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Agent Memory & RAG

Synix

Synix is a Python command-line tool for defining and building agent-memory pipelines from source data. It can produce episode summaries, grouped rollups, core memory documents and full-text search indexes, then release memory snapshots for agents to query or load as context.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Synix — OpenViST project profile in Agent Memory & RAG.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use Synix when you want a programmable pipeline for constructing, releasing and searching agent memory, especially when the memory structure may need iteration.

Who it is for

  • Developers building AI agents who need to generate and search structured memory from source data.
  • Teams that want to revise memory prompts, grouping or pipeline layers as their requirements change.

Documented uses

  • Turn source files into episode summaries and higher-level rollups.
  • Compress accumulated memory into a core document for agent context.
  • Release versioned memory snapshots and search their contents.
  • Change pipeline transformations and rebuild affected outputs.
Before you choose

Requirements & limits

The repository is public and licensed under MIT. The documented CLI quick start uses `uvx` and requires an API key for its example LLM-backed pipeline.

  • The starter pipeline uses an LLM to summarize and synthesize source data; its README example configures Anthropic.
  • Synix separates memory building from agent inference: an agent can read or search a released output without Synix running while it serves requests.
  • The README documents both CLI and Python access to released memory, plus separate integration options including a knowledge server and Claude Code plugin.
  • Generic transforms include map, group, reduce, fold and chunk patterns for shaping custom pipelines.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Build, release and search a starter memory

Create a local memory release from source files and run a full-text search against it.

Before you start

  • A project initialized with Synix
  • Source data placed in the project’s ./sources/ directory
  • An API key added to the project’s .env file

Steps

  1. Initialize a project with uvx synix init my-project and change into its directory.

  2. Copy .env.example to .env, add the API key, and add source data under ./sources/.

  3. Run uvx synix build to generate the starter memory pipeline’s outputs.

  4. Release the build with uvx synix release HEAD --to local.

  5. Search the release with uvx synix search "your query" --release local.

Expected outcome

A local release with episode summaries, monthly rollups, a core memory document and full-text search.

Guide limitations

  • The example pipeline uses an LLM provider configured in the project; the README’s example specifies Anthropic.
  • This recipe follows the documented starter pipeline and does not cover changing its transformations.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
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16 October 2026
Original website title
marklubin/synix · Official homepage title · retained in its source language
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