unindent the second prompt as well

semantic_router/route.py

@@ -96,29 +96,29 @@ class Route(BaseModel):
         logger.info("Generating dynamic route...")
 
         prompt = f"""
-        You are tasked to generate a JSON configuration based on the provided
-        function schema. Please follow the template below, no other tokens allowed:
-
-        <config>
-        {{
-            "name": "<function_name>",
-            "utterances": [
-                "<example_utterance_1>",
-                "<example_utterance_2>",
-                "<example_utterance_3>",
-                "<example_utterance_4>",
-                "<example_utterance_5>"]
-        }}
-        </config>
-
-        Only include the "name" and "utterances" keys in your answer.
-        The "name" should match the function name and the "utterances"
-        should comprise a list of 5 example phrases that could be used to invoke
-        the function. Use real values instead of placeholders.
-
-        Input schema:
-        {function_schema}
-        """
+You are tasked to generate a JSON configuration based on the provided
+function schema. Please follow the template below, no other tokens allowed:
+
+<config>
+{{
+    "name": "<function_name>",
+    "utterances": [
+        "<example_utterance_1>",
+        "<example_utterance_2>",
+        "<example_utterance_3>",
+        "<example_utterance_4>",
+        "<example_utterance_5>"]
+}}
+</config>
+
+Only include the "name" and "utterances" keys in your answer.
+The "name" should match the function name and the "utterances"
+should comprise a list of 5 example phrases that could be used to invoke
+the function. Use real values instead of placeholders.
+
+Input schema:
+{function_schema}
+"""
 
         llm_input = [Message(role="user", content=prompt)]
         output = llm(llm_input)