details to existing data
    reports_df = pd.concat([reports_df, new_report], ignore_index=True)
    
    # Save updated reports data
    reports_df.to_csv(reports_file_path, index=False)
    
    return f"Report uploaded successfully for {patient_name}."

def gradio_interface():
    """Create Gradio interface for adding reports."""
    with gr.Blocks() as demo:
        with gr.Row():
            # Input for patient ID
            patient_id = gr.Number(label="Patient ID", precision=0)

            # Output for patient name
            patient_name = gr.Textbox(label="Patient Name", interactive=False)

            # Function to update patient name
            def update_patient_name(id):
                return autofill_patient_name(str(id))

            # Update patient name when Patient ID changes
            patient_id.change(
                fn=update_patient_name,
                inputs=patient_id,
                outputs=patient_name
            )

            # File upload for report
            file_upload = gr.File(label="Upload Report (PDF or JPG)", type="filepath")

            # Button to submit the report
            submit_button = gr.Button("Submit")

            # Output for submission result
            output_text = gr.Textbox(label="Submission Result", interactive=False)

            # Handle file upload when the button is clicked
            submit_button.click(
                fn=handle_file_upload,
                inputs=[patient_id, file_upload],
                outputs=output_text
            )

    return demo

if __name__ == "__main__":
    interface = gradio_interface()
    interface.launch()