Spaces:
Running
Running
import base64 | |
import os | |
import pathlib | |
import json5 | |
import logging | |
import shutil | |
import time | |
import streamlit as st | |
import streamlit.runtime.scriptrunner as st_sr | |
from typing import List, Tuple | |
import metaphor_python as metaphor | |
import tempfile | |
import llm_helper | |
import pptx_helper | |
from global_config import GlobalConfig | |
APP_TEXT = json5.loads(open(GlobalConfig.APP_STRINGS_FILE, 'r').read()) | |
GB_CONVERTER = 2 ** 30 | |
logging.basicConfig( | |
level=GlobalConfig.LOG_LEVEL, | |
format='%(asctime)s - %(message)s', | |
) | |
def get_contents_wrapper(text: str) -> str: | |
""" | |
Fetch and cache the slide deck contents on a topic by calling an external API. | |
:param text: The presentation topic | |
:return: The slide deck contents or outline in JSON format | |
""" | |
logging.info('LLM call because of cache miss...') | |
return llm_helper.generate_slides_content(text).strip() | |
def get_metaphor_client_wrapper() -> metaphor.Metaphor: | |
""" | |
Create a Metaphor client for semantic Web search. | |
:return: Metaphor instance | |
""" | |
return metaphor.Metaphor(api_key=GlobalConfig.METAPHOR_API_KEY) | |
def get_web_search_results_wrapper(text: str) -> List[Tuple[str, str]]: | |
""" | |
Fetch and cache the Web search results on a given topic. | |
:param text: The topic | |
:return: A list of (title, link) tuples | |
""" | |
results = [] | |
search_results = get_metaphor_client_wrapper().search( | |
text, | |
use_autoprompt=True, | |
num_results=5 | |
) | |
for a_result in search_results.results: | |
results.append((a_result.title, a_result.url)) | |
return results | |
def get_ai_image_wrapper(text: str) -> str: | |
""" | |
Fetch and cache a Base 64-encoded image by calling an external API. | |
:param text: The image prompt | |
:return: The Base 64-encoded image | |
""" | |
return llm_helper.get_ai_image(text) | |
def get_disk_used_percentage() -> float: | |
""" | |
Compute the disk usage. | |
:return: Percentage of the disk space currently used | |
""" | |
total, used, free = shutil.disk_usage(__file__) | |
total = total // GB_CONVERTER | |
used = used // GB_CONVERTER | |
free = free // GB_CONVERTER | |
used_perc = 100.0 * used / total | |
logging.debug(f'Total: {total} GB\n' | |
f'Used: {used} GB\n' | |
f'Free: {free} GB') | |
logging.debug('\n'.join(os.listdir())) | |
return used_perc | |
def build_ui(): | |
""" | |
Display the input elements for content generation. Only covers the first step. | |
""" | |
# get_disk_used_percentage() | |
st.title(APP_TEXT['app_name']) | |
st.subheader(APP_TEXT['caption']) | |
with st.form('my_form'): | |
# Topic input | |
try: | |
with open(GlobalConfig.PRELOAD_DATA_FILE, 'r') as in_file: | |
preload_data = json5.loads(in_file.read()) | |
except (FileExistsError, FileNotFoundError): | |
preload_data = {'topic': '', 'audience': ''} | |
topic = st.text_area( | |
APP_TEXT['input_labels'][0], | |
value=preload_data['topic'] | |
) | |
texts = list(GlobalConfig.PPTX_TEMPLATE_FILES.keys()) | |
captions = [GlobalConfig.PPTX_TEMPLATE_FILES[x]['caption'] for x in texts] | |
pptx_template = st.radio( | |
'Select a presentation template:', | |
texts, | |
captions=captions, | |
horizontal=True | |
) | |
st.divider() | |
submit = st.form_submit_button('Generate slide deck') | |
if submit: | |
# st.write(f'Clicked {time.time()}') | |
st.session_state.submitted = True | |
# https://github.com/streamlit/streamlit/issues/3832#issuecomment-1138994421 | |
if 'submitted' in st.session_state: | |
progress_text = 'Generating the slides...give it a moment' | |
progress_bar = st.progress(0, text=progress_text) | |
topic_txt = topic.strip() | |
generate_presentation(topic_txt, pptx_template, progress_bar) | |
st.divider() | |
st.text(APP_TEXT['tos']) | |
st.text(APP_TEXT['tos2']) | |
st.markdown( | |
'![Visitors](https://api.visitorbadge.io/api/visitors?path=https%3A%2F%2Fhuggingface.co%2Fspaces%2Fbarunsaha%2Fslide-deck-ai&countColor=%23263759)' | |
) | |
def generate_presentation(topic: str, pptx_template: str, progress_bar): | |
""" | |
Process the inputs to generate the slides. | |
:param topic: The presentation topic based on which contents are to be generated | |
:param pptx_template: The PowerPoint template name to be used | |
:param progress_bar: Progress bar from the page | |
:return: | |
""" | |
topic_length = len(topic) | |
logging.debug(f'Input length:: topic: {topic_length}') | |
if topic_length >= 10: | |
logging.debug( | |
f'Topic: {topic}\n' | |
) | |
target_length = min(topic_length, GlobalConfig.LLM_MODEL_MAX_INPUT_LENGTH) | |
try: | |
# Step 1: Generate the contents in JSON format using an LLM | |
json_str = process_slides_contents(topic[:target_length], progress_bar) | |
# Step 2: Generate the slide deck based on the template specified | |
if len(json_str) > 0: | |
st.info( | |
'Tip: The generated content doesn\'t look so great?' | |
' Need alternatives? Just change your description text and try again.', | |
icon="💡️" | |
) | |
else: | |
st.error('Unfortunately, JSON generation failed, so the next steps would lead to nowhere.' | |
' Try again or come back later.') | |
return | |
all_headers = generate_slide_deck(json_str, pptx_template, progress_bar) | |
# Step 3: Bonus stuff: Web references and AI art | |
show_bonus_stuff(all_headers) | |
except ValueError as ve: | |
st.error(f'Unfortunately, an error occurred: {ve}! ' | |
f'Please change the text, try again later, or report it, sharing your inputs.') | |
else: | |
st.error('Not enough information provided! Please be little more descriptive :)') | |
def process_slides_contents(text: str, progress_bar: st.progress) -> str: | |
""" | |
Convert given text into structured data and display. Update the UI. | |
:param text: The topic description for the presentation | |
:param progress_bar: Progress bar for this step | |
:return: The contents as a JSON-formatted string | |
""" | |
json_str = '' | |
try: | |
logging.info(f'Calling LLM for content generation on the topic: {text}') | |
json_str = get_contents_wrapper(text) | |
except Exception as ex: | |
st.error(f'An exception occurred while trying to convert to JSON.' | |
f' It could be because of heavy traffic or something else.' | |
f' Try doing it again or try again later.\n' | |
f' Error message: {ex}') | |
logging.debug(f'JSON: {json_str}') | |
progress_bar.progress(50, text='Contents generated') | |
with st.expander('The generated contents (in JSON format)'): | |
st.code(json_str, language='json') | |
return json_str | |
def generate_slide_deck(json_str: str, pptx_template: str, progress_bar) -> List: | |
""" | |
Create a slide deck. | |
:param json_str: The contents in JSON format | |
:param pptx_template: The PPTX template name | |
:param progress_bar: Progress bar | |
:return: A list of all slide headers and the title | |
""" | |
progress_text = 'Creating the slide deck...give it a moment' | |
progress_bar.progress(75, text=progress_text) | |
# # Get a unique name for the file to save -- use the session ID | |
# ctx = st_sr.get_script_run_ctx() | |
# session_id = ctx.session_id | |
# timestamp = time.time() | |
# output_file_name = f'{session_id}_{timestamp}.pptx' | |
temp = tempfile.NamedTemporaryFile(delete=False, suffix='.pptx') | |
path = pathlib.Path(temp.name) | |
logging.info('Creating PPTX file...') | |
all_headers = pptx_helper.generate_powerpoint_presentation( | |
json_str, | |
as_yaml=False, | |
slides_template=pptx_template, | |
output_file_path=path | |
) | |
progress_bar.progress(100, text='Done!') | |
with open(path, 'rb') as f: | |
st.download_button('Download PPTX file', f, file_name='Presentation.pptx') | |
return all_headers | |
def show_bonus_stuff(ppt_headers: List[str]): | |
""" | |
Show bonus stuff for the presentation. | |
:param ppt_headers: A list of the slide headings. | |
""" | |
# Use the presentation title and the slide headers to find relevant info online | |
logging.info('Calling Metaphor search...') | |
ppt_text = ' '.join(ppt_headers) | |
search_results = get_web_search_results_wrapper(ppt_text) | |
md_text_items = [] | |
for (title, link) in search_results: | |
md_text_items.append(f'[{title}]({link})') | |
with st.expander('Related Web references'): | |
st.markdown('\n\n'.join(md_text_items)) | |
# Avoid image generation. It costs time and an API call, so just limit to the text generation. | |
with st.expander('AI-generated image on the presentation topic'): | |
logging.info('Calling SDXL for image generation...') | |
# img_empty.write('') | |
# img_text.write(APP_TEXT['image_info']) | |
image = get_ai_image_wrapper(ppt_text) | |
if len(image) > 0: | |
image = base64.b64decode(image) | |
st.image(image, caption=ppt_text) | |
st.info('Tip: Right-click on the image to save it.', icon="💡️") | |
logging.info('Image added') | |
def main(): | |
build_ui() | |
if __name__ == '__main__': | |
main() | |