fix CI

examples/flex-flows/langchain-eval/flow.py

@@ -1,13 +1,10 @@
 from dataclasses import dataclass
-from pathlib import Path
 
-from promptflow.tracing import trace
-from promptflow.connections import CustomConnection
-
-
-from langchain.evaluation import load_evaluator
 from langchain.chat_models import AzureChatOpenAI, ChatAnthropic
+from langchain.evaluation import load_evaluator
 
+from promptflow.connections import CustomConnection
+from promptflow.tracing import trace
 
 
 @dataclass
@@ -23,7 +20,9 @@ def __init__(self, custom_connection: CustomConnection):
 
         # create llm according to the secrets in custom connection
         if "anthropic_api_key" in self.custom_connection.secrets:
-            self.llm = ChatAnthropic(temperature=0, anthropic_api_key=self.custom_connection.secrets["anthropic_api_key"])
+            self.llm = ChatAnthropic(
+                temperature=0, anthropic_api_key=self.custom_connection.secrets["anthropic_api_key"]
+            )
         elif "openai_api_key" in self.custom_connection.secrets:
             self.llm = AzureChatOpenAI(
                 deployment_name="gpt-35-turbo",
@@ -35,17 +34,16 @@ def __init__(self, custom_connection: CustomConnection):
             )
         else:
             raise ValueError("No valid API key found in the connection.")
-        
+
         self.evaluator = load_evaluator("criteria", llm=self.llm, criteria="conciseness")
 
     @trace
     def __call__(
-        self, input: str, prediction: str, 
+        self,
+        input: str,
+        prediction: str,
     ) -> Result:
         """Evaluate with langchain evaluator."""
 
-        eval_result = self.evaluator.evaluate_strings(
-            prediction=prediction, input=input
-        )
+        eval_result = self.evaluator.evaluate_strings(prediction=prediction, input=input)
         return Result(**eval_result)
-

examples/flex-flows/langchain-eval/langchain-eval.ipynb

@@ -51,9 +51,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Create a custom connection to protect your LLM's API key\n",
+    "## Create a custom connection to protect your API key\n",
     "\n",
-    "You can protect your LLM's API key in custom connection's secrets."
+    "You can protect your API key in custom connection's secrets."
    ]
   },
   {
@@ -71,7 +71,7 @@
     "    # load environment variables from .env file\n",
     "    load_dotenv()\n",
     "\n",
-    "# put LLM's API key in secrets\n",
+    "# put API key in secrets\n",
     "connection = CustomConnection(\n",
     "    name=\"my_llm_connection\",\n",
     "    secrets={\n",