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참고/guardrails-main/tests/integration_tests/test_run.py

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+import pytest
+
+from guardrails.classes.history.call import Call
+from guardrails.classes.history.iteration import Iteration
+from guardrails.classes.llm.llm_response import LLMResponse
+from guardrails.classes.output_type import OutputTypes
+from guardrails.llm_providers import AsyncLiteLLMCallable, LiteLLMCallable
+from guardrails.run import AsyncRunner, Runner
+from guardrails.types.on_fail import OnFailAction
+
+from .test_assets import string
+from tests.integration_tests.test_assets.validators.two_words import TwoWords
+
+PROMPT = string.COMPILED_PROMPT
+INSTRUCTIONS = """You are a helpful assistant, and you are helping me
+     come up with a name for a pizza. ${gr.complete_string_suffix}"""
+
+
+OUTPUT_SCHEMA = {"type": "string", "description": "Name for the pizza"}
+two_words = TwoWords(on_fail=OnFailAction.REASK)
+validation_map = {"$": [two_words]}
+
+
+OUTPUT = "Tomato Cheese Pizza"
+
+
+def runner_instance(is_sync: bool):
+    if is_sync:
+        return Runner(
+            OutputTypes.STRING,
+            output_schema=OUTPUT_SCHEMA,
+            num_reasks=0,
+            validation_map=validation_map,
+            messages=[
+                {"role": "system", "content": INSTRUCTIONS},
+                {"role": "user", "content": PROMPT},
+            ],
+            api=LiteLLMCallable,
+        )
+    else:
+        return AsyncRunner(
+            OutputTypes.STRING,
+            output_schema=OUTPUT_SCHEMA,
+            num_reasks=0,
+            validation_map=validation_map,
+            messages=[
+                {"role": "system", "content": INSTRUCTIONS},
+                {"role": "user", "content": PROMPT},
+            ],
+            api=AsyncLiteLLMCallable,
+        )
+
+
+@pytest.mark.asyncio
+async def test_sync_async_validate_equivalence(mocker):
+    mock_invoke_llm = mocker.patch(
+        "guardrails.llm_providers.AsyncLiteLLMCallable.invoke_llm",
+    )
+    mock_invoke_llm.side_effect = [
+        LLMResponse(
+            output=string.LLM_OUTPUT,
+            prompt_token_count=123,
+            response_token_count=1234,
+        )
+    ]
+
+    iteration = Iteration(
+        call_id="mock-call",
+        index=0,
+    )
+
+    parsed_output, _ = runner_instance(True).parse(OUTPUT, OUTPUT_SCHEMA)
+
+    # Call the 'validate' method synchronously
+    result_sync = runner_instance(True).validate(
+        iteration, 1, parsed_output, OUTPUT_SCHEMA
+    )
+
+    # Call the 'async_validate' method asynchronously
+    result_async = await runner_instance(False).async_validate(
+        iteration, 1, parsed_output, OUTPUT_SCHEMA
+    )
+    assert result_sync == result_async
+
+
+@pytest.mark.asyncio
+async def test_sync_async_step_equivalence(mocker):
+    mock_invoke_llm = mocker.patch(
+        "guardrails.llm_providers.AsyncLiteLLMCallable.invoke_llm",
+    )
+    mock_invoke_llm.side_effect = [
+        LLMResponse(
+            output=string.LLM_OUTPUT,
+            prompt_token_count=123,
+            response_token_count=1234,
+        )
+    ]
+
+    call_log = Call()
+
+    # Call the 'step' method synchronously
+    sync_iteration = runner_instance(True).step(
+        1,
+        OUTPUT_SCHEMA,
+        call_log,
+        api=LiteLLMCallable(**{"temperature": 0}),
+        messages=[
+            {"role": "system", "content": INSTRUCTIONS},
+            {"role": "user", "content": PROMPT},
+        ],
+        prompt_params={},
+        output=OUTPUT,
+    )
+
+    # Call the 'async_step' method asynchronously
+    async_iteration = await runner_instance(False).async_step(
+        1,
+        OUTPUT_SCHEMA,
+        call_log,
+        api=AsyncLiteLLMCallable(**{"temperature": 0}),
+        messages=[
+            {"role": "system", "content": INSTRUCTIONS},
+            {"role": "user", "content": PROMPT},
+        ],
+        prompt_params={},
+        output=OUTPUT,
+    )
+
+    assert sync_iteration.guarded_output == async_iteration.guarded_output
+    assert sync_iteration.reasks == async_iteration.reasks