Fixed topic relevance user prompt

backend/app/core/validators/prompts/topic_relevance_llm/v1.md

@@ -1,5 +1,3 @@
-{{USER_PROMPT}}
-
 Rules:
 
 - Use semantic meaning, not keyword matching.

backend/app/core/validators/prompts/topic_relevance_llm/v2.md

@@ -1,5 +1,3 @@
-{{USER_PROMPT}}
-
 Rules:
 
 - Use semantic meaning, not keyword matching.

backend/app/core/validators/prompts/topic_relevance_llm/v3.md

@@ -1,5 +1,3 @@
-{{USER_PROMPT}}
-
 Rules:
 
 - Use semantic meaning, not keyword matching.

backend/app/core/validators/topic_relevance_llm.py

@@ -23,8 +23,6 @@
     supports_response_format,
 )
 
-# Placeholder in user-message templates marking where the user's query is injected.
-_USER_PROMPT_PLACEHOLDER = "{{USER_PROMPT}}"
 _PROMPTS_DIR = Path(__file__).parent / "prompts" / "topic_relevance_llm"
 
 # Valid scope scores returned by the model; the highest means "clearly in scope".
@@ -35,7 +33,7 @@
 
 @lru_cache(maxsize=8)
 def _load_prompt_template(prompt_schema_version: int) -> str:
-    """Load and cache the user-message prompt template for the given schema version."""
+    """Load and cache the scoring instruction block for the given schema version."""
     if prompt_schema_version < 1:
         raise ValueError("prompt_schema_version must be a positive integer")
 
@@ -45,12 +43,7 @@ def _load_prompt_template(prompt_schema_version: int) -> str:
             f"Topic relevance (LLM) prompt template for version {prompt_schema_version} not found"
         )
 
-    template = prompt_file.read_text(encoding="utf-8")
-    if _USER_PROMPT_PLACEHOLDER not in template:
-        raise ValueError(
-            f"Prompt template v{prompt_schema_version} must contain {_USER_PROMPT_PLACEHOLDER}"
-        )
-    return template
+    return prompt_file.read_text(encoding="utf-8")
 
 
 @register_validator(name="topic-relevance-llm", data_type="string")
@@ -59,10 +52,10 @@ class TopicRelevanceLLM(Validator):
     Validates whether a user message is within the defined topic scope
     using a direct LLM call via litellm.
 
-    The caller supplies the topic configuration as ``system_prompt``, which
-    becomes the system message. Scoring and response-format instructions are
-    loaded from a versioned prompt template (v1/v2/v3) and injected as the
-    user message alongside the query.
+    The caller supplies the topic configuration as ``system_prompt``. Scoring
+    and response-format instructions are loaded from a versioned prompt template
+    (v1/v2/v3) and appended to the system message. The user message contains
+    only the raw query.
 
     Scores 1–3 where 3 = clearly in scope, 2 = partially related,
     1 = outside scope. Passes when score >= threshold (default 2).
@@ -87,20 +80,19 @@ def __init__(
         self.threshold = threshold
         self._invalid_config_reason: Optional[str] = None
         self._system_prompt: Optional[str] = None
-        self._user_message_template: Optional[str] = None
         self._supports_response_format: bool = False
 
         if not system_prompt or not system_prompt.strip():
             self._invalid_config_reason = "system_prompt is blank or missing"
             return
 
         try:
-            self._user_message_template = _load_prompt_template(prompt_schema_version)
+            scoring_rules = _load_prompt_template(prompt_schema_version)
         except ValueError as e:
             self._invalid_config_reason = str(e)
             return
 
-        self._system_prompt = system_prompt.strip()
+        self._system_prompt = f"{system_prompt.strip()}\n\n{scoring_rules}"
         self._supports_response_format = supports_response_format(llm_callable)
 
     def _validate(
@@ -112,16 +104,12 @@ def _validate(
         if not value or not value.strip():
             return FailResult(error_message=EMPTY_MESSAGE_ERROR)
 
-        user_message = self._user_message_template.replace(
-            _USER_PROMPT_PLACEHOLDER, value
-        )
-
         try:
             kwargs = {
                 "model": self.llm_callable,
                 "messages": [
                     {"role": "system", "content": self._system_prompt},
-                    {"role": "user", "content": user_message},
+                    {"role": "user", "content": value},
                 ],
                 "max_tokens": _MAX_TOKENS,
             }

backend/app/tests/validators/test_topic_relevance_llm.py

@@ -3,10 +3,7 @@
 import pytest
 from guardrails.validators import FailResult, PassResult
 
-from app.core.validators.topic_relevance_llm import (
-    TopicRelevanceLLM,
-    _USER_PROMPT_PLACEHOLDER,
-)
+from app.core.validators.topic_relevance_llm import TopicRelevanceLLM
 
 TOPIC_CONFIG = "Only answer questions about cooking and recipes."
 
@@ -234,16 +231,15 @@ def test_fails_when_score_is_boolean(validator):
 # ---------------------------------------------------------------------------
 
 
-def test_user_message_contains_query_not_placeholder(validator):
+def test_user_message_is_exactly_the_query(validator):
     query = "How do I make pasta?"
     with patch("app.core.validators.topic_relevance_llm.completion") as mock_llm:
         mock_llm.return_value = _make_llm_response('{"scope_violation": 3}')
         validator._validate(query)
 
     _, kwargs = mock_llm.call_args
     user_message = kwargs["messages"][1]["content"]
-    assert query in user_message
-    assert _USER_PROMPT_PLACEHOLDER not in user_message
+    assert user_message == query
 
 
 # ---------------------------------------------------------------------------
@@ -311,25 +307,15 @@ def test_system_prompt_contains_topic_config():
     assert TOPIC_CONFIG in validator._system_prompt
 
 
-def test_user_message_template_contains_json_instruction():
+def test_system_prompt_contains_json_instruction():
     with patch(
         "app.core.validators.llm_utils.get_supported_openai_params",
         return_value=[],
     ):
         validator = TopicRelevanceLLM(system_prompt=TOPIC_CONFIG)
 
-    assert "scope_violation" in validator._user_message_template
-    assert "JSON" in validator._user_message_template
-
-
-def test_user_message_template_contains_user_prompt_placeholder():
-    with patch(
-        "app.core.validators.llm_utils.get_supported_openai_params",
-        return_value=[],
-    ):
-        validator = TopicRelevanceLLM(system_prompt=TOPIC_CONFIG)
-
-    assert _USER_PROMPT_PLACEHOLDER in validator._user_message_template
+    assert "scope_violation" in validator._system_prompt
+    assert "JSON" in validator._system_prompt
 
 
 def test_prompt_schema_version_v2_loads_forbidden_template():
@@ -341,7 +327,7 @@ def test_prompt_schema_version_v2_loads_forbidden_template():
             system_prompt=TOPIC_CONFIG, prompt_schema_version=2
         )
 
-    assert "forbidden" in v2_validator._user_message_template.lower()
+    assert "forbidden" in v2_validator._system_prompt.lower()
 
 
 def test_prompt_schema_version_v3_loads_combined_template():
@@ -353,8 +339,8 @@ def test_prompt_schema_version_v3_loads_combined_template():
             system_prompt=TOPIC_CONFIG, prompt_schema_version=3
         )
 
-    assert "forbidden" in v3_validator._user_message_template.lower()
-    assert "allowed" in v3_validator._user_message_template.lower()
+    assert "forbidden" in v3_validator._system_prompt.lower()
+    assert "allowed" in v3_validator._system_prompt.lower()
 
 
 def test_invalid_prompt_schema_version_returns_fail():