LangDB Embedder

Generate embeddings through a LangDB project endpoint.

LangDBEmbedder routes OpenAI-compatible embedding requests through the project selected by LANGDB_PROJECT_ID.

from os import environ

from agno.knowledge.embedder.langdb import LangDBEmbedder

project_id = environ["LANGDB_PROJECT_ID"]
embedder = LangDBEmbedder(
    base_url=f"https://api.langdb.ai/{project_id}/v1",
)
embedding = embedder.get_embedding(
    "The quick brown fox jumps over the lazy dog."
)

print(f"First values: {embedding[:5]}")
print(f"Dimensions: {len(embedding)}")

The default model is text-embedding-ada-002 with 1536 dimensions. Pass id and dimensions together when selecting another model.

Agno constructs the legacy api.us-east-1.langdb.ai host when base_url is omitted. LangDB's current API guide uses api.langdb.ai. Pass base_url as shown above.

Run the Example

Set up your virtual environment

uv venv --python 3.12
source .venv/bin/activate

Configure the project

export LANGDB_API_KEY=your_langdb_api_key_here
export LANGDB_PROJECT_ID=your_langdb_project_id_here

Install dependencies

uv pip install -U agno openai

Run the example

python langdb_embedder.py

Developer Resources