DeepSeek Agent integration

What the DeepSeek Agent package does

DeepSeek Harness agent running in-process on a pure-Go JS engine - no Node.js, no runtime downloads. Compose the agent from harness plugins and wire Robomotion nodes in as tools.

Namespace

Robomotion.DeepSeekAgent

Latest version

0.9.0 (6 versions published)

Written in

Go

Categories

Artificial Intelligence

DeepSeek Agent nodes (12)

These are the node IDs an agentic flow or an RPA bot uses, exactly as they appear in the Flow Designer and in flow code.

Platforms

The DeepSeek Agent package runs on Windows, macOS and Linux robots. Any Robomotion robot on these operating systems can run a flow that uses it.

How to install the DeepSeek Agent package

1. Open Packages in the Robomotion Flow Designer.
2. Search for DeepSeek Agent or Robomotion.DeepSeekAgent, then click Install on its card.
3. The DeepSeek Agent nodes appear in the node palette for everyone in the workspace, because installation is per workspace.

From a terminal, the Robomotion CLI installs the same package:

robomotion install Robomotion.DeepSeekAgent

Templates that use DeepSeek Agent

3 ready-made templates use DeepSeek Agent nodes in their flows. Open one to start from a working flow.

• Website Pitch Builder

  Finds a shop that has no website and builds it one. Google Maps is searched through the scrape.do API, the listings are filtered down to businesses with a phone, enough reviews to prove they have customers, and no real site of their own - a Facebook page or a Wix subdomain counts as no site - and the best one is scored out. Its opening hours, ten best reviews and four public domain photographs are gathered, and a DeepSeek Agent writes a single self-contained page from that brief and nothing else. A real browser then photographs the page, and the screenshot and a CSV row are mailed to you. Google Maps has no email column, so the packet comes to you with the shop's phone number in it, and a person makes the call.

• RAG with DeepSeek

  Retrieval-augmented generation over your own documents, with the retrieval handed to the agent instead of done for it. Documents are read, chunked, embedded and stored in LanceDB - an embedded vector database that is just a directory on disk. A DeepSeek Agent then answers questions through a search_knowledge tool built from ordinary flow nodes, writing its own queries and searching as many times as a question needs, with the source document named against every fact.

• Self-Learning Invoice Agent

  An invoice-processing DeepSeek Agent that teaches itself vendors. The first invoice from a supplier is worked out from scratch and the procedure is written down as a learned skill in the agent's memory; every invoice after runs on what it learned. Extracted fields are recorded to a CSV ledger through a Tool In / Tool Out pair, and memory syncs to the workspace so a whole fleet can run what one robot learned.

Related integrations

Packages that share a category or keywords with DeepSeek Agent. It is filed under Artificial Intelligence.

• DSPyConnect to self-hosted DSPy servers for predictions, chain-of-thought reasoning, and ReAct agents
• Hermes AgentSelf-improving Hermes Agent (Nous Research) with skills, sessions, MCP, and visual tool wiring
• OllamaOllama package is for interacting with advanced machine learning models, supporting a wide range of operations including text generation, chat completion, model management, and multimodal functionalities.
• OpenRouterOpenRouter integration with text generation, chat completions, image generation, speech generation, reasoning mode, and streaming support. Access 480+ AI models (Gemini, Claude, GPT, Grok, DeepSeek, Flux) through a unified API with simplified outputs, plus fast decision models (TypeSafe jev) for classifying and scoring at scale.
• PerplexityConnect to Perplexity AI for AI-powered search and chat completions with real-time web data
• QolabaAI-driven platform for chat, image generation, and speech synthesis with 30+ models