Fix imports and references of old repo name

demo/app.py

@@ -61,7 +61,7 @@ def load_text_to_speech_model_and_tokenizer():
     st.divider()
     st.header("Loading and Cleaning Data")
     st.markdown(
-        "[API Reference for data_cleaners](https://mozilla-ai.github.io/document-to-podcast/api/#opennotebookllm.preprocessing.data_cleaners)"
+        "[API Reference for data_cleaners](https://mozilla-ai.github.io/document-to-podcast/api/#document_to_podcast.preprocessing.data_cleaners)"
     )
 
     extension = Path(uploaded_file.name).suffix
@@ -81,7 +81,7 @@ def load_text_to_speech_model_and_tokenizer():
     st.divider()
     st.header("Downloading and Loading models")
     st.markdown(
-        "[API Reference for model_loaders](https://mozilla-ai.github.io/document-to-podcast/api/#opennotebookllm.inference.model_loaders)"
+        "[API Reference for model_loaders](https://mozilla-ai.github.io/document-to-podcast/api/#document_to_podcast.inference.model_loaders)"
     )
 
     text_model = load_text_to_text_model()

docs/step-by-step-guide.md

@@ -41,7 +41,7 @@ Cleaner input data ensures that the model works with reliable and consistent inf
 
  **2 - Text Cleaning**
 
-   - Uses functions defined in [`data_cleaners.py`](../api/#opennotebookllm.inference.data_cleaners)
+   - Uses functions defined in [`data_cleaners.py`](../api/#document_to_podcast.inference.data_cleaners)
 
    - Removes unwanted elements like URLs, email addresses, and special characters using Python's `re` library, which leverages **Regular Expressions** (regex) to identify and manipulate specific patterns in text.
 
@@ -55,15 +55,15 @@ In this step, the pre-processed text is transformed into a conversational podcas
 
  **1 - Model Loading**
 
-   - The [`model_loader.py`](../api/#opennotebookllm.inference.model_loaders) script is responsible for loading GGUF-type models using the `llama_cpp` library.
+   - The [`model_loader.py`](../api/#document_to_podcast.inference.model_loaders) script is responsible for loading GGUF-type models using the `llama_cpp` library.
 
    - The function `load_llama_cpp_model` takes a model ID in the format `{org}/{repo}/{filename}` and loads the specified model.
 
    - This approach of using the `llama_cpp` library supports efficient CPU-based inference, making language models accessible even on machines without GPUs.
 
  **2 - Text-to-Text Generation**
 
-   - The [`text_to_text.py`](../api/#opennotebookllm.inference.text_to_text) script manages the interaction with the language model, converting input text into a structured conversational podcast script.
+   - The [`text_to_text.py`](../api/#document_to_podcast.inference.text_to_text) script manages the interaction with the language model, converting input text into a structured conversational podcast script.
 
    - It uses the `chat_completion` function to process the input text and a customizable system prompt, guiding the language to generate a text output (e.g. a coherent podcast script between speakers).
 

src/opennotebookllm/podcast_maker/script_to_audio.py → src/document_to_podcast/podcast_maker/script_to_audio.py

@@ -1,9 +1,11 @@
 import numpy as np
 import soundfile as sf
 
-from opennotebookllm.inference.model_loaders import load_parler_tts_model_and_tokenizer
-from opennotebookllm.inference.text_to_speech import text_to_speech
-from opennotebookllm.podcast_maker.config import PodcastConfig, SpeakerConfig
+from document_to_podcast.inference.model_loaders import (
+    load_parler_tts_model_and_tokenizer,
+)
+from document_to_podcast.inference.text_to_speech import text_to_speech
+from document_to_podcast.podcast_maker.config import PodcastConfig, SpeakerConfig
 
 
 def parse_script_to_waveform(script: str, podcast_config: PodcastConfig):

tests/conftest.py

@@ -2,8 +2,10 @@
 
 import pytest
 
-from opennotebookllm.inference.model_loaders import load_parler_tts_model_and_tokenizer
-from opennotebookllm.podcast_maker.config import (
+from document_to_podcast.inference.model_loaders import (
+    load_parler_tts_model_and_tokenizer,
+)
+from document_to_podcast.podcast_maker.config import (
     PodcastConfig,
     SpeakerConfig,
 )

tests/integration/test_text_to_text_to_speech.py

@@ -1,11 +1,11 @@
 import os
 from pathlib import Path
 
-from opennotebookllm.inference.model_loaders import load_llama_cpp_model
-from opennotebookllm.inference.text_to_speech import text_to_speech
-from opennotebookllm.inference.text_to_text import text_to_text
-from opennotebookllm.podcast_maker.config import PodcastConfig
-from opennotebookllm.podcast_maker.script_to_audio import save_waveform_as_file
+from document_to_podcast.inference.model_loaders import load_llama_cpp_model
+from document_to_podcast.inference.text_to_speech import text_to_speech
+from document_to_podcast.inference.text_to_text import text_to_text
+from document_to_podcast.podcast_maker.config import PodcastConfig
+from document_to_podcast.podcast_maker.script_to_audio import save_waveform_as_file
 
 
 def test_text_to_text_to_speech(tmp_path: Path, podcast_config: PodcastConfig):

tests/unit/inference/test_text_to_speech.py

@@ -1,9 +1,9 @@
 from pathlib import Path
 
-from opennotebookllm.inference.text_to_speech import text_to_speech
+from document_to_podcast.inference.text_to_speech import text_to_speech
 
-from opennotebookllm.podcast_maker.config import PodcastConfig
-from opennotebookllm.podcast_maker.script_to_audio import save_waveform_as_file
+from document_to_podcast.podcast_maker.config import PodcastConfig
+from document_to_podcast.podcast_maker.script_to_audio import save_waveform_as_file
 
 
 def test_text_to_speech_parler(

tests/unit/podcast_maker/test_script_to_audio.py

@@ -3,8 +3,8 @@
 
 import numpy as np
 
-from opennotebookllm.podcast_maker.config import PodcastConfig
-from opennotebookllm.podcast_maker.script_to_audio import (
+from document_to_podcast.podcast_maker.config import PodcastConfig
+from document_to_podcast.podcast_maker.script_to_audio import (
     parse_script_to_waveform,
     save_waveform_as_file,
 )