Orchestration

Learn how orchestration is handled inside R2R

Introduction to orchestration

R2R uses Hatchet for orchestrating complex workflows, particularly for ingestion and knowledge graph construction processes.

Hatchet is a distributed, fault-tolerant task queue that solves scaling problems like concurrency, fairness, and rate limiting. It allows R2R to distribute functions between workers with minimal configuration.

Key Concepts

1. Workflows: Sets of functions executed in response to external triggers.
2. Workers: Long-running processes that execute workflow functions.
3. Managed Queue: Low-latency queue for handling real-time tasks.

Orchestration in R2R

Benefits of orchestration

1. Scalability: Efficiently handles large-scale tasks.
2. Fault Tolerance: Built-in retry mechanisms and error handling.
3. Flexibility: Easy to add or modify workflows as R2R’s capabilities expand.

Workflows in R2R

1. IngestFilesWorkflow: Handles file ingestion, parsing, chunking, and embedding.
2. UpdateFilesWorkflow: Manages the process of updating existing files.
3. KgExtractAndStoreWorkflow: Extracts and stores knowledge graph information.
4. CreateGraphWorkflow: Orchestrates the creation of knowledge graphs.
5. EnrichGraphWorkflow: Handles graph enrichment processes like node creation and clustering.

Orchestration GUI

By default, the R2R Docker ships with with Hatchet’s front-end application on port 7274. This can be accessed by navigating to http://localhost:7274.

You may login with the following credentials:

Email: [e-mail]

Password: Admin123!!

Login

Running Tasks

The panel below shows the state of the Hatchet workflow panel at http://localhost:7274/workflow-runs immediately after calling r2r ingest-sample-files:

Inspecting a workflow

You can inspect a workflow within Hatchet and can even attempt to retry the job from directly in the GUI in the case of failure:

Long running tasks

Hatchet supports long running tasks, which is very useful during knowledge graph construction:

Coming Soon

In the coming day(s) / week(s) we will further highlight the available feature set and best practices for orchestrating your ingestion workflows inside R2R.