Top Open‑Source NotebookLM Alternatives: AI‑Powered Docs, Podcasts & Research Tools
This article surveys the most popular open‑source replacements for Google NotebookLM, detailing each project's star count, supported AI models, multimodal input capabilities, Docker deployment options, and unique features such as multi‑speaker podcast generation, semantic search, and collaborative knowledge‑base integration.
Google's NotebookLM is an AI‑assisted note‑taking tool that limits answers to uploaded documents and can generate realistic dual‑speaker podcast dialogues. The following open‑source projects provide comparable or extended functionality without relying on Google’s cloud services.
Open Notebook
Open Notebook is the highest‑starred GitHub alternative (≈14.6k stars). It offers a full‑featured local knowledge‑management solution that can be deployed via Docker. The platform supports more than 16 AI providers, including OpenAI, Anthropic, Gemini, and local models through Ollama or LM Studio, allowing users to switch models based on cost, privacy, or performance.
Key capabilities include multimodal content ingestion (PDF, web pages, audio, YouTube), advanced podcast generation with up to four speakers, fine‑grained script control, and role‑based access control (RBAC) for team collaboration.
Open source: https://github.com/lfnovo/open-notebookSurfSense
SurfSense (≈11.4k stars) positions itself as an open‑source AI search and research agent, aiming to replace NotebookLM, Perplexity, and Glean. It integrates a wide range of data sources (Notion, YouTube, GitHub, etc.) and combines semantic and full‑text search with re‑ranking algorithms for fast, accurate answer retrieval.
The system supports over 16 AI providers and local models, offers multimodal input (PDF, web, audio, video), and includes a built‑in rapid podcast generation agent that can turn chat content into engaging audio using multiple TTS services (OpenAI, Google, ElevenLabs, Microsoft Edge).
Open source: https://github.com/MODSetter/SurfSensePodcastfy
Podcastfy focuses on high‑quality podcast creation, converting multimodal content (text, images, websites, PDFs) into multilingual audio dialogues. It integrates more than 100 LLMs for script generation and supports various TTS engines (OpenAI, Google, ElevenLabs, Microsoft Edge) to produce natural‑sounding speech.
The tool is available as a Python package, a command‑line interface, and a web UI, catering to developers and non‑technical users alike.
Open source: https://github.com/souzatharsis/podcastfyNotebookLlama
NotebookLlama, released by the LlamaIndex team, is a fully open‑source notebook‑to‑podcast pipeline with about 1.7k stars. It leverages the LlamaCloud ecosystem for complex document parsing and uses open‑source models to transform documents into podcasts, covering text extraction, script generation, dramatization, and TTS.
Users can choose OpenAI, ElevenLabs, or entirely local models for the end‑to‑end workflow.
Open source: https://github.com/run-llama/notebookllamaPageLM
PageLM (≈1.0k stars) turns learning materials into interactive resources, offering AI‑enhanced Cornell‑style notes, quizzes, flashcards, and exam simulations. It also converts study content into podcasts, supporting both reading and listening modes.
The platform supports major AI models such as Google Gemini, OpenAI GPT, Anthropic Claude, and local Ollama models, allowing flexible backend configuration based on budget and hardware.
Open source: https://github.com/CaviraOSS/PageLMInsightsLM
InsightsLM (≈0.5k stars) emphasizes low‑code/no‑code notebook functionality. It uses Supabase for storage, N8N for workflow automation, and a React front‑end. The system supports local deployment with Ollama or Qwen3 models, enabling offline AI interaction.
Core features include document‑based chat, citation‑rich answers, and podcast generation.
Open source: https://github.com/theaiautomators/insights-lm-publicAll listed projects provide Docker deployment options and, where applicable, role‑based access control, making them suitable for individual researchers as well as collaborative team environments.
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