OpenAI Key Request While Using Other Models

Agno defaults to OpenAI for models and embedders. Set both explicitly to remove the OPENAI_API_KEY requirement.

If you see a request for an OpenAI API key but haven’t configured OpenAI, it’s because Agno uses OpenAI by default in two places:

• The default model when Agent has no model set
• The default embedder (OpenAIEmbedder) for vector databases

Quick fix: Configure a Different Model

Specify the model explicitly. Without one, the agent defaults to OpenAIResponses with gpt-5.4, which requires OPENAI_API_KEY.

For example, to use Google’s Gemini instead of OpenAI:

from agno.agent import Agent
from agno.models.google import Gemini

agent = Agent(
    model=Gemini(id="gemini-3.5-flash"),
    markdown=True,
)

# Print the response in the terminal
agent.print_response("Share a 2 sentence horror story.")

See Models for the full provider list.

Quick fix: Configure a Different Embedder

The same applies to embeddings. To use an embedder other than OpenAIEmbedder, configure it explicitly.

For example, to use Google’s Gemini as an embedder, use GeminiEmbedder:

from agno.knowledge.knowledge import Knowledge
from agno.vectordb.pgvector import PgVector
from agno.knowledge.embedder.google import GeminiEmbedder

# Embed a sentence
embeddings = GeminiEmbedder().get_embedding("The quick brown fox jumps over the lazy dog.")

# Print the embeddings and their dimensions
print(f"Embeddings: {embeddings[:5]}")
print(f"Dimensions: {len(embeddings)}")

# Use an embedder in a knowledge base
knowledge = Knowledge(
    vector_db=PgVector(
        db_url="postgresql+psycopg://ai:ai@localhost:5532/ai",
        table_name="gemini_embeddings",
        embedder=GeminiEmbedder(),
    ),
    max_results=2,
)

See Embedders for the available options.