Fix openai not conditioned imports

.github/workflows/smoketest.yaml

@@ -0,0 +1,41 @@
+name: Smoketest
+on:
+  push:
+    branches:
+    - main
+    - release/*
+  pull_request:
+    branches:
+    - main
+    - release/*
+  workflow_dispatch:
+# Cancel old runs when a new commit is pushed to the same branch if not on main or dev
+concurrency:
+  group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
+  cancel-in-progress: ${{ github.ref != 'refs/heads/main' && github.ref != 'refs/heads/dev' }}
+defaults:
+  run:
+    working-directory: .
+jobs:
+  smoketest:
+    runs-on: ubuntu-20.04
+    timeout-minutes: 10
+    strategy:
+      matrix:
+        python_version:
+        - "3.9"
+        - "3.10"
+    steps:
+    - uses: actions/checkout@v3
+    - uses: actions/setup-python@v4
+      with:
+        python-version: ${{ matrix.python_version }}
+    - name: Setup
+      run: |
+        set -ex
+        python -m pip install --upgrade 'pip<23' wheel
+        python -m pip install --upgrade .
+        python -m pip install pytest==7.2.1 pytest_codeblocks==0.16.1
+    - name: Run checks
+      run: |
+        pytest tests/test_smoketest.py

llmfoundry/models/inference_api_wrapper/openai_causal_lm.py

@@ -23,9 +23,11 @@
     'OpenAICausalLMEvalWrapper',
     'OpenAIChatAPIEvalWrapper',
 ]
-from openai.types.chat.chat_completion import ChatCompletion
-from openai.types.completion import Completion
-from openai.types.completion_choice import Logprobs
+
+if TYPE_CHECKING:
+    from openai.types.chat.chat_completion import ChatCompletion
+    from openai.types.completion import Completion
+    from openai.types.completion_choice import Logprobs
 
 MAX_RETRIES = 10
 
@@ -99,7 +101,7 @@ def __init__(self, model_cfg: Dict, tokenizer: AutoTokenizer) -> None:
                 'role':
                     'system',
                 'content':
-                    model_cfg.get('sytsem_role_prompt',
+                    model_cfg.get('system_role_prompt',
                                   'Please complete the following text: ')
             }, {
                 'role': 'user',
@@ -201,7 +203,7 @@ def eval_forward(self, batch: Batch, outputs: Optional[Any] = None):
 
         return torch.stack(output_logits_batch).to(batch['input_ids'].device)
 
-    def process_result(self, completion: Optional[ChatCompletion]):
+    def process_result(self, completion: Optional['ChatCompletion']):
         if completion is None:
             raise ValueError("Couldn't generate model output")
 
@@ -234,7 +236,7 @@ def __init__(self, model_cfg: Dict, tokenizer: AutoTokenizer) -> None:
             logprobs=5,
             temperature=0.0)
 
-    def process_result(self, completion: Optional[Completion]):
+    def process_result(self, completion: Optional['Completion']):
         if completion is None:
             raise ValueError("Couldn't generate model output")
 

tests/test_smoketest.py

@@ -0,0 +1,16 @@
+# Copyright 2022 MosaicML LLM Foundry authors
+# SPDX-License-Identifier: Apache-2.0
+
+from llmfoundry import callbacks, data, models, optim, tokenizers, utils
+
+
+# This very simple test is just to use the above imports, which check and make sure we can import all the top-level
+# modules from foundry. This is mainly useful for checking that we have correctly conditionally imported all optional
+# dependencies.
+def test_smoketest():
+    assert callbacks
+    assert data
+    assert models
+    assert optim
+    assert tokenizers
+    assert utils