Get Eval Dataset Execution Result
GET/api/v1/pipelines/:pipeline_id/eval-datasets/:eval_dataset_id/execute/result
Get the result of an EvalDatasetExecution. If eval_question_ids is specified, only the results for the specified questions will be returned. If any of the specified questions do not have a result, they will be ignored.
Request
Path Parameters
Cookie Parameters
Responses
- 200
- 422
Successful Response
- application/json
- Schema
- Example (from schema)
Schema
Array [
Array [
- MOD1
Array [
]
- RelatedNodeInfo
- MOD2
- ObjectType
- MOD2
- MOD1
Array [
- ObjectType
- MOD2
- MOD1
]
- MOD1
- MOD1
]
- MOD1
- MOD1
- MOD1
]
The ID of the question that was executed.
The ID of the pipeline that the question was executed against.
source_nodes
object[]
required
The nodes retrieved by the pipeline for the given question.
Unique ID of the node.
embedding
object
Embedding of the node.
anyOf
number
A flat dictionary of metadata fields
Metadata keys that are excluded from text for the embed model.
Metadata keys that are excluded from text for the LLM.
relationships
object
A mapping of relationships to other node information.
property name*
object
anyOf
node_type
object
anyOf
string
Possible values: [1
, 2
, 3
, 4
, 5
]
string
hash
object
anyOf
string
RelatedNodeInfo
node_type
object
anyOf
string
Possible values: [1
, 2
, 3
, 4
, 5
]
string
hash
object
anyOf
string
RelatedNodeInfo
Template for how metadata is formatted, with {key} and {value} placeholders.
{key}: {value}
Separator between metadata fields when converting to string.
Text content of the node.
MIME type of the node content.
text/plain
start_char_idx
object
Start char index of the node.
anyOf
integer
end_char_idx
object
End char index of the node.
anyOf
integer
Separator between metadata fields when converting to string.
Template for how text is formatted, with {content} and {metadata_str} placeholders.
{metadata_str}
{content}
TextNode
The answer to the question.
eval_metrics
object
required
The eval metrics for the question.
property name*
MetricResult
passing
object
Whether the metric passed or not.
anyOf
boolean
score
object
The score for the metric.
anyOf
number
feedback
object
The reasoning for the metric.
anyOf
string
The ID of the EvalDatasetJobRecord that this result was generated from.
eval_dataset_execution_params
object
required
Schema for the params for an eval execution.
The LLM model to use within eval execution.
Possible values: [GPT_3_5_TURBO
, GPT_4
, GPT_4_TURBO
, GPT_4O
, GPT_4O_MINI
, AZURE_OPENAI
, CLAUDE_3_5_SONNET
]
GPT_4O
The template to use for the question answering prompt.
Context information is below.
---------------------
{context_str}
---------------------
Given the context information and not prior knowledge, answer the query.
Query: {query_str}
Answer:
The timestamp when the eval finished.
EvalQuestionResult
[
{
"eval_question_id": "3fa85f64-5717-4562-b3fc-2c963f66afa6",
"pipeline_id": "3fa85f64-5717-4562-b3fc-2c963f66afa6",
"source_nodes": [
{
"id_": "string",
"embedding": [
null
],
"extra_info": {},
"excluded_embed_metadata_keys": [
"string"
],
"excluded_llm_metadata_keys": [
"string"
],
"relationships": {},
"metadata_template": "{key}: {value}",
"metadata_separator": "\n",
"text": "string",
"mimetype": "text/plain",
"start_char_idx": 0,
"end_char_idx": 0,
"metadata_seperator": "\n",
"text_template": "{metadata_str}\n\n{content}",
"class_name": "TextNode"
}
],
"answer": "string",
"eval_metrics": {},
"eval_dataset_execution_id": "3fa85f64-5717-4562-b3fc-2c963f66afa6",
"eval_dataset_execution_params": {
"llm_model": "GPT_4O",
"qa_prompt_tmpl": "Context information is below.\n---------------------\n{context_str}\n---------------------\nGiven the context information and not prior knowledge, answer the query.\nQuery: {query_str}\nAnswer: "
},
"eval_finished_at": "2024-07-29T15:51:28.071Z",
"class_name": "EvalQuestionResult"
}
]
Validation Error
- application/json
- Schema
- Example (from schema)
Schema
Array [
Array [
- MOD1
- MOD2
]
]
detail
object[]
loc
object[]
required
anyOf
string
integer
{
"detail": [
{
"loc": [
"string",
0
],
"msg": "string",
"type": "string"
}
]
}