For a complete reference of all LLM enrichments with output columns and sub-metrics, see the LLM Observability Metrics Reference.
| Metric | Metric Category | Description | Enrichment | LLM Used? | LLM Type |
|---|---|---|---|---|---|
| Faithfulness | Hallucination | This enrichment identifies the accuracy and reliability of facts presented in AI-generated texts | faithfulness | Yes | OpenAI |
| Centor Faithfulness | Hallucination | This enrichment identifies the accuracy and reliability of facts presented in AI-generated texts. It is generated by Fiddler’s Fiddler Centor Models | ftl_response_faithfulness | Yes | Fiddler Fiddler Centor Model |
| Answer Relevance | Hallucination | This enrichment measures the pertinence of AI-generated responses to their inputs | answer_relevance | Yes | OpenAI |
| Conciseness | Hallucination | This enrichment evaluates the brevity and clarity of AI-generated responses | conciseness | Yes | OpenAI |
| Coherence | Hallucination | This enrichment assesses the logical flow and clarity of AI-generated responses | coherence | Yes | OpenAI |
| Centor Safety | Safety | This enrichment generates 11 different safety metrics to measure texts upon. These metrics are: illegal, hateful, harassing, racist, sexist, violent, sexual, harmful, unethical, jailbreaking, roleplaying | ftl_prompt_safety | Yes | Fiddler Fiddler Centor Model |
| PII | Safety | This enrichment flags the presence of sensitive information within textual data | pii | No | |
| Regex Match | Safety | This enrichment compares the text with a regular expression string | regex_match | No | |
| Topic | Safety | This enrichment classifies the text into several preset dimensions using a zero-shot classifier | topic_model | No | |
| Banned Keywords | Safety | This enrichment detects the presence of banned keywords configured by the user | banned_keywords | No | |
| Profanity | Safety | This enrichment flags the use of offensive or inappropriate language | profanity | No | |
| Language Detection | Safety | This enrichment identifies the language of the source text | language_detection | No | |
| Evaluate | Text Statistics | This enrichment provides classic text evaluation methods such as BLEU, ROUGE, and Meteor | evaluate | No | |
| Sentiment | Text Statistics | This enrichment provides sentiment analysis of the target text | sentiment | No | |
| TextStat | Text Statistics | This enrichment provides various text statistics such as character/letter count, Flesch-Kincaid, and others | textstat | No | |
| Token Count | Text Statistics | The Token Count enrichment is designed to count the number of tokens in a string. | token_count | No | |
| SQLValidation | Text Validation | Evaluates different query dialects for syntax correctness. | sql_validation | No | |
| JSONValidation | Text Validation | Validates JSON for correctness and optionally against a user-defined schema. | json_validation | No |