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POST
/
api
/
v1
/
knowledge-engines
/
{id}
/
query
Query Knowledge Engine
curl --request POST \
  --url https://api.getdecisional.ai/api/v1/knowledge-engines/{id}/query \
  --header 'Authorization: Basic <encoded-value>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "query": "<string>",
  "name": "<string>",
  "advanced_reasoning": true,
  "model": "llama-v3-70b",
  "context_id": "<string>"
}
'
"<string>"
Query a knowledge engine with a natural language question. This endpoint uses Server-Sent Events (SSE) to stream the response back to the client.

​
Request Format

​
query
string
required
The natural language query to ask the knowledge engine
​
name
string
required
A name for this query workflow
​
context_id
string
Context ID used in case of thread mode for chat based workflows
​
advanced_reasoning
boolean
Flag to enable advanced reasoning for the query
​
model
string
The model to use for the query

​
Example Request

{
  "query": "What were the company's revenue figures for 2023?",
  "name": "Revenue Analysis",
  "advanced_reasoning": true,
  "model": "llama-v3-70b"
}

​
Response Format

The response is streamed using Server-Sent Events (SSE) with the following event types:
  • message: Contains intermediate response chunks as they are generated
  • error: Contains error messages if something goes wrong
  • done: Final event containing the complete response with metadata

​
Example Response Stream

// Intermediate messages
event: message
data: "Based on the available information, "
event: message
data: "the company's revenue in 2023 was "
event: message
data: "$1.2 billion, representing a 15% increase from 2022."
// Final response with complete result
event: done
data: {
"id": "wf_abc123xyz789",
"name": "Revenue Analysis",
"query": "What were the company's revenue figures for 2023?",
"type": "query",
"knowledge_engine_id": "kng_abc123xyz789",
"status": "processed",
"response": "Based on the available information, the company's revenue in 2023 was $1.2 billion, representing a 15% increase from 2022.",
"citations": [
{
"text": "In fiscal year 2023, total revenue reached $1.2B, up 15% YoY",
"source": "Annual Report 2023",
"page": 45
}
],
"created_at": 1679644800
}

​
Notes

  • The streaming response allows for real-time display of the AI’s response as it’s being generated
  • The final done event includes the complete response along with metadata and citations
  • If an error occurs, the stream will emit an error event and close the connection
  • Clients should handle connection closure appropriately using the close event
The streaming response requires a client that supports Server-Sent Events (SSE). Most modern browsers and HTTP clients support this feature.

​
Response Object

​
id
string
Unique identifier for the workflow
​
name
string
Name of the workflow
​
query
string
The original query that was asked
​
type
string
Type of workflow (always “query”)
​
knowledge_engine_id
string
ID of the knowledge engine that was queried
​
status
string
Status of the workflow (“processed” when complete)
​
response
string
The complete response text
​
citations
array
Array of citations supporting the response
​
created_at
number
Unix timestamp when the workflow was created

Authorizations

​
Authorization
string
header
required

Basic authentication header of the form Basic <encoded-value>, where <encoded-value> is the base64-encoded string username:password.

Path Parameters

​
id
string
required

Knowledge engine ID

Body

application/json
​
query
string
required

The natural language query

​
name
string
required

Name of the workflow

​
advanced_reasoning
boolean

Enable advanced reasoning

​
model
enum<string>

LLM to use for the query

Available options:
auto,
claude-3.5-sonnet,
llama-v3-70b,
o1,
o3-mini,
gpt-4o,
gpt-5
Example:

"llama-v3-70b"

​
context_id
string

Context ID for maintaining conversation history in chat mode

Response

Streaming response using Server-Sent Events

The response is of type string.