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Local-NotebookLM - An open-source AI tool for converting PDFs to podcasts, with customizable audio.

Local-NotebookLM is an open-source local AI tool that converts PDF documents into engaging audio content such as podcasts, interviews, and debates. It supports multiple output formats and content styles, allowing users to choose according to their needs...

What is Local-NotebookLM?

Local-NotebookLM is an open-source local AI tool that converts PDF documents into engaging audio content such as podcasts, interviews, and debates. It supports multiple output formats and content styles, allowing users to choose different audio lengths and styles, such as short, medium, and long pieces, as well as normal, casual, formal, technical, and academic styles. It supports various LLM providers, such as OpenAI, Groq, and Azure OpenAI, and includes text-to-speech functionality, allowing users to customize voice characters. The tool offers multiple usage methods, including a command-line interface, Python API, Grado Web UI, and FastAPI server, facilitating integration and use according to user needs. It supports multiple languages, allowing users to select different languages to generate audio content.

Main functions of Local-NotebookLM

  • PDF Text Extraction and ProcessingAutomatically extracts text from PDF documents, cleans up formatting errors and redundant content, and supports processing academic papers containing mathematical formulas.
  • Custom audio generationSupports multiple audio output formats, such as podcasts, interviews, debates, lectures, etc.; provides multiple content styles, including normal, casual, formal, technical, academic, etc.; supports different content lengths, from short to long.
  • Multilingual supportUsers can select different languages to generate audio content as needed, ensuring that the selected LLM and TTS models support the target language.
  • Flexible model supportIt supports multiple LLM providers, such as OpenAI, Groq, Azure OpenAI, LMStudio, Ollama, etc., allowing users to choose different models according to their needs.
  • Text-to-speech conversionIt supports voice selection and can generate natural and fluent audio content. Users can customize their voice characters.
  • Multiple ways to useIt offers multiple usage methods, including command-line interface, Python API, Grado Web UI, and FastAPI server, making it convenient for users to integrate and use it according to their own needs.
  • Fully configurable processUsers can customize the processing flow through configuration files, including various steps such as text processing and audio generation.

Local-NotebookLM project address

  • Github repositoryhttps://github.com/Goekdeniz-Guelmez/Local-NotebookLM

How to use Local-NotebookLM

  • InstallThere are two ways to install: from PyPI or from source code. Installing from PyPI simply requires running...pip install local-notebooklmInstalling from source code requires cloning the repository, creating a virtual environment, and installing dependencies.
  • Command line usage:runpython -m local_notebooklm.start --pdf PATH_TO_PDF [options]It generates audio content by specifying the PDF file path and related options (such as output format, style, length, etc.).
  • Programming API usageImporting in Python codepodcast_processorThis function, when called with parameters such as the PDF file path and configuration file path, generates audio programmatically.
  • Web UI usage:runpython -m local_notebooklm.web_uiLaunch the Gradio Web UI and access it through a browser to operate using the graphical interface; no command-line knowledge is required.
  • FastAPI server uses:runpython -m local_notebooklm.serverStart the FastAPI server to access functionality via the Web API, making it easy to integrate into other projects.

Application scenarios of Local-NotebookLM

  • EducationTeachers can convert teaching materials into audio lectures, making it easier for students to learn in different scenarios and improving the flexibility and convenience of learning.
  • academic researchResearchers can transform academic papers into podcasts to facilitate peer exchange and knowledge dissemination, thereby expanding the impact of their research findings.
  • Content creationContent creators can transform various documents into audio content of different styles, such as interviews and debates, enriching the creative forms and attracting more listeners.
  • Corporate TrainingCompanies can convert training materials into audio files for employees to learn during their spare time, thereby improving training efficiency and employee engagement.
  • Personal learningIndividual users can convert books or articles of interest into audio and use fragmented time such as commuting or exercising to learn and improve their self-improvement efficiency.
  • Knowledge sharingConvert professional knowledge documents into audio, making them easy to share on social media or professional platforms and promoting the widespread dissemination of knowledge.
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