app.py

import streamlit as st
from langchain.prompts import PromptTemplate
import requests
from langchain.llms import HuggingFaceHub
from langchain.chains import LLMChain
import io
from PIL import Image
import json
from model import create_model
import torch
api_key = st.secrets["API"]

device = torch.device("cuda" if torch.cuda.is_available() else "cpu")

model,tokenizer = create_model()
# Load existing ideas from a file
def load_ideas():
    try:
        with open("ideas.json", "r") as file:
            ideas = json.load(file)
    except FileNotFoundError:
        ideas = []
    return ideas

# Save ideas to a file
def save_ideas(ideas):
    with open("ideas.json", "w") as file:
        json.dump(ideas, file)

# Save image to a file
def save_image(image, image_path):
    image.save(image_path)



# content generation
def generate_content(topic):
  keyword=topic
  prompt = [{'role': 'user', 'content': f'''Write a comprehensive article about {keyword} covering the following aspects:
          Introduction, History and Background, Key Concepts and Terminology, Use Cases and Applications, Benefits and Drawbacks, Future Outlook, Conclusion
          Ensure that the article is well-structured, informative, and at least 2000 words long. Use SEO best practices for content optimization.
          Add ## before section headers
  '''}]
  inputs = tokenizer.apply_chat_template(
      prompt,
      add_generation_prompt=True,
      return_tensors='pt'
  )

  tokens = model.generate(
      inputs.to(model.device),
      max_new_tokens=10024,
      temperature=0.8,
      do_sample=True
  )

  content = tokenizer.decode(tokens[0], skip_special_tokens=False)
  # print(content)
  return content

def divide_content(text):
    sections = {}
    lines = text.split('\n')

    current_section = None

    for line in lines:
        line = line.strip()  # Remove leading and trailing whitespaces
        if line.startswith("##"):
            # Found a new section marker
            current_section = line[2:]
            sections[current_section] = ""
        elif current_section is not None and line:
            # Append the line to the current section if it's not empty
            sections[current_section] += line + " "

    # Remove trailing whitespaces from each section
    for section_name, section_content in sections.items():
        sections[section_name] = section_content.rstrip()

    return sections


# Image Generation
API_URL = "https://api-inference.huggingface.co/models/goofyai/3d_render_style_xl"
headers = {"Authorization": f"Bearer {api_key}"}

def query(payload):
	response = requests.post(API_URL, headers=headers, json=payload)
	return response.content

def generat_image(image_prompt,name):
      image_bytes = query({
          "inputs": image_prompt,
      })
      image = Image.open(io.BytesIO(image_bytes))
      image.save(f"{name}.png")
      return image

# st.title('AI Blog Content Generator')

# st.header('What is the topic of your blog post?')
# topic_text = st.text_input('Topic:', placeholder='Example: Generative AI')
# submitted = st.button('Submit')

def display_content_with_images(blog):
    # Streamlit Display
    st.header(blog['title'])

    # Introduction
    col1, col2 = st.columns(2, gap='medium')
    with col1:
      st.header('Introduction')
      st.write(blog['Introduction'])
    with col2:
      st.image(blog['introduction_image'], use_column_width=True)

    # History
    st.header('History and Background')
    st.write(blog['History and Background'])
    st.image(blog['History and Background_image'], use_column_width=True)

    # Content
    col1, col2 = st.columns(2, gap='medium')
    with col1:
      st.header('Key Concepts and Terminology')
      st.write(blog['Key Concepts and Terminology'])
    with col2:
      st.image(blog['Key Concepts and Terminology_image'], use_column_width=True)

    # Use Cases and Applications
    st.header('Use Cases and Applications')
    st.write(blog['Use Cases and Applications'])

    # Benefits and Drawbacks
    st.header('Benefits and Drawbacks')
    st.write(blog['Benefits and Drawbacks'])

    # Future Outlook
    st.header('Future Outlook')
    st.write(blog['Future Outlook'])

    # Conclusion
    col1, col2 = st.columns(2, gap='medium')
    with col1:
      st.header('Conclusion')
      st.write(blog['Conclusion'])
    with col2:
      st.image(blog['Conclusion_image'])



# Streamlit App

# Title
st.sidebar.title('📝 Previous Ideas')
st.title("AI Blog Content Generator 😊")
# Main Page
col1, col2, col3 = st.columns((1, 3, 1), gap='large')


existing_ideas = load_ideas()

# Input and button
topic = st.text_input("Enter Title for the blog")
button_clicked = st.button("Create blog!❤️")


# Display existing ideas in the sidebar
keys = list(set([key for idea in existing_ideas for key in idea.keys()]))
if topic in keys:
    index = keys.index(topic)
    selected_idea = st.sidebar.selectbox("Select Idea", keys, key=f"selectbox{topic}", index=index)
    # Display content and image for the selected idea
    selected_idea_from_list = next((idea for idea in existing_ideas if selected_idea in idea), None)
    st.subheader(topic)
    display_content_with_images(selected_idea_from_list[selected_idea])
else:
    index = 0

# Check if the topic exists in previous ideas before generating
if button_clicked and topic not in keys:
    st.write('Generating blog post about', topic, '...')
    st.write('This may take a few minutes.')

    topic_query = topic

    content = generate_content(topic)
    # st.write(content)
    blog = divide_content(content)
    print(blog)
    st.header(topic)
    # Introduction
    col1, col2 = st.columns(2, gap='medium')
    with col1:
      st.subheader('Introduction')
      st.write(blog[' Introduction'])
    with col2:
      image_prompt = blog[' Introduction'].splitlines()[0]
      introduction_image = generat_image(image_prompt,f" Introduction{topic}")
      st.image(introduction_image, use_column_width=True)

    st.divider()

    # History
    st.subheader('History and Background')
    st.write(blog[' History and Background'])
    image_prompt = blog[' History and Background'].splitlines()[0]
    history_image =generat_image(image_prompt,f" History and Background{topic}")
    st.image(history_image, use_column_width=True)
    st.divider()

    # Key Concepts and Terminology
    col1, col2 = st.columns(2, gap='medium')
    with col1:
      st.subheader('Key Concepts and Terminology')
      st.write(blog[' Key Concepts and Terminology'])
    with col2:
      image_prompt = blog[' Key Concepts and Terminology'].splitlines()[0]
      key_concepts_image = generat_image(image_prompt,f" Key Concepts and Terminology{topic}")
      st.image(key_concepts_image, use_column_width=True)
    st.divider()

    # Use Cases and Applications
    st.subheader('Use Cases and Applications')
    st.write(blog[' Use Cases and Applications'])

    # Benefits and Drawbacks
    st.subheader('Benefits and Drawbacks')
    st.write(blog[' Benefits and Drawbacks'])

    # Future Outlook
    st.subheader('Future Outlook')
    st.write(blog[' Future Outlook'])

    # Conclusion
    col1, col2 = st.columns(2, gap='medium')
    with col1:
      st.subheader('Conclusion')
      st.write(blog[' Conclusion'])
    with col2:
      image_prompt = blog[' Conclusion'].splitlines()[0]
      conclusion_image = generat_image(image_prompt,f" Conclusion{topic}")
      st.image(conclusion_image, use_column_width=True)


    # Blog Data
    blog_data = {
        'title': topic,
        'Introduction': blog[' Introduction'],
        'introduction_image': f" Introduction{topic}.png",
        'History and Background': blog[' History and Background'],
        'History and Background_image':  f" History and Background{topic}.png",
        'Key Concepts and Terminology': blog[' Key Concepts and Terminology'],
        'Key Concepts and Terminology_image': f" Key Concepts and Terminology{topic}.png",
        'Use Cases and Applications': blog[' Use Cases and Applications'],
        'Benefits and Drawbacks': blog[' Benefits and Drawbacks'],
        'Future Outlook': blog[' Future Outlook'],
        'Conclusion': blog[' Conclusion'],
        'Conclusion_image': f" Conclusion{topic}.png"
    }

    # Save blog with images
    existing_ideas.append({topic: blog_data})
    # Update keys and selected idea in the sidebar
    keys = list(set([key for idea in existing_ideas for key in idea.keys()]))
    selected_idea = st.sidebar.selectbox("Select Idea", keys, key=f"selectbox{topic}", index=keys.index(topic))

    save_ideas(existing_ideas)