Database
- Indexes
- Namespaces
- Vectors
- Search
- Imports
- Backups
Inference
- Embed
- Rerank
- Models
Admin
- API keys
- Projects
- Service accounts
Architecture
Indexes
Create an index with integrated embedding
Create an index with integrated embedding.
With this type of index, you provide source text, and Pinecone uses a hosted embedding model to convert the text automatically during upsert and search.
For guidance and examples, see Create an index.
POST
/
indexes
/
create-for-model
Copy
PINECONE_API_KEY="YOUR_API_KEY"
curl https://api.pinecone.io/indexes/create-for-model \
-H "Content-Type: application/json" \
-H "Api-Key: $PINECONE_API_KEY" \
-H "X-Pinecone-Api-Version: 2025-10" \
-d '{
"name": "integrated-dense-curl",
"cloud": "aws",
"region": "us-east-1",
"embed": {
"model": "llama-text-embed-v2",
"metric": "cosine",
"field_map": {
"text": "chunk_text"
},
"write_parameters": {
"input_type": "passage",
"truncate": "END"
},
"read_parameters": {
"input_type": "query",
"truncate": "END"
}
}
}'
Copy
{
"id": "9dabb7cb-ec0a-4e2e-b79e-c7c997e592ce",
"name": "integrated-dense-curl",
"metric": "cosine",
"dimension": 1024,
"status": {
"ready": false,
"state": "Initializing"
},
"host": "integrated-dense-curl-govk0nt.svc.aped-4627-b74a.pinecone.io",
"spec": {
"serverless": {
"region": "us-east-1",
"cloud": "aws"
}
},
"deletion_protection": "disabled",
"tags": null,
"embed": {
"model": "llama-text-embed-v2",
"field_map": {
"text": "chunk_text"
},
"dimension": 1024,
"metric": "cosine",
"write_parameters": {
"input_type": "passage",
"truncate": "END"
},
"read_parameters": {
"input_type": "query",
"truncate": "END"
}
}
}
Copy
PINECONE_API_KEY="YOUR_API_KEY"
curl https://api.pinecone.io/indexes/create-for-model \
-H "Content-Type: application/json" \
-H "Api-Key: $PINECONE_API_KEY" \
-H "X-Pinecone-Api-Version: 2025-10" \
-d '{
"name": "integrated-dense-curl",
"cloud": "aws",
"region": "us-east-1",
"embed": {
"model": "llama-text-embed-v2",
"metric": "cosine",
"field_map": {
"text": "chunk_text"
},
"write_parameters": {
"input_type": "passage",
"truncate": "END"
},
"read_parameters": {
"input_type": "query",
"truncate": "END"
}
}
}'
Copy
{
"id": "9dabb7cb-ec0a-4e2e-b79e-c7c997e592ce",
"name": "integrated-dense-curl",
"metric": "cosine",
"dimension": 1024,
"status": {
"ready": false,
"state": "Initializing"
},
"host": "integrated-dense-curl-govk0nt.svc.aped-4627-b74a.pinecone.io",
"spec": {
"serverless": {
"region": "us-east-1",
"cloud": "aws"
}
},
"deletion_protection": "disabled",
"tags": null,
"embed": {
"model": "llama-text-embed-v2",
"field_map": {
"text": "chunk_text"
},
"dimension": 1024,
"metric": "cosine",
"write_parameters": {
"input_type": "passage",
"truncate": "END"
},
"read_parameters": {
"input_type": "query",
"truncate": "END"
}
}
}
Authorizations
Body
application/json
The desired configuration for the index and associated embedding model.
Response
201
application/json
The index has successfully been created for the embedding model.
The IndexModel describes the configuration and status of a Pinecone index.
Was this page helpful?
Copy
PINECONE_API_KEY="YOUR_API_KEY"
curl https://api.pinecone.io/indexes/create-for-model \
-H "Content-Type: application/json" \
-H "Api-Key: $PINECONE_API_KEY" \
-H "X-Pinecone-Api-Version: 2025-10" \
-d '{
"name": "integrated-dense-curl",
"cloud": "aws",
"region": "us-east-1",
"embed": {
"model": "llama-text-embed-v2",
"metric": "cosine",
"field_map": {
"text": "chunk_text"
},
"write_parameters": {
"input_type": "passage",
"truncate": "END"
},
"read_parameters": {
"input_type": "query",
"truncate": "END"
}
}
}'
Copy
{
"id": "9dabb7cb-ec0a-4e2e-b79e-c7c997e592ce",
"name": "integrated-dense-curl",
"metric": "cosine",
"dimension": 1024,
"status": {
"ready": false,
"state": "Initializing"
},
"host": "integrated-dense-curl-govk0nt.svc.aped-4627-b74a.pinecone.io",
"spec": {
"serverless": {
"region": "us-east-1",
"cloud": "aws"
}
},
"deletion_protection": "disabled",
"tags": null,
"embed": {
"model": "llama-text-embed-v2",
"field_map": {
"text": "chunk_text"
},
"dimension": 1024,
"metric": "cosine",
"write_parameters": {
"input_type": "passage",
"truncate": "END"
},
"read_parameters": {
"input_type": "query",
"truncate": "END"
}
}
}
Assistant
Responses are generated using AI and may contain mistakes.