# Original code
# https://www.youtube.com/watch?app=desktop&v=_j7JEDWuqLE&ab_channel=AIJason

# OpenAI break 
# https://github.com/langchain-ai/langchain/issues/12949

import os
import requests
from transformers import pipeline
#from langchain import PromptTemplate, LLMChain, OpenAI
from langchain.prompts import PromptTemplate
from langchain.chains import LLMChain
from langchain.llms import OpenAI
import streamlit as st

#from huggingface_hub import HfApi
HUGGING_FACE_API_TOKEN = st.secrets["HUGGING_FACE_API_TOKEN"]

#api = HfApi()
#if api.is_authenticated():
#    print('HF server')
#    HUGGING_FACE_API_TOKEN = os.environ("HUGGING_FACE_API_TOKEN")
#else:
#    print('Local machine')
#    HUGGING_FACE_API_TOKEN = st.secrets("HUGGING_FACE_API_TOKEN")

# img2text
def img2text(url):
    image_to_text = pipeline("image-to-text", model="Salesforce/blip-image-captioning-base")

    text = image_to_text(url)[0]["generated_text"]

    print(text)
    return text

# llm
def generate_story(scenario):
    template = """
    You are a story teller;
    You can generate a short story based on a simple narrative, the story should be no more than 20 words;

    CONTEXT: {scenario}
    STORY:
    """

    prompt = PromptTemplate(template=template, input_variables=["scenario"])

    story_llm = LLMChain(llm=OpenAI(
        model_name="gpt-3.5-turbo", temperature=1), prompt=prompt, verbose=True)
    
    story = story_llm.predict(scenario=scenario)

    print(story)
    return story

# text to speech
def text2speech(message):
    API_URL = "https://api-inference.huggingface.co/models/espnet/kan-bayashi_ljspeech_vits"
    headers = {"Authorization": f"Bearer {HUGGING_FACE_API_TOKEN}"}
    payloads = {
        "inputs": message
    }

    response = requests.post(API_URL, headers=headers, json=payloads)
    with open('audio.flac', 'wb') as file:
        file.write(response.content)

def main():

    st.set_page_config(page_title="img 2 audio story", page_icon="A")

    st.header("Turn img into audio story")
    uploaded_file = st.file_uploader("Chose an image...", type="jpg")

    if uploaded_file is not None:
        bytes_data = uploaded_file.getvalue()
        with open(uploaded_file.name, "wb") as file:
            file.write(bytes_data)
        st.image(uploaded_file, caption="Uploaded Image.",
                 use_column_width=True)
        scenario = img2text(uploaded_file.name)
        story = generate_story(scenario)
        text2speech(story)

        with st.expander("scenario"):
            st.write(scenario)
        with st.expander("story"):
            st.write(story)

        st.audio("audio.flac")

if __name__ == '__main__':
    main()

# Debug
#scenario = img2text("photo.jpg")
#story = generate_story(scenario)
#text2speech(story)