import time
import os
import gradio as gr
from utils.doc_contact import Doctor
from openai import OpenAI

client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])

def create_thread():
    thread = client.beta.threads.create()
    return thread.id

# Initialize thread ID for the current session
thread_id = create_thread()

# Initialize the client
# Set your OpenAI API key

"""file = client.files.create(
    file=open("songs.txt", "rb"),
    purpose='assistants'
)"""

# Step 1: Create an Assistant
assistant = client.beta.assistants.create(
    name="MeroHealthAI",
    instructions="You are a highly qualified and skilled doctor \
                    who asks all the right questions to the patient to know about their symptoms \
                    and create an engaging and interesting conversation \
                    and make patients let out all the diseases they are \
                    suffering from. Then, create a medical report \
                    based on the symptoms automatically after you receive all the required information from the patient. \
                    Report the symptoms in a formal \
                    formatted diagnosis report. Make sure to include all the vital \
                    informations by asking the patients. Strictly start with asking their name, age, gender and if they have any previous medical condition(eg: high blood pressure, sugar, diabetes,etc.).\
                    Also ask their weight and height(if they know). Ask one question at a time so that the user doesn't feel overwhelmed. After completing asking the \
                    symptoms, automatically generate the symptoms in a medical report like format along with the patient's information. If the user tries to ask anything else which is not\
                    related to health and symptoms, deviate the topic back to health and symptoms.\
                    After documenting the symptoms,tell the user to visit the type of doctor(example: neurologist, dermatologist, urologist, ER medical surgeon, etc.) according to the symptoms, they're suffering from.",
                    
    model="gpt-3.5-turbo-16k",
  #  file_ids=[file.id],
    #tools=[{"type": "retrieval"}]
)

def main(query, history):
    global thread_id  # Ensure we're using the global thread_id variable
    # Generate a new thread ID if it's a new session
    if not history:
        thread_id = create_thread()

    # Step 3: Add a Message to a Thread
    history = (history,)
    message = client.beta.threads.messages.create(
        thread_id=thread_id, role="user", content=query
    )

    # Step 4: Run the Assistant
    run = client.beta.threads.runs.create(
        thread_id=thread_id,
        assistant_id=assistant.id,
        instructions="User is a health patient, who is suffering from {disease}. You are supposed to create a medical report based on the symptoms. If you are 100% sure, you can also predict the disease else just report the symptoms in a formal formatted diagnosis report.\
                        Make sure to include all the vital informations by asking the patients. Ask their name, address and gender before beginning asking for symptoms. Ask one question at a time so that the user doesn't feel overwhelmed. Ask if they have any more symptoms and after completing asking for the detailed symptoms, generate the symptoms in a medical report like format along with the patient's information.",
    )

    while True:
        # Wait for 5 seconds
        time.sleep(0.5)

        # Retrieve the run status
        run_status = client.beta.threads.runs.retrieve(
            thread_id=thread_id, run_id=run.id
        )

        # If run is completed, get messages
        if run_status.status == "completed":
            messages = client.beta.threads.messages.list(thread_id=thread_id)
            response = ""

            data = messages.data
            first_thread_message = data[0]
            content = first_thread_message.content
            response = content[0].text.value
            return response
        else:
            continue


# Create a Gradio Interface
with gr.Blocks() as iface:
    with gr.Tab("MeroHealthAI Chatbot"):
       # gr.Markdown("MeroHealthAI is an AI assited chatbot that gathers symptoms from the user, documents it and sends it to the nearest most relevant doctor available. Our app also suppors medical report analysis")
  
        symptom_chatbot = gr.ChatInterface(
                main,
                clear_btn="Find Relevant Doctors"
             , description="MeroHealthAI is an AI assited chatbot that gathers symptoms from the user, documents it and sends it to the nearest most relevant doctor available. Our app also suppors medical report analysis",\
                                            examples=["I am having persistent headache, loss of feeling, tingling, Weakness or loss of muscle strength.",\
                                            "I have been having headache for the past 4 days.",\
                                                            "My limb looks swollen and my joint hurts.", \
                                                            "Hello, I have been having severe panic and anxiety attack."]).queue()

        symptom_chatbot
    with gr.Tab("Contact Doctor "):
        profession_key = gr.Textbox(label="Profession", interactive=True)
        doc_info = gr.Textbox(label="Doctor Information")  # Define textbox globally
    
        gr.Button("Find Relevant Doctors").click(
            # Pass textbox element directly
            Doctor.display_profession,
            inputs=profession_key,
            outputs=doc_info,
        )

if __name__ == "__main__":
    iface.launch()