[LEADS-504] Simplify Ragas context precision metric names

Author: bsatapat-jpg

README.md

@@ -217,8 +217,8 @@ uv run lightspeed-eval --system-config <AGENTS_CONFIG.yaml> --eval-data <PROPOSA
   - Context Evaluation
     - [`context_recall`](https://docs.ragas.io/en/stable/concepts/metrics/available_metrics/context_recall/)
     - [`context_relevance`](https://docs.ragas.io/en/stable/concepts/metrics/available_metrics/nvidia_metrics/#context-relevance)
-    - [`context_precision_without_reference`](https://docs.ragas.io/en/stable/concepts/metrics/available_metrics/context_precision/#context-precision-without-reference)
-    - [`context_precision_with_reference`](https://docs.ragas.io/en/stable/concepts/metrics/available_metrics/context_precision/#context-precision-with-reference)
+    - [`context_utilization`](https://docs.ragas.io/en/stable/concepts/metrics/available_metrics/context_precision/#context-precision-without-reference) (context precision without reference)
+    - [`context_precision`](https://docs.ragas.io/en/stable/concepts/metrics/available_metrics/context_precision/#context-precision-with-reference) (context precision with reference)
 - **Custom**
   - Response Evaluation
     - [`answer_correctness`](src/lightspeed_evaluation/core/metrics/custom/custom.py)

config/evaluation_data.yaml

@@ -20,7 +20,7 @@
       turn_metrics:
       - ragas:faithfulness
       - ragas:response_relevancy
-      - ragas:context_precision_without_reference
+      - ragas:context_utilization
       turn_metrics_metadata:
         ragas:faithfulness:
           threshold: 0.99
@@ -42,7 +42,7 @@
       turn_metrics:
         - ragas:context_recall
         - ragas:context_relevance
-        - ragas:context_precision_with_reference
+        - ragas:context_precision
 
 - conversation_group_id: conv_group_3
   description: conversation group description

config/system.yaml

@@ -108,7 +108,7 @@ agents:
 quality_score:
   metrics:
     - "ragas:faithfulness"
-    - "ragas:context_precision_with_reference"
+    - "ragas:context_precision"
     - "custom:tool_eval"
     - "custom:answer_correctness"
   default: true # If true, all metrics in this list get default: true
@@ -133,11 +133,11 @@ metrics_metadata:
       threshold: 0.8
       description: "Did we fetch every fact the answer needs?"
 
-    "ragas:context_precision_with_reference":
+    "ragas:context_precision":
       threshold: 0.7
       description: "How precise the retrieved context is (with reference)"
 
-    "ragas:context_precision_without_reference":
+    "ragas:context_utilization":
       threshold: 0.7
       description: "How precise the retrieved context is (without reference)"
 

docs/EVALUATION_GUIDE.md

@@ -687,8 +687,8 @@ What are you evaluating?
 │  ├─ Context / Retrieval Quality?
 │  │  ├─ Found everything needed? → context_recall
 │  │  ├─ Is retrieved context relevant? → context_relevance
-│  │  ├─ Precision (have expected answer)? → context_precision_with_reference
-│  │  └─ Precision (no expected answer)? → context_precision_without_reference
+│  │  ├─ Precision (have expected answer)? → context_precision
+│  │  └─ Precision (no expected answer)? → context_utilization
 │  │
 │  ├─ Tool Calls & AI Behavior?
 │  │  ├─ Right intent? → intent_eval
@@ -1401,7 +1401,7 @@ The Quality Score aggregates selected sub-metrics into a single number that repr
 quality_score:
   metrics:
     - "ragas:faithfulness"
-    - "ragas:context_precision_with_reference"
+    - "ragas:context_precision"
     - "custom:tool_eval"
   default: true
 ```
@@ -1985,8 +1985,8 @@ lightspeed-eval --eval-data config/eval_batch2.yaml
 | **ragas:faithfulness** | 0-1 | No made-up information | 0.8 | response, contexts |
 | **ragas:context_recall** | 0-1 | Found all needed info | 0.8 | contexts, expected_response |
 | **ragas:context_relevance** | 0-1 | Retrieved info is relevant | 0.7 | query, contexts |
-| **ragas:context_precision_without_reference** | 0-1 | Retrieved info is useful | 0.7 | query, contexts, response |
-| **ragas:context_precision_with_reference** | 0-1 | Retrieved info is useful (vs reference) | 0.7 | query, contexts, response, expected_response |
+| **ragas:context_utilization** | 0-1 | Retrieved info is useful | 0.7 | query, contexts, response |
+| **ragas:context_precision** | 0-1 | Retrieved info is useful (vs reference) | 0.7 | query, contexts, response, expected_response |
 | **custom:answer_correctness** | 0-1 | Matches expected answer | 0.75 | query, response, expected_response |
 | **custom:intent_eval** | 0/1 | Has right intent | 1 | query, response, expected_intent |
 | **custom:tool_eval** | 0/1 | Called correct tools with expected results | 1 | expected_tool_calls, tool_calls |

examples/02_metrics/context_quality/README.md

@@ -20,8 +20,8 @@ uv run lightspeed-eval \
 |-----------------------------------------------|---------------------|---------------------------------------------------------------------------------------|--------------------------------------------|-----------------------------|
 | `ragas:context_recall`                        | Context Recall      | Measures how well retrieved context covers the expected answer                        | query, response, contexts, expected_response | query, expected_response  |
 | `ragas:context_relevance`                     | Context Relevance   | Evaluates relevance of retrieved context to the query                                 | query, response, contexts                  | query                       |
-| `ragas:context_precision_without_reference`   | Context Utilization | Assesses context ranking quality without using reference answer                       | query, response, contexts                  | query                       |
-| `ragas:context_precision_with_reference`      | Context Precision   | Assesses context ranking quality using expected answer                                | query, response, contexts, expected_response | query, expected_response  |
+| `ragas:context_utilization`                   | Context Utilization | Assesses context ranking quality without using reference answer                       | query, response, contexts                  | query                       |
+| `ragas:context_precision`                     | Context Precision   | Assesses context ranking quality using expected answer                                | query, response, contexts, expected_response | query, expected_response  |
 
 **Note:** In live mode, `response` and `contexts` are fetched from live API; only `query` and expected fields go in YAML.
 

examples/02_metrics/context_quality/system.yaml

@@ -31,11 +31,11 @@ metrics_metadata:
       threshold: 0.7
       description: Measures relevance of retrieved context to the query
       default: true
-    ragas:context_precision_without_reference:  # ContextUtilization
+    ragas:context_utilization:  # ContextUtilization
       threshold: 0.7
       description: Evaluates precision of context ranking (no reference needed)
       default: true
-    ragas:context_precision_with_reference:  # ContextPrecision
+    ragas:context_precision:  # ContextPrecision
       threshold: 0.7
       description: Evaluates precision of context using expected answer
       default: true

src/lightspeed_evaluation/core/metrics/ragas.py

@@ -88,10 +88,8 @@ def __init__(self, llm_manager: LLMManager, embedding_manager: EmbeddingManager)
             # Context/Retrieval evaluation metrics
             "context_recall": self._evaluate_context_recall,
             "context_relevance": self._evaluate_context_relevance,
-            "context_precision_with_reference": self._evaluate_context_precision_with_reference,
-            "context_precision_without_reference": (
-                self._evaluate_context_precision_without_reference
-            ),
+            "context_precision": self._evaluate_context_precision,
+            "context_utilization": self._evaluate_context_utilization,
         }
 
     @property
@@ -220,16 +218,16 @@ def _evaluate_faithfulness(
         score = _clamp_score(float(result.value))
         return score, f"Ragas faithfulness: {score:.2f}"
 
-    def _evaluate_context_precision_without_reference(
+    def _evaluate_context_utilization(
         self,
         _conv_data: Any,
         _turn_idx: Optional[int],
         turn_data: Optional[TurnData],
         is_conversation: bool,
     ) -> tuple[Optional[float], str]:
-        """Evaluate context precision without reference using Ragas 0.4+ score()."""
+        """Evaluate context utilization using Ragas 0.4+ ContextUtilization."""
         if is_conversation:
-            return None, "Context precision without reference is a turn-level metric"
+            return None, "Context utilization is a turn-level metric"
 
         query, response, contexts = self._extract_turn_data(turn_data)
 
@@ -242,21 +240,21 @@ def _evaluate_context_precision_without_reference(
         )
 
         score = _clamp_score(float(result.value))
-        return score, f"Ragas context precision without reference: {score:.2f}"
+        return score, f"Ragas context utilization: {score:.2f}"
 
-    def _evaluate_context_precision_with_reference(
+    def _evaluate_context_precision(
         self,
         _conv_data: Any,
         _turn_idx: Optional[int],
         turn_data: Optional[TurnData],
         is_conversation: bool,
     ) -> tuple[Optional[float], str]:
-        """Evaluate context precision with reference using Ragas 0.4+ score()."""
+        """Evaluate context precision using Ragas 0.4+ ContextPrecision."""
         if is_conversation:
-            return None, "Context precision with reference is a turn-level metric"
+            return None, "Context precision is a turn-level metric"
 
         if turn_data is None:
-            return None, "TurnData is required for context precision with reference"
+            return None, "TurnData is required for context precision"
 
         query, _, contexts = self._extract_turn_data(turn_data)
 
@@ -269,7 +267,7 @@ def _evaluate_context_precision_with_reference(
         )
 
         score = _clamp_score(float(result.value))
-        return score, f"Ragas context precision with reference: {score:.2f}"
+        return score, f"Ragas context precision: {score:.2f}"
 
     def _evaluate_context_recall(
         self,

src/lightspeed_evaluation/core/system/validator.py

@@ -32,11 +32,11 @@
         "required_fields": ["response", "contexts"],
         "description": "requires 'response' and 'contexts' fields",
     },
-    "ragas:context_precision_with_reference": {
+    "ragas:context_precision": {
         "required_fields": ["response", "contexts", "expected_response"],
         "description": "requires 'response', 'contexts', and 'expected_response' fields",
     },
-    "ragas:context_precision_without_reference": {
+    "ragas:context_utilization": {
         "required_fields": ["response", "contexts"],
         "description": "requires 'response' and 'contexts' fields",
     },