test: add tests for bedrock client

adalflow/adalflow/components/model_client/bedrock_client.py

@@ -1,19 +1,13 @@
 """AWS Bedrock ModelClient integration."""
+
 import json
 import os
-from typing import (
-    Dict,
-    Optional,
-    Any,
-    Callable,
-    Generator as GeneratorType
-)
+from typing import Dict, Optional, Any, Callable, Generator as GeneratorType
 import backoff
 import logging
 
 from adalflow.core.model_client import ModelClient
 from adalflow.core.types import ModelType, CompletionUsage, GeneratorOutput
-from adalflow.utils import printc
 
 from adalflow.utils.lazy_import import safe_import, OptionalPackages
 
@@ -166,21 +160,46 @@ def init_async_client(self):
         raise NotImplementedError("Async call not implemented yet.")
 
     def handle_stream_response(self, stream: dict) -> GeneratorType:
+        r"""Handle the stream response from bedrock. Yield the chunks.
+
+        Args:
+            stream (dict): The stream response generator from bedrock.
+
+        Returns:
+            GeneratorType: A generator that yields the chunks from bedrock stream.
+        """
         try:
             stream: GeneratorType = stream["stream"]
             for chunk in stream:
                 log.debug(f"Raw chunk: {chunk}")
                 yield chunk
         except Exception as e:
             print(f"Error in handle_stream_response: {e}")  # Debug print
-            raise from e
+            raise
 
     def parse_chat_completion(self, completion: dict) -> "GeneratorOutput":
-        """Parse the completion, and put it into the raw_response."""
+        r"""Parse the completion, and assign it into the raw_response attribute.
+
+        If the completion is a stream, it will be handled by the handle_stream_response
+        method that returns a Generator. Otherwise, the completion will be parsed using
+        the get_first_message_content method.
+
+        Args:
+            completion (dict): The completion response from bedrock API call.
+
+        Returns:
+            GeneratorOutput: A generator output object with the parsed completion. May
+                return a generator if the completion is a stream.
+        """
         try:
+            usage = None
+            print(completion)
             data = self.chat_completion_parser(completion)
+            if not isinstance(data, GeneratorType):
+                # Streaming completion usage tracking is not implemented.
+                usage = self.track_completion_usage(completion)
             return GeneratorOutput(
-                data=None, error=None, raw_response=data
+                data=None, error=None, raw_response=data, usage=usage
             )
         except Exception as e:
             log.error(f"Error parsing the completion: {e}")
@@ -254,7 +273,9 @@ def call(
         if model_type == ModelType.LLM:
             if "stream" in api_kwargs and api_kwargs.get("stream", False):
                 log.debug("Streaming call")
-                api_kwargs.pop("stream")  # stream is not a valid parameter for bedrock
+                api_kwargs.pop(
+                    "stream", None
+                )  # stream is not a valid parameter for bedrock
                 self.chat_completion_parser = self.handle_stream_response
                 return self.sync_client.converse_stream(**api_kwargs)
             else:

adalflow/pyproject.toml

@@ -80,6 +80,7 @@ groq = "^0.9.0"
 google-generativeai = "^0.7.2"
 anthropic = "^0.31.1"
 lancedb = "^0.5.2"
+boto3 = "^1.35.19"
 
 
 

adalflow/tests/test_aws_bedrock_client.py

@@ -0,0 +1,80 @@
+import unittest
+from unittest.mock import patch, Mock
+
+# use the openai for mocking standard data types
+
+from adalflow.core.types import ModelType, GeneratorOutput
+from adalflow.components.model_client import BedrockAPIClient
+
+
+def getenv_side_effect(key):
+    # This dictionary can hold more keys and values as needed
+    env_vars = {
+        "AWS_ACCESS_KEY_ID": "fake_api_key",
+        "AWS_SECRET_ACCESS_KEY": "fake_api_key",
+        "AWS_REGION_NAME": "fake_api_key",
+    }
+    return env_vars.get(key, None)  # Returns None if key is not found
+
+
+# modified from test_openai_client.py
+class TestBedrockClient(unittest.TestCase):
+    def setUp(self):
+        self.client = BedrockAPIClient()
+        self.mock_response = {
+            "ResponseMetadata": {
+                "RequestId": "43aec10a-9780-4bd5-abcc-857d12460569",
+                "HTTPStatusCode": 200,
+                "HTTPHeaders": {
+                    "date": "Sat, 30 Nov 2024 14:27:44 GMT",
+                    "content-type": "application/json",
+                    "content-length": "273",
+                    "connection": "keep-alive",
+                    "x-amzn-requestid": "43aec10a-9780-4bd5-abcc-857d12460569",
+                },
+                "RetryAttempts": 0,
+            },
+            "output": {
+                "message": {"role": "assistant", "content": [{"text": "Hello, world!"}]}
+            },
+            "stopReason": "end_turn",
+            "usage": {"inputTokens": 20, "outputTokens": 10, "totalTokens": 30},
+            "metrics": {"latencyMs": 430},
+        }
+
+        self.api_kwargs = {
+            "messages": [{"role": "user", "content": "Hello"}],
+            "model": "gpt-3.5-turbo",
+        }
+
+    @patch.object(BedrockAPIClient, "init_sync_client")
+    @patch("adalflow.components.model_client.bedrock_client.boto3")
+    def test_call(self, MockBedrock, mock_init_sync_client):
+        mock_sync_client = Mock()
+        MockBedrock.return_value = mock_sync_client
+        mock_init_sync_client.return_value = mock_sync_client
+
+        # Mock the client's api: converse
+        mock_sync_client.converse = Mock(return_value=self.mock_response)
+
+        # Set the sync client
+        self.client.sync_client = mock_sync_client
+
+        # Call the call method
+        result = self.client.call(api_kwargs=self.api_kwargs, model_type=ModelType.LLM)
+
+        # Assertions
+        mock_sync_client.converse.assert_called_once_with(**self.api_kwargs)
+        self.assertEqual(result, self.mock_response)
+
+        # test parse_chat_completion
+        output = self.client.parse_chat_completion(completion=self.mock_response)
+        self.assertTrue(isinstance(output, GeneratorOutput))
+        self.assertEqual(output.raw_response, "Hello, world!")
+        self.assertEqual(output.usage.prompt_tokens, 20)
+        self.assertEqual(output.usage.completion_tokens, 10)
+        self.assertEqual(output.usage.total_tokens, 30)
+
+
+if __name__ == "__main__":
+    unittest.main()