added metadata (#467)

Author: drorIvry

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "qualifire"
-version = "0.14.0"
+version = "0.15.0"
 description = "Qualifire Python SDK"
 authors = [{ name = "qualifire-dev", email = "dror@qualifire.ai" }]
 requires-python = ">=3.8,<4"

qualifire/client.py

@@ -67,6 +67,7 @@ def evaluate(
         topic_scoping_multi_turn_mode: bool = False,
         topic_scoping_target: PolicyTarget = PolicyTarget.BOTH,
         allowed_topics: Optional[List[str]] = None,
+        metadata: Optional[Dict[str, str]] = None,
     ) -> Union[EvaluationResponse, None]:
         """
         Evaluates the given input and output pairs.
@@ -113,6 +114,7 @@ def evaluate(
         :param topic_scoping_multi_turn_mode: Enable multi-turn mode for topic scoping check.
         :param topic_scoping_target: Target topic for topic scoping check.
         :param allowed_topics: List of allowed topics for topic scoping check.
+        :param metadata: Optional dictionary of string key-value pairs to attach to the evaluation invocation.
 
         :return: An EvaluationResponse object containing the evaluation results.
         :raises Exception: If an error occurs during the evaluation.
@@ -236,6 +238,7 @@ def evaluate(
             topic_scoping_multi_turn_mode=topic_scoping_multi_turn_mode,
             topic_scoping_target=topic_scoping_target,
             allowed_topics=allowed_topics,
+            metadata=metadata,
         )
 
         response = requests.post(
@@ -264,6 +267,7 @@ def invoke_evaluation(
             Optional[List[Dict[str, Any]]],
         ] = None,
         available_tools: Optional[List[LLMToolDefinition]] = None,
+        metadata: Optional[Dict[str, str]] = None,
     ) -> EvaluationResponse:
         url = f"{self._base_url}/api/evaluation/invoke/"
 
@@ -279,6 +283,7 @@ def invoke_evaluation(
             output=output,
             messages=messages,  # type: ignore
             available_tools=available_tools,
+            metadata=metadata,
         )
 
         response = requests.request(

qualifire/types.py

@@ -70,6 +70,7 @@ class EvaluationRequest(BaseModel):
     topic_scoping_multi_turn_mode: bool = False
     topic_scoping_target: PolicyTarget = PolicyTarget.BOTH
     allowed_topics: Optional[List[str]] = None
+    metadata: Optional[Dict[str, str]] = None
 
     @model_validator(mode="after")
     def validate_model(self) -> "EvaluationRequest":
@@ -118,6 +119,7 @@ class EvaluationInvokeRequest(BaseModel):
     output: Optional[str] = None
     messages: Optional[List[LLMMessage]] = None
     available_tools: Optional[List[LLMToolDefinition]] = None
+    metadata: Optional[Dict[str, str]] = None
 
     @model_validator(mode="after")
     def validate_model(self) -> "EvaluationInvokeRequest":