microsoft-foundry / microsoft-foundry/Model-Router-Auto-Evaluation

[Bug]: Support Foundry OpenAI v1 and Responses API endpoints in live evaluations

Offen
#11 1 Kommentar 0 Reaktionen 0 zugewiesene Personen Auf GitHub ansehen

Dieses Issue hat noch niemand übernommen.

bug
Vorherrschende Sprache
HTML
Sterne
29
Forks
11
Ø Merge
2 Std. 48 Min.
Gemergte PRs (30 T.)
2

Beschreibung

Pre-flight checklist
  • I have searched existing issues and this is not a duplicate.
  • I have read the FAQ.
  • I have removed any API keys, endpoints, or other secrets from logs and config snippets I paste below.
Summary

Live evaluations returned 404 Resource not found for every Model Router and baseline request, despite valid keys and deployments.

The repository configured all endpoints using AsyncAzureOpenAI and hard-coded chat.completions.create(). However, current Foundry endpoints use the OpenAI v1 format: https://<resource>.services.ai.azure.com/openai/v1

Model Router uses /chat/completions, while some baseline and judge deployments use /responses. Supplying the full portal Target URI did not work because the SDK appended another operation path. Removing part of the resource hostname caused APIConnectionError because the resulting hostname did not exist.

A secondary error occurred after all requests failed: AttributeError: 'NoneType' object has no attribute 'get'

The verifier assumed cost and latency metrics were dictionaries, but all-error runs serialize them as null.

I used GitHub Copilot to resolve the issue and I'm sharing it's summarized proposed fix below:

  1. Add an endpoint api_mode setting supporting: chat_completions and responses
  2. Use AsyncOpenAI with the Foundry /openai/v1 base URL.
  3. Map request and token fields appropriately for each API.
  4. Configure Model Router for Chat Completions and baseline/judge models for Responses.
  5. Reject URLs ending in /chat/completions or /responses with an actionable configuration error.
  6. Update .env.example, presets, documentation, and SDK dependency requirements.
  7. Treat null cost and latency metrics as missing data instead of crashing verification.

When validating this fix, all three configured live deployments succeeded with minimal smoke requests. The non-live suite passed with 181 tests, along with lint, dependency checks, and configuration dry-run validation.

Steps to reproduce
  1. Update .env baseline model to gpt-5.6-sol and the judge model to gpt-5.5
  2. Set pricing region to westus3
  3. In live_demo.yaml replace dataset with a custom dataset.
  4. Run .\scripts\demo.ps1 -Live
Expected behaviour

Evaluation should happen, including the generated report.

Actual behaviour

Model Router errors: 10/10 [nwt_001] NotFoundError: Error code: 404 - {'error': {'code': '404', 'message': 'Resource not found'}} [nwt_002] NotFoundError: Error code: 404 - {'error': {'code': '404', 'message': 'Resource not found'}} [nwt_003] NotFoundError: Error code: 404 - {'error': {'code': '404', 'message': 'Resource not found'}} [nwt_004] NotFoundError: Error code: 404 - {'error': {'code': '404', 'message': 'Resource not found'}} [nwt_006] NotFoundError: Error code: 404 - {'error': {'code': '404', 'message': 'Resource not found'}} [nwt_005] NotFoundError: Error code: 404 - {'error': {'code': '404', 'message': 'Resource not found'}} [nwt_007] NotFoundError: Error code: 404 - {'error': {'code': '404', 'message': 'Resource not found'}} [nwt_008] NotFoundError: Error code: 404 - {'error': {'code': '404', 'message': 'Resource not found'}} [nwt_010] NotFoundError: Error code: 404 - {'error': {'code': '404', 'message': 'Resource not found'}} [nwt_009] NotFoundError: Error code: 404 - {'error': {'code': '404', 'message': 'Resource not found'}} Baseline errors: 10/10 [nwt_001] NotFoundError: Error code: 404 - {'error': {'code': '404', 'message': 'Resource not found'}} [nwt_002] NotFoundError: Error code: 404 - {'error': {'code': '404', 'message': 'Resource not found'}} [nwt_003] NotFoundError: Error code: 404 - {'error': {'code': '404', 'message': 'Resource not found'}} [nwt_004] NotFoundError: Error code: 404 - {'error': {'code': '404', 'message': 'Resource not found'}} [nwt_006] NotFoundError: Error code: 404 - {'error': {'code': '404', 'message': 'Resource not found'}} [nwt_005] NotFoundError: Error code: 404 - {'error': {'code': '404', 'message': 'Resource not found'}} [nwt_007] NotFoundError: Error code: 404 - {'error': {'code': '404', 'message': 'Resource not found'}} [nwt_008] NotFoundError: Error code: 404 - {'error': {'code': '404', 'message': 'Resource not found'}} [nwt_010] NotFoundError: Error code: 404 - {'error': {'code': '404', 'message': 'Resource not found'}} [nwt_009] NotFoundError: Error code: 404 - {'error': {'code': '404', 'message': 'Resource not found'}} Traceback (most recent call last): File "C:\Users\apspeigh\Documents\Model-Router-Auto-Evaluation\scripts\run_eval.py", line 167, in <module> main()

File "C:\Users\apspeigh\Documents\Model-Router-Auto-Evaluation\scripts\run_eval.py", line 160, in main
vr = verify_local_eval(config.output_directory)
File "C:\Users\apspeigh\Documents\Model-Router-Auto-Evaluation\src\verify.py", line 102, in verify_local_eval
if cost.get("estimated_cost_usd") is not None:
^^^^^^^^
AttributeError: 'NoneType' object has no attribute 'get'
Exception: C:\Users\apspeigh\Documents\Model-Router-Auto-Evaluation\scripts\demo.ps1:65:13
Line |
65 | throw "Live evaluation failed."
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
| Live evaluation failed.

### Which part of the pipeline is affected?

Other / not sure

### Python version

3.13.15

### Operating system

Windows 11

### Repo commit or release

_No response_

### Relevant configuration

```yaml

```

### Logs and screenshots

```shell

```

### Additional context

I have the updated files w/ the GitHub Copilot fix if you'd like it.

Beitragsleitfaden

Beitragsleitfaden öffnen

Erste Schritte

  1. Lies das ganze Issue und danach den Beitragsleitfaden des Projekts.
  2. Schreib ins Issue, dass du es übernimmst — das erspart doppelte Arbeit.
  3. Forke das Repository und arbeite in einem Branch.
  4. Öffne einen Pull Request, der die Issue-Nummer nennt.

Rechercherichtung

Beginne mit scripts/run_eval.py und src/verify.py und verfolge anschließend die Endpunktkonfiguration durch live_demo.yaml, .env.example, Presets und die Dokumentation. Prüfe, wie der Evaluierungsclient zwischen Chat Completions und Responses auswählt und wie die Verifizierung mit null-Kosten- und Latenzmetriken umgeht. Als abgeschlossen gilt die Aufgabe, wenn Live-Bereitstellungen abgeschlossen werden und einen Bericht erzeugen, während die bestehende 181-Testsuite, Lint, Abhängigkeitsprüfungen und Konfigurationsvalidierung weiterhin erfolgreich sind.

Vom Indexierungsmodell aus dem Issue-Text verfasst.

Bewertung

Tech-Stack
azure, python
Bereich
ai, api, testing
Issue-Typ
Bug
Schwierigkeit
4/5
Geschätzter Aufwand
3-5 Tage
Aktivitätsstatus
Aktiv
Klarheit
Größtenteils klar
Anfängerfreundlichkeit
52/100

Neue Issues direkt in Ihr Postfach

Eine kurze Übersicht über anfängerfreundliche GitHub-Issues.