Vector Embeddings Tools — Pinecone & Qdrant Integration
Langoedge Team2 min read
What are the Vector Embeddings Tools?
To support advanced Retrieval-Augmented Generation (RAG) and semantic databases, Langoedge provides native embedding tools for Qdrant and Pinecone.
These tools convert unstructured text strings (like chat logs, user queries, or document paragraphs) into high-dimensional vector representations using your graph's configured embedding models (e.g. OpenAI's text-embedding-3-small).
**Prerequisite: Active Database Connection Required**
Before your AI agents can read or write vector embeddings, you **must** connect your Pinecone or Qdrant keys on the **[Connect Page](https://app.langoedge.com/connect)**.
Without active credential connections established, vector embedding operations will fail to compile or execute at runtime.
Available Embedding Tools
1. Qdrant Embeddings (create_qdrant_embedding)
Generates text vector representations and inserts them into your Qdrant collections.
| Parameter | Type | Required | Description |
|---|---|---|---|
text |
string |
Yes | The source text string to embed. |
collection_name |
string |
Yes | Target collection name inside your Qdrant instance. |
2. Pinecone Embeddings (create_pinecone_embedding)
Generates text vector representations and inserts them into your Pinecone indices.
| Parameter | Type | Required | Description |
|---|---|---|---|
text |
string |
Yes | The source text string to embed. |
index_name |
string |
Yes | Target index name inside your Pinecone instance. |
Frequently Asked Questions
What embedding model is used by these tools?
The tools automatically invoke the model configured as the graph's default embedding model (e.g. `text-embedding-ada-002` or `text-embedding-3-small`).
Do I need to configure collections beforehand?
Yes. Ensure that the collection name or index name matches an existing index in your Qdrant or Pinecone deployments, and that you have authorized connection credentials on the **[Connect Page](https://app.langoedge.com/connect)**.