Gemini Embedding 001
by Google
Google high-dimensional embedding model optimized for semantic search and Retrieval-Augmented Generation (RAG).
Run queries immediately, pay only for usage
Per 1M Tokens
About this model
Google high-dimensional embedding model optimized for semantic search and Retrieval-Augmented Generation (RAG).
Capabilities
Model Details
- Provider
- Model ID
- gemini-embedding-001
- Parameters
- Embedding
- Context Length
- 2K tokens
- Category
- embedding
API Usage
Use the DOS API to integrate Gemini Embedding 001 into your applications. Our API is compatible with OpenAI's client libraries for easy migration.
Model ID
gemini-embedding-001Python
from dos import DOS
client = DOS()
response = client.chat.completions.create(
model="gemini-embedding-001",
messages=[
{"role": "user", "content": "Hello, how are you?"}
]
)
print(response.choices[0].message.content)cURL
curl https://api.dos.ai/v1/chat/completions \
-H "Authorization: Bearer $DOS_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gemini-embedding-001",
"messages": [
{"role": "user", "content": "Hello, how are you?"}
]
}'Node.js
import DOS from 'dos-ai';
const client = new DOS();
const response = await client.chat.completions.create({
model: "gemini-embedding-001",
messages: [
{ role: "user", content: "Hello, how are you?" }
]
});
console.log(response.choices[0].message.content);Related Models
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