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Testing Chunk Retrieval API Endpoints in private-gpt

This test suite validates the chunk retrieval functionality in the private-gpt repository, focusing on the chunks API endpoint and data retrieval operations. The tests ensure proper handling of text chunk queries and response validation.

Test Coverage Overview

The test coverage focuses on the core chunk retrieval functionality through the /v1/chunks endpoint.

Key areas tested include:

File ingestion for test data preparation
POST request handling with chunk query
Response status code validation
Response data structure verification
Chunk data presence verification

Implementation Analysis

The testing approach utilizes FastAPI’s TestClient for HTTP request simulation and response validation. The implementation follows a fixture-based pattern with the IngestHelper utility for test data setup. The test demonstrates clean separation of concerns between test setup, execution, and validation phases.

Technical patterns include:

Fixture dependency injection
Model-based request/response handling
Path-based file operations
Pydantic model validation

Technical Details

Testing tools and components:

FastAPI TestClient for API testing
Pydantic models (ChunksBody, ChunksResponse)
Path from pathlib for file operations
Custom IngestHelper fixture for data preparation
Python’s built-in assertion framework

Best Practices Demonstrated

The test exemplifies several testing best practices including proper test isolation through fixtures, clear test data setup, and comprehensive response validation. Notable practices include:

Explicit test data preparation
Strong type checking with Pydantic models
Clear assertion patterns
Resource cleanup through fixture management
Focused test scope with single responsibility

zylon-ai/private-gpt

tests/server/chunks/test_chunk_routes.py

            
from pathlib import Path

from fastapi.testclient import TestClient

from private_gpt.server.chunks.chunks_router import ChunksBody, ChunksResponse
from tests.fixtures.ingest_helper import IngestHelper


def test_chunks_retrieval(test_client: TestClient, ingest_helper: IngestHelper) -> None:
    # Make sure there is at least some chunk to query in the database
    path = Path(__file__).parents[0] / "chunk_test.txt"
    ingest_helper.ingest_file(path)

    body = ChunksBody(text="b483dd15-78c4-4d67-b546-21a0d690bf43")
    response = test_client.post("/v1/chunks", json=body.model_dump())
    assert response.status_code == 200
    chunk_response = ChunksResponse.model_validate(response.json())
    assert len(chunk_response.data) > 0