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Topic Stream

A personal reading stream inside Obsidian, shaped by the sources and topics you choose.

Topic Stream brings articles, papers, videos, and repositories into one place. Describe what you want to follow, read a focused Feed, and use feedback to improve future recommendations. The server runs on your own machine. The current Obsidian plugin provides an early Feed view; the backend exposes the broader reading and retrieval capabilities through its API.

What you can do

In the current plugin you can create Topics, request Sync all, browse already-published Feed history, open original links, and give Like/Dislike feedback with optional comments. Its Source form still sends the old request shape; create Sources through the backend API using the guide. Its Refresh button rereads saved history. To publish recommendations, use the backend Feed Refresh API.

The backend also supports arXiv, GitHub Trending and YouTube Sources, Topic corrections, archive Search, cleaned content and image delivery, explicit Item AI summaries, and scheduled Digests. Search, Reader, Digest, Task Center and AI-summary controls are not yet available in the plugin. The plugin does not yet write Vault Snapshots. See the current Obsidian capabilities.

Get started

You need Docker with Compose v2, mise, Obsidian, and a running local OpenAI-compatible embedding service. Building the plugin also requires Node.js and pnpm. The server stack includes PostgreSQL and Qdrant; AI models are managed separately.

  1. Clone this repository and copy .env.example to .env.

  2. Set a stable UUIDv4 Workspace ID and the embedding endpoint, model, and dimensions. For a provider on your Docker host, use http://host.docker.internal:11434/v1 rather than localhost.

  3. Start the server stack:

    mise run up

    The generated .env defaults to the public latest backend image. To run the current checkout instead, build and select the local image explicitly:

    mise run image-build
    TOPIC_STREAM_BACKEND_IMAGE=topic-stream:local mise run up
  4. Build and install the Obsidian plugin, connect to http://127.0.0.1:7331, and follow the first Feed steps, including API publication.

The getting started guide walks through configuration, model setup, and your first Feed. The default deployment exposes the API only on localhost; it has no built-in authentication.

Learn more

MIT license.

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