Skip to content

API Reference

Complete API documentation for DeepFix SDK, Server, and Core components.

Overview

The DeepFix API is organized into three main components:

  1. SDK API: Client library for interacting with DeepFix server
  2. Server API: REST API endpoints for analysis
  3. Core API: Shared data models and types

API Components

SDK API

The DeepFix SDK provides a Python client for interacting with the DeepFix server.

Main Components: - DeepFixClient: Main client class for analysis requests - MLflowConfig: Configuration for MLflow integration - ArtifactConfig: Configuration for artifact loading - Dataset classes: ImageClassificationDataset, TabularDataset, NLPDataset

Location: deepfix-sdk/src/deepfix_sdk/

SDK Reference →

Server API

The DeepFix Server provides REST API endpoints for artifact analysis.

Main Components: - AnalyseArtifactsAPI: Main API endpoint for analysis - ArtifactAnalysisCoordinator: Coordinates agent execution - Agent classes: Specialized analyzers for different artifact types

Location: deepfix-server/src/deepfix_server/

Server Reference →

Core API

DeepFix Core provides shared data models and types used across components.

Main Components: - APIRequest: Request model for analysis - APIResponse: Response model for analysis results - AgentResult: Agent analysis results - Artifact models: Dataset, Deepchecks, Model Checkpoint, Training

Location: deepfix-core/src/deepfix_core/

Core Reference →

Usage Examples

SDK Usage

from deepfix_sdk.client import DeepFixClient
from deepfix_sdk.config import MLflowConfig

# Initialize client
client = DeepFixClient(api_url="http://localhost:8844")

# Diagnose dataset
result = client.diagnose_dataset(dataset_name="my-dataset")
print(result.to_text())

Server Usage

# Server runs via CLI
uv run deepfix-server launch -e .env -port 8844

Core Models

from deepfix_core.models import APIRequest, APIResponse

# Create request
request = APIRequest(
    dataset_name="my-dataset",
    dataset_artifacts={...},
    language="english"
)

# Process response
response: APIResponse = analyze(request)
print(response.summary)