import codecs
import json
import time
import openai
import gradio as gr
import os
from dotenv import load_dotenv

# OpenAI API キーの設定
load_dotenv()
openai.api_key = os.getenv('OPENAI_API_KEY')
assistant_id = os.getenv('OPENAI_ASSISTANT_ID')

import json

assistant = None
client = openai.OpenAI()

print("### Step 1: Get the Assistant's ID ###")
assistant = client.beta.assistants.retrieve(assistant_id)
print(assistant)
assistant_name = assistant.name
assistant_description = assistant.description
assistant_model = assistant.model
assistant_tools = assistant.tools
assistant_file_ids = assistant.file_ids

if assistant_description is None:
    
    assistant_description += f"このアシスタントは、OpenAI APIで {assistant_model} を使用して作成されました。"

def assistant_response(prompt):

    "### Step 2: Create a Thread ###"
    empty_thread = client.beta.threads.create()
    thread_id = empty_thread.id
    print(empty_thread)

    print("### Step 3: Add a Message to the Thread ###")
    thread = client.beta.threads.retrieve(thread_id)
    print(thread)

    print("### Step 4: Add a Message to the Thread ###")
    thread_message = client.beta.threads.messages.create(
        thread_id,
        role="user",
        content=prompt,
    )
    message_id = thread_message.id
    print(thread_message)

    print("### Step 5: Retrieve the Message ###")
    message = client.beta.threads.messages.retrieve(
        message_id=message_id,
        thread_id=thread_id,
    )
    print(message)

    print("### Step 6: Run the Assistant ###")
    run = client.beta.threads.runs.create(
        thread_id=thread.id,
        assistant_id=assistant.id,
    )

    print("### Step 7: Wait for the Assistant to Finish ###")
    def wait_on_run(run, thread):
        while run.status == "queued" or run.status == "in_progress":
            run = client.beta.threads.runs.retrieve(
                thread_id=thread.id,
                run_id=run.id,
            )
            time.sleep(0.5)
        return run

    run = wait_on_run(run, thread)
    print(run)

    print("### Step 8: Retrieve the Messages ###")
    messages = client.beta.threads.messages.list(
        thread_id=thread.id
    )

    messages_str = json.dumps(messages.dict(), indent=2)
    print(codecs.decode(messages_str, 'unicode-escape'))

    print("### Step 9: Retrieve the Assistant's Response ###")
    answers = []
    for message in messages.data:
        if message.role == "assistant":
            if message.content[0].type == "text":
                answers.append(message.content[0].text.value + "\n\n")
            else:
                answers.append("Content is not text.\n\n")
        elif message.role == "user":
            break

    # answersを逆順にする
    answers.reverse()
    
    return "".join(answers)
    

title = "OpenAPI Assistant API: " + assistant_name
description = assistant_description

# Gradio インターフェースの設定
iface = gr.Interface(
    title=title,
    description=description,
    fn=assistant_response,
    inputs=gr.Textbox(lines=2, placeholder="Enter your prompt here..."),
    outputs=gr.Textbox(),
)

# アプリケーションの起動
iface.launch()