hermes

Connect Hermes to Weaviate

Give an AI agent your Weaviate cluster as a tool and it can build and query a knowledge base on its own while it works. It can create collections, insert and index documents, run hybrid and vector searches, and call Generative Search to answer questions over what it just stored, each one an operation it invokes when it needs it. Instead of asking you to look something up, the agent retrieves the right context itself and acts on it.

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Opens a workflow with 14 tools ready to use.

Tools Hermes gets

Pick the operations you want and each becomes a tool the agent can call directly while it works.

Weaviate

14 tools
Query / Search

Vector similarity search (GraphQL nearVector).

Query by Text

Semantic search by text (GraphQL nearText — requires the class to have a text2vec vectorizer module).

Hybrid Search

Hybrid BM25 + vector search (GraphQL hybrid).

Generative Search (RAG)

Generative search (RAG): retrieve objects then generate text with an LLM (GraphQL generate). The collection must have a generative module configured in its schema (e.g. generative-openai, generative-anthropic, generative-cohere). Pass the corresponding API key in the credential. Provide single_prompt, group_task, or both.

Aggregate

Aggregate statistics over a collection (GraphQL Aggregate — count, mean, topOccurrences, etc.).

Insert Object

Insert an object (REST).

Get Object

Get an object by ID (REST).

Update Object

Partial update (PATCH /v1/objects/{class}/{id}) — merges provided fields.

Delete Object

Delete an object by ID (REST).

List Collections

List collections (schema classes).

Create Collection

Create a collection (schema class).

Delete Collection

Drop a collection and ALL of its objects — permanent.

Batch Delete Objects

Batch-delete objects matching a where filter (up to 10,000 per call).

Upload & Index Document

Upload a document file, chunk + embed it, and batch-insert objects.

What you can build

When a new document lands in your storage, upload and index it into Weaviate so it becomes searchable within seconds.
Answer support questions automatically by running Generative Search over a collection of past tickets and product docs.
On a schedule, aggregate the objects in a collection to track how your indexed dataset is growing over time.
Take an inbound question, run a hybrid search to pull the most relevant objects, then feed them to an AI step for a grounded reply.
Keep records current by updating existing objects when their source changes and batch-deleting ones that are pulled or expired.
Spin up a fresh collection, insert a batch of objects, and query it by text in one automated pipeline.

About Hermes

Hermes is an open agent built on Nous Research’s Hermes models. NoClick runs it hosted and connects your apps to it as tools, so it can do real work across your systems. Wire an integration into the agent and Hermes can use that app’s operations directly while it reasons through a task. It is a strong pick when you want an open-model agent with genuine tool access.

Built on open Hermes models
Capable general reasoning
Flexible, open-model foundation
Hosted with apps wired in as tools

Frequently asked questions

Build a custom Hermes agentWeaviate integration

Open your Hermes agent in one click

NoClick runs Hermes for you with Weaviate wired in as tools. Connect your account and run.