FTLResponseFaithfulness
API reference for FTLResponseFaithfulness
FTLResponseFaithfulness
FTLResponseFaithfulness
Evaluator to assess response faithfulness using Fiddler’s Trust Model.
The FTLResponseFaithfulness evaluator uses Fiddler’s proprietary Trust Model to evaluate how faithful an LLM response is to the provided context. This evaluator helps ensure that responses accurately reflect the information in the source context and don’t contain hallucinated or fabricated information.
Key Features:
Faithfulness Assessment: Evaluates how well the response reflects the context
Probability-Based Scoring: Returns probability scores (0.0-1.0) for faithfulness
Context-Response Alignment: Compares response against provided context
Fiddler Trust Model: Uses Fiddler’s proprietary faithfulness evaluation model
Hallucination Detection: Identifies responses that go beyond the context
Faithfulness Categories Evaluated:
faithful_prob: Probability that the response is faithful to the context
Use Cases:
RAG Systems: Ensuring responses stay grounded in retrieved context
Document Q&A: Verifying answers are based on provided documents
Fact-Checking: Validating that responses don’t contain fabricated information
Content Validation: Ensuring responses accurately reflect source material
Hallucination Detection: Identifying responses that go beyond the context
Scoring Logic: : The faithfulness score represents the probability that the response is faithful to the context:
0.0-0.3: Low faithfulness (likely contains hallucinated information)
0.3-0.7: Medium faithfulness (some information may not be grounded)
0.7-1.0: High faithfulness (response accurately reflects context)
Parameters
response
str
✗
None
The LLM response to evaluate for faithfulness.
context
str
✗
None
The source context that the response should be faithful to.
Returns
A list of Score objects containing: : - name: The faithfulness category name (“faithful_prob”)
evaluator_name: “FTLResponseFaithfulness”
value: Probability score (0.0-1.0) for faithfulness Return type: list[Score]
Raises
ValueError – If the response or context is empty or None.
Example
FTLResponseFaithfulness
FTLResponseFaithfulness
Evaluator to assess response faithfulness using Fiddler’s Trust Model.
The FTLResponseFaithfulness evaluator uses Fiddler’s proprietary Trust Model to evaluate how faithful an LLM response is to the provided context. This evaluator helps ensure that responses accurately reflect the information in the source context and don’t contain hallucinated or fabricated information.
Key Features:
Faithfulness Assessment: Evaluates how well the response reflects the context
Probability-Based Scoring: Returns probability scores (0.0-1.0) for faithfulness
Context-Response Alignment: Compares response against provided context
Fiddler Trust Model: Uses Fiddler’s proprietary faithfulness evaluation model
Hallucination Detection: Identifies responses that go beyond the context
Faithfulness Categories Evaluated:
faithful_prob: Probability that the response is faithful to the context
Use Cases:
RAG Systems: Ensuring responses stay grounded in retrieved context
Document Q&A: Verifying answers are based on provided documents
Fact-Checking: Validating that responses don’t contain fabricated information
Content Validation: Ensuring responses accurately reflect source material
Hallucination Detection: Identifying responses that go beyond the context
Scoring Logic: : The faithfulness score represents the probability that the response is faithful to the context:
0.0-0.3: Low faithfulness (likely contains hallucinated information)
0.3-0.7: Medium faithfulness (some information may not be grounded)
0.7-1.0: High faithfulness (response accurately reflects context)
Parameters
response
str
✗
None
The LLM response to evaluate for faithfulness.
context
str
✗
None
The source context that the response should be faithful to.
Returns
A list of Score objects containing: : - name: The faithfulness category name (“faithful_prob”)
evaluator_name: “FTLResponseFaithfulness”
value: Probability score (0.0-1.0) for faithfulness Return type: list[Score]
Raises
ValueError – If the response or context is empty or None.
Example
>>> from fiddler_evals.evaluators import FTLResponseFaithfulness
>>> evaluator = FTLResponseFaithfulness()
# Faithful response
context = “The capital of France is Paris. It is located in northern Europe.”
response = “Paris is the capital of France.”
scores = evaluator.score(response=response, context=context)
for score in scores:
> print(f”{score.name}: {score.value}”)
# faithful_prob: 0.95
# Unfaithful response with hallucination
context = “The capital of France is Paris.”
response = “The capital of France is Paris, and it has a population of 2.1 million people.”
scores = evaluator.score(response=response, context=context)
for score in scores:
> print(f”{score.name}: {score.value}”)
# faithful_prob: 0.65 (population info not in context)
# Highly unfaithful response
context = “The capital of France is Paris.”
response = “The capital of France is London.”
scores = evaluator.score(response=response, context=context)
for score in scores:
> print(f”{score.name}: {score.value}”)
# faithful_prob: 0.05
# Filter based on faithfulness threshold
faithful_score = next(s for s in scores if s.name == “faithful_prob”)
if faithful_score.value < 0.7:
> print(“Response flagged as potentially unfaithful”)
{% hint style="info" %}
This evaluator is designed for response faithfulness assessment and should be used
in conjunction with other evaluation metrics for comprehensive response quality
assessment. The probability scores should be interpreted in context and combined
with other quality measures for robust response validation.
{% endhint %}
#### name *= 'ftl_response_faithfulness'*
#### score()
Score the faithfulness of a response to its context.
#### Parameters
| Parameter | Type | Required | Default | Description |
|-----------|------|----------|---------|-------------|
| `response` | `str` | ✗ | `None` | The LLM response to evaluate for faithfulness. |
| `context` | `str` | ✗ | `None` | The source context that the response should be faithful to. |
#### Returns
A Score object for faithfulness probability.
**Return type:** Score
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