opensource_notebooklm: open source implementation of NotebookLM based on Deepseek-V3 and PlayHT TTS

General Introduction

Open Source NotebookLM is an innovative AI project that combines Deepseek-V3's language understanding capabilities with PlayHT's speech synthesis technology with the aim of creating an intelligent note-taking conversation system. Developed by the Build Fast with AI team, the project transforms textual content into a natural, educational form of dialog with realistic voice output. The system is particularly suited for educational content creation, capable of generating podcast-like style two-person conversations that make learning content more interactive and interesting. By combining advanced AI modeling and speech technology, NotebookLM offers users a new way to learn and create content.

Function List

• AI-driven natural conversation generation: creating fluent educational conversations using the Deepseek-V3 model
• Speech synthesis function: integrated PlayHT technology to convert text into realistic speech output
• Interactive dialog format: automatic generation of podcast-style two-person dialog content
• Educational content customization: ability to create in-depth, insightful discussions on any topic
• Google Colab support: provides a cloud-based operating environment for rapid deployment and use
• Open source code implementation: support for community collaboration and secondary development

Using Help

1. Environmental configuration

1.1 Basic requirements:

• Ensure that Python 3.x is installed on your system
• Need to register and get FAL API key
• Need to register and get the OpenRouter API key

1.2 Quick start method:

• Visit the Google Colab link provided with the project: https://colab.research.google.com/drive/1lSzgEXw9F4X65qSSgOs47ejMGRDkbuZH?usp=sharing
• In the Colab environment, you can run projects directly without local configuration!

2. Utilization process

2.1 API key configuration:

• Save the obtained FAL API key in the environment variable
• Configuring OpenRouter API keys for accessing AI model services

2.2 Dialogue generation:

• Prepare the topic or content you want to discuss
• Enter text using the interface provided by the system
• Deepseek-V3 model will automatically process and generate educational conversations

2.3 Speech conversion:

• The system automatically calls the PlayHT service
• Converts generated dialog text into natural speech output
• Supports multiple voice styles and tone adjustments

3. Best practice recommendations

• It is recommended to test with shorter texts first
• Ensure that inputs are educationally valuable and logical
• Dialogue generation can be optimized by adjusting parameters
• Regular backups of generated content and configurations

4. Cautions

• There may be fees associated with API usage
• It is recommended to use API quotas wisely
• Pay attention to the terms of use of the relevant services
• Periodically check the validity of the API key

5. Troubleshooting

• If the API call fails, please check the key configuration
• Ensure stable network connectivity
• Review system logs to locate specific problems
• Feedback on issues can be submitted through the project's GitHub page