Deep Dive
Build Paths
- Studio (No-code Interface)
- Lyzr Developer API (Programmatic Access)
Tools
- Studio
- API Endpoints
RAG
Orchestration
Manager Agent
API Endpoints
Create RAG Configuration
Creates a new RAG configuration using LLM, embedding, and vector store credentials.
POST
/
rag
curl --request POST \
--url https://rag-dev.test.studio.lyzr.ai/v3/rag/ \
--header 'Content-Type: application/json' \
--header 'x-api-key: <api-key>' \
--data '{
"user_id": "<string>",
"llm_credential_id": "<string>",
"embedding_credential_id": "<string>",
"vector_db_credential_id": "<string>",
"description": "",
"collection_name": "<string>",
"llm_model": "<string>",
"embedding_model": "<string>",
"vector_store_provider": "<string>",
"semantic_data_model": false,
"meta_data": {}
}'
{
"id": "<string>",
"user_id": "<string>",
"llm_credential_id": "<string>",
"embedding_credential_id": "<string>",
"vector_db_credential_id": "<string>",
"description": "<string>",
"collection_name": "<string>",
"llm_model": "<string>",
"embedding_model": "<string>",
"vector_store_provider": "<string>",
"semantic_data_model": true,
"meta_data": {}
}
Endpoint
POST /v3/rag/
Authentication
API Key (x-api-key
) must be included in the header.
Request Body (JSON)
{
"user_id": "string",
"llm_credential_id": "string",
"embedding_credential_id": "string",
"vector_db_credential_id": "string",
"description": "",
"collection_name": "string",
"llm_model": "string",
"embedding_model": "string",
"vector_store_provider": "string",
"semantic_data_model": false,
"meta_data": {}
}
Curl Request
curl -X POST "https://rag-dev.test.studio.lyzr.ai/v3/rag/" ^
-H "accept: application/json" ^
-H "content-type: application/json" ^
-H "x-api-key: sk-default-REDACTED" ^
-d "{
\"user_id\": \"string\",
\"llm_credential_id\": \"string\",
\"embedding_credential_id\": \"string\",
\"vector_db_credential_id\": \"string\",
\"description\": \"\",
\"collection_name\": \"string\",
\"llm_model\": \"string\",
\"embedding_model\": \"string\",
\"vector_store_provider\": \"string\",
\"semantic_data_model\": false,
\"meta_data\": {}
}"
Response Example
{
"id": "string",
"user_id": "string",
"llm_credential_id": "string",
"embedding_credential_id": "string",
"vector_db_credential_id": "string",
"description": "",
"collection_name": "string",
"llm_model": "string",
"embedding_model": "string",
"vector_store_provider": "string",
"semantic_data_model": false,
"meta_data": {}
}
Error Response (422 Validation Error)
{
"detail": [
{
"loc": [
"string",
0
],
"msg": "string",
"type": "string"
}
]
}
Authorizations
Body
application/json
Response
200
application/json
Successful Response
The response is of type object
.
curl --request POST \
--url https://rag-dev.test.studio.lyzr.ai/v3/rag/ \
--header 'Content-Type: application/json' \
--header 'x-api-key: <api-key>' \
--data '{
"user_id": "<string>",
"llm_credential_id": "<string>",
"embedding_credential_id": "<string>",
"vector_db_credential_id": "<string>",
"description": "",
"collection_name": "<string>",
"llm_model": "<string>",
"embedding_model": "<string>",
"vector_store_provider": "<string>",
"semantic_data_model": false,
"meta_data": {}
}'
{
"id": "<string>",
"user_id": "<string>",
"llm_credential_id": "<string>",
"embedding_credential_id": "<string>",
"vector_db_credential_id": "<string>",
"description": "<string>",
"collection_name": "<string>",
"llm_model": "<string>",
"embedding_model": "<string>",
"vector_store_provider": "<string>",
"semantic_data_model": true,
"meta_data": {}
}
Assistant
Responses are generated using AI and may contain mistakes.