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🌿 Fern Regeneration -- July 27, 2024 (#4)
* SDK regeneration * address pydantic naming conflict * 🌿 SDK regeneration --------- Co-authored-by: fern-api <115122769+fern-api[bot]@users.noreply.github.com>
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.mock/definition/__package__.yml

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.mock/definition/api.yml

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@@ -3,7 +3,7 @@ error-discrimination:
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strategy: status-code
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display-name: Humanloop API
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environments:
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Default: https://api.humanloop.com/v5
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Default: https://neostaging.humanloop.ml/v5
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default-environment: Default
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auth-schemes:
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APIKeyHeader:

.mock/definition/datasets.yml

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path: /datasets
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method: GET
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auth: true
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docs: List a list of all Datasets.
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docs: List all Datasets.
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pagination:
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offset: $request.page
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results: $response.records
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errors:
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- root.UnprocessableEntityError
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examples:
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- name: Create dataset
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- name: AddToDataset
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request:
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path: test-questions
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datapoints:
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status: committed
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last_used_at: '2024-05-01T12:00:00Z'
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datapoints_count: 4
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- name: CreateSupportDataset
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request:
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path: datasets/support-queries
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datapoints:
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- messages:
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- role: user
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content: >-
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Hi Humanloop support team, I'm having trouble
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understanding how to use the evaluations feature in your
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software. Can you provide a step-by-step guide or any
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resources to help me get started?
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target:
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feature: evaluations
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issue: needs step-by-step guide
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- messages:
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- role: user
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content: >-
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Hi there, I'm interested in fine-tuning a language model
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using your software. Can you explain the process and
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provide any best practices or guidelines?
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target:
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feature: fine-tuning
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issue: process explanation and best practices
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action: add
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commit_message: Add two new questions and answers
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response:
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body:
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id: ds_mno345
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path: test-questions
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name: test-questions
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version_id: dsv_pqr678
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type: dataset
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created_at: '2024-05-01T12:00:00Z'
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updated_at: '2024-05-01T12:00:00Z'
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status: committed
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last_used_at: '2024-05-01T12:00:00Z'
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datapoints_count: 4
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get:
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path: /datasets/{id}
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method: GET
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datapoints_count: 1
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datapoints:
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- inputs:
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inputs: inputs
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key: value
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messages:
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- role: user
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target:
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target: target
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key: value
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id: id
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listDatapoints:
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path: /datasets/{id}/datapoints
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datapoints_count: 1
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datapoints:
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- inputs:
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inputs: inputs
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key: value
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messages:
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- role: user
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target:
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target: target
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key: value
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id: id
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setDeployment:
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path: /datasets/{id}/environments/{environment_id}
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stop: stop
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presence_penalty: 1.1
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frequency_penalty: 1.1
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other:
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key: value
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seed: 1
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response_format:
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type: json_object

.mock/definition/evaluations.yml

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id: id
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log:
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id: id
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config:
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prompt:
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path: path
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id: id
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type: model
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name: name
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version_id: version_id
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created_at: '2024-01-15T09:30:00Z'
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updated_at: '2024-01-15T09:30:00Z'
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status: uncommitted
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last_used_at: '2024-01-15T09:30:00Z'
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model: model
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evaluation_results:
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- id: id
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evaluator_id: evaluator_id
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evaluator_version_id: evaluator_version_id
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log_id: log_id
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updated_at: '2024-01-15T09:30:00Z'
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created_at: '2024-01-15T09:30:00Z'
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observability_status: pending
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updated_at: '2024-01-15T09:30:00Z'
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version_logs_count: 1
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total_logs_count: 1
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inputs:
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- name: name
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evaluator_logs:
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- id: id
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config:
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prompt:
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path: path
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id: id
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type: model
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name: name
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version_id: version_id
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created_at: '2024-01-15T09:30:00Z'
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updated_at: '2024-01-15T09:30:00Z'
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status: uncommitted
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last_used_at: '2024-01-15T09:30:00Z'
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model: model
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evaluation_results:
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- id: id
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evaluator_id: evaluator_id
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evaluator_version_id: evaluator_version_id
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log_id: log_id
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updated_at: '2024-01-15T09:30:00Z'
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created_at: '2024-01-15T09:30:00Z'
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observability_status: pending
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updated_at: '2024-01-15T09:30:00Z'
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version_logs_count: 1
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total_logs_count: 1
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inputs:
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- name: name
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page: 1
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size: 1
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total: 1

.mock/definition/evaluators.yml

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total_logs_count: 1
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inputs:
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- name: answer
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log:
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path: /evaluators/log
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method: POST
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auth: true
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docs: >-
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Submit evalutor judgment for an existing Log. Creates a new Log and
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makes evaluated one its parent.
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display-name: Log
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request:
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name: CreateEvaluatorLogRequest
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query-parameters:
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version_id:
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type: optional<string>
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docs: ID of the Evaluator version to log against.
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environment:
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type: optional<string>
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docs: Name of the Environment identifying a deployed version to log to.
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body:
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properties:
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path:
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type: optional<string>
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docs: >-
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Path of the Evaluator, including the name, which is used as a
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unique identifier.
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id:
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type: optional<string>
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docs: ID for an existing Evaluator to update.
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output:
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type: optional<string>
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docs: >-
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Generated output from the LLM. Only populated for LLM Evaluator
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Logs.
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created_at:
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type: optional<datetime>
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docs: 'User defined timestamp for when the log was created. '
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error:
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type: optional<string>
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docs: Error message if the log is an error.
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provider_latency:
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type: optional<double>
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docs: Duration of the logged event in seconds.
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provider_request:
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type: optional<map<string, unknown>>
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docs: >-
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Raw request sent to provider. Only populated for LLM Evaluator
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Logs.
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provider_response:
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type: optional<map<string, unknown>>
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docs: >-
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Raw response received the provider. Only populated for LLM
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Evaluator Logs.
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session_id:
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type: optional<string>
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docs: >-
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Unique identifier for the Session to associate the Log to.
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Allows you to record multiple Logs to a Session (using an ID
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kept by your internal systems) by passing the same `session_id`
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in subsequent log requests.
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parent_id:
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type: string
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docs: >-
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Identifier of the evaluated Log. The newly created Log will have
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this one set as parent.
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inputs:
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type: optional<map<string, unknown>>
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docs: The inputs passed to the prompt template.
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source:
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type: optional<string>
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docs: Identifies where the model was called from.
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metadata:
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type: optional<map<string, unknown>>
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docs: Any additional metadata to record.
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save:
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type: optional<boolean>
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docs: >-
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Whether the request/response payloads will be stored on
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Humanloop.
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default: true
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source_datapoint_id:
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type: optional<string>
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docs: >-
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Unique identifier for the Datapoint that this Log is derived
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from. This can be used by Humanloop to associate Logs to
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Evaluations. If provided, Humanloop will automatically associate
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this Log to Evaluations that require a Log for this
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Datapoint-Version pair.
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batches:
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type: optional<list<string>>
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docs: >-
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Array of Batch Ids that this log is part of. Batches are used to
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group Logs together for offline Evaluations
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user:
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type: optional<string>
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docs: End-user ID related to the Log.
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environment:
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type: optional<string>
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docs: The name of the Environment the Log is associated to.
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name: createEvaluatorLogRequestEnvironment
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judgment: optional<unknown>
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spec: optional<CreateEvaluatorLogRequestSpec>
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response:
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docs: Successful Response
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type: root.CreateEvaluatorLogResponse
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errors:
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- root.UnprocessableEntityError
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examples:
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- request:
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parent_id: parent_id
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response:
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body:
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id: id
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parent_id: parent_id
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session_id: session_id
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version_id: version_id
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types:
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SrcExternalAppModelsV5EvaluatorsEvaluatorRequestSpec:
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discriminated: false
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- root.CodeEvaluatorRequest
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- root.HumanEvaluatorRequest
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- root.ExternalEvaluatorRequest
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CreateEvaluatorLogRequestSpec:
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discriminated: false
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union:
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- root.LlmEvaluatorRequest
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- root.CodeEvaluatorRequest
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- root.HumanEvaluatorRequest
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- root.ExternalEvaluatorRequest

.mock/definition/logs.yml

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returned.
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type: root.PaginatedPromptLogResponse
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type: root.PaginatedDataLogResponse
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errors:
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examples:
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display-name: Get Log
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response:
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docs: Successful Response
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type: root.SrcExternalAppModelsV5LogsLogResponse
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errors:
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- root.UnprocessableEntityError
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examples:

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