Merge pull request #7 from barun-saha/chat-interface

.streamlit/config.toml

@@ -0,0 +1,10 @@
+[server]
+runOnSave = true
+headless = false
+maxUploadSize = 0
+
+[browser]
+gatherUsageStats = false
+
+[theme]
+base = "dark"

README.md

@@ -4,7 +4,7 @@ emoji: 🏢
 colorFrom: yellow
 colorTo: green
 sdk: streamlit
-sdk_version: 1.26.0
+sdk_version: 1.32.2
 app_file: app.py
 pinned: false
 license: mit
@@ -16,36 +16,57 @@ We spend a lot of time on creating the slides and organizing our thoughts for an
 With SlideDeck AI, co-create slide decks on any topic with Generative Artificial Intelligence.
 Describe your topic and let SlideDeck AI generate a PowerPoint slide deck for you—it's as simple as that!
 
-SlideDeck AI is powered by [Mistral 7B Instruct](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1).
+SlideDeck AI is powered by [Mistral 7B Instruct](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2).
 Originally, it was built using the Llama 2 API provided by Clarifai.
 
+*Update*: Legacy SlideDeck AI allowed one-shot generation of a slide deck based on the inputs. 
+In contrast, SlideDeck AI *Reloaded* enables an iterative workflow with a conversational interface,
+where you can create and improve the presentation.
+
+
 # Process
 
 SlideDeck AI works in the following way:
 
-1. Given a topic description, it uses Mistral 7B Instruct to generate the outline/contents of the slides. 
+1. Given a topic description, it uses Mistral 7B Instruct to generate the *initial* content of the slides. 
 The output is generated as structured JSON data based on a pre-defined schema.
 2. Subsequently, it uses the `python-pptx` library to generate the slides, 
 based on the JSON data from the previous step. 
-Here, a user can choose from a set of three pre-defined presentation templates.
-3. In addition, it uses Metaphor to fetch Web pages related to the topic.
+A user can choose from a set of three pre-defined presentation templates.
+3. At this stage onward, a user can provide additional instructions to refine the content.
+For example, one can ask to add another slide or modify an existing slide.
+A history of instructions is maintained.
+4. Every time SlideDeck AI generates a PowerPoint presentation, a download button is provided.
+Clicking on the button will download the file.
+
+
+# Known Issues
+
+- **Incorrect JSON**: Sometimes the JSON generated could be syntactically incorrect. 
+You can try asking SlideDeck AI to regenerate the content and fix the JSON syntax error.
+This, however, is not guaranteed to work. The alternative is to reload the website and try again.
+- **Connection timeout**: Requests sent to the Hugging Face Inference endpoint might time out.
+A maximum of five retries are attempted. If it still does not work, wait for a while and try again.
 
-4. ~~Finally, it uses Stable Diffusion 2 to generate an image, based on the title and each slide heading.~~
+The following is not an issue but might appear as a strange behavior:
+- **Cannot paste text in the input box**: If the length of the copied text is greater than the maximum
+number of allowed characters in the textbox, pasting would not work.
 
 
 # Local Development
 
-SlideDeck AI uses [Mistral 7B Instruct](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) 
+SlideDeck AI uses [Mistral 7B Instruct](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) 
 via the Hugging Face Inference API.
-To run this project by yourself, you need to provide the `HUGGINGFACEHUB_API_TOKEN` and `METAPHOR_API_KEY` API keys,
+To run this project by yourself, you need to provide the `HUGGINGFACEHUB_API_TOKEN` API key,
 for example, in a `.env` file. Visit the respective websites to obtain the keys.
 
 
 # Live Demo
 
-[SlideDeck AI](https://huggingface.co/spaces/barunsaha/slide-deck-ai)
+- [SlideDeck AI](https://huggingface.co/spaces/barunsaha/slide-deck-ai) on Hugging Face Spaces
+- [Demo video](https://youtu.be/QvAKzNKtk9k) of the chat interface on YouTube
 
 
 # Award
 
-SlideDeck AI has won the 3rd Place in the [Llama 2 Hackathon with Clarifai](https://lablab.ai/event/llama-2-hackathon-with-clarifai).
+SlideDeck AI has won the 3rd Place in the [Llama 2 Hackathon with Clarifai](https://lablab.ai/event/llama-2-hackathon-with-clarifai) in 2023.

app.py

@@ -1,309 +1,366 @@
-import pathlib
+import datetime
 import logging
+import pathlib
+import random
 import tempfile
-from typing import List, Tuple
+from typing import List
 
 import json5
-import metaphor_python as metaphor
 import streamlit as st
+from langchain_community.chat_message_histories import (
+    StreamlitChatMessageHistory
+)
+from langchain_core.messages import HumanMessage
+from langchain_core.prompts import ChatPromptTemplate
+# from transformers import AutoTokenizer
 
-import llm_helper
-import pptx_helper
 from global_config import GlobalConfig
-
-
-APP_TEXT = json5.loads(open(GlobalConfig.APP_STRINGS_FILE, 'r', encoding='utf-8').read())
-GB_CONVERTER = 2 ** 30
-
-
-logging.basicConfig(
-    level=GlobalConfig.LOG_LEVEL,
-    format='%(asctime)s - %(message)s',
-)
+from helpers import llm_helper, pptx_helper, text_helper
 
 
 @st.cache_data
-def get_contents_wrapper(text: str) -> str:
+def _load_strings() -> dict:
     """
-    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
+    Load various strings to be displayed in the app.
+    :return: The dictionary of strings.
     """
 
-    logging.info('LLM call because of cache miss...')
-    return llm_helper.generate_slides_content(text).strip()
-
-
-@st.cache_resource
-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)
+    with open(GlobalConfig.APP_STRINGS_FILE, 'r', encoding='utf-8') as in_file:
+        return json5.loads(in_file.read())
 
 
 @st.cache_data
-def get_web_search_results_wrapper(text: str) -> List[Tuple[str, str]]:
+def _get_prompt_template(is_refinement: bool) -> str:
     """
-    Fetch and cache the Web search results on a given topic.
+    Return a prompt template.
 
-    :param text: The topic
-    :return: A list of (title, link) tuples
+    :param is_refinement: Whether this is the initial or refinement prompt.
+    :return: The prompt template as f-string.
     """
 
-    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))
+    if is_refinement:
+        with open(GlobalConfig.REFINEMENT_PROMPT_TEMPLATE, 'r', encoding='utf-8') as in_file:
+            template = in_file.read()
+    else:
+        with open(GlobalConfig.INITIAL_PROMPT_TEMPLATE, 'r', encoding='utf-8') as in_file:
+            template = in_file.read()
 
-    return results
+    return template
 
 
-# def get_disk_used_percentage() -> float:
+# @st.cache_resource
+# def _get_tokenizer() -> AutoTokenizer:
 #     """
-#     Compute the disk usage.
+#     Get Mistral tokenizer for counting tokens.
 #
-#     :return: Percentage of the disk space currently used
+#     :return: The tokenizer.
 #     """
 #
-#     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
+#     return AutoTokenizer.from_pretrained(
+#         pretrained_model_name_or_path=GlobalConfig.HF_LLM_MODEL_NAME
+#     )
 
 
-def build_ui():
+APP_TEXT = _load_strings()
+
+# Session variables
+CHAT_MESSAGES = 'chat_messages'
+DOWNLOAD_FILE_KEY = 'download_file_name'
+IS_IT_REFINEMENT = 'is_it_refinement'
+
+logger = logging.getLogger(__name__)
+progress_bar = st.progress(0, text='Setting up SlideDeck AI...')
+
+texts = list(GlobalConfig.PPTX_TEMPLATE_FILES.keys())
+captions = [GlobalConfig.PPTX_TEMPLATE_FILES[x]['caption'] for x in texts]
+pptx_template = st.sidebar.radio(
+    'Select a presentation template:',
+    texts,
+    captions=captions,
+    horizontal=True
+)
+
+
+def display_page_header_content():
     """
-    Display the input elements for content generation. Only covers the first step.
+    Display content in the page header.
     """
 
-    # get_disk_used_percentage()
-
     st.title(APP_TEXT['app_name'])
     st.subheader(APP_TEXT['caption'])
     st.markdown(
-        'Powered by'
-        ' [Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2).'
-    )
-    st.markdown(
-        '*If the JSON is generated or parsed incorrectly, try again later by making minor changes'
-        ' to the input text.*'
+        '![Visitors](https://api.visitorbadge.io/api/visitors?path=https%3A%2F%2Fhuggingface.co%2Fspaces%2Fbarunsaha%2Fslide-deck-ai&countColor=%23263759)'  # noqa: E501
     )
 
-    with st.form('my_form'):
-        # Topic input
-        try:
-            with open(GlobalConfig.PRELOAD_DATA_FILE, 'r', encoding='utf-8') 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
-        )
+def display_page_footer_content():
+    """
+    Display content in the page footer.
+    """
 
-        st.divider()
-        submit = st.form_submit_button('Generate slide deck')
+    st.text(APP_TEXT['tos'] + '\n\n' + APP_TEXT['tos2'])
 
-    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)
+def build_ui():
+    """
+    Display the input elements for content generation.
+    """
 
-        topic_txt = topic.strip()
-        generate_presentation(topic_txt, pptx_template, progress_bar)
+    display_page_header_content()
 
-    st.divider()
-    st.text(APP_TEXT['tos'])
-    st.text(APP_TEXT['tos2'])
+    with st.expander('Usage Policies and Limitations'):
+        display_page_footer_content()
 
-    st.markdown(
-        '![Visitors]'
-        '(https://api.visitorbadge.io/api/visitors?path=https%3A%2F%2Fhuggingface.co%2Fspaces%2Fbarunsaha%2Fslide-deck-ai&countColor=%23263759)'
-    )
+    progress_bar.progress(50, text='Setting up chat interface...')
+    set_up_chat_ui()
 
 
-def generate_presentation(topic: str, pptx_template: str, progress_bar):
+def set_up_chat_ui():
     """
-    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:
+    Prepare the chat interface and related functionality.
     """
 
-    topic_length = len(topic)
-    logging.debug('Input length:: topic: %s', topic_length)
-
-    if topic_length >= 10:
-        logging.debug('Topic: %s', topic)
-        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)
-            logging.debug('Truncated topic: %s', topic[:target_length])
-            logging.debug('Length of JSON: %d', len(json_str))
-
-            # 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.')
+    with st.expander('Usage Instructions'):
+        st.write(GlobalConfig.CHAT_USAGE_INSTRUCTIONS)
+        st.markdown(
+            'SlideDeck AI is powered by'
+            ' [Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2)'
+        )
+
+    # view_messages = st.expander('View the messages in the session state')
+
+    st.chat_message('ai').write(
+        random.choice(APP_TEXT['ai_greetings'])
+    )
+    progress_bar.progress(100, text='Done!')
+    progress_bar.empty()
+
+    history = StreamlitChatMessageHistory(key=CHAT_MESSAGES)
 
+    if _is_it_refinement():
+        template = _get_prompt_template(is_refinement=True)
     else:
-        st.error('Not enough information provided! Please be little more descriptive :)')
+        template = _get_prompt_template(is_refinement=False)
+
+    prompt_template = ChatPromptTemplate.from_template(template)
+
+    # Since Streamlit app reloads at every interaction, display the chat history
+    # from the save session state
+    for msg in history.messages:
+        msg_type = msg.type
+        if msg_type == 'user':
+            st.chat_message(msg_type).write(msg.content)
+        else:
+            st.chat_message(msg_type).code(msg.content, language='json')
+
+    if prompt := st.chat_input(
+        placeholder=APP_TEXT['chat_placeholder'],
+        max_chars=GlobalConfig.LLM_MODEL_MAX_INPUT_LENGTH
+    ):
+
+        progress_bar_pptx = st.progress(0, 'Preparing to run...')
+        if not text_helper.is_valid_prompt(prompt):
+            st.error(
+                'Not enough information provided!'
+                ' Please be a little more descriptive and type a few words'
+                ' with a few characters :)'
+            )
+            return
+
+        logger.info('User input: %s | #characters: %d', prompt, len(prompt))
+        st.chat_message('user').write(prompt)
+
+        user_messages = _get_user_messages()
+        user_messages.append(prompt)
+        list_of_msgs = [
+            f'{idx + 1}. {msg}' for idx, msg in enumerate(user_messages)
+        ]
+        list_of_msgs = '\n'.join(list_of_msgs)
+
+        if _is_it_refinement():
+            formatted_template = prompt_template.format(
+                **{
+                    'instructions': list_of_msgs,
+                    'previous_content': _get_last_response()
+                }
+            )
+        else:
+            formatted_template = prompt_template.format(
+                **{
+                    'question': prompt,
+                }
+            )
+
+        progress_bar_pptx.progress(5, 'Calling LLM...will retry if connection times out...')
+        response: dict = llm_helper.hf_api_query({
+            'inputs': formatted_template,
+            'parameters': {
+                'temperature': GlobalConfig.LLM_MODEL_TEMPERATURE,
+                'min_length': GlobalConfig.LLM_MODEL_MIN_OUTPUT_LENGTH,
+                'max_length': GlobalConfig.LLM_MODEL_MAX_OUTPUT_LENGTH,
+                'max_new_tokens': GlobalConfig.LLM_MODEL_MAX_OUTPUT_LENGTH,
+                'num_return_sequences': 1,
+                'return_full_text': False,
+                # "repetition_penalty": 0.0001
+            },
+            'options': {
+                'wait_for_model': True,
+
+                'use_cache': True
+            }
+        })
+
+        if len(response) > 0 and 'generated_text' in response[0]:
+            response: str = response[0]['generated_text'].strip()
+
+        st.chat_message('ai').code(response, language='json')
+
+        history.add_user_message(prompt)
+        history.add_ai_message(response)
+
+        # if GlobalConfig.COUNT_TOKENS:
+        #     tokenizer = _get_tokenizer()
+        #     tokens_count_in = len(tokenizer.tokenize(formatted_template))
+        #     tokens_count_out = len(tokenizer.tokenize(response))
+        #     logger.debug(
+        #         'Tokens count:: input: %d, output: %d',
+        #         tokens_count_in, tokens_count_out
+        #     )
+
+        # _display_messages_history(view_messages)
+
+        # The content has been generated as JSON
+        # There maybe trailing ``` at the end of the response -- remove them
+        # To be careful: ``` may be part of the content as well when code is generated
+        progress_bar_pptx.progress(50, 'Analyzing response...')
+        response_cleaned = text_helper.get_clean_json(response)
+
+        logger.info(
+            'Cleaned JSON response:: original length: %d | cleaned length: %d',
+            len(response), len(response_cleaned)
+        )
+        logger.debug('Cleaned JSON: %s', response_cleaned)
+
+        # Now create the PPT file
+        progress_bar_pptx.progress(75, 'Creating the slide deck...give it a moment...')
+        generate_slide_deck(response_cleaned)
+        progress_bar_pptx.progress(100, text='Done!')
 
+        logger.info(
+            '#messages in history / 2: %d',
+            len(st.session_state[CHAT_MESSAGES]) / 2
+        )
 
-def process_slides_contents(text: str, progress_bar: st.progress) -> str:
+
+def generate_slide_deck(json_str: str):
     """
-    Convert given text into structured data and display. Update the UI.
+    Create a slide deck.
 
-    :param text: The topic description for the presentation
-    :param progress_bar: Progress bar for this step
-    :return: The contents as a JSON-formatted string
+    :param json_str: The content in *valid* JSON format.
     """
 
-    json_str = ''
+    if DOWNLOAD_FILE_KEY in st.session_state:
+        path = pathlib.Path(st.session_state[DOWNLOAD_FILE_KEY])
+    else:
+        temp = tempfile.NamedTemporaryFile(delete=False, suffix='.pptx')
+        path = pathlib.Path(temp.name)
+        st.session_state[DOWNLOAD_FILE_KEY] = str(path)
+
+        if temp:
+            temp.close()
+
+    logger.debug('Creating PPTX file: %s...', st.session_state[DOWNLOAD_FILE_KEY])
 
     try:
-        logging.info('Calling LLM for content generation on the topic: %s', text)
-        json_str = get_contents_wrapper(text)
-    except Exception as ex:
+        pptx_helper.generate_powerpoint_presentation(
+            json_str,
+            slides_template=pptx_template,
+            output_file_path=path
+        )
+
+        _display_download_button(path)
+    except ValueError as ve:
         st.error(
-            f'An exception occurred while trying to convert to JSON. It could be because of heavy'
-            f' traffic or something else. Try doing it again or try again later.'
-            f'\nError message: {ex}'
+            f"{APP_TEXT['json_parsing_error']}"
+            f"\n\nAdditional error info: {ve}"
+            f"\n\nHere are some sample instructions that you could try to possibly fix this error;"
+            f" if these don't work, try rephrasing or refreshing:"
+            f"\n\n"
+            "- Regenerate content and fix the JSON error."
+            "\n- Regenerate content and fix the JSON error. Quotes inside quotes should be escaped."
         )
+        logger.error('%s', APP_TEXT['json_parsing_error'])
+        logger.error('Additional error info: %s', str(ve))
+    except Exception as ex:
+        st.error(APP_TEXT['content_generation_error'])
+        logger.error('Caught a generic exception: %s', str(ex))
+
+
+def _is_it_refinement() -> bool:
+    """
+    Whether it is the initial prompt or a refinement.
+
+    :return: True if it is the initial prompt; False otherwise.
+    """
 
-    progress_bar.progress(50, text='Contents generated')
+    if IS_IT_REFINEMENT in st.session_state:
+        return True
 
-    with st.expander('The generated contents (in JSON format)'):
-        st.code(json_str, language='json')
+    if len(st.session_state[CHAT_MESSAGES]) >= 2:
+        # Prepare for the next call
+        st.session_state[IS_IT_REFINEMENT] = True
+        return True
 
-    return json_str
+    return False
 
 
-def generate_slide_deck(json_str: str, pptx_template: str, progress_bar) -> List:
+def _get_user_messages() -> List[str]:
     """
-    Create a slide deck.
+    Get a list of user messages submitted until now from the session state.
 
-    :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
+    :return: The list of user messages.
     """
 
-    progress_text = 'Creating the slide deck...give it a moment'
-    progress_bar.progress(75, text=progress_text)
+    return [
+        msg.content for msg in st.session_state[CHAT_MESSAGES] if isinstance(msg, HumanMessage)
+    ]
 
-    # # 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)
+def _get_last_response() -> str:
+    """
+    Get the last response generated by AI.
 
-    logging.info('Creating PPTX file...')
-    all_headers = pptx_helper.generate_powerpoint_presentation(
-        json_str,
-        slides_template=pptx_template,
-        output_file_path=path
-    )
-    progress_bar.progress(100, text='Done!')
+    :return: The response text.
+    """
 
-    with open(path, 'rb') as f:
-        st.download_button('Download PPTX file', f, file_name='Presentation.pptx')
+    return st.session_state[CHAT_MESSAGES][-1].content
 
-    return all_headers
 
+def _display_messages_history(view_messages: st.expander):
+    """
+    Display the history of messages.
 
-def show_bonus_stuff(ppt_headers: List[str]):
+    :param view_messages: The list of AI and Human messages.
     """
-    Show bonus stuff for the presentation.
 
-    :param ppt_headers: A list of the slide headings.
+    with view_messages:
+        view_messages.json(st.session_state[CHAT_MESSAGES])
+
+
+def _display_download_button(file_path: pathlib.Path):
+    """
+    Display a download button to download a slide deck.
+
+    :param file_path: The path of the .pptx file.
     """
 
-    # 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))
-
-    logging.info('Done!')
-
-    # # 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')
+    with open(file_path, 'rb') as download_file:
+        st.download_button(
+            'Download PPTX file ⬇️',
+            data=download_file,
+            file_name='Presentation.pptx',
+            key=datetime.datetime.now()
+        )
 
 
 def main():

global_config.py

@@ -1,3 +1,4 @@
+import logging
 import os
 
 from dataclasses import dataclass
@@ -12,17 +13,20 @@ class GlobalConfig:
     HF_LLM_MODEL_NAME = 'mistralai/Mistral-7B-Instruct-v0.2'
     LLM_MODEL_TEMPERATURE: float = 0.2
     LLM_MODEL_MIN_OUTPUT_LENGTH: int = 50
-    LLM_MODEL_MAX_OUTPUT_LENGTH: int = 2000
-    LLM_MODEL_MAX_INPUT_LENGTH: int = 300
+    LLM_MODEL_MAX_OUTPUT_LENGTH: int = 4096
+    LLM_MODEL_MAX_INPUT_LENGTH: int = 750
 
     HUGGINGFACEHUB_API_TOKEN = os.environ.get('HUGGINGFACEHUB_API_TOKEN', '')
     METAPHOR_API_KEY = os.environ.get('METAPHOR_API_KEY', '')
 
     LOG_LEVEL = 'DEBUG'
+    COUNT_TOKENS = False
     APP_STRINGS_FILE = 'strings.json'
     PRELOAD_DATA_FILE = 'examples/example_02.json'
     SLIDES_TEMPLATE_FILE = 'langchain_templates/template_combined.txt'
     JSON_TEMPLATE_FILE = 'langchain_templates/text_to_json_template_02.txt'
+    INITIAL_PROMPT_TEMPLATE = 'langchain_templates/chat_prompts/initial_template.txt'
+    REFINEMENT_PROMPT_TEMPLATE = 'langchain_templates/chat_prompts/refinement_template.txt'
 
     PPTX_TEMPLATE_FILES = {
         'Blank': {
@@ -38,3 +42,27 @@ class GlobalConfig:
             'caption': 'Marvel in a monochrome dream'
         }
     }
+
+    # This is a long text, so not incorporated as a string in `strings.json`
+    CHAT_USAGE_INSTRUCTIONS = (
+        'Briefly describe your topic of presentation in the textbox provided below.'
+        ' For example, "Make a slide deck on AI." Subsequently, you can add follow-up'
+        ' instructions, e.g., "Can you add a slide on GPUs?" You can also ask it to refine any'
+        ' particular slide, e.g., "Make the slide with title \'Examples of AI\' a bit more'
+        ' descriptive." See this [demo video](https://youtu.be/QvAKzNKtk9k).'
+        ' As another example, sometimes the formatting of generated Python code can be a bit weird.'
+        ' You can try it telling, "Split multi-line codes into multiple lines," and hope for a fix.'
+        '\n\n'
+        'SlideDeck AI generates only text content. It does not have access to the Web.'
+        '\n\n'
+        'If you like SlideDeck AI, please consider leaving a heart ❤️ on the'
+        ' [Hugging Face Space](https://huggingface.co/spaces/barunsaha/slide-deck-ai/) or'
+        ' a star ⭐ on [GitHub](https://github.com/barun-saha/slide-deck-ai).'
+    )
+
+
+logging.basicConfig(
+    level=GlobalConfig.LOG_LEVEL,
+    format='%(asctime)s - %(levelname)s - %(name)s - %(message)s',
+    datefmt='%Y-%m-%d %H:%M:%S'
+)

llm_helper.py → helpers/llm_helper.py

@@ -1,5 +1,10 @@
 import logging
 import requests
+from requests.adapters import HTTPAdapter
+from urllib3.util import Retry
+
+from langchain_community.llms.huggingface_endpoint import HuggingFaceEndpoint
+from langchain_core.language_models import LLM
 
 from global_config import GlobalConfig
 
@@ -7,28 +12,58 @@ from global_config import GlobalConfig
 HF_API_URL = f"https://api-inference.huggingface.co/models/{GlobalConfig.HF_LLM_MODEL_NAME}"
 HF_API_HEADERS = {"Authorization": f"Bearer {GlobalConfig.HUGGINGFACEHUB_API_TOKEN}"}
 
-logging.basicConfig(
-    level=GlobalConfig.LOG_LEVEL,
-    format='%(asctime)s - %(message)s',
+logger = logging.getLogger(__name__)
+
+retries = Retry(
+    total=5,
+    backoff_factor=0.25,
+    backoff_jitter=0.3,
+    status_forcelist=[502, 503, 504],
+    allowed_methods={'POST'},
 )
+adapter = HTTPAdapter(max_retries=retries)
+http_session = requests.Session()
+http_session.mount('https://', adapter)
+http_session.mount('http://', adapter)
+
+
+def get_hf_endpoint() -> LLM:
+    """
+    Get an LLM via the HuggingFaceEndpoint of LangChain.
+
+    :return: The LLM.
+    """
+
+    logger.debug('Getting LLM via HF endpoint')
 
-# llm = None
+    return HuggingFaceEndpoint(
+        repo_id=GlobalConfig.HF_LLM_MODEL_NAME,
+        max_new_tokens=GlobalConfig.LLM_MODEL_MAX_OUTPUT_LENGTH,
+        top_k=40,
+        top_p=0.95,
+        temperature=GlobalConfig.LLM_MODEL_TEMPERATURE,
+        repetition_penalty=1.03,
+        streaming=True,
+        huggingfacehub_api_token=GlobalConfig.HUGGINGFACEHUB_API_TOKEN,
+        return_full_text=False,
+        stop_sequences=['</s>'],
+    )
 
 
-def hf_api_query(payload: dict):
+def hf_api_query(payload: dict) -> dict:
     """
     Invoke HF inference end-point API.
 
-    :param payload: The prompt for the LLM and related parameters
-    :return: The output from the LLM
+    :param payload: The prompt for the LLM and related parameters.
+    :return: The output from the LLM.
     """
 
     try:
-        response = requests.post(HF_API_URL, headers=HF_API_HEADERS, json=payload, timeout=15)
+        response = http_session.post(HF_API_URL, headers=HF_API_HEADERS, json=payload, timeout=15)
         result = response.json()
     except requests.exceptions.Timeout as te:
-        logging.error('*** Error: hf_api_query timeout! %s', str(te))
-        result = {}
+        logger.error('*** Error: hf_api_query timeout! %s', str(te))
+        result = []
 
     return result
 
@@ -37,8 +72,8 @@ def generate_slides_content(topic: str) -> str:
     """
     Generate the outline/contents of slides for a presentation on a given topic.
 
-    :param topic: Topic on which slides are to be generated
-    :return: The content in JSON format
+    :param topic: Topic on which slides are to be generated.
+    :return: The content in JSON format.
     """
 
     with open(GlobalConfig.SLIDES_TEMPLATE_FILE, 'r', encoding='utf-8') as in_file:
@@ -46,8 +81,8 @@ def generate_slides_content(topic: str) -> str:
         template_txt = template_txt.replace('<REPLACE_PLACEHOLDER>', topic)
 
     output = hf_api_query({
-        "inputs": template_txt,
-        "parameters": {
+        'inputs': template_txt,
+        'parameters': {
             'temperature': GlobalConfig.LLM_MODEL_TEMPERATURE,
             'min_length': GlobalConfig.LLM_MODEL_MIN_OUTPUT_LENGTH,
             'max_length': GlobalConfig.LLM_MODEL_MAX_OUTPUT_LENGTH,
@@ -56,7 +91,7 @@ def generate_slides_content(topic: str) -> str:
             'return_full_text': False,
             # "repetition_penalty": 0.0001
         },
-        "options": {
+        'options': {
             'wait_for_model': True,
             'use_cache': True
         }
@@ -70,7 +105,7 @@ def generate_slides_content(topic: str) -> str:
         # logging.debug(f'{json_end_idx=}')
         output = output[:json_end_idx]
 
-    logging.debug('generate_slides_content: output: %s', output)
+    logger.debug('generate_slides_content: output: %s', output)
 
     return output
 

pptx_helper.py → helpers/pptx_helper.py

@@ -2,6 +2,7 @@ import logging
 import pathlib
 import re
 import tempfile
+
 from typing import List, Tuple
 
 import json5
@@ -28,17 +29,14 @@ SAMPLE_JSON_FOR_PPTX = '''
 }
 '''
 
-logging.basicConfig(
-    level=GlobalConfig.LOG_LEVEL,
-    format='%(asctime)s - %(message)s',
-)
+logger = logging.getLogger(__name__)
 
 
 def remove_slide_number_from_heading(header: str) -> str:
     """
     Remove the slide number from a given slide header.
 
-    :param header: The header of a slide
+    :param header: The header of a slide.
     """
 
     if PATTERN.match(header):
@@ -56,17 +54,17 @@ def generate_powerpoint_presentation(
     """
     Create and save a PowerPoint presentation file containing the content in JSON format.
 
-    :param structured_data: The presentation contents as "JSON" (may contain trailing commas)
-    :param slides_template: The PPTX template to use
-    :param output_file_path: The path of the PPTX file to save as
-    :return A list of presentation title and slides headers
+    :param structured_data: The presentation contents as "JSON" (may contain trailing commas).
+    :param slides_template: The PPTX template to use.
+    :param output_file_path: The path of the PPTX file to save as.
+    :return A list of presentation title and slides headers.
     """
 
     # The structured "JSON" might contain trailing commas, so using json5
     parsed_data = json5.loads(structured_data)
 
-    logging.debug(
-        "*** Using PPTX template: %s",
+    logger.debug(
+        '*** Using PPTX template: %s',
         GlobalConfig.PPTX_TEMPLATE_FILES[slides_template]['file']
     )
     presentation = pptx.Presentation(GlobalConfig.PPTX_TEMPLATE_FILES[slides_template]['file'])
@@ -77,7 +75,10 @@ def generate_powerpoint_presentation(
     title = slide.shapes.title
     subtitle = slide.placeholders[1]
     title.text = parsed_data['title']
-    logging.debug('Presentation title is: %s', title.text)
+    logger.info(
+        'PPT title: %s | #slides: %d',
+        title.text, len(parsed_data['slides'])
+    )
     subtitle.text = 'by Myself and SlideDeck AI :)'
     all_headers = [title.text, ]
 
@@ -125,9 +126,9 @@ def get_flat_list_of_contents(items: list, level: int) -> List[Tuple]:
     Flatten a (hierarchical) list of bullet points to a single list containing each item and
     its level.
 
-    :param items: A bullet point (string or list)
-    :param level: The current level of hierarchy
-    :return: A list of (bullet item text, hierarchical level) tuples
+    :param items: A bullet point (string or list).
+    :param level: The current level of hierarchy.
+    :return: A list of (bullet item text, hierarchical level) tuples.
     """
 
     flat_list = []
@@ -240,3 +241,5 @@ if __name__ == '__main__':
         output_file_path=path,
         slides_template='Blank'
     )
+
+    temp.close()

helpers/text_helper.py

@@ -0,0 +1,56 @@
+def is_valid_prompt(prompt: str) -> bool:
+    """
+    Verify whether user input satisfies the concerned constraints.
+
+    :param prompt: The user input text.
+    :return: True if all criteria are satisfied; False otherwise.
+    """
+
+    if len(prompt) < 7 or ' ' not in prompt:
+        return False
+
+    return True
+
+
+def get_clean_json(json_str: str) -> str:
+    """
+    Attempt to clean a JSON response string from the LLM by removing the trailing ```
+    and any text beyond that.
+    CAUTION: May not be always accurate.
+
+    :param json_str: The input string in JSON format.
+    :return: The "cleaned" JSON string.
+    """
+
+    # An example of response containing JSON and other text:
+    # {
+    #     "title": "AI and the Future: A Transformative Journey",
+    #     "slides": [
+    #       ...
+    #     ]
+    # }    <<---- This is end of valid JSON content
+    # ```
+    #
+    # ```vbnet
+    # Please note that the JSON output is in valid format but the content of the "Role of GPUs in AI" slide is just an example and may not be factually accurate. For accurate information, you should consult relevant resources and update the content accordingly.
+    # ```
+    response_cleaned = json_str
+
+    while True:
+        idx = json_str.rfind('```')  # -1 on failure
+
+        if idx <= 0:
+            break
+
+        # In the ideal scenario, the character before the last ``` should be
+        # a new line or a closing bracket }
+        prev_char = json_str[idx - 1]
+
+        if prev_char == '}':
+            response_cleaned = json_str[:idx]
+        elif prev_char == '\n' and json_str[idx - 2] == '}':
+            response_cleaned = json_str[:idx]
+
+        json_str = json_str[:idx]
+
+    return response_cleaned

langchain_templates/chat_prompts/initial_template.txt

@@ -0,0 +1,41 @@
+You are a helpful, intelligent chatbot. Create the slides for a presentation on the given topic.
+Include main headings for each slide, detailed bullet points for each slide.
+Add relevant content to each slide.
+The content of each slide should be verbose, descriptive, and very detailed.
+If relevant, add one or two examples to illustrate the concept.
+Unless explicitly specified with the topic, create about 10 slides.
+
+
+### Topic:
+{question}
+
+
+The output must be only a valid and syntactically correct JSON adhering to the following schema:
+{{
+    "title": "Presentation Title",
+    "slides": [
+        {{
+            "heading": "Heading for the First Slide",
+            "bullet_points": [
+                "First bullet point",
+                [
+                    "Sub-bullet point 1",
+                    "Sub-bullet point 2"
+                ],
+                "Second bullet point"
+            ]
+        }},
+        {{
+            "heading": "Heading for the Second Slide",
+            "bullet_points": [
+                "First bullet point",
+                "Second bullet item",
+                "Third bullet point"
+            ]
+        }}
+    ]
+}}
+
+
+### Output:
+```json

langchain_templates/chat_prompts/refinement_template.txt

@@ -0,0 +1,49 @@
+You are a helpful, intelligent chatbot. You follow instructions to refine an existing slide deck.
+A list of user instructions is provided below in sequential order -- from the oldest to the latest.
+The previously generated content of the slide deck in JSON format is also provided.
+Follow the instructions to revise the content of the previously generated slides of the presentation on the given topic.
+Include main headings for each slide, detailed bullet points for each slide.
+Add relevant content to each slide.
+The content of the slides should be descriptive, verbose, and detailed.
+If relevant, add one or two examples to illustrate the concept.
+Unless explicitly specified with the topic, create about 10 slides.
+You also fix any syntax error that may be present in the JSON-formatted content.
+
+
+### List of instructions:
+{instructions}
+
+
+### Previously generated slide deck content as JSON:
+{previous_content}
+
+
+The output must be only a valid and syntactically correct JSON adhering to the following schema:
+{{
+    "title": "Presentation Title",
+    "slides": [
+        {{
+            "heading": "Heading for the First Slide",
+            "bullet_points": [
+                "First bullet point",
+                [
+                    "Sub-bullet point 1",
+                    "Sub-bullet point 2"
+                ],
+                "Second bullet point"
+            ]
+        }},
+        {{
+            "heading": "Heading for the Second Slide",
+            "bullet_points": [
+                "First bullet point",             
+                "Second bullet item",
+                "Third bullet point"
+            ]
+        }}
+    ]
+}}
+
+
+### Output:
+```json

legacy_app.py

@@ -0,0 +1,294 @@
+import pathlib
+import logging
+import tempfile
+from typing import List, Tuple
+
+import json5
+import metaphor_python as metaphor
+import streamlit as st
+
+from helpers import llm_helper, pptx_helper
+from global_config import GlobalConfig
+
+
+APP_TEXT = json5.loads(open(GlobalConfig.APP_STRINGS_FILE, 'r', encoding='utf-8').read())
+GB_CONVERTER = 2 ** 30
+
+
+logger = logging.getLogger(__name__)
+
+
+@st.cache_data
+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.
+    """
+
+    logger.info('LLM call because of cache miss...')
+    return llm_helper.generate_slides_content(text).strip()
+
+
+@st.cache_resource
+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)
+
+
+@st.cache_data
+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 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'])
+    st.markdown(
+        'Powered by'
+        ' [Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2).'
+    )
+    st.markdown(
+        '*If the JSON is generated or parsed incorrectly, try again later by making minor changes'
+        ' to the input text.*'
+    )
+
+    with st.form('my_form'):
+        # Topic input
+        try:
+            with open(GlobalConfig.PRELOAD_DATA_FILE, 'r', encoding='utf-8') 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.
+    """
+
+    topic_length = len(topic)
+    logger.debug('Input length:: topic: %s', topic_length)
+
+    if topic_length >= 10:
+        logger.debug('Topic: %s', topic)
+        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)
+            logger.debug('Truncated topic: %s', topic[:target_length])
+            logger.debug('Length of JSON: %d', len(json_str))
+
+            # 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:
+        logger.info('Calling LLM for content generation on the topic: %s', text)
+        json_str = get_contents_wrapper(text)
+    except Exception as ex:
+        st.error(
+            f'An exception occurred while trying to convert to JSON. It could be because of heavy'
+            f' traffic or something else. Try doing it again or try again later.'
+            f'\nError message: {ex}'
+        )
+
+    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)
+
+    logger.info('Creating PPTX file...')
+    all_headers = pptx_helper.generate_powerpoint_presentation(
+        json_str,
+        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')
+
+    if temp:
+        temp.close()
+
+    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
+    logger.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))
+
+    logger.info('Done!')
+
+    # # 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'):
+    #     logger.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="💡️")
+    #         logger.info('Image added')
+
+
+def main():
+    """
+    Trigger application run.
+    """
+
+    build_ui()
+
+
+if __name__ == '__main__':
+    main()

requirements.txt

@@ -6,4 +6,9 @@ streamlit~=1.32.2
 python-pptx
 metaphor-python
 json5~=0.9.14
-requests~=2.31.0
+requests~=2.31.0
+
+transformers~=4.39.2
+langchain-community
+
+urllib3~=2.2.1

strings.json

@@ -1,6 +1,6 @@
 {
-    "app_name": "SlideDeck AI",
-    "caption": "*:green[Co-create your next PowerPoint slide deck with AI]*",
+    "app_name": ":green[SlideDeck AI $^{[Reloaded]}$]",
+    "caption": "*Converse, create, and improve your next PowerPoint slide deck*",
     "section_headers": [
         "Step 1: Generate your content",
         "Step 2: Make it structured",
@@ -23,7 +23,15 @@
     ],
     "urls_info": "Here is a list of some online resources that you can consult for further information on this topic:",
     "image_info": "Got some more minutes? We are also trying to deliver an AI-generated art on the presentation topic, fresh off the studio, just for you!",
-    "content_generation_failure_error": "Unfortunately, SlideDeck AI failed to generate any content for you! Please try again later.",
+    "content_generation_error": "Unfortunately, SlideDeck AI failed to generate any content for you! Please try again later.",
+    "json_parsing_error": "Unfortunately, SlideDeck AI failed to parse the response from LLM! Please try again by rephrasing the query or refreshing the page.",
     "tos": "SlideDeck AI is an experimental prototype, and it has its limitations.\nPlease carefully review any and all AI-generated content.",
-    "tos2": "By using SlideDeck AI, you agree to fair and responsible usage.\nNo liability assumed by any party."
+    "tos2": "By using SlideDeck AI, you agree to fair and responsible usage.\nNo liability assumed by any party.",
+    "ai_greetings": [
+        "How may I help you today?",
+        "Stuck with creating your presentation? Let me help you.",
+        "Looks like you have a looming deadline. Can I help you get started with your slide deck?",
+        "Hello! What topic do you have on your mind today?"
+    ],
+    "chat_placeholder": "Write the topic or instructions here"
 }