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tldw

tldw is a free, open-source, self-hosted research system for collecting, transcribing, searching, and querying source material.

Place
#25 of 25
Score
5.6
tldw's website

What tldw is

tldw is a free, open-source, self-hosted research system for collecting, transcribing, searching, and querying source material. It accepts video, audio, PDFs, web pages, EPUB, DOCX, Markdown, XML, and other inputs, including YouTube URLs and local video files. Recordings become searchable text for quoting, summaries, and reuse. Hybrid retrieval searches transcripts, notes, and documents with full-text search, vectors, and reranking. Users can combine local inference, hosted model APIs, or both through one interface. The project provides OpenAI-compatible Chat, Audio, Embeddings, and Evals APIs. Notes, prompts, chats, artifacts, and source material share a workspace, with study packs, flashcard templates, study suggestions, and evaluation workflows. Listed hosted providers include OpenAI, Anthropic, Google, Cohere, DeepSeek, Groq, Mistral, OpenRouter, HuggingFace, and Qwen; local options include Ollama, vLLM, and llama.cpp. MCP automation offers bounded command execution, policy-aware discovery, and approval gates. Data stays on infrastructure users control, with no telemetry, analytics, or phone-home behavior. The v0.1.31 release is beta, and PyPI installation is not generally available.

Good

  • Accepts video, audio, documents, and web sources
  • Produces searchable transcript output
  • Combines full-text, vector, and reranked retrieval
  • Supports hosted and local model providers
  • Keeps data on infrastructure users control

Watch out

  • Project is labeled beta
  • PyPI installation is not generally available
  • Installation directs users to a repository checkout
  • Self-hosted deployment requires setup

Who it suits

tldw suits researchers and learners who want self-hosted ingestion, transcription, retrieval, and model flexibility. It is intended for people comfortable using a beta project and installing from a repository checkout.

Verdict

tldw provides a broad, self-controlled workspace for source collection, transcription, search, and AI-assisted study. Its beta status and repository-based installation matter for anyone seeking a packaged installation.

The facts

Each one read from tldw's own pages, with the date it was checked.

What it does

API
The project provides OpenAI-compatible Chat, Audio, Embeddings, and Evals APIs.checked 7 Oct 2026
APIs and automation
The project provides OpenAI-compatible Chat, Audio, Embeddings, and Evals APIs, plus MCP tool execution and metrics.checked 7 Oct 2026
Automation
MCP automation includes workspace-bounded command execution, policy-aware discovery, and approval gates.checked 7 Oct 2026
Availability
The project is labeled beta, and the site says PyPI installation is not generally available yet.checked 7 Oct 2026
Community support
The site directs users to Discord, Zulip, and GitHub for discussion, help, and contribution.checked 7 Oct 2026
Data handling
The site says users keep data on infrastructure they control, with no telemetry, analytics, or phone-home behavior.checked 7 Oct 2026
Deployment
The site documents Docker single-user, Docker multi-user with Postgres, and local single-user setup paths.checked 7 Oct 2026
Installation limit
The site says PyPI installation is not generally available yet and directs users to install from a repository checkout.checked 7 Oct 2026
Integrations
The site lists hosted model providers including OpenAI, Anthropic, Google, Cohere, DeepSeek, Groq, Mistral, OpenRouter, HuggingFace, and Qwen, plus local options including Ollama, vLLM, and llama.cpp.checked 7 Oct 2026
Model integrations
It supports hosted model providers including OpenAI, Anthropic, Google, Cohere, Groq, Mistral, and OpenRouter, as well as local options such as Ollama, llama.cpp, and vLLM.checked 7 Oct 2026
Models
It supports local inference, hosted model APIs, or both through one interface.checked 7 Oct 2026
Privacy
The site says data stays on infrastructure users control and that tldw has no telemetry, analytics, or phone-home behavior.checked 7 Oct 2026
Project status
The site labels the current release v0.1.31 beta and says it is usable now for people comfortable with a beta project.checked 7 Oct 2026
Purpose
tldw is an open-source, self-hosted research system for ingesting, transcribing, searching, and querying source material.checked 7 Oct 2026
Search
Hybrid retrieval searches across transcripts, notes, and documents using full-text search, vectors, and reranking.checked 7 Oct 2026
Security
The v0.1.31 release notes describe hardening for authentication and authorization, outbound scraping policy, audit durability, and workspace-bounded MCP command execution.checked 7 Oct 2026
Study tools
The v0.1.31 beta includes Study Packs, flashcard templates, study suggestions, and a recipe-based evaluation framework.checked 7 Oct 2026
Support and community
The site directs users to Discord and Zulip for community discussion and help.checked 7 Oct 2026
Supported content
It accepts video, audio, PDFs, web pages, EPUB, DOCX, Markdown, XML, and other inputs.checked 7 Oct 2026
Supported inputs
It accepts video, audio, PDFs, web pages, EPUB, DOCX, Markdown, XML, and other formats.checked 7 Oct 2026
Transcription
It converts recordings into searchable text that can be quoted, summarized, and reused.checked 7 Oct 2026
Transcription and retrieval
It turns recordings into searchable text and uses hybrid retrieval across transcripts, notes, and documents.checked 7 Oct 2026
Workspace
Notes, prompts, chats, artifacts, and source material can live in the same system.checked 7 Oct 2026
Workspace features
It includes notes, prompts, chatbooks, study packs, flashcard templates, study suggestions, and evaluation workflows.checked 7 Oct 2026

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