Merge pull request #152 from barun-saha/refactor-to-package-v2

MANIFEST.in

@@ -0,0 +1,6 @@
+include src/slidedeckai/strings.json
+recursive-include src/slidedeckai/prompts *.txt
+recursive-include src/slidedeckai/pptx_templates *.pptx
+recursive-include src/slidedeckai/icons *.png
+recursive-include src/slidedeckai/icons *.txt
+recursive-include src/slidedeckai/file_embeddings *.npy

README.md

@@ -41,6 +41,34 @@ Clicking on the button will download the file.
 In addition, SlideDeck AI can also create a presentation based on PDF files.
 
 
+## Python API Usage
+
+```python
+from slidedeckai import SlideDeckAI
+
+
+slide_generator = SlideDeckAI(
+    model='[gg]gemini-2.5-flash-lite',
+    topic='Make a slide deck on AI',
+    api_key='your-google-api-key',
+)
+pptx_path = slide_generator.generate()
+print(f"Generated slide deck: {pptx_path}")
+```
+
+## CLI Usage
+
+Generate a new slide deck:
+```bash
+slidedeckai generate --model '[gg]gemini-2.5-flash-lite' --topic 'Make a slide deck on AI' --api-key 'your-google-api-key'
+```
+
+Launch the Streamlit app:
+```bash
+slidedeckai launch
+```
+
+
 ## Summary of the LLMs
 
 SlideDeck AI allows the use of different LLMs from several online providers—Azure OpenAI, Google, Cohere, Together AI, and OpenRouter. Most of these service providers offer generous free usage of relevant LLMs without requiring any billing information.  

app.py

@@ -6,6 +6,7 @@ import logging
 import os
 import pathlib
 import random
+import sys
 import tempfile
 from typing import List, Union
 
@@ -17,13 +18,35 @@ import requests
 import streamlit as st
 from dotenv import load_dotenv
 
-import global_config as gcfg
-import helpers.file_manager as filem
-from global_config import GlobalConfig
-from helpers import chat_helper, llm_helper, pptx_helper, text_helper
+sys.path.insert(0, os.path.abspath('src'))
+from slidedeckai.core import SlideDeckAI
+from slidedeckai import global_config as gcfg
+from slidedeckai.global_config import GlobalConfig
+from slidedeckai.helpers import llm_helper, text_helper
+import slidedeckai.helpers.file_manager as filem
+from slidedeckai.helpers.chat_helper import ChatMessage, HumanMessage, AIMessage
+from slidedeckai.helpers import chat_helper
 
 load_dotenv()
 
+class StreamlitChatMessageHistory:
+    """Chat message history stored in Streamlit session state."""
+
+    def __init__(self, key: str):
+        self.key = key
+        if key not in st.session_state:
+            st.session_state[key] = []
+
+    @property
+    def messages(self):
+        return st.session_state[self.key]
+
+    def add_user_message(self, content: str):
+        st.session_state[self.key].append(HumanMessage(content))
+
+    def add_ai_message(self, content: str):
+        st.session_state[self.key].append(AIMessage(content))
+
 RUN_IN_OFFLINE_MODE = os.getenv('RUN_IN_OFFLINE_MODE', 'False').lower() == 'true'
 
 
@@ -309,7 +332,7 @@ def set_up_chat_ui():
     st.info(APP_TEXT['like_feedback'])
     st.chat_message('ai').write(random.choice(APP_TEXT['ai_greetings']))
 
-    history = chat_helper.StreamlitChatMessageHistory(key=CHAT_MESSAGES)
+    history = StreamlitChatMessageHistory(key=CHAT_MESSAGES)
     prompt_template = chat_helper.ChatPromptTemplate.from_template(
         _get_prompt_template(
             is_refinement=_is_it_refinement()
@@ -363,104 +386,39 @@ def set_up_chat_ui():
                         f' {st.session_state["end_page"]} in {st.session_state["pdf_file"].name}'
                     )
 
-            # Get pdf contents
-            st.session_state[ADDITIONAL_INFO] = filem.get_pdf_contents(
-                st.session_state[PDF_FILE_KEY],
-                (st.session_state['start_page'], st.session_state['end_page'])
-            )
-        provider, llm_name = llm_helper.get_provider_model(
-            llm_provider_to_use,
-            use_ollama=RUN_IN_OFFLINE_MODE
-        )
-
-        # Validate that provider and model were parsed successfully
-        if not provider or not llm_name:
-            handle_error(
-                f'Failed to parse provider and model from: "{llm_provider_to_use}". '
-                f'Please select a valid LLM from the dropdown.',
-                True
-            )
-            return
-
-        user_key = api_key_token.strip()
-        az_deployment = azure_deployment.strip()
-        az_endpoint = azure_endpoint.strip()
-        api_ver = api_version.strip()
-
-        if not are_all_inputs_valid(
-                prompt_text, provider, llm_name, user_key,
-                az_deployment, az_endpoint, api_ver
-        ):
-            return
-
-        logger.info(
-            'User input: %s | #characters: %d | LLM: %s',
-            prompt_text, len(prompt_text), llm_name
-        )
         st.chat_message('user').write(prompt_text)
 
-        if _is_it_refinement():
-            user_messages = _get_user_messages()
-            user_messages.append(prompt_text)
-            list_of_msgs = [
-                f'{idx + 1}. {msg}' for idx, msg in enumerate(user_messages)
-            ]
-            formatted_template = prompt_template.format(
-                **{
-                    'instructions': '\n'.join(list_of_msgs),
-                    'previous_content': _get_last_response(),
-                    'additional_info': st.session_state.get(ADDITIONAL_INFO, ''),
-                }
-            )
-        else:
-            formatted_template = prompt_template.format(
-                **{
-                    'question': prompt_text,
-                    'additional_info': st.session_state.get(ADDITIONAL_INFO, ''),
-                }
-            )
+        slide_generator = SlideDeckAI(
+            model=llm_provider_to_use,
+            topic=prompt_text,
+            api_key=api_key_token.strip(),
+            template_idx=list(GlobalConfig.PPTX_TEMPLATE_FILES.keys()).index(pptx_template),
+            pdf_path_or_stream=st.session_state.get(PDF_FILE_KEY),
+            pdf_page_range=(st.session_state.get('start_page'), st.session_state.get('end_page')),
+        )
 
         progress_bar = st.progress(0, 'Preparing to call LLM...')
-        response = ''
+
+        def progress_callback(current_progress):
+            progress_bar.progress(min(current_progress / gcfg.get_max_output_tokens(llm_provider_to_use), 0.95), text='Streaming content...this might take a while...')
 
         try:
-            llm = llm_helper.get_litellm_llm(
-                provider=provider,
-                model=llm_name,
-                max_new_tokens=gcfg.get_max_output_tokens(llm_provider_to_use),
-                api_key=user_key,
-                azure_endpoint_url=az_endpoint,
-                azure_deployment_name=az_deployment,
-                azure_api_version=api_ver,
-            )
+            if _is_it_refinement():
+                path = slide_generator.revise(instructions=prompt_text, progress_callback=progress_callback)
+            else:
+                path = slide_generator.generate(progress_callback=progress_callback)
 
-            if not llm:
-                handle_error(
-                    'Failed to create an LLM instance! Make sure that you have selected the'
-                    ' correct model from the dropdown list and have provided correct API key'
-                    ' or access token.',
-                    False
-                )
-                return
+            progress_bar.progress(1.0, text='Done!')
+
+            if path:
+                st.session_state[DOWNLOAD_FILE_KEY] = str(path)
+                history.add_user_message(prompt_text)
+                history.add_ai_message(slide_generator.last_response)
+                st.chat_message('ai').code(slide_generator.last_response, language='json')
+                _display_download_button(path)
+            else:
+                handle_error("Failed to generate slide deck.", True)
 
-            for chunk in llm.stream(formatted_template):
-                if isinstance(chunk, str):
-                    response += chunk
-                else:
-                    content = getattr(chunk, 'content', None)
-                    if content is not None:
-                        response += content
-                    else:
-                        response += str(chunk)
-
-                # Update the progress bar with an approx progress percentage
-                progress_bar.progress(
-                    min(
-                        len(response) / gcfg.get_max_output_tokens(llm_provider_to_use),
-                        0.95
-                    ),
-                    text='Streaming content...this might take a while...'
-                )
         except (httpx.ConnectError, requests.exceptions.ConnectionError):
             handle_error(
                 'A connection error occurred while streaming content from the LLM endpoint.'
@@ -469,22 +427,19 @@ def set_up_chat_ui():
                 ' using Ollama, make sure that Ollama is already running on your system.',
                 True
             )
-            return
         except huggingface_hub.errors.ValidationError as ve:
             handle_error(
                 f'An error occurred while trying to generate the content: {ve}'
                 '\nPlease try again with a significantly shorter input text.',
                 True
             )
-            return
         except ollama.ResponseError:
             handle_error(
-                f'The model `{llm_name}` is unavailable with Ollama on your system.'
-                f' Make sure that you have provided the correct LLM name or pull it using'
-                f' `ollama pull {llm_name}`. View LLMs available locally by running `ollama list`.',
+                f'The model is unavailable with Ollama on your system.'
+                f' Make sure that you have provided the correct LLM name or pull it.'
+                f' View LLMs available locally by running `ollama list`.',
                 True
             )
-            return
         except Exception as ex:
             _msg = str(ex)
             if 'payment required' in _msg.lower():
@@ -509,101 +464,6 @@ def set_up_chat_ui():
                     ' Read **[how to get free LLM API keys](https://github.com/barun-saha/slide-deck-ai?tab=readme-ov-file#summary-of-the-llms)**.',
                     True
                 )
-            return
-
-        history.add_user_message(prompt_text)
-        history.add_ai_message(response)
-
-        # 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
-        response = text_helper.get_clean_json(response)
-        logger.info(
-            'Cleaned JSON length: %d', len(response)
-        )
-
-        # Now create the PPT file
-        progress_bar.progress(
-            GlobalConfig.LLM_PROGRESS_MAX,
-            text='Finding photos online and generating the slide deck...'
-        )
-        progress_bar.progress(1.0, text='Done!')
-        st.chat_message('ai').code(response, language='json')
-
-        if path := generate_slide_deck(response):
-            _display_download_button(path)
-
-        logger.info(
-            '#messages in history / 2: %d',
-            len(st.session_state[CHAT_MESSAGES]) / 2
-        )
-
-
-def generate_slide_deck(json_str: str) -> Union[pathlib.Path, None]:
-    """
-    Create a slide deck and return the file path. In case there is any error creating the slide
-    deck, the path may be to an empty file.
-
-    :param json_str: The content in *valid* JSON format.
-    :return: The path to the .pptx file or `None` in case of error.
-    """
-
-    try:
-        parsed_data = json5.loads(json_str)
-    except ValueError:
-        handle_error(
-            'Encountered error while parsing JSON...will fix it and retry',
-            True
-        )
-        try:
-            parsed_data = json5.loads(text_helper.fix_malformed_json(json_str))
-        except ValueError:
-            handle_error(
-                'Encountered an error again while fixing JSON...'
-                'the slide deck cannot be created, unfortunately ☹'
-                '\nPlease try again later.',
-                True
-            )
-            return None
-    except RecursionError:
-        handle_error(
-            'Encountered a recursion error while parsing JSON...'
-            'the slide deck cannot be created, unfortunately ☹'
-            '\nPlease try again later.',
-            True
-        )
-        return None
-    except Exception:
-        handle_error(
-            'Encountered an error while parsing JSON...'
-            'the slide deck cannot be created, unfortunately ☹'
-            '\nPlease try again later.',
-            True
-        )
-        return None
-
-    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()
-
-    try:
-        logger.debug('Creating PPTX file: %s...', st.session_state[DOWNLOAD_FILE_KEY])
-        pptx_helper.generate_powerpoint_presentation(
-            parsed_data,
-            slides_template=pptx_template,
-            output_file_path=path
-        )
-    except Exception as ex:
-        st.error(APP_TEXT['content_generation_error'])
-        logger.exception('Caught a generic exception: %s', str(ex))
-
-    return path
 
 
 def _is_it_refinement() -> bool:
@@ -643,9 +503,6 @@ def _get_last_response() -> str:
     :return: The response text.
     """
 
-    return st.session_state[CHAT_MESSAGES][-1].content
-
-
 def _display_messages_history(view_messages: st.expander):
     """
     Display the history of messages.

pyproject.toml

@@ -0,0 +1,39 @@
+[build-system]
+requires = ["setuptools>=77.0.3"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "slidedeckai"
+authors = [
+  { name="Barun Saha", email="[email protected]" }
+]
+description = "A Python package to generate slide decks using AI."
+readme = "README.md"
+requires-python = ">=3.10"
+classifiers = [
+    "Programming Language :: Python :: 3",
+    "License :: OSI Approved :: MIT License",
+    "Operating System :: OS Independent"
+]
+dynamic = ["dependencies", "version"]
+
+[tool.setuptools]
+package-dir = {"" = "src"}
+include-package-data = true
+
+[tool.setuptools.packages.find]
+where = ["src"]
+
+[tool.setuptools.dynamic]
+dependencies = {file = ["requirements.txt"]}
+version = {attr = "slidedeckai._version.__version__"}
+
+[tool.setuptools.package-data]
+slidedeckai = ["prompts/**/*.txt", "strings.json", "pptx_templates/*.pptx", "icons/png128/*.png", "icons/svg_repo.txt", "file_embeddings/*.npy"]
+
+[project.urls]
+"Homepage" = "https://github.com/barun-saha/slide-deck-ai"
+"Bug Tracker" = "https://github.com/barun-saha/slide-deck-ai/issues"
+
+[project.scripts]
+slidedeckai = "slidedeckai.cli:main"

src/slidedeckai/_version.py

@@ -0,0 +1 @@
+__version__ = "8.0.0"

src/slidedeckai/cli.py

@@ -0,0 +1,53 @@
+"""
+Command-line interface for SlideDeckAI.
+"""
+import argparse
+import subprocess
+import sys
+from .core import SlideDeckAI
+
+def main():
+    """
+    The main function for the CLI.
+    """
+    parser = argparse.ArgumentParser(description='Generate slide decks with SlideDeckAI.')
+    subparsers = parser.add_subparsers(dest='command')
+
+    # 'generate' command
+    parser_generate = subparsers.add_parser('generate', help='Generate a new slide deck.')
+    parser_generate.add_argument('--model', required=True, help='The name of the LLM model to use.')
+    parser_generate.add_argument('--topic', required=True, help='The topic of the slide deck.')
+    parser_generate.add_argument('--api-key', help='The API key for the LLM provider.')
+    parser_generate.add_argument('--template-id', type=int, default=0, help='The index of the PowerPoint template to use.')
+    parser_generate.add_argument('--output-path', help='The path to save the generated .pptx file.')
+
+    # 'launch' command
+    subparsers.add_parser('launch', help='Launch the Streamlit app.')
+
+    args = parser.parse_args()
+
+    if args.command == 'generate':
+        slide_generator = SlideDeckAI(
+            model=args.model,
+            topic=args.topic,
+            api_key=args.api_key,
+            template_idx=args.template_id,
+        )
+
+        pptx_path = slide_generator.generate()
+
+        if args.output_path:
+            import shutil
+            shutil.move(str(pptx_path), args.output_path)
+            print(f"Slide deck saved to {args.output_path}")
+        else:
+            print(f"Slide deck saved to {pptx_path}")
+    elif args.command == 'launch':
+        # Get the path to the app.py file
+        import os
+        import slidedeckai
+        app_path = os.path.join(os.path.dirname(slidedeckai.__file__), '..', '..', 'app.py')
+        subprocess.run([sys.executable, '-m', 'streamlit', 'run', app_path])
+
+if __name__ == '__main__':
+    main()

src/slidedeckai/core.py

@@ -0,0 +1,208 @@
+"""
+Core classes for SlideDeckAI.
+"""
+import logging
+import os
+import pathlib
+import tempfile
+from typing import Union
+
+import json5
+from dotenv import load_dotenv
+
+from . import global_config as gcfg
+from .global_config import GlobalConfig
+from .helpers import llm_helper, pptx_helper, text_helper
+from .helpers.chat_helper import ChatMessageHistory
+
+load_dotenv()
+
+RUN_IN_OFFLINE_MODE = os.getenv('RUN_IN_OFFLINE_MODE', 'False').lower() == 'true'
+
+logger = logging.getLogger(__name__)
+
+from .helpers import file_manager as filem
+
+class SlideDeckAI:
+    """
+    The main class for generating slide decks.
+    """
+
+    def __init__(self, model, topic, api_key=None, pdf_path_or_stream=None, pdf_page_range=None, template_idx=0):
+        """
+        Initializes the SlideDeckAI object.
+
+        :param model: The name of the LLM model to use.
+        :param topic: The topic of the slide deck.
+        :param api_key: The API key for the LLM provider.
+        :param pdf_path_or_stream: The path to a PDF file or a file-like object.
+        :param pdf_page_range: A tuple representing the page range to use from the PDF file.
+        :param template_idx: The index of the PowerPoint template to use.
+        """
+        self.model = model
+        self.topic = topic
+        self.api_key = api_key
+        self.pdf_path_or_stream = pdf_path_or_stream
+        self.pdf_page_range = pdf_page_range
+        self.template_idx = template_idx
+        self.chat_history = ChatMessageHistory()
+        self.last_response = None
+
+    def _get_prompt_template(self, is_refinement: bool) -> str:
+        """
+        Return a prompt template.
+
+        :param is_refinement: Whether this is the initial or refinement prompt.
+        :return: The prompt template as f-string.
+        """
+        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 template
+
+    def generate(self, progress_callback=None):
+        """
+        Generates the initial slide deck.
+        :return: The path to the generated .pptx file.
+        """
+        additional_info = ''
+        if self.pdf_path_or_stream:
+            additional_info = filem.get_pdf_contents(self.pdf_path_or_stream, self.pdf_page_range)
+
+        self.chat_history.add_user_message(self.topic)
+        prompt_template = self._get_prompt_template(is_refinement=False)
+        formatted_template = prompt_template.format(question=self.topic, additional_info=additional_info)
+
+        provider, llm_name = llm_helper.get_provider_model(self.model, use_ollama=RUN_IN_OFFLINE_MODE)
+
+        llm = llm_helper.get_litellm_llm(
+            provider=provider,
+            model=llm_name,
+            max_new_tokens=gcfg.get_max_output_tokens(self.model),
+            api_key=self.api_key,
+        )
+
+        response = ""
+        for chunk in llm.stream(formatted_template):
+            if isinstance(chunk, str):
+                response += chunk
+            else:
+                content = getattr(chunk, 'content', None)
+                if content is not None:
+                    response += content
+                else:
+                    response += str(chunk)
+            if progress_callback:
+                progress_callback(len(response))
+
+        self.last_response = text_helper.get_clean_json(response)
+        self.chat_history.add_ai_message(self.last_response)
+
+        return self._generate_slide_deck(self.last_response)
+
+    def revise(self, instructions, progress_callback=None):
+        """
+        Revises the slide deck with new instructions.
+
+        :param instructions: The instructions for revising the slide deck.
+        :return: The path to the revised .pptx file.
+        """
+        if not self.last_response:
+            raise ValueError("You must generate a slide deck before you can revise it.")
+
+        if len(self.chat_history.messages) >= 16:
+            raise ValueError("Chat history is full. Please reset to continue.")
+
+        self.chat_history.add_user_message(instructions)
+
+        prompt_template = self._get_prompt_template(is_refinement=True)
+
+        list_of_msgs = [f'{idx + 1}. {msg.content}' for idx, msg in enumerate(self.chat_history.messages) if msg.role == 'user']
+
+        additional_info = ''
+        if self.pdf_path_or_stream:
+            additional_info = filem.get_pdf_contents(self.pdf_path_or_stream, self.pdf_page_range)
+
+        formatted_template = prompt_template.format(
+            instructions='\n'.join(list_of_msgs),
+            previous_content=self.last_response,
+            additional_info=additional_info,
+        )
+
+        provider, llm_name = llm_helper.get_provider_model(self.model, use_ollama=RUN_IN_OFFLINE_MODE)
+
+        llm = llm_helper.get_litellm_llm(
+            provider=provider,
+            model=llm_name,
+            max_new_tokens=gcfg.get_max_output_tokens(self.model),
+            api_key=self.api_key,
+        )
+
+        response = ""
+        for chunk in llm.stream(formatted_template):
+            if isinstance(chunk, str):
+                response += chunk
+            else:
+                content = getattr(chunk, 'content', None)
+                if content is not None:
+                    response += content
+                else:
+                    response += str(chunk)
+            if progress_callback:
+                progress_callback(len(response))
+
+        self.last_response = text_helper.get_clean_json(response)
+        self.chat_history.add_ai_message(self.last_response)
+
+        return self._generate_slide_deck(self.last_response)
+
+    def _generate_slide_deck(self, json_str: str) -> Union[pathlib.Path, None]:
+        """
+        Create a slide deck and return the file path.
+
+        :param json_str: The content in *valid* JSON format.
+        :return: The path to the .pptx file or `None` in case of error.
+        """
+        try:
+            parsed_data = json5.loads(json_str)
+        except (ValueError, RecursionError) as e:
+            logger.error("Error parsing JSON: %s", e)
+            try:
+                parsed_data = json5.loads(text_helper.fix_malformed_json(json_str))
+            except (ValueError, RecursionError) as e2:
+                logger.error("Error parsing fixed JSON: %s", e2)
+                return None
+
+        temp = tempfile.NamedTemporaryFile(delete=False, suffix='.pptx')
+        path = pathlib.Path(temp.name)
+        temp.close()
+
+        try:
+            pptx_helper.generate_powerpoint_presentation(
+                parsed_data,
+                slides_template=list(GlobalConfig.PPTX_TEMPLATE_FILES.keys())[self.template_idx],
+                output_file_path=path
+            )
+        except Exception as ex:
+            logger.exception('Caught a generic exception: %s', str(ex))
+            return None
+
+        return path
+
+    def set_template(self, idx):
+        """
+        Sets the PowerPoint template to use.
+
+        :param idx: The index of the template to use.
+        """
+        self.template_idx = idx
+
+    def reset(self):
+        """
+        Resets the chat history.
+        """
+        self.chat_history = ChatMessageHistory()
+        self.last_response = None

global_config.py → src/slidedeckai/global_config.py

@@ -4,6 +4,7 @@ A set of configurations used by the app.
 import logging
 import os
 import re
+from pathlib import Path
 
 from dataclasses import dataclass
 from dotenv import load_dotenv
@@ -11,6 +12,7 @@ from dotenv import load_dotenv
 
 load_dotenv()
 
+_SRC_DIR = Path(__file__).resolve().parent
 
 @dataclass(frozen=True)
 class GlobalConfig:
@@ -128,32 +130,32 @@ class GlobalConfig:
 
     LOG_LEVEL = 'DEBUG'
     COUNT_TOKENS = False
-    APP_STRINGS_FILE = 'strings.json'
-    PRELOAD_DATA_FILE = 'examples/example_02.json'
-    INITIAL_PROMPT_TEMPLATE = 'prompts/initial_template_v4_two_cols_img.txt'
-    REFINEMENT_PROMPT_TEMPLATE = 'prompts/refinement_template_v4_two_cols_img.txt'
+    APP_STRINGS_FILE = _SRC_DIR / 'strings.json'
+    PRELOAD_DATA_FILE = _SRC_DIR / 'examples/example_02.json'
+    INITIAL_PROMPT_TEMPLATE = _SRC_DIR / 'prompts/initial_template_v4_two_cols_img.txt'
+    REFINEMENT_PROMPT_TEMPLATE = _SRC_DIR / 'prompts/refinement_template_v4_two_cols_img.txt'
 
     LLM_PROGRESS_MAX = 90
-    ICONS_DIR = 'icons/png128/'
+    ICONS_DIR = _SRC_DIR / 'icons/png128/'
     TINY_BERT_MODEL = 'gaunernst/bert-mini-uncased'
-    EMBEDDINGS_FILE_NAME = 'file_embeddings/embeddings.npy'
-    ICONS_FILE_NAME = 'file_embeddings/icons.npy'
+    EMBEDDINGS_FILE_NAME = _SRC_DIR / 'file_embeddings/embeddings.npy'
+    ICONS_FILE_NAME = _SRC_DIR / 'file_embeddings/icons.npy'
 
     PPTX_TEMPLATE_FILES = {
         'Basic': {
-            'file': 'pptx_templates/Blank.pptx',
+            'file': _SRC_DIR / 'pptx_templates/Blank.pptx',
             'caption': 'A good start (Uses [photos](https://unsplash.com/photos/AFZ-qBPEceA) by [cetteup](https://unsplash.com/@cetteup?utm_content=creditCopyText&utm_medium=referral&utm_source=unsplash) on [Unsplash](https://unsplash.com/photos/a-foggy-forest-filled-with-lots-of-trees-d3ci37Gcgxg?utm_content=creditCopyText&utm_medium=referral&utm_source=unsplash)) 🟧'
         },
         'Ion Boardroom': {
-            'file': 'pptx_templates/Ion_Boardroom.pptx',
+            'file': _SRC_DIR / 'pptx_templates/Ion_Boardroom.pptx',
             'caption': 'Make some bold decisions 🟥'
         },
         'Minimalist Sales Pitch': {
-            'file': 'pptx_templates/Minimalist_sales_pitch.pptx',
+            'file': _SRC_DIR / 'pptx_templates/Minimalist_sales_pitch.pptx',
             'caption': 'In high contrast ⬛'
         },
         'Urban Monochrome': {
-            'file': 'pptx_templates/Urban_monochrome.pptx',
+            'file': _SRC_DIR / 'pptx_templates/Urban_monochrome.pptx',
             'caption': 'Marvel in a monochrome dream ⬜'
         },
     }

{helpers → src/slidedeckai/helpers}/chat_helper.py

@@ -27,24 +27,17 @@ class AIMessage(ChatMessage):
         super().__init__(content, 'ai')
 
 
-class StreamlitChatMessageHistory:
-    """Chat message history stored in Streamlit session state."""
+class ChatMessageHistory:
+    """Chat message history stored in a list."""
     
-    def __init__(self, key: str):
-        self.key = key
-        if key not in st.session_state:
-            st.session_state[key] = []
-    
-    @property
-    def messages(self):
-        return st.session_state[self.key]
+    def __init__(self):
+        self.messages = []
     
     def add_user_message(self, content: str):
-        st.session_state[self.key].append(HumanMessage(content))
+        self.messages.append(HumanMessage(content))
     
     def add_ai_message(self, content: str):
-        st.session_state[self.key].append(AIMessage(content))
-
+        self.messages.append(AIMessage(content))
 
 class ChatPromptTemplate:
     """Template for chat prompts."""

{helpers → src/slidedeckai/helpers}/file_manager.py

@@ -8,10 +8,7 @@ import sys
 import streamlit as st
 from pypdf import PdfReader
 
-sys.path.append('..')
-sys.path.append('../..')
-
-from global_config import GlobalConfig
+from ..global_config import GlobalConfig
 
 
 logger = logging.getLogger(__name__)

{helpers → src/slidedeckai/helpers}/icons_embeddings.py

@@ -11,10 +11,7 @@ import numpy as np
 from sklearn.metrics.pairwise import cosine_similarity
 from transformers import BertTokenizer, BertModel
 
-sys.path.append('..')
-sys.path.append('../..')
-
-from global_config import GlobalConfig
+from ..global_config import GlobalConfig
 
 
 tokenizer = BertTokenizer.from_pretrained(GlobalConfig.TINY_BERT_MODEL)
@@ -28,9 +25,9 @@ def get_icons_list() -> List[str]:
     :return: The icons file names.
     """
 
-    items = pathlib.Path('../' + GlobalConfig.ICONS_DIR).glob('*.png')
+    items = GlobalConfig.ICONS_DIR.glob('*.png')
     items = [
-        os.path.basename(str(item)).removesuffix('.png') for item in items
+        item.stem for item in items
     ]
 
     return items

{helpers → src/slidedeckai/helpers}/llm_helper.py

@@ -8,9 +8,7 @@ import urllib3
 from typing import Tuple, Union, Iterator, Optional
 
 
-sys.path.append('..')
-
-from global_config import GlobalConfig
+from ..global_config import GlobalConfig
 
 try:
     import litellm

{helpers → src/slidedeckai/helpers}/pptx_helper.py

@@ -16,12 +16,9 @@ from dotenv import load_dotenv
 from pptx.enum.shapes import MSO_AUTO_SHAPE_TYPE
 from pptx.shapes.placeholder import PicturePlaceholder, SlidePlaceholder
 
-sys.path.append('..')
-sys.path.append('../..')
-
-import helpers.icons_embeddings as ice
-import helpers.image_search as ims
-from global_config import GlobalConfig
+from . import icons_embeddings as ice
+from . import image_search as ims
+from ..global_config import GlobalConfig
 
 
 load_dotenv()