ignore linting

libs/experimental/tests/unit_tests/rl_chain/test_pick_best_chain_call.py

@@ -90,11 +90,11 @@ def test_update_with_delayed_score_with_auto_validator_throws() -> None:
         User=rl_chain.BasedOn("Context"),
         action=rl_chain.ToSelectFrom(actions),
     )
-    assert response["response"] == "hey"
-    selection_metadata = response["selection_metadata"]
-    assert selection_metadata.selected.score == 3.0
+    assert response["response"] == "hey" # type: ignore
+    selection_metadata = response["selection_metadata"] # type: ignore
+    assert selection_metadata.selected.score == 3.0 # type: ignore
     with pytest.raises(RuntimeError):
-        chain.update_with_delayed_score(chain_response=response, score=100)
+        chain.update_with_delayed_score(chain_response=response, score=100)  # type: ignore
 
 
 @pytest.mark.requires("vowpal_wabbit_next", "sentence_transformers")
@@ -115,13 +115,13 @@ def test_update_with_delayed_score_force() -> None:
         User=rl_chain.BasedOn("Context"),
         action=rl_chain.ToSelectFrom(actions),
     )
-    assert response["response"] == "hey"
-    selection_metadata = response["selection_metadata"]
-    assert selection_metadata.selected.score == 3.0
+    assert response["response"] == "hey"  # type: ignore
+    selection_metadata = response["selection_metadata"]  # type: ignore
+    assert selection_metadata.selected.score == 3.0  # type: ignore
     chain.update_with_delayed_score(
-        chain_response=response, score=100, force_score=True
+        chain_response=response, score=100, force_score=True  # type: ignore
     )
-    assert selection_metadata.selected.score == 100.0
+    assert selection_metadata.selected.score == 100.0  # type: ignore
 
 
 @pytest.mark.requires("vowpal_wabbit_next", "sentence_transformers")
@@ -140,11 +140,11 @@ def test_update_with_delayed_score() -> None:
         User=rl_chain.BasedOn("Context"),
         action=rl_chain.ToSelectFrom(actions),
     )
-    assert response["response"] == "hey"
-    selection_metadata = response["selection_metadata"]
-    assert selection_metadata.selected.score is None
-    chain.update_with_delayed_score(chain_response=response, score=100)
-    assert selection_metadata.selected.score == 100.0
+    assert response["response"] == "hey"  # type: ignore
+    selection_metadata = response["selection_metadata"]  # type: ignore
+    assert selection_metadata.selected.score is None  # type: ignore
+    chain.update_with_delayed_score(chain_response=response, score=100)  # type: ignore
+    assert selection_metadata.selected.score == 100.0  # type: ignore
 
 
 @pytest.mark.requires("vowpal_wabbit_next", "sentence_transformers")
@@ -174,9 +174,9 @@ def test_user_defined_scorer() -> None:
         User=rl_chain.BasedOn("Context"),
         action=rl_chain.ToSelectFrom(actions),
     )
-    assert response["response"] == "hey"
-    selection_metadata = response["selection_metadata"]
-    assert selection_metadata.selected.score == 200.0
+    assert response["response"] == "hey"  # type: ignore
+    selection_metadata = response["selection_metadata"]  # type: ignore
+    assert selection_metadata.selected.score == 200.0  # type: ignore
 
 
 @pytest.mark.requires("vowpal_wabbit_next", "sentence_transformers")
@@ -208,8 +208,8 @@ def test_everything_embedded() -> None:
         User=rl_chain.EmbedAndKeep(rl_chain.BasedOn(ctx_str_1)),
         action=rl_chain.EmbedAndKeep(rl_chain.ToSelectFrom(actions)),
     )
-    selection_metadata = response["selection_metadata"]
-    vw_str = feature_embedder.format(selection_metadata)
+    selection_metadata = response["selection_metadata"]  # type: ignore
+    vw_str = feature_embedder.format(selection_metadata) # type: ignore
     assert vw_str == expected
 
 
@@ -236,8 +236,8 @@ def test_default_auto_embedder_is_off() -> None:
         User=pick_best_chain.base.BasedOn(ctx_str_1),
         action=pick_best_chain.base.ToSelectFrom(actions),
     )
-    selection_metadata = response["selection_metadata"]
-    vw_str = feature_embedder.format(selection_metadata)
+    selection_metadata = response["selection_metadata"]  # type: ignore
+    vw_str = feature_embedder.format(selection_metadata) # type: ignore
     assert vw_str == expected
 
 
@@ -264,8 +264,8 @@ def test_default_w_embeddings_off() -> None:
         User=rl_chain.BasedOn(ctx_str_1),
         action=rl_chain.ToSelectFrom(actions),
     )
-    selection_metadata = response["selection_metadata"]
-    vw_str = feature_embedder.format(selection_metadata)
+    selection_metadata = response["selection_metadata"] # type: ignore
+    vw_str = feature_embedder.format(selection_metadata) # type: ignore
     assert vw_str == expected
 
 
@@ -292,8 +292,8 @@ def test_default_w_embeddings_on() -> None:
         User=rl_chain.BasedOn(ctx_str_1),
         action=rl_chain.ToSelectFrom(actions),
     )
-    selection_metadata = response["selection_metadata"]
-    vw_str = feature_embedder.format(selection_metadata)
+    selection_metadata = response["selection_metadata"] # type: ignore
+    vw_str = feature_embedder.format(selection_metadata) # type: ignore
     assert vw_str == expected
 
 
@@ -324,8 +324,8 @@ def test_default_embeddings_mixed_w_explicit_user_embeddings() -> None:
         User2=rl_chain.BasedOn(ctx_str_2),
         action=rl_chain.ToSelectFrom(actions),
     )
-    selection_metadata = response["selection_metadata"]
-    vw_str = feature_embedder.format(selection_metadata)
+    selection_metadata = response["selection_metadata"] # type: ignore
+    vw_str = feature_embedder.format(selection_metadata) # type: ignore
     assert vw_str == expected
 
 
@@ -345,9 +345,9 @@ def test_default_no_scorer_specified() -> None:
         action=rl_chain.ToSelectFrom(["0", "1", "2"]),
     )
     # chain llm used for both basic prompt and for scoring
-    assert response["response"] == "hey"
-    selection_metadata = response["selection_metadata"]
-    assert selection_metadata.selected.score == 100.0
+    assert response["response"] == "hey" # type: ignore
+    selection_metadata = response["selection_metadata"] # type: ignore
+    assert selection_metadata.selected.score == 100.0 # type: ignore
 
 
 @pytest.mark.requires("vowpal_wabbit_next", "sentence_transformers")
@@ -366,9 +366,9 @@ def test_explicitly_no_scorer() -> None:
         action=rl_chain.ToSelectFrom(["0", "1", "2"]),
     )
     # chain llm used for both basic prompt and for scoring
-    assert response["response"] == "hey"
-    selection_metadata = response["selection_metadata"]
-    assert selection_metadata.selected.score is None
+    assert response["response"] == "hey" # type: ignore
+    selection_metadata = response["selection_metadata"] # type: ignore
+    assert selection_metadata.selected.score is None # type: ignore
 
 
 @pytest.mark.requires("vowpal_wabbit_next", "sentence_transformers")
@@ -388,9 +388,9 @@ def test_auto_scorer_with_user_defined_llm() -> None:
         action=rl_chain.ToSelectFrom(["0", "1", "2"]),
     )
     # chain llm used for both basic prompt and for scoring
-    assert response["response"] == "hey"
-    selection_metadata = response["selection_metadata"]
-    assert selection_metadata.selected.score == 300.0
+    assert response["response"] == "hey" # type: ignore
+    selection_metadata = response["selection_metadata"] # type: ignore
+    assert selection_metadata.selected.score == 300.0 # type: ignore
 
 
 @pytest.mark.requires("vowpal_wabbit_next", "sentence_transformers")
@@ -434,24 +434,24 @@ def test_activate_and_deactivate_scorer() -> None:
         action=pick_best_chain.base.ToSelectFrom(["0", "1", "2"]),
     )
     # chain llm used for both basic prompt and for scoring
-    assert response["response"] == "hey1"
-    selection_metadata = response["selection_metadata"]
-    assert selection_metadata.selected.score == 300.0
+    assert response["response"] == "hey1" # type: ignore
+    selection_metadata = response["selection_metadata"] # type: ignore
+    assert selection_metadata.selected.score == 300.0 # type: ignore
 
     chain.deactivate_selection_scorer()
     response = chain.run(
         User=pick_best_chain.base.BasedOn("Context"),
         action=pick_best_chain.base.ToSelectFrom(["0", "1", "2"]),
     )
-    assert response["response"] == "hey2"
-    selection_metadata = response["selection_metadata"]
-    assert selection_metadata.selected.score is None
+    assert response["response"] == "hey2" # type: ignore
+    selection_metadata = response["selection_metadata"] # type: ignore
+    assert selection_metadata.selected.score is None # type: ignore
 
     chain.activate_selection_scorer()
     response = chain.run(
         User=pick_best_chain.base.BasedOn("Context"),
         action=pick_best_chain.base.ToSelectFrom(["0", "1", "2"]),
     )
-    assert response["response"] == "hey3"
-    selection_metadata = response["selection_metadata"]
-    assert selection_metadata.selected.score == 400.0
+    assert response["response"] == "hey3" # type: ignore
+    selection_metadata = response["selection_metadata"] # type: ignore
+    assert selection_metadata.selected.score == 400.0 # type: ignore