pass

Author: rafaelpierrehf

requirements-test.txt

@@ -1,5 +1,3 @@
-tox
-pytest
 pytest-xdist
 parameterized
 psutil
@@ -8,4 +6,8 @@ pytest-sugar
 mock==2.0.0
 docker
 requests
-tenacity
+tenacity
+termcolor
+execnet
+pluggy
+py

setup.py

@@ -5,7 +5,7 @@
 # We don't declare our dependency on transformers here because we build with
 # different packages for different variants
 
-VERSION = "0.2.0"
+VERSION = "0.3.0"
 
 
 # Ubuntu packages
@@ -15,14 +15,10 @@
 
 install_requires = [
     # transformers
-    "transformers[sklearn,sentencepiece]==4.27.0",
+    "transformers[sklearn,sentencepiece]==4.37.2",
     "huggingface_hub>=0.20.3",
-    # api stuff
     "orjson",
-    # "robyn",
-    # vision
     "Pillow",
-    # speech + torchaudio
     "librosa",
     "pyctcdecode>=0.3.0",
     "phonemizer",
@@ -34,9 +30,9 @@
 extras["st"] = ["sentence_transformers==2.2.1"]
 extras["diffusers"] = ["diffusers==0.26.3", "accelerate==0.27.2"]
 extras["torch"] = ["torch==2.2.0", "torchaudio"]
-extras["tensorflow"] = ["tensorflow==2.9.3"]
+extras["tensorflow"] = ["tensorflow"]
 extras["test"] = [
-    "pytest",
+    "pytest==7.2.1",
     "pytest-xdist",
     "parameterized",
     "psutil",

src/huggingface_inference_toolkit/utils.py

@@ -74,19 +74,14 @@ def wrap_conversation_pipeline(pipeline):
     """
 
     def wrapped_pipeline(inputs, *args, **kwargs):
-        converted_input = Conversation(
-            inputs["text"],
-            past_user_inputs=inputs.get("past_user_inputs", []),
-            generated_responses=inputs.get("generated_responses", []),
-        )
+        logging.info(f"Inputs: {inputs}")
+        logging.info(f"Args: {args}")
+        logging.info(f"KWArgs: {kwargs}")
+        converted_input = Conversation(messages = inputs)
         prediction = pipeline(converted_input, *args, **kwargs)
-        return {
-            "generated_text": prediction.generated_responses[-1],
-            "conversation": {
-                "past_user_inputs": prediction.past_user_inputs,
-                "generated_responses": prediction.generated_responses,
-            },
-        }
+        logging.info(f"Prediction: {prediction}")
+        return prediction
+        
 
     return wrapped_pipeline
 
@@ -295,11 +290,12 @@ def get_pipeline(
     ):
         # set chunk length to 30s for whisper to enable long audio files
         hf_pipeline._preprocess_params["chunk_length_s"] = 30
-        hf_pipeline._preprocess_params["ignore_warning"] = True
+        #hf_pipeline._preprocess_params["ignore_warning"] = True
         # set decoder to english by default
         # TODO: replace when transformers 4.26.0 is release with
         hf_pipeline.model.config.forced_decoder_ids = hf_pipeline.tokenizer.get_decoder_prompt_ids(
-            language="english", task="transcribe"
+            language="english",
+            task="transcribe"
         )
         """"
         hf_pipeline.tokenizer.language = "english"

tests/unit/test_utils.py

@@ -160,29 +160,49 @@ def test_wrap_conversation_pipeline():
         framework="pt",
     )
     conv_pipe = wrap_conversation_pipeline(init_pipeline)
-    data = {
-        "past_user_inputs": ["Which movie is the best ?"],
-        "generated_responses": ["It's Die Hard for sure."],
-        "text": "Can you explain why?",
-    }
+    data = [
+        {
+            "role": "user",
+            "content": "Which movie is the best ?"
+        },
+        {
+            "role": "assistant",
+            "content": "It's Die Hard for sure."
+        },
+        {
+            "role": "user",
+            "content": "Can you explain why?"
+        }
+    ]
     res = conv_pipe(data)
-    assert "conversation" in res
-    assert "generated_text" in res
+    assert "content" in res.messages[-1]
 
 
 @require_torch
 def test_wrapped_pipeline():
     with tempfile.TemporaryDirectory() as tmpdirname:
-        storage_dir = _load_repository_from_hf("hf-internal-testing/tiny-random-blenderbot", tmpdirname, framework="pytorch")
+        storage_dir = _load_repository_from_hf(
+            repository_id = "microsoft/DialoGPT-small",
+            target_dir = tmpdirname,
+            framework="pytorch"
+        )
         conv_pipe = get_pipeline("conversational", storage_dir.as_posix())
-        data = {
-            "past_user_inputs": ["Which movie is the best ?"],
-            "generated_responses": ["It's Die Hard for sure."],
-            "text": "Can you explain why?",
-        }
+        data = [
+            {
+                "role": "user",
+                "content": "Which movie is the best ?"
+            },
+            {
+                "role": "assistant",
+                "content": "It's Die Hard for sure."
+            },
+            {
+                "role": "user",
+                "content": "Can you explain why?"
+            }
+        ]
         res = conv_pipe(data)
-        assert "conversation" in res
-        assert "generated_text" in res
+        assert "content" in res.messages[-1]
 
 
 def test_local_custom_pipeline():

tox.ini

@@ -1,28 +1,38 @@
 [tox]
-envlist = py39
+envlist = 311
 skipsdist = true
+allowlist_externals = 
+    pytest
 
 [testenv]
-deps = -r requirements.txt
-install_command = 
-  pip install -U pip
-  pip install -e .
-setenv =
-  PYTHONPATH=.
+deps =
+    uv
+    pytest
+allowlist_externals = 
+    pytest
+    uv
+commands_pre =
+    uv pip install -e ".[test]"
+commands = pytest --version
+setenv = 
+    PYTHONPATH = .
 
 [testenv:lint]
-basepython = python 
+basepython = python
 commands = ruff src
 
 [testenv:fix]
 basepython = python 
 commands = ruff src --fix
 
 [testenv:unit-torch]
-install_command = 
-    pip install -e ".[test,torch,st]"
+install_command =
+    uv pip install -e ".[torch,st]"
 allowlist_externals = 
     pytest
+    uv
+    source
+    rm
 commands =
     pytest -s -v \
     {tty:--color=yes} \
@@ -32,8 +42,12 @@ commands =
     tests/unit/test_serializer.py \ 
     tests/unit/test_utils.py \
     {posargs} \
-    --log-cli-level=DEBUG \
+    --log-cli-level=INFO \
     --log-format='%(asctime)s %(levelname)s %(module)s:%(lineno)d %(message)s'
+setenv = 
+    PYTHONPATH=.
+    TORCH_USE_CUDA_DSA=true
+
 
 [testenv:unit-torch-slow]
 install_command = pip install -e ".[torch, st, diffusers]"