Create an Evaluator
Create a new evaluator to assess LLM outputs. Configure scoring criteria, models, and thresholds for automated quality assessment of AI responses.
Documentation Index
Fetch the complete documentation index at: https://docs.orq.ai/llms.txt
Use this file to discover all available pages before exploring further.
Authorizations
Bearer authentication header of the form Bearer <token>, where <token> is your auth token.
Body
- LLM
- LLM
- JSON
- HTTP
- Python
llm_eval Entity storage path.
With workspace-level API keys, use the format project/folder/subfolder/.... The first element identifies the project, followed by nested folders (auto-created as needed). Example: Default/agents.
With project-level API keys, the project is predetermined by the API key, so the path is relative to that project. Example: agents. For backward compatibility, a leading project name is ignored when it matches the scoped project.
"Default"
1^[a-zA-Z0-9]([a-zA-Z0-9_-]*[a-zA-Z0-9])?$single - Boolean
- Categorical
- Number
The type of output expected from the evaluator
boolean, categorical, number, string 1 <= x <= 3Response
Successfully created an evaluator
- LLM
- LLM
- JSON
- HTTP
- Python
- Function
- Ragas
- Typescript
llm_eval 1^[a-zA-Z0-9]([a-zA-Z0-9_-]*[a-zA-Z0-9])?$single - Boolean
- Categorical
- Number
1 <= x <= 3