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Brain

Overview

Knowledge graph visualization endpoints

Available Operations

perform_visualization

Trigger unified graph rendering. Supports legacy connection_id and preferred connection_ids. If no connections are provided, returns the base Neo4j schema. Discovers external relationships between connections when enabled.

Example Usage

from fermisdk import Fermisdk
import os


with Fermisdk(
    bearer_auth=os.getenv("FERMISDK_BEARER_AUTH", ""),
) as f_client:

    res = f_client.brain.perform_visualization(action="visualization", discover_external_relationships=True, confidence_threshold="high", response_format="html")

    # Handle response
    print(res)

Parameters

Parameter Type Required Description
action models.VisualizationRequestAction :heavy_check_mark: Must be 'visualization'
connection_ids List[str] :heavy_minus_sign: Multiple connections to merge (preferred)
connection_id Optional[str] :heavy_minus_sign: Legacy single-connection input
discover_external_relationships Optional[bool] :heavy_minus_sign: Enable LLM-based cross-connection edges
confidence_threshold Optional[models.ConfidenceThreshold] :heavy_minus_sign: Confidence level for external relationship filtering
response_format Optional[models.ResponseFormat] :heavy_minus_sign: Response format: 'html' returns PyVis HTML, 'json' returns MongoDB schema-style JSON
retries Optional[utils.RetryConfig] :heavy_minus_sign: Configuration to override the default retry behavior of the client.

Response

models.PerformVisualizationResponse

Errors

Error Type Status Code Content Type
errors.Error 400, 404 application/json
errors.Error 500 application/json
errors.FermisdkDefaultError 4XX, 5XX */*