Fix huggingface inference endpoint name

garak/generators/huggingface.py

@@ -256,7 +256,7 @@ def __init__(self, name="", config_root=_config):
         self.name = name
         super().__init__(self.name, config_root=config_root)
 
-        self.uri = self.URI + name
+        self.uri = self.URI + self.name
 
         # special case for api token requirement this also reserves `headers` as not configurable
         if self.api_key:
@@ -376,7 +376,7 @@ class InferenceEndpoint(InferenceAPI):
 
     def __init__(self, name="", config_root=_config):
         super().__init__(name, config_root=config_root)
-        self.uri = name
+        self.uri = self.name
 
     @backoff.on_exception(
         backoff.fibo,

tests/generators/conftest.py

@@ -11,3 +11,10 @@ def openai_compat_mocks():
     """Mock responses for OpenAI compatible endpoints"""
     with open(pathlib.Path(__file__).parents[0] / "openai.json") as mock_openai:
         return json.load(mock_openai)
+
+
+@pytest.fixture
+def hf_endpoint_mocks():
+    """Mock responses for Huggingface InferenceAPI based endpoints"""
+    with open(pathlib.Path(__file__).parents[0] / "hf_inference.json") as mock_openai:
+        return json.load(mock_openai)

tests/generators/hf_inference.json

@@ -0,0 +1,10 @@
+{
+    "hf_inference": {
+        "code": 200,
+        "json": [
+            {
+                "generated_text":"restricted by their policy,"
+           }
+         ]
+    }
+}

tests/generators/test_huggingface.py

@@ -1,4 +1,5 @@
 import pytest
+import requests
 import transformers
 import garak.generators.huggingface
 from garak._config import GarakSubConfig
@@ -8,6 +9,7 @@
 def hf_generator_config():
     gen_config = {
         "huggingface": {
+            "api_key": "fake",
             "hf_args": {
                 "device": "cpu",
                 "torch_dtype": "float32",
@@ -19,6 +21,17 @@ def hf_generator_config():
     return config_root
 
 
+@pytest.fixture
+def hf_mock_response(hf_endpoint_mocks):
+    import json
+
+    mock_resp_data = hf_endpoint_mocks["hf_inference"]
+    mock_resp = requests.Response()
+    mock_resp.status_code = mock_resp_data["code"]
+    mock_resp._content = json.dumps(mock_resp_data["json"]).encode("UTF-8")
+    return mock_resp
+
+
 def test_pipeline(hf_generator_config):
     generations = 10
     g = garak.generators.huggingface.Pipeline("gpt2", config_root=hf_generator_config)
@@ -37,16 +50,55 @@ def test_pipeline(hf_generator_config):
         assert isinstance(item, str)
 
 
-def test_inference():
-    return  # slow w/o key
-    g = garak.generators.huggingface.InferenceAPI("gpt2")
-    assert g.name == "gpt2"
+def test_inference(mocker, hf_mock_response, hf_generator_config):
+    model_name = "gpt2"
+    mock_request = mocker.patch.object(
+        requests, "request", return_value=hf_mock_response
+    )
+
+    g = garak.generators.huggingface.InferenceAPI(
+        model_name, config_root=hf_generator_config
+    )
+    assert g.name == model_name
+    assert model_name in g.uri
+
+    hf_generator_config.generators["huggingface"]["name"] = model_name
+    g = garak.generators.huggingface.InferenceAPI(config_root=hf_generator_config)
+    assert g.name == model_name
+    assert model_name in g.uri
+    assert isinstance(g.max_tokens, int)
+    g.max_tokens = 99
+    assert g.max_tokens == 99
+    g.temperature = 0.1
+    assert g.temperature == 0.1
+    output = g.generate("")
+    mock_request.assert_called_once()
+    assert len(output) == 1  # 1 generation by default
+    for item in output:
+        assert isinstance(item, str)
+
+
+def test_endpoint(mocker, hf_mock_response, hf_generator_config):
+    model_name = "https://localhost:8000/gpt2"
+    mock_request = mocker.patch.object(requests, "post", return_value=hf_mock_response)
+
+    g = garak.generators.huggingface.InferenceEndpoint(
+        model_name, config_root=hf_generator_config
+    )
+    assert g.name == model_name
+    assert g.uri == model_name
+
+    hf_generator_config.generators["huggingface"]["name"] = model_name
+    g = garak.generators.huggingface.InferenceEndpoint(config_root=hf_generator_config)
+    assert g.name == model_name
+    assert g.uri == model_name
     assert isinstance(g.max_tokens, int)
     g.max_tokens = 99
     assert g.max_tokens == 99
     g.temperature = 0.1
     assert g.temperature == 0.1
     output = g.generate("")
+    mock_request.assert_called_once()
     assert len(output) == 1  # 1 generation by default
     for item in output:
         assert isinstance(item, str)