Add hooks

docs/configuration.md

@@ -9,6 +9,7 @@ tests:
     expected_results:
     initial_prompt:
     max_turns:
+    hook:
 ```
 
 `evaluator` _(map)_
@@ -32,5 +33,6 @@ A list of tests. Each test maps with the following fields:
 - `expected_results` _(list of strings)_: The expected results for the test.
 - `initial_prompt` _(string; optional)_: The first message that is sent to the agent, which starts the conversation. If unspecified, the message will be generated based on the `steps` provided.
 - `max_turns` _(integer; optional)_: The maximum number of user-agent exchanges before the test fails. The default is `2`.
+- `hook` _(string; optional)_: The module path to an evaluation hook.
 
 ---

docs/reference/hook.md

@@ -0,0 +1 @@
+::: src.agenteval.hook

docs/targets/index.md

@@ -63,9 +63,9 @@ If you want to test an agent that is not natively supported, you can bring your
             return TargetResponse(response=response)
     ```
 
-Once you have created your subclass, specify the Target in `agenteval.yaml`.
+Once you have created your subclass, specify the Target in `agenteval.yml`.
 
-!!! example "agenteval.yaml"
+!!! example "agenteval.yml"
 
     ```yaml
     target:
@@ -124,7 +124,7 @@ We will create a simple [LangChain](https://python.langchain.com/docs/modules/ag
 
 Create a test plan that references `MyLangChainTarget`.
 
-!!! example "agenteval.yaml"
+!!! example "agenteval.yml"
 
     ```yaml
     evaluator:

docs/user_guide.md

@@ -6,7 +6,7 @@ To begin, initialize a test plan.
 agenteval init
 ```
 
-This will create an `agenteval.yaml` file in the current directory.
+This will create an `agenteval.yml` file in the current directory.
 
 ```yaml
 evaluator:
@@ -99,3 +99,108 @@ tests:
       - The agent returns the details on claim-006.
     initial_prompt: Can you let me know which claims are open?
 ```
+
+## Evaluation hooks
+You can specify hooks that run before and/or after evaluating a test. This is useful for performing integration testing, as well as any setup or cleanup tasks required.
+
+To create hooks, you will define a subclass of [Hook](reference/hook.md#src.agenteval.hook.Hook).
+
+For a hook that runs *before* evaluation, implement a `pre_evaluate` method. In this method, you have access to the [Test](reference/test.md#src.agenteval.test.Test) and [TraceHandler](reference/trace_handler.md#src.agenteval.trace_handler.TraceHandler) via the `test` and `trace` arguments, respectively.
+
+For a hook that runs *after* evaluation, implement a `post_evaluate` method. Similar to the `pre_evaluate` method, you have access to the `Test` and `TraceHandler`. You also have access to the [TestResult](reference/test_result.md#src.agenteval.test_result.TestResult) via the `test_result` argument. You may override the attributes of the `TestResult` if you plan to use this hook to perform additional testing, such as integration testing.
+
+!!! example "my_evaluation_hook.py"
+
+    ```python
+    from agenteval import Hook
+
+    class MyEvaluationHook(Hook):
+
+      def pre_evaluate(test, trace):
+        # implement logic here
+
+      def post_evaluate(test, test_result, trace):
+        # implement logic here
+    ```
+
+Once you have created your subclass, specify the hook for the test in `agenteval.yml`.
+
+!!! example "agenteval.yml"
+
+    ```yaml
+    tests:
+      - name: MakeReservation
+        hook: my_evaluation_hook.MyEvaluationHook
+    ```
+
+### Examples
+
+#### Integration testing using `post_evaluate`
+
+In this example, we will test an agent that can make dinner reservations. In addition to evaluating the conversation, we want to test that the reservation is written to the backend database. To do this, we will create a post evaluation hook that queries a PostgreSQL database for the reservation record. If the record is not found, we will override the `TestResult`.
+
+!!! example "test_record_insert.py"
+
+    ```python
+    import boto3
+    import json
+    import psycopg2
+
+    from agenteval import Hook
+
+    SECRET_NAME = "test-secret"
+
+    def get_db_secret() -> dict:
+
+      session = boto3.session.Session()
+      client = session.client(
+          service_name='secretsmanager',
+      )
+      get_secret_value_response = client.get_secret_value(
+          SecretId=SECRET_NAME
+      )
+      secret = get_secret_value_response['SecretString']
+
+      return json.loads(secret)
+
+    class TestRecordInsert(Hook):
+
+      def post_evaluate(test, test_result, trace):
+
+        # get database secret from AWS Secrets Manager
+        secret = get_db_secret()
+
+        # connect to database
+        conn = psycopg2.connect(
+          database=secret["dbname"],
+          user=secret["username"],
+          password=secret["password"],
+          host=secret["host"],
+          port=secret["port"]
+        )
+
+        # check if record is written to database
+        with conn.cursor() as cur:
+          cur.execute("SELECT * FROM reservations WHERE name = 'Bob'")
+          row = cur.fetchone()
+
+        # override the test result based on query result 
+        if not row:
+          test_result.success = False
+          test_result.result = "Integration test failed"
+          test_result.reasoning = "Record was not inserted into the database"
+    ```
+
+Create a test that references the hook.
+
+!!! example "agenteval.yml"
+
+    ```yaml
+    tests:
+    - name: MakeReservation
+      steps:
+      - Ask agent to make a reservation under the name Bob for 7 PM.
+      expected_results:
+      - The agent confirms that a reservation has been made.
+      hook: test_record_insert.TestRecordInsert
+    ```

mkdocs.yml

@@ -40,6 +40,7 @@ nav:
     - cli: reference/cli.md
     - conversation_handler: reference/conversation_handler.md
     - evaluator: reference/evaluator.md
+    - hook: reference/hook.md
     - target: reference/target.md
     - test: reference/test.md
     - test_result: reference/test_result.md

src/agenteval/__init__.py

@@ -6,6 +6,9 @@
 from jinja2 import Environment, PackageLoader
 from rich.logging import RichHandler
 
+from .hook import Hook
+
+__all__ = ["Hook"]
 _LOG_LEVEL_ENV = "LOG_LEVEL"
 _FORMAT = "%(message)s"
 

src/agenteval/evaluators/claude/claude.py

@@ -166,7 +166,7 @@ def _invoke_target(self, user_input) -> str:
 
         return target_response.response
 
-    def run(self) -> TestResult:
+    def evaluate(self) -> TestResult:
         success = False
         eval_reasoning = ""
         result = "Max turns reached."

src/agenteval/evaluators/evaluator.py

@@ -6,10 +6,12 @@
 from botocore.client import BaseClient
 
 from agenteval.conversation_handler import ConversationHandler
+from agenteval.hook import Hook
 from agenteval.targets import BaseTarget
 from agenteval.test import Test
 from agenteval.test_result import TestResult
 from agenteval.trace_handler import TraceHandler
+from agenteval.utils import import_class, validate_subclass
 
 _BEDROCK_RUNTIME_BOTO3_NAME = "bedrock-runtime"
 
@@ -19,41 +21,58 @@ class BaseEvaluator(ABC):
     classes.
 
     Attributes:
-        test (Test): The test to conduct.
+        test (Test): The test case.
         target (BaseTarget): The target agent being evaluated.
         conversation (ConversationHandler): Conversation handler for capturing the interaction
             between the evaluator (user) and target (agent).
         trace (TraceHandler): Trace handler for capturing steps during evaluation.
+        test_result (TestResult): The result of the test which is set in `BaseEvaluator.run`.
     """
 
     def __init__(self, test: Test, target: BaseTarget):
         """Initialize the evaluator instance for a given `Test` and `Target`.
 
         Args:
-            test (Test): The test to conduct.
+            test (Test): The test case.
             target (BaseTarget): The target agent being evaluated.
         """
         self.test = test
         self.target = target
         self.conversation = ConversationHandler()
         self.trace = TraceHandler(test_name=test.name)
+        self.test_result = None
 
     @abstractmethod
-    def run(self) -> TestResult:
+    def evaluate(self) -> TestResult:
         """Conduct a test.
 
         Returns:
             TestResult: The result of the test.
         """
         pass
 
-    def trace_run(self):
+    def _get_hook_cls(self, hook: Optional[str]) -> Optional[type[Hook]]:
+        if hook:
+            hook_cls = import_class(hook)
+            validate_subclass(hook_cls, Hook)
+            return hook_cls
+
+    def run(self) -> TestResult:
         """
-        Runs the evaluator within a trace context manager to
-        capture trace data.
+        Run the evaluator within a trace context manager and run hooks
+        if provided.
         """
+
+        hook_cls = self._get_hook_cls(self.test.hook)
+
         with self.trace:
-            return self.run()
+            if hook_cls:
+                hook_cls.pre_evaluate(self.test, self.trace)
+            self.test_result = self.evaluate()
+            if hook_cls:
+                hook_cls.post_evaluate(self.test, self.test_result, self.trace)
+
+        return self.test_result
 
 
 class AWSEvaluator(BaseEvaluator):

src/agenteval/hook.py

@@ -0,0 +1,30 @@
+from agenteval.test import Test
+from agenteval.test_result import TestResult
+from agenteval.trace_handler import TraceHandler
+
+
+class Hook:
+    """An evaluation hook."""
+
+    def pre_evaluate(test: Test, trace: TraceHandler) -> None:
+        """
+        Method called before evaluation. Can be used to perform any setup tasks.
+
+        Args:
+            test (Test): The test case.
+            trace (TraceHandler): Trace handler for capturing steps during evaluation.
+        """
+        pass
+
+    def post_evaluate(test: Test, test_result: TestResult, trace: TraceHandler) -> None:
+        """
+        Method called after evaluation. This may be used to perform integration testing
+        or clean up tasks.
+
+        Args:
+            test (Test): The test case.
+            test_result (TestResult): The result of the test, which can be overriden
+                by updating the attributes of this object.
+            trace (TraceHandler): Trace handler for capturing steps during evaluation.
+        """
+        pass

src/agenteval/plan.py

@@ -1,10 +1,9 @@
 from __future__ import annotations
 
-import importlib
 import logging
 import os
 import sys
-from typing import Optional, Union
+from typing import Optional
 
 import yaml
 from pydantic import BaseModel, model_validator
@@ -18,6 +17,7 @@
     SageMakerEndpointTarget,
 )
 from agenteval.test import Test
+from agenteval.utils import import_class, validate_subclass
 
 _PLAN_FILE_NAME = "agenteval.yml"
 
@@ -86,10 +86,8 @@ def create_evaluator(self, test: Test, target: BaseTarget) -> BaseEvaluator:
         if self.evaluator_config.type in _EVALUATOR_MAP:
             evaluator_cls = _EVALUATOR_MAP[self.evaluator_config.type]
         else:
-            evaluator_cls = self._get_class(self.evaluator_config)
-
-            if not issubclass(evaluator_cls, BaseEvaluator):
-                raise TypeError(f"{evaluator_cls} is not a Evaluator subclass")
+            evaluator_cls = import_class(self.evaluator_config.type)
+            validate_subclass(evaluator_cls, BaseEvaluator)
 
         return evaluator_cls(
             test=test,
@@ -103,23 +101,11 @@ def create_target(
         if self.target_config.type in _TARGET_MAP:
             target_cls = _TARGET_MAP[self.target_config.type]
         else:
-            target_cls = self._get_class(self.target_config)
-
-            if not issubclass(target_cls, BaseTarget):
-                raise TypeError(f"{target_cls} is not a Target subclass")
+            target_cls = import_class(self.target_config.type)
+            validate_subclass(target_cls, BaseTarget)
 
         return target_cls(**self.target_config.model_dump(exclude="type"))
 
-    def _get_class(self, config: Union[EvaluatorConfig, TargetConfig]) -> type:
-        module_path, class_name = config.type.rsplit(".", 1)
-        return self._import_class(module_path, class_name)
-
-    @staticmethod
-    def _import_class(module_path: str, class_name: str) -> type[BaseTarget]:
-        module = importlib.import_module(module_path)
-        target_cls = getattr(module, class_name)
-        return target_cls
-
     @staticmethod
     def _load_yaml(path: str) -> dict:
         with open(path) as stream:
@@ -136,6 +122,7 @@ def _load_tests(test_config: list[dict]) -> list[Test]:
                     expected_results=t.get("expected_results"),
                     initial_prompt=t.get("initial_prompt"),
                     max_turns=t.get("max_turns", defaults.MAX_TURNS),
+                    hook=t.get("hook"),
                 )
             )
         return tests

src/agenteval/runner/runner.py

@@ -63,7 +63,7 @@ def run_test(self, test):
                 target=target,
             )
 
-            result = evaluator.trace_run()
+            result = evaluator.run()
             if result.success is False:
                 self.num_failed += 1
 

src/agenteval/test.py

@@ -7,11 +7,12 @@ class Test(BaseModel, validate_assignment=True):
     """A test case for an agent.
 
     Attributes:
-        name: Name of the test
-        steps: List of step to perform for the test
-        expected_results: List of expected results for the test
-        initial_prompt: Optional initial prompt
-        max_turns: Maximum number of turns allowed for the test
+        name: Name of the test.
+        steps: List of step to perform for the test.
+        expected_results: List of expected results for the test.
+        initial_prompt: Optional initial prompt.
+        max_turns: Maximum number of turns allowed for the test.
+        hook: The module path to an evaluation hook.
     """
 
     # do not collect as a test
@@ -22,3 +23,4 @@ class Test(BaseModel, validate_assignment=True):
     expected_results: list[str]
     initial_prompt: Optional[str] = None
     max_turns: int
+    hook: Optional[str] = None

src/agenteval/utils/__init__.py

@@ -0,0 +1,3 @@
+from .imports import import_class, validate_subclass
+
+__all__ = ["import_class", "validate_subclass"]