| Name |
Type |
Description |
Notes |
| access |
AiConfigsAccess |
|
[optional] |
| links |
ParentAndSelfLinks |
|
[optional] |
| id |
UUID |
The result ID |
|
| run_id |
UUID |
The ID of the run this result belongs to |
|
| agent_optimization_id |
UUID |
The agent optimization ID |
|
| agent_optimization_version |
int |
The version of the agent optimization used |
|
| status |
AgentOptimizationResultStatus |
|
|
| activity |
AgentOptimizationResultActivity |
|
|
| iteration |
int |
The iteration number within the run |
|
| instructions |
str |
The instructions used for this attempt |
|
| parameters |
Dict[str, object] |
The model parameters used for this attempt |
[optional] |
| user_input |
str |
The user input used for this attempt |
|
| completion_response |
str |
The model response |
[optional] |
| variation |
Dict[str, object] |
The variation that was tested |
[optional] |
| scores |
Dict[str, object] |
The scores for the response |
[optional] |
| generation_tokens |
Dict[str, object] |
Token usage for generating the response |
[optional] |
| evaluation_tokens |
Dict[str, object] |
Token usage for judging the response |
[optional] |
| generation_latency |
int |
How long the response took to generate |
[optional] |
| evaluation_latencies |
Dict[str, object] |
How long each evaluation took |
[optional] |
| completed_at |
int |
When this finished, in Unix milliseconds |
[optional] |
| created_variation_key |
str |
The key of the variation created from this result |
[optional] |
| created_at |
int |
When this resource was created, in Unix milliseconds |
|
| updated_at |
int |
When this resource was last updated, in Unix milliseconds |
|
from launchdarkly_api.models.agent_optimization_result import AgentOptimizationResult
# TODO update the JSON string below
json = "{}"
# create an instance of AgentOptimizationResult from a JSON string
agent_optimization_result_instance = AgentOptimizationResult.from_json(json)
# print the JSON string representation of the object
print(AgentOptimizationResult.to_json())
# convert the object into a dict
agent_optimization_result_dict = agent_optimization_result_instance.to_dict()
# create an instance of AgentOptimizationResult from a dict
agent_optimization_result_from_dict = AgentOptimizationResult.from_dict(agent_optimization_result_dict)
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