참고소스 수정본

참고/guardrails-main/tests/unit_tests/mocks/__init__.py

@@ -0,0 +1,12 @@
+from .mock_async_validator_service import MockAsyncValidatorService
+from .mock_custom_llm import MockAsyncOpenAILlm, MockOpenAILlm
+from .mock_loop import MockLoop
+from .mock_sequential_validator_service import MockSequentialValidatorService
+
+__all__ = [
+    "MockAsyncValidatorService",
+    "MockSequentialValidatorService",
+    "MockLoop",
+    "MockOpenAILlm",
+    "MockAsyncOpenAILlm",
+]

참고/guardrails-main/tests/unit_tests/mocks/mock_async_validator_service.py

@@ -0,0 +1,17 @@
+import asyncio
+
+
+class MockAsyncValidatorService:
+    initialized: bool
+
+    def __init__(self, *args, **kwargs):
+        self.initialized = True
+
+    async def async_validate(self, *args):
+        await asyncio.sleep(0.1)
+        # The return value doesn't really matter here.
+        # We just need something to identify which class and method was called.
+        return "MockAsyncValidatorService.async_validate", {"async": True}
+
+    def validate(self, *args):
+        return "MockAsyncValidatorService.validate", {"sync": True}

참고/guardrails-main/tests/unit_tests/mocks/mock_custom_llm.py

@@ -0,0 +1,38 @@
+from unittest.mock import Mock
+from openai import APIError
+
+
+class MockOpenAILlm:
+    def __init__(self, times_called=0, response="Hello world!"):
+        self.times_called = times_called
+        self.response = response
+
+    def fail_retryable(self, messages, *args, **kwargs) -> str:
+        if self.times_called == 0:
+            self.times_called = self.times_called + 1
+            raise APIError("ServiceUnavailableError", Mock(), body=None)
+        return self.response
+
+    def fail_non_retryable(self, messages, *args, **kwargs) -> str:
+        raise Exception("Non-Retryable Error!")
+
+    def succeed(self, messages, *args, **kwargs) -> str:
+        return self.response
+
+
+class MockAsyncOpenAILlm:
+    def __init__(self, times_called=0, response="Hello world!"):
+        self.times_called = times_called
+        self.response = response
+
+    async def fail_retryable(self, messages, *args, **kwargs) -> str:
+        if self.times_called == 0:
+            self.times_called = self.times_called + 1
+            raise APIError("ServiceUnavailableError", Mock(), body=None)
+        return self.response
+
+    async def fail_non_retryable(self, messages, *args, **kwargs) -> str:
+        raise Exception("Non-Retryable Error!")
+
+    async def succeed(self, messages, *args, **kwargs) -> str:
+        return self.response

참고/guardrails-main/tests/unit_tests/mocks/mock_file.py

@@ -0,0 +1,31 @@
+from contextlib import AbstractContextManager
+from types import TracebackType
+from typing import Optional, Type
+
+
+class MockFile(AbstractContextManager):
+    def __exit__(
+        self,
+        __exc_type: Optional[Type[BaseException]],
+        __exc_value: Optional[BaseException],
+        __traceback: Optional[TracebackType],
+    ) -> Optional[bool]:
+        return super().__exit__(__exc_type, __exc_value, __traceback)
+
+    def readlines(self):
+        pass
+
+    def writelines(self, *args):
+        pass
+
+    def close(self):
+        pass
+
+    def read(self, *args):
+        pass
+
+    def write(self, *args):
+        pass
+
+    def seek(self, *args):
+        pass

참고/guardrails-main/tests/unit_tests/mocks/mock_hf_models.py

@@ -0,0 +1,47 @@
+import os
+
+
+def make_mock_model_and_tokenizer():
+    """Returns a tuple of HF AutoModelForCausalLM and AutoTokenizer."""
+    import torch
+
+    torch.set_num_threads(1)
+
+    from transformers import AutoModelForCausalLM, AutoTokenizer
+
+    # Can regenerate the sample pipe with this:
+    # pipeline(
+    #     "text-generation",
+    #     "hf-internal-testing/tiny-random-gpt2",
+    # ).save_pretrained("...")
+
+    savedir = os.path.join(
+        os.path.abspath(os.path.normpath(os.path.dirname(__file__))), "tiny-random-gpt2"
+    )
+
+    model = AutoModelForCausalLM.from_pretrained(
+        savedir,
+        local_files_only=True,
+    )
+
+    tokenizer = AutoTokenizer.from_pretrained(
+        savedir,
+        local_files_only=True,
+    )
+
+    return model, tokenizer
+
+
+def make_mock_pipeline():
+    from transformers import pipeline
+
+    model, tokenizer = make_mock_model_and_tokenizer()
+
+    pipe = pipeline(
+        task="text-generation",
+        model=model,
+        tokenizer=tokenizer,
+        trust_remote_code=False,
+        device_map="cpu",  # Force CPU to avoid multithreaded fighting.
+    )
+    return pipe

참고/guardrails-main/tests/unit_tests/mocks/mock_hub.py

@@ -0,0 +1,14 @@
+from typing import Any, Dict
+
+from guardrails.validator_base import (
+    PassResult,
+    ValidationResult,
+    Validator,
+    register_validator,
+)
+
+
+@register_validator(name="mock-validator", data_type="string")
+class MockValidator(Validator):
+    def validate(self, value: Any, metadata: Dict) -> ValidationResult:
+        return PassResult()

참고/guardrails-main/tests/unit_tests/mocks/mock_loop.py

@@ -0,0 +1,12 @@
+class MockLoop:
+    def __init__(self, loop_is_running: bool):
+        self.loop_is_running = loop_is_running
+
+    def is_running(self):
+        return self.loop_is_running
+
+    def run_until_complete(self, future):
+        return future
+
+    def run_in_executor(self, executor, func, *args):
+        return func(*args)

참고/guardrails-main/tests/unit_tests/mocks/mock_sequential_validator_service.py

@@ -0,0 +1,8 @@
+class MockSequentialValidatorService:
+    initialized: bool
+
+    def __init__(self, *args, **kwargs):
+        self.initialized = True
+
+    def validate(self, *args):
+        return "MockSequentialValidatorService.validate", {"sync": True}

참고/guardrails-main/tests/unit_tests/mocks/mock_span.py

@@ -0,0 +1,18 @@
+from contextlib import AbstractContextManager
+from types import TracebackType
+from typing import Optional, Type
+from unittest.mock import MagicMock
+
+
+class MockSpan(AbstractContextManager):
+    def __exit__(
+        self,
+        __exc_type: Optional[Type[BaseException]],
+        __exc_value: Optional[BaseException],
+        __traceback: Optional[TracebackType],
+    ) -> Optional[bool]:
+        return super().__exit__(__exc_type, __exc_value, __traceback)
+
+    def __init__(self):
+        super().__init__()
+        self.set_attribute = MagicMock()

참고/guardrails-main/tests/unit_tests/mocks/mock_validator.py

@@ -0,0 +1,37 @@
+from typing import Any, Callable, Dict, Union
+
+from guardrails import Validator, register_validator
+from guardrails_ai.types import (
+    FailResult,
+    PassResult,
+    ValidationResult,
+)
+
+
+def create_mock_validator(
+    name: str,
+    on_fail: Union[str, Callable] = None,
+    should_pass: bool = True,
+    return_value: Any = None,
+):
+    def validate(self, value: Any, metadata: Dict[str, Any]) -> ValidationResult:
+        if self.should_pass:
+            return self.return_value if self.return_value is not None else PassResult()
+        else:
+            return FailResult(
+                error_message="Value is not valid.",
+            )
+
+    validator_type = type(
+        name,
+        (Validator,),
+        {
+            "validate": validate,
+            "name": name,
+            "on_fail": on_fail,
+            "should_pass": should_pass,
+            "return_value": return_value,
+        },
+    )
+    register_validator(name=name, data_type=["string"])(validator_type)
+    return validator_type

참고/guardrails-main/tests/unit_tests/mocks/tiny-random-gpt2/config.json

@@ -0,0 +1,40 @@
+{
+  "_name_or_path": "hf-internal-testing/tiny-random-gpt2",
+  "activation_function": "gelu_new",
+  "architectures": [
+    "GPT2LMHeadModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "attn_pdrop": 0.1,
+  "bos_token_id": 98,
+  "embd_pdrop": 0.1,
+  "eos_token_id": 98,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "initializer_range": 0.02,
+  "intermediate_size": 37,
+  "layer_norm_epsilon": 1e-05,
+  "model_type": "gpt2",
+  "n_ctx": 512,
+  "n_embd": 32,
+  "n_head": 4,
+  "n_inner": null,
+  "n_layer": 5,
+  "n_positions": 512,
+  "pad_token_id": 98,
+  "reorder_and_upcast_attn": false,
+  "resid_pdrop": 0.1,
+  "scale_attn_by_inverse_layer_idx": false,
+  "scale_attn_weights": true,
+  "summary_activation": null,
+  "summary_first_dropout": 0.1,
+  "summary_proj_to_labels": true,
+  "summary_type": "cls_index",
+  "summary_use_proj": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.36.2",
+  "type_vocab_size": 16,
+  "use_cache": true,
+  "vocab_size": 1000
+}

참고/guardrails-main/tests/unit_tests/mocks/tiny-random-gpt2/generation_config.json

@@ -0,0 +1,7 @@
+{
+  "_from_model_config": true,
+  "bos_token_id": 98,
+  "eos_token_id": 98,
+  "pad_token_id": 98,
+  "transformers_version": "4.36.2"
+}

참고/guardrails-main/tests/unit_tests/mocks/tiny-random-gpt2/merges.txt

@@ -0,0 +1,807 @@
+#version: 0.2
+Ġ t
+h e
+Ġ a
+i n
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+o n
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+Ġ =
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+d er
+Ġp ol
+Ġm ay
+a pt
+el s
+ĠW h
+Ġcomp le
+Ġar t
+ĠB r
+ĠI s
+un e
+t il
+Ġc rit
+Ġh ist
+Ġear ly
+Ġc ould
+ĠC on
+Ġd id
+Ġb el
+Ġcall ed
+u ed
+Ġn ear
+Ġepis ode
+y p
+Ġdesc rib

참고/guardrails-main/tests/unit_tests/mocks/tiny-random-gpt2/special_tokens_map.json

@@ -0,0 +1,23 @@
+{
+  "bos_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

참고/guardrails-main/tests/unit_tests/mocks/tiny-random-gpt2/tokenizer_config.json

@@ -0,0 +1,19 @@
+{
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<|endoftext|>",
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|endoftext|>",
+  "model_max_length": 1024,
+  "tokenizer_class": "GPT2Tokenizer",
+  "unk_token": "<|endoftext|>"
+}