250 lines
11 KiB
Python
250 lines
11 KiB
Python
import pytest
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from fastapi import HTTPException
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from jira_webhook_llm import app
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from llm.models import JiraWebhookPayload
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from database.crud import create_analysis_record, get_analysis_by_id
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from database.models import JiraAnalysis
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from database.database import get_db
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from database.models import JiraAnalysis
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from database.crud import create_analysis_record, update_record_status, get_analysis_by_id
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from unittest.mock import MagicMock # Import MagicMock
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from datetime import datetime, timezone
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def test_error_handling_middleware(test_client, mock_jira_payload):
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# Test 404 error handling
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response = test_client.post("/nonexistent-endpoint", json={})
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assert response.status_code == 404
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assert "detail" in response.json() # FastAPI's default 404 response uses "detail"
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# Test validation error handling
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invalid_payload = mock_jira_payload.copy()
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invalid_payload.pop("issueKey")
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response = test_client.post("/api/jira-webhook", json=invalid_payload)
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assert response.status_code == 422
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assert "detail" in response.json() # FastAPI's default 422 response uses "detail"
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def test_webhook_handler(setup_db, test_client, mock_full_jira_payload, monkeypatch):
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# Mock the LLM analysis chain to avoid external calls
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mock_chain = MagicMock()
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mock_chain.ainvoke.return_value = { # Use ainvoke as per webhooks/handlers.py
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"hasMultipleEscalations": False,
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"customerSentiment": "neutral",
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"analysisSummary": "Mock analysis summary.",
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"actionableItems": ["Mock action item 1", "Mock action item 2"],
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"analysisFlags": ["mock_flag"]
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}
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monkeypatch.setattr("llm.chains.analysis_chain", mock_chain)
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# Test successful webhook handling with full payload
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response = test_client.post("/api/jira-webhook", json=mock_full_jira_payload)
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assert response.status_code == 202
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response_data = response.json()
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assert "status" in response_data
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assert response_data["status"] in ["success", "skipped", "queued"]
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if response_data["status"] == "success":
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assert "analysis_flags" in response_data
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# Validate database storage
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from database.models import JiraAnalysis
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from database.database import get_db
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with get_db() as db:
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record = db.query(JiraAnalysis).filter_by(issue_key=mock_full_jira_payload["issueKey"]).first()
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assert record is not None
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assert record.issue_summary == mock_full_jira_payload["summary"]
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assert record.request_payload == mock_full_jira_payload
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def test_llm_test_endpoint(test_client):
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# Test LLM test endpoint
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response = test_client.post("/api/test-llm")
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assert response.status_code == 200
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assert "response" in response.json()
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def test_create_analysis_record_endpoint(setup_db, test_client, mock_full_jira_payload):
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# Test successful creation of a new analysis record via API
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response = test_client.post("/api/request", json=mock_full_jira_payload)
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assert response.status_code == 201
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response_data = response.json()
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assert "message" in response_data
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assert response_data["message"] == "Record created successfully"
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assert "record_id" in response_data
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# Verify the record exists in the database
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with get_db() as db:
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record = get_analysis_by_id(db, response_data["record_id"])
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assert record is not None
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assert record.issue_key == mock_full_jira_payload["issueKey"]
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assert record.issue_summary == mock_full_jira_payload["summary"]
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assert record.request_payload == mock_full_jira_payload
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@pytest.mark.asyncio
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async def test_retry_decorator():
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# Test retry decorator functionality
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from jira_webhook_llm import retry # Import decorator from main module
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@retry(max_retries=3) # Use imported decorator
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async def failing_function():
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raise Exception("Test error")
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with pytest.raises(Exception):
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await failing_function()
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def test_get_pending_queue_records_endpoint(setup_db, test_client, mock_full_jira_payload):
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# Create a pending record
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with get_db() as db:
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payload_model = JiraWebhookPayload(**mock_full_jira_payload)
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pending_record = create_analysis_record(db, payload_model)
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db.commit()
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db.refresh(pending_record)
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response = test_client.get("/api/queue/pending")
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assert response.status_code == 200, f"Expected 200 but got {response.status_code}. Response: {response.text}"
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data = response.json()["data"]
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assert len(data) == 1
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assert data[0]["issue_key"] == mock_full_jira_payload["issueKey"]
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assert data[0]["status"] == "pending"
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def test_get_pending_queue_records_endpoint_empty(setup_db, test_client):
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# Ensure no records exist
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with get_db() as db:
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db.query(JiraAnalysis).delete()
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db.commit()
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response = test_client.get("/api/queue/pending")
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assert response.status_code == 200
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data = response.json()["data"]
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assert len(data) == 0
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def test_get_pending_queue_records_endpoint_error(test_client, monkeypatch):
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def mock_get_pending_analysis_records(db):
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raise Exception("Database error")
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monkeypatch.setattr("api.handlers.get_pending_analysis_records", mock_get_pending_analysis_records)
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response = test_client.get("/api/queue/pending")
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assert response.status_code == 500, f"Expected 500 but got {response.status_code}. Response: {response.text}"
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assert "detail" in response.json() # FastAPI's HTTPException uses "detail"
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assert response.json()["detail"] == "Database error: Database error"
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def test_retry_analysis_record_endpoint_success(setup_db, test_client, mock_full_jira_payload):
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# Create a failed record
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with get_db() as db:
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payload_model = JiraWebhookPayload(**mock_full_jira_payload)
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failed_record = create_analysis_record(db, payload_model)
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update_record_status(db, failed_record.id, "failed", error_message="LLM failed")
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db.commit()
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db.refresh(failed_record)
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response = test_client.post(f"/api/queue/{failed_record.id}/retry")
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assert response.status_code == 200
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assert response.json()["message"] == f"Record {failed_record.id} marked for retry."
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with get_db() as db:
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updated_record = get_analysis_by_id(db, failed_record.id)
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assert updated_record.status == "pending"
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assert updated_record.error_message is None
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assert updated_record.analysis_result is None
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assert updated_record.raw_response is None
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assert updated_record.next_retry_at is None
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def test_retry_analysis_record_endpoint_not_found(test_client):
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response = test_client.post("/api/queue/99999/retry")
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assert response.status_code == 404
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# Handle both possible error response formats
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assert "detail" in response.json() # FastAPI's HTTPException uses "detail"
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assert response.json()["detail"] == "Analysis record not found"
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def test_retry_analysis_record_endpoint_invalid_status(setup_db, test_client, mock_full_jira_payload):
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# Create a successful record
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with get_db() as db:
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payload_model = JiraWebhookPayload(**mock_full_jira_payload)
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successful_record = create_analysis_record(db, payload_model)
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update_record_status(db, successful_record.id, "success")
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db.commit()
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db.refresh(successful_record)
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response = test_client.post(f"/api/queue/{successful_record.id}/retry")
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assert response.status_code == 400
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assert response.json()["detail"] == f"Record status is 'success'. Only 'failed', 'processing' or 'validation_failed' records can be retried."
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def test_retry_analysis_record_endpoint_db_update_failure(setup_db, test_client, mock_full_jira_payload, monkeypatch):
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# Create a failed record
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with get_db() as db:
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payload_model = JiraWebhookPayload(**mock_full_jira_payload)
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failed_record = create_analysis_record(db, payload_model)
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update_record_status(db, failed_record.id, "failed", error_message="LLM failed")
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db.commit()
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db.refresh(failed_record)
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def mock_update_record_status(*args, **kwargs):
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return None # Simulate update failure
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monkeypatch.setattr("api.handlers.update_record_status", mock_update_record_status)
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response = test_client.post(f"/api/queue/{failed_record.id}/retry")
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assert response.status_code == 500, f"Expected 500 but got {response.status_code}. Response: {response.text}"
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assert response.json()["detail"] == "Failed to update record for retry."
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def test_retry_analysis_record_endpoint_retry_count_and_next_retry_at(setup_db, test_client, mock_full_jira_payload):
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# Create a failed record with an initial retry count and next_retry_at
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with get_db() as db:
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payload_model = JiraWebhookPayload(**mock_full_jira_payload)
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failed_record = create_analysis_record(db, payload_model)
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update_record_status(
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db,
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failed_record.id,
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"failed",
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error_message="LLM failed",
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retry_count_increment=1,
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next_retry_at=datetime.now(timezone.utc)
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)
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db.commit()
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db.refresh(failed_record)
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initial_retry_count = failed_record.retry_count
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response = test_client.post(f"/api/queue/{failed_record.id}/retry")
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assert response.status_code == 200
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with get_db() as db:
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updated_record = get_analysis_by_id(db, failed_record.id)
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assert updated_record.status == "pending"
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assert updated_record.error_message is None
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assert updated_record.next_retry_at is None # Should be reset to None
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# The retry endpoint itself doesn't increment retry_count,
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# it just resets the status. The increment happens during processing.
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# So, we assert it remains the same as before the retry request.
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assert updated_record.retry_count == initial_retry_count
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@pytest.mark.asyncio
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async def test_concurrent_retry_operations(setup_db, test_client, mock_full_jira_payload):
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# Create multiple failed records
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record_ids = []
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with get_db() as db:
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for i in range(5):
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payload = mock_full_jira_payload.copy()
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payload["issueKey"] = f"TEST-{i}"
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payload_model = JiraWebhookPayload(**payload)
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failed_record = create_analysis_record(db, payload_model)
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update_record_status(db, failed_record.id, "failed", error_message=f"LLM failed {i}")
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db.commit()
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db.refresh(failed_record)
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record_ids.append(failed_record.id)
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# Simulate concurrent retry requests
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import asyncio
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async def send_retry_request(record_id):
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return test_client.post(f"/api/queue/{record_id}/retry")
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tasks = [send_retry_request(rid) for rid in record_ids]
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responses = await asyncio.gather(*tasks)
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for response in responses:
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assert response.status_code == 200
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assert "message" in response.json()
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# Verify all records are marked as pending
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with get_db() as db:
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for record_id in record_ids:
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updated_record = get_analysis_by_id(db, record_id)
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assert updated_record.status == "pending"
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assert updated_record.error_message is None
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assert updated_record.next_retry_at is None |